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Dag, Antymos. "Autonomous Indoor Navigation System for Mobile Robots." Thesis, Linköpings universitet, Programvara och system, 2016. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-129419.
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With an increasing need for greater traffic safety, there is an increasing demand for means by which solutions to the traffic safety problem can be studied. The purpose of this thesis is to investigate the feasibility of using an autonomous indoor navigation system as a component in a demonstration system for studying cooperative vehicular scenarios. Our method involves developing and evaluating such a navigation system. Our navigation system uses a pre-existing localization system based on passive RFID, odometry and a particle filter. The localization system is used to estimate the robot pose, which is used to calculate a trajectory to the goal. A control system with a feedback loop is used to control the robot actuators and to drive the robot to the goal. The results of our evaluation tests show that the system generally fulfills the performance requirements stated for the tests. There is however some uncertainty about the consistency of its performance. Results did not indicate that this was caused by the choice of localization techniques. The conclusion is that an autonomous navigation system using the aforementioned localization techniques is plausible for use in a demonstration system. However, we suggest that the system is further tested and evaluated before it is used with applications where accuracy is prioritized.
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Althaus, Philipp. "Indoor Navigation for Mobile Robots : Control and Representations." Doctoral thesis, KTH, Numerical Analysis and Computer Science, NADA, 2003. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-3644.
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This thesis deals with various aspects of indoor navigationfor mobile robots. For a system that moves around in ahousehold or office environment,two major problems must betackled. First, an appropriate control scheme has to bedesigned in order to navigate the platform. Second, the form ofrepresentations of the environment must be chosen.
Behaviour based approaches have become the dominantmethodologies for designing control schemes for robotnavigation. One of them is the dynamical systems approach,which is based on the mathematical theory of nonlineardynamics. It provides a sound theoretical framework for bothbehaviour design and behaviour coordination. In the workpresented in this thesis, the approach has been used for thefirst time to construct a navigation system for realistic tasksin large-scale real-world environments. In particular, thecoordination scheme was exploited in order to combinecontinuous sensory signals and discrete events for decisionmaking processes. In addition, this coordination frameworkassures a continuous control signal at all times and permitsthe robot to deal with unexpected events.
In order to act in the real world, the control system makesuse of representations of the environment. On the one hand,local geometrical representations parameterise the behaviours.On the other hand, context information and a predefined worldmodel enable the coordination scheme to switchbetweensubtasks. These representations constitute symbols, on thebasis of which the system makes decisions. These symbols mustbe anchored in the real world, requiring the capability ofrelating to sensory data. A general framework for theseanchoring processes in hybrid deliberative architectures isproposed. A distinction of anchoring on two different levels ofabstraction reduces the complexity of the problemsignificantly.
A topological map was chosen as a world model. Through theadvanced behaviour coordination system and a proper choice ofrepresentations,the complexity of this map can be kept at aminimum. This allows the development of simple algorithms forautomatic map acquisition. When the robot is guided through theenvironment, it creates such a map of the area online. Theresulting map is precise enough for subsequent use innavigation.
In addition, initial studies on navigation in human-robotinteraction tasks are presented. These kinds of tasks posedifferent constraints on a robotic system than, for example,delivery missions. It is shown that the methods developed inthis thesis can easily be applied to interactive navigation.Results show a personal robot maintaining formations with agroup of persons during social interaction.
Keywords:mobile robots, robot navigation, indoornavigation, behaviour based robotics, hybrid deliberativesystems, dynamical systems approach, topological maps, symbolanchoring, autonomous mapping, human-robot interaction
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Hennig, Matthias, Henri Kirmse, and Klaus Janschek. "Global Localization of an Indoor Mobile Robot with a single Base Station." Saechsische Landesbibliothek- Staats- und Universitaetsbibliothek Dresden, 2012. http://nbn-resolving.de/urn:nbn:de:bsz:14-qucosa-83687.
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The navigation tasks in advanced home robotic applications incorporating reliable revisiting strategies are dependent on very low cost but nevertheless rather accurate localization systems. In this paper a localization system based on the principle of trilateration is described. The proposed system uses only a single small base station, but achieves accuracies comparable to systems using spread beacons and it performs sufficiently for map building. Thus it is a standalone system and needs no odometry or other auxiliary sensors. Furthermore a new approach for the problem of the reliably detection of areas without direct line of sight is presented. The described system is very low cost and it is designed for use in indoor service robotics. The paper gives an overview on the system concept and special design solutions and proves the possible performances with experimental results.
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Rojas, Castro Dalia Marcela. "The RHIZOME architecture : a hybrid neurobehavioral control architecture for autonomous vision-based indoor robot navigation." Thesis, La Rochelle, 2017. http://www.theses.fr/2017LAROS001/document.
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Les travaux décrits dans cette thèse apportent une contribution au problème de la navigation autonome de robots mobiles dans un contexte de vision indoor. Il s’agit de chercher à concilier les avantages des différents paradigmes d’architecture de contrôle et des stratégies de navigation. Ainsi, nous proposons l’architecture RHIZOME (Robotic Hybrid Indoor-Zone Operational ModulE) : une architecture unique de contrôle robotique mettant en synergie ces différentes approches en s’appuyant sur un système neuronal. Les interactions du robot avec son environnement ainsi que les multiples connexions neuronales permettent à l’ensemble du système de s’adapter aux conditions de navigation. L’architecture RHIZOME proposée combine les avantages des approches comportementales (e.g. rapidité de réaction face à des problèmes imprévus dans un contexte d’environnement dynamique), et ceux des approches délibératives qui tirent profit d’une connaissance a priori de l’environnement. Cependant, cette connaissance est uniquement exploitée pour corroborer les informations perçues visuellement avec celles embarquées. Elle est représentée par une séquence de symboles artificiels de navigation guidant le robot vers sa destination finale. Cette séquence est présentée au robot soit sous la forme d’une liste de paramètres, soit sous la forme d’un plan. Dans ce dernier cas, le robot doit extraire lui-même la séquence de symboles à suivre grâce à une chaine de traitements d’images. Ainsi, afin de prendre la bonne décision lors de sa navigation, le robot traite l’ensemble de l’information perçue, la compare en temps réel avec l’information a priori apportée ou extraite, et réagit en conséquence. Lorsque certains symboles de navigation ne sont plus présents dans l’environnement de navigation, l’architecture RHIZOME construit de nouveaux lieux de référence à partir des panoramas extraits de ces lieux. Ainsi, le robot, lors de phases exploratoires, peut s’appuyer sur ces nouvelles informations pour atteindre sa destination finale, et surmonter des situations imprévues. Nous avons mis en place notre architecture sur le robot humanoïde NAO. Les résultats expérimentaux obtenus lors d’une navigation indoor, dans des scenarios à la fois déterministes et stochastiques, montrent la faisabilité et la robustesse de cette approche unifiéeThe work described in this dissertation is a contribution to the problem of autonomous indoor vision-based mobile robot navigation, which is still a vast ongoing research topic. It addresses it by trying to conciliate all differences found among the state-of-the-art control architecture paradigms and navigation strategies. Hence, the author proposes the RHIZOME architecture (Robotic Hybrid Indoor-Zone Operational ModulE) : a unique robotic control architecture capable of creating a synergy of different approaches by merging them into a neural system. The interactions of the robot with its environment and the multiple neural connections allow the whole system to adapt to navigation conditions. The RHIZOME architecture preserves all the advantages of behavior-based architectures such as rapid responses to unforeseen problems in dynamic environments while combining it with the a priori knowledge of the world used indeliberative architectures. However, this knowledge is used to only corroborate the dynamic visual perception information and embedded knowledge, instead of directly controlling the actions of the robot as most hybrid architectures do. The information is represented by a sequence of artificial navigation signs leading to the final destination that are expected to be found in the navigation path. Such sequence is provided to the robot either by means of a program command or by enabling it to extract itself the sequence from a floor plan. This latter implies the execution of a floor plan analysis process. Consequently, in order to take the right decision during navigation, the robot processes both set of information, compares them in real time and reacts accordingly. When navigation signs are not present in the navigation environment as expected, the RHIZOME architecture builds new reference places from landmark constellations, which are extracted from these places and learns them. Thus, during navigation, the robot can use this new information to achieve its final destination by overcoming unforeseen situations.The overall architecture has been implemented on the NAO humanoid robot. Real-time experimental results during indoor navigation under both, deterministic and stochastic scenarios show the feasibility and robustness of the proposed unified approach
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McConnell, Michael, Daniel Chionuma, Jordan Wright, Jordan Brandt, and Liu Zhe. "Design of an Autonomous Robot for Indoor Navigation." International Foundation for Telemetering, 2013. http://hdl.handle.net/10150/579708.
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ITC/USA 2013 Conference Proceedings / The Forty-Ninth Annual International Telemetering Conference and Technical Exhibition / October 21-24, 2013 / Bally's Hotel & Convention Center, Las Vegas, NVThis paper describes the design and implementation of an autonomous robot to navigate indoors to a specified target using an inexpensive commercial off the shelf USB camera and processor running an imbedded Linux system. The robot identifies waypoints to aid in navigation, which in our case consists of a series of quick response (QR) codes. Using a 1080p USB camera, the robot could successfully identify waypoints at a distance of over 4 meters, and navigate at a rate of 50 cm/sec.
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Keepence, B. S. "Navigation of autonomous mobile robots." Thesis, Cardiff University, 1988. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.304921.
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Miah, Md Suruz. "Autonomous mobile robot navigation using RFID technology." Thesis, University of Ottawa (Canada), 2007. http://hdl.handle.net/10393/27891.
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Navigation techniques are of a paramount importance in the field of mobile robotics. They are employed in many contexts in indoor and outdoor environments such as delivering payloads in a dynamic environment, building safety, security, building measurement, research, and driving on highways. Skilled navigation in mobile robotics usually requires solving two problems, determining the position of the robot, and selecting a motion control strategy. Moreover, when no prior knowledge of the environment is available, the problem becomes even more difficult, as the robot has to build a map of its surroundings as it moves. These three tasks ought to be solved in conjunction, since they depend on each other.
This dissertation explores the design of a cost-effective and modular navigation method for mobile robots. In particular, we will look at the process of navigating a mobile robot using the emerging RFID technology. A successful realization of this process has been addressed with two separate navigation modules. Each module presents a separate navigation algorithm for a mobile robot. In the first module, a customized RFID reader is mounted on the robot. The information provided by the reader will then be used for navigation. On the contrary, in the second module, custom-made RFID tags are attached at different locations in the navigation environment (on the ceiling of a building, posts, for instance). The position of the mobile robot is then determined based on the information provided by the tags in the robot's operating region. The angle between the robot's current direction and the target tag is used to provide actions to the actuators. In both modules, the algorithms take advantage of using analogue features of the RFID system instead of relying only on the binary tag number which conventional RFID-driven applications depend on.
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Campion, Joseph (Joseph F. ). "Autonomous navigation with mobile robot using ultrasonic rangefinders." Thesis, Massachusetts Institute of Technology, 2015. http://hdl.handle.net/1721.1/98957.
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Thesis: S.B., Massachusetts Institute of Technology, Department of Mechanical Engineering, 2015.Cataloged from PDF version of thesis.
In this thesis, I designed and implemented an autonomous navigation system for a four-wheeled mobile robot with ultrasonic sonar sensors and a National Instruments myRIO real-time controller. LabVIEW code was developed to control the motors with PWM signals based on sensor feedback. A low-pass filter was used to improve the signal to noise ratio since the signals from the ultrasonic sonar sensors were quite noisy. Finally, I developed two basic algorithms to maneuver the mobile robot: the first algorithm uses proportional control to maintain a specific distance from a target in front of the mobile robot; the second also uses proportional control to keep the robot at a specified distance away from a wall to its side as it travels forward.
by Joseph Campion.
S.B.
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Tennety, Srinivas. "Mobile robot navigation in hilly terrains." University of Cincinnati / OhioLINK, 2011. http://rave.ohiolink.edu/etdc/view?acc_num=ucin1313757135.
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Perko, Eric Michael. "Precision Navigation for Indoor Mobile Robots." Case Western Reserve University School of Graduate Studies / OhioLINK, 2013. http://rave.ohiolink.edu/etdc/view?acc_num=case1345513785.
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Ramamurthy, Mahesh. "INDOOR GEO-LOCATION AND TRACKING OF MOBILE AUTONOMOUS ROBOT." Master's thesis, University of Central Florida, 2005. http://digital.library.ucf.edu/cdm/ref/collection/ETD/id/3270.
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The field of robotics has always been one of fascination right from the day of Terminator. Even though we still do not have robots that can actually replicate human action and intelligence, progress is being made in the right direction. Robotic applications range from defense to civilian, in public safety and fire fighting. With the increase in urban-warfare robot tracking inside buildings and in cities form a very important application. The numerous applications range from munitions tracking to replacing soldiers for reconnaissance information. Fire fighters use robots for survey of the affected area. Tracking robots has been limited to the local area under consideration. Decision making is inhibited due to limited local knowledge and approximations have to be made. An effective decision making would involve tracking the robot in earth co-ordinates such as latitude and longitude. GPS signal provides us sufficient and reliable data for such decision making. The main drawback of using GPS is that it is unavailable indoors and also there is signal attenuation outdoors. Indoor geolocation forms the basis of tracking robots inside buildings and other places where GPS signals are unavailable. Indoor geolocation has traditionally been the field of wireless networks using techniques such as low frequency RF signals and ultra-wideband antennas. In this thesis we propose a novel method for achieving geolocation and enable tracking. Geolocation and tracking are achieved by a combination of Gyroscope and encoders together referred to as the Inertial Navigation System (INS). Gyroscopes have been widely used in aerospace applications for stabilizing aircrafts. In our case we use gyroscope as means of determining the heading of the robot. Further, commands can be sent to the robot when it is off balance or off-track. Sensors are inherently error prone; hence the process of geolocation is complicated and limited by the imperfect mathematical modeling of input noise. We make use of Kalman Filter for processing erroneous sensor data, as it provides us a robust and stable algorithm. The error characteristics of the sensors are input to the Kalman Filter and filtered data is obtained. We have performed a large set of experiments, both indoors and outdoors to test the reliability of the system. In outdoors we have used the GPS signal to aid the INS measurements. When indoors we utilize the last known position and extrapolate to obtain the GPS co-ordinates.M.S.Cp.E.
Department of Electrical and Computer Engineering
Engineering and Computer Science
Computer Engineering
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Prusakiewicz, Lukas, and Simon Tönnes. "Comparison of autonomous waypoint navigation methods for an indoor blimp robot." Thesis, KTH, Mekatronik, 2020. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-284458.
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The Unmanned Aerial Vehicle (UAV) has over the last years become an increasingly prevalent technology in several sectors of modern society. Many UAVs are today used in a wide series of applications, from disaster relief to surveillance. A recent initiative by the Swedish Sea Rescue Society (SSRS) aims to implement UAVs in their emergency response. By quickly deploying drones to an area of interest, an assessment can be made, prior to personnel getting there, thus saving time and increasing the likelihood of a successful rescue operation. An aircraft like this, that will travel great distances, have to rely on a navigation system that does not require an operator to continuously see the vehicle. To travel to its goal, or search an area, the operator should be able to define a travel route that the UAV follows, by feeding it a series of waypoints. As an initial step towards that kind of system, this thesis has developed and tested the concept of waypoint navigation on a small and slow airship/blimp, in a simulated indoor environment. Mainly, two commonly used navigation algorithms were tested and compared. One is inspired by a sub-category of machine learning: reinforcement learning (RL), and the other one is based on the rapidly exploring random tree (RRT) algorithm. Four experiments were conducted to compare the two methods in terms of travel distance, average speed, energy efficiency, as well as robustness towards changes in the waypoint configurations. Results show that when the blimp was controlled by the best performing RL-based version, it generally travelled a more optimal (distance-wise) path than the RRT-based method. It also, in most cases, proved to be more robust against changes in the test tracks, and performed more consistently over different waypoint configurations. However, the RRT approach usually resulted in a higher average speed and energy efficiency. Also, the RL algorithm had some trouble navigating tracks where a physical obstacle was present. To sum up, the choice of algorithm depends on which parameters are prioritized by the blimp operator for a certain track. If a high velocity and energy efficiency is desirable, the RRT-based method is recommended. However, if it is important that the blimp travels as short a distance as possible between waypoints, and a higher degree of consistency in its performance is wanted, then the RL-method should be used. Moving forward from this report, toward the future implementation of both methods in rescue operations, it would be reasonable to analyze their performance under more realistic conditions. This can be done using a real indoor airship. Looking at how hardware that do not exceed the payload of the blimp can execute both methods and how the blimp will determine its position and orientation is recommended. It would also be interesting to see how different reward function affect the performance of the blimp.Den obemannade luftfarkosten (UAV) har under de senaste åren blivit en teknik vars användning blivit allt vanligare i flera sektorer av det moderna samhället. Olika sorters UAV robotar associeras idag med en omfattande serie användningsområden, från katastrofhjälp till övervakning. Ett nyligen påbörjat initiativ från svenska sjöräddningssällskapet (SSRS) syftar till att implementera drönare i deras utryckningar. Genom att snabbt sända drönare till platsen i fråga, kan en bedömning göras innan personal kommer dit, vilket sparar tid och ökar sannolikheten för en framgångsrik räddningsaktion. En farkost som denna, som kommer att resa långa sträckor, måste förlita sig på ett navigationssystem som inte kräver att en operatör kontinuerligt ser farkosten. För att resa till sitt mål, eller söka av ett område, bör operatören kunna definiera en resväg som drönaren följer genom att ge den en serie vägpunkter. Som ett inledande steg mot den typen av system har denna uppsats utvecklat och testat begreppet vägpunktsnavigering på ett litet och långsamt luftskepp/blimp, i en simulerad inomhusmiljö. Huvudsakligen testades och jämfördes två vanligt förekommande navigationsalgoritmer. En inspirerad av en underkategori till maskininlärning: förstärkningsinlärning (RL), och den andra baserad på rapidly exploring random tree (RRT) algoritmen. Fyra experiment utfördes för jämföra båda metoderna med avseende på färdsträcka, medelhastighet, energieffektivitet samt robusthet gentemot ändringar i färdpunktskonfigurationerna. Resultaten visar att när blimpen kontrollerades av den bästa RL-baserade versionen åkte den generellt en mer avståndsmässigt optimal väg än när den RRT-baserade metoden användes. I de flesta fallen visade sig även RL-metoden vara mer robust mot förändringar i testbanorna, och presterade mer konsekvent över olika vägpunktskonfigurationer. RRT-metoden resulterade dock vanligtvis i en högre medelhastighet och energieffektivitet. RL-algoritmen hade också problem med att navigera banor där den behövde ta sig runt ett hinder. Sammanfattningsvis beror valet av algoritm på vilka parametrar som prioriteras av blimpoperatören för en viss bana. Om en hög hastighet och energieffektivitet är önskvärd rekommenderas den RRT-baserade metoden. Men om det är viktigt att blimpen reser så kort avstånd som möjligt mellan färdpunkterna, och har en jämnare prestanda, bör RL-metoden användas. För att ta nästa steg, mot en framtida implementering av båda metoder i räddningsoperationer, vore det rimligt att analysera deras prestanda under mer realistiska förhållanden. Detta skulle kunna göras inomhus med ett riktigt luftskepp. Författarna rekommenderar att undersöka om hårdvara som inte överstiger blimpens maxlast kan utföra båda metodernas beräkningar och hur blimpen bestämmer sin position och orientering. Det skulle också vara intressant att se hur olika belöningsfunktioner påverkar blimpens prestanda.
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Alsaab, Ahmad. "Behavioural strategy for indoor mobile robot navigation in dynamic environments." Thesis, University of Newcastle upon Tyne, 2015. http://hdl.handle.net/10443/2880.
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Development of behavioural strategies for indoor mobile navigation has become a challenging and practical issue in a cluttered indoor environment, such as a hospital or factory, where there are many static and moving objects, including humans and other robots, all of which trying to complete their own specific tasks; some objects may be moving in a similar direction to the robot, whereas others may be moving in the opposite direction. The key requirement for any mobile robot is to avoid colliding with any object which may prevent it from reaching its goal, or as a consequence bring harm to any individual within its workspace. This challenge is further complicated by unobserved objects suddenly appearing in the robots path, particularly when the robot crosses a corridor or an open doorway. Therefore the mobile robot must be able to anticipate such scenarios and manoeuvre quickly to avoid collisions. In this project, a hybrid control architecture has been designed to navigate within dynamic environments. The control system includes three levels namely: deliberative, intermediate and reactive, which work together to achieve short, fast and safe navigation. The deliberative level creates a short and safe path from the current position of the mobile robot to its goal using the wavefront algorithm, estimates the current location of the mobile robot, and extracts the region from which unobserved objects may appear. The intermediate level links the deliberative level and the reactive level, that includes several behaviours for implementing the global path in such a way to avoid any collision. In avoiding dynamic obstacles, the controller has to identify and extract obstacles from the sensor data, estimate their speeds, and then regular its speed and direction to minimize the collision risk and maximize the speed to the goal. The velocity obstacle approach (VO) is considered an easy and simple method for avoiding dynamic obstacles, whilst the collision cone principle is used to detect the collision situation between two circular-shaped objects. However the VO approach has two challenges when applied in indoor environments. The first challenge is extraction of collision cones of non-circular objects from sensor data, in which applying fitting circle methods generally produces large and inaccurate collision cones especially for line-shaped obstacle such as walls. The second challenge is that the mobile robot cannot sometimes move to its goal because all its velocities to the goal are located within collision cones. In this project, a method has been demonstrated to extract the colliii sion cones of circular and non-circular objects using a laser sensor, where the obstacle size and the collision time are considered to weigh the robot velocities. In addition the principle of the virtual obstacle was proposed to minimize the collision risk with unobserved moving obstacles. The simulation and experiments using the proposed control system on a Pioneer mobile robot showed that the mobile robot can successfully avoid static and dynamic obstacles. Furthermore the mobile robot was able to reach its target within an indoor environment without causing any collision or missing the target.
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Bui, Don T. "ORB : object recognition for real-time autonomous mobile robot navigation." Thesis, McGill University, 1997. http://digitool.Library.McGill.CA:80/R/?func=dbin-jump-full&object_id=20795.
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An object recognition system called ORB1 is proposed and implemented for use on a mobile robot. ORB utilizes the QUADRIS sensor platform developed at the Centre for Intelligent Machines (CIM) at McGill University, which is composed of two BIRIS2 laser rangefinders. ORB performs a series of sensory and perceptual tasks in conjunction with a mobile robot control architecture called SPOTT. ORB's main task is to sense the mobile robot's surroundings and provide laser range data, in the form of line segments, for SPOTT's map database. In an office environment, ORB also identifies and labels the structural objects (i.e., walls, doors) in this map. While navigating through an office space, the mobile robot may be required to search for certain objects in the area. In these scenarios, ORB is used to recognize the movable objects (i.e., chairs, tables and desks).ORB is able to perform its tasks in a fast and efficient manner by using simple models to represent the structural and movable objects in its database. ORB's recognition procedures only require sparse sets of range scans to identify the aforementioned objects. The structural object models are built from prior knowledge of the office environment. For example, the doorway model would consist of the known doorway widths found on the experimental office floor. ORB has been tested extensively in the CIM environment, but it can also be applied to any office space provided the structural dimensions are known a priori. ORB's models for the movable objects are idealized descriptions with the object's surfaces represented by planes. The physical dimensions of the movable object models are defined by Architectural Standards, as office furniture are built to conform to these standards.
1A system for O&barbelow;bject R&barbelow;ecognition and map B&barbelow;uilding using the QUADRIS sensor platform on a mobile robot. 2Official trademark of the National Research Council of Canada.
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Paul, André. "Design of an autonomous navigation system for a mobile robot." Thesis, McGill University, 2005. http://digitool.Library.McGill.CA:80/R/?func=dbin-jump-full&object_id=99565.
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An autonomous navigational system for a mobile robot was developed based on a Laser-Range-Finder-based path planning and navigational algorithms. The system was enhanced by incorporating collision avoidance algorithms using data from a sonar sensor array, and further improved by establishing two virtual regions in front of the robot for obstacle detection and avoidance. Several virtual detector bands with varying dimensions were also added to the sides of the robot to check for rotational clearance safety and to determine the direction of rotation. The autonomous navigational system was tested extensively under indoor environment. Test results showed that the system performed satisfactorily in navigating the mobile robot in three structured mazes under indoor conditions.An artificial landmark localization algorithm was also developed to continuously record the positions of the robot whilst it was moving. The algorithm was tested on a grid layout of 6 m x 6 m. The performance of the artificial landmark localization technique was compared with odometric and inertial measurements obtained using a dead-reckoning method and a gyroscope-corrected dead-reckoning method. The artificial landmark localization method resulted in much smaller root mean square error (0.033 m) of position estimates compared to the other two methods (0.175 m and 0.135 m respectively).
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Bui, Don T. "ORB, object recognition for real-time autonomous mobile robot navigation." Thesis, National Library of Canada = Bibliothèque nationale du Canada, 1998. http://www.collectionscanada.ca/obj/s4/f2/dsk1/tape11/PQDD_0001/MQ43999.pdf.
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Ezequiel, Carlos Favis. "Real-Time Map Manipulation for Mobile Robot Navigation." Scholar Commons, 2013. http://scholarcommons.usf.edu/etd/4481.
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Mobile robots are gaining increased autonomy due to advances in sensor and computing technology. In their current form however, robots still lack algorithms for rapid perception of objects in a cluttered environment and can benefit from the assistance of a human operator. Further, fully autonomous systems will continue to be computationally expensive and costly for quite some time. Humans can visually assess objects and determine whether a certain path is traversable, but need not be involved in the low-level steering around any detected obstacles as is necessary in remote-controlled systems. If only used for rapid perception tasks, the operator could potentially assist several mobile robots performing various tasks such as exploration, surveillance, industrial work and search and rescue operations. There is a need to develop better human-robot interaction paradigms that would allow the human operator to effectively control and manage one or more mobile robots.
This paper proposes a method of enhancing user effectiveness in controlling multiple mobile robots through real-time map manipulation. An interface is created that would allow a human operator to add virtual obstacles to the map that represents areas that the robot should avoid. A video camera is connected to the robot that would allow a human user to view the robot's environment. The combination of real-time map editing and live video streaming enables the robot to take advantage of human vision, which is still more effective at general object identification than current computer vision technology. Experimental results show that the robot is able to plan a faster path around an obstacle when the user marks the obstacle on the map, as opposed to allowing the robot to navigate on its own around an unmapped obstacle. Tests conducted on multiple users suggest that the accuracy in placing obstacles on the map decreases with increasing distance of the viewing apparatus from the obstacle. Despite this, the user can take advantage of landmarks found in the video and in the map in order to determine an obstacle's position on the map.
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Khalil, Azher Othamn K. "Fuzzy logic control and navigation of mobile vehicles." Thesis, University of Newcastle Upon Tyne, 2000. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.323486.
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Robinson, Stephen David. "The design and intelligent control of an autonomous mobile robot." Thesis, Durham University, 1996. http://etheses.dur.ac.uk/5341/.
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This thesis presents an investigation into the problems of exploration, map building and collision free navigation for intelligent autonomous mobile robots. The project began with an extensive review of currently available literature in the field of mobile robot research, which included intelligent control techniques and their application. It became clear that there was scope for further development with regard to map building and exploration in new and unstructured environments. Animals have an innate propensity to exhibit such abilities, and so the analogous use of artificial neural networks instead of actual neural systems was examined for use as a method of robot mapping. A simulated behaviour based mobile robot was used in conjunction with a growing cell structure neural network to map out new environments. When using the direct application of this algorithm, topological irregularities were observed to be the direct result of correlations within the input data stream. A modification to this basic system was shown to correct the problem, but further developments would be required to produce a generic solution. The mapping algorithms gained through this approach, although more similar to biological systems, are computationally inefficient in comparison to the methods which were subsequently developed. A novel mapping method was proposed based on the robot creating new location vectors, or nodes, when it exceeded a distance threshold from its mapped area. Network parameters were developed to monitor the state of growth of the network and aid the robot search process. In simulation, the combination of the novel mapping and search process were shown to be able to construct maps which could be subsequently used for collision free navigation. To develop greater insights into the control problem and to validate the simulation work the control structures were ported to a prototype mobile robot. The mobile robot was of circular construction, with a synchro-drive wheel configuration, and was equipped with eight ultrasonic distance sensors and an odometric positioning system. It was self-sufficient, incorporating all its power and computational resources. The experiments observed the effects of odometric drift and demonstrated methods of re-correction which were shown to be effective. Both the novel mapping method, and a new algorithm based on an exhaustive mesh search, were shown to be able to explore different environments and subsequently achieve collision free navigation. This was shown in all cases by monitoring the estimates in the positional error which remained within fixed bounds.
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Williams, Stefan Bernard. "Efficient Solutions to Autonomous Mapping and Navigation Problems." University of Sydney. Aerospace, Mechanical and Mechatronic Engineering, 2002. http://hdl.handle.net/2123/809.
Full textAbstract:
This thesis deals with the Simultaneous Localisation and Mapping algorithm as it pertains to the deployment of mobile systems in unknown environments. Simultaneous Localisation and Mapping (SLAM) as defined in this thesis is the process of concurrently building up a map of the environment and using this map to obtain improved estimates of the location of the vehicle. In essence, the vehicle relies on its ability to extract useful navigation information from the data returned by its sensors. The vehicle typically starts at an unknown location with no a priori knowledge of landmark locations. From relative observations of landmarks, it simultaneously computes an estimate of vehicle location and an estimate of landmark locations. While continuing in motion, the vehicle builds a complete map of landmarks and uses these to provide continuous estimates of the vehicle location. The potential for this type of navigation system for autonomous systems operating in unknown environments is enormous. One significant obstacle on the road to the implementation and deployment of large scale SLAM algorithms is the computational effort required to maintain the correlation information between features in the map and between the features and the vehicle. Performing the update of the covariance matrix is of O(n�) for a straightforward implementation of the Kalman Filter. In the case of the SLAM algorithm, this complexity can be reduced to O(n�) given the sparse nature of typical observations. Even so, this implies that the computational effort will grow with the square of the number of features maintained in the map. For maps containing more than a few tens of features, this computational burden will quickly make the update intractable - especially if the observation rates are high. An effective map-management technique is therefore required in order to help manage this complexity. The major contributions of this thesis arise from the formulation of a new approach to the mapping of terrain features that provides improved computational efficiency in the SLAM algorithm. Rather than incorporating every observation directly into the global map of the environment, the Constrained Local Submap Filter (CLSF) relies on creating an independent, local submap of the features in the immediate vicinity of the vehicle. This local submap is then periodically fused into the global map of the environment. This representation is shown to reduce the computational complexity of maintaining the global map estimates as well as improving the data association process by allowing the association decisions to be deferred until an improved local picture of the environment is available. This approach also lends itself well to three natural extensions to the representation that are also outlined in the thesis. These include the prospect of deploying multi-vehicle SLAM, the Constrained Relative Submap Filter and a novel feature initialisation technique. Results of this work are presented both in simulation and using real data collected during deployment of a submersible vehicle equipped with scanning sonar.
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Mayran, de Chamisso Fabrice. "Lifelong Exploratory Navigation : integrating planning, navigation and SLAM for autonomous mobile robots with finite resources." Thesis, Université Paris-Saclay (ComUE), 2016. http://www.theses.fr/2016SACLS413/document.
Full textAbstract:
Il est fondamental pour un robot d'être capable de se déplacer de manière complètement autonome afin d'accomplir une mission qui lui a été confiée, et ce avec un budget énergétique fini, dans un laps de temps contraint et sans connaissances préalables de l’environnement. Afin d'atteindre un objectif dans le plan ou l'espace, un robot doit à minima être capable d'accomplir quatre tâches: maintenir une représentation abstraite de l'environnement (une carte), être capable de se localiser à l'intérieur de cette représentation, utiliser la représentation pour planifier des itinéraires et naviguer le long de la trajectoire prévue tout en s'adaptant aux dynamiques de l'environnement et en évitant les obstacles. Chacun de ces problèmes a été étudié par la communauté de la robotique. Cependant, ces quatre composants sont en général étudiés séparément et sont par conséquent incompatibles entre eux pour l'essentiel. De plus, étant donné qu'humains et robots ne disposent que de ressources computationelles et mémorielles finies, les algorithmes de planification, navigation et SLAM devraient être capables de fonctionner avec des données incomplètes ou compressées tout en garantissant que le ou les objectifs fixés soient atteints. Dans cette thèse, la planification, la navigation et le SLAM dans des environnements arbitrairement grands et avec des ressources computationelles et mémorielles finies sont vues comme un seul problème, créant un nouveau paradigme que nous appelons Navigation Exploratoire au long de la Vie ou Lifelong Exploratory NavigationOne of the yet unresolved canonical problems of robotics is to have robots move completely autonomously in order to accomplish any mission they are charged with, with time and resource constraints and without prior knowledge of the environment. Reaching a goal requires the robot to perform at least four tasks: maintaining an abstract representation of the environment (map), being able to localize itself within this representation, using the representation to plan paths and navigating on the planned paths while handling dynamics of the environment and avoiding obstacles. Each of these problems has been studied extensively by the robotics community. However, the four components are usually studied separately, and as a result are mostly incompatible with each other. Additionally, since humans as well as robots have to operate with finite memory and computing resources, long running planning, navigation and SLAM algorithms may have to operate on incomplete or compressed data while guaranteeing that the goal(s) can still be reached. In this thesis, planning, navigation and SLAM in arbitrarily large environments with finite computing resources and memory are considered as one single problem, for a new bio-inspired paradigm which we call Lifelong Exploratory Navigation
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Ferreira, Caetano Filipe Costa de Noronha. "Autonomous navigation and multi-sensorial real-time mocalization for a mobile robot." Doctoral thesis, Universidade de Aveiro, 2008. http://hdl.handle.net/10773/2468.
Full textAbstract:
Doutoramento em Engenharia MecânicaO principio por detrás da proposta desta tese é a navegação de ambientes utilizando uma sequência de instruções condicionadas nas observações feitas pelo robô. Esta sequência é denominada como uma 'missão de navegação'. A interacção com um robô através de missões permitirá uma interface mais eficaz com humanos e a navegação de ambientes de maior escala e duma forma mais simplificada. No entanto, esta abordagem abre problemas novos no que diz respeito à forma como os dados sensoriais devem ser representados e utilizados. Neste trabalho representações binárias foram introduzidas para facilitar a integração dos dados multi-sensoriais, a dimensionalidade da qual foi reduzida através da utilização de Misturas de Distribuições de tipo Bernoulli. Foi também aplicada a técnica de cadeias de Markov ocultas (Hidden Markov Models), que contou com o desenvolvimento e a utilização dum modelo de cadeia de Markov original, esta que consegue explorar a informação contextual da sequência da missão. Uma aplicação que surgiu da aplicação do método de localização foi a criação de representações topologicas do ambiente sem ter que previamente recorrer à criação de mapas geométricos. Outras contribuições incluem a aplicação de métodos para a extracção de propriedades locais em imagens e o desenvolvimento de propriedades extraídas a partir de varrimentos dum medidor de distancia laser.
This thesis evaluates the requisites for the specification of mobile robot 'Missions' for navigation within environments that are typically used by human beings. The principal idea behind the proposal of this thesis was to allow localization and navigation by providing a sequence of instructions, the execution of each instruction being conditional on the expected sensor data. This approach to navigation is expected to lead to new applications which will include the autonomous navigation of environments of very large scale. It is also expected to lead to a more intuitive interaction between mobile robots and humans. However, the concept of the navigation Mission opens up new problems namely in the way in which the sequence of instructions and the expected observations are to be represented. To solve this problem, binary features were used to integrate observations from multiple sensors, the dimensionality of which was reduced by modelling the binary data as a Finite Mixture Model comprised of Bernoulli distributions. Another original contribution was the modification of the Markov Chains used in Hidden Markov Models to enable the use of the sequential context in which the expected observations are specified in the navigation Mission. The localization method that was developed enabled the direct creation of a topological representation of an environment without recourse to an intermediate geometric map. Other contributions include developments that were made in the characterisation of images through the application of local features and of laser range scans through the creation of original features based on the scan contour and free-area properties.
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Muhammad, Naveed. "Contributions to the use of 3D lidars for autonomous navigation : calibration and qualitative localization." Thesis, Toulouse, INSA, 2012. http://www.theses.fr/2012ISAT0001/document.
Full textAbstract:
Afin de permettre une navigation autonome d'un robot dans un environnement, le robot doit être capable de percevoir son environnement. Dans la littérature, d'une manière générale, les robots perçoivent leur environnement en utilisant des capteurs de type sonars, cameras et lidar 2D. L'introduction de nouveaux capteurs, nommés lidar 3D, tels que le Velodyne HDL-64E S2, a permis aux robots d'acquérir plus rapidement des données 3D à partir de leur environnement. La première partie de cette thèse présente une technique pour la calibrage des capteurs lidar 3D. La technique est basée sur la comparaison des données lidar à un modèle de vérité de terrain afin d'estimer les valeurs optimales des paramètres de calibrage. La deuxième partie de la thèse présente une technique pour la localisation et la détection de fermeture de boucles pour les robots autonomes. La technique est basée sur l'extraction et l'indexation des signatures de petite-taille à partir de données lidar 3D. Les signatures sont basées sur les histogrammes de l'information de normales de surfaces locale extraite à partir des données lidar en exploitant la disposition des faisceaux laser dans le dispositif lidarIn order to autonomously navigate in an environment, a robot has to perceive its environment correctly. Rich perception information from the environment enables the robot to perform tasks like avoiding obstacles, building terrain maps, and localizing itself. Classically, outdoor robots have perceived their environment using vision or 2D lidar sensors. The introduction of novel 3D lidar sensors such as the Velodyne device has enabled the robots to rapidly acquire rich 3D data about their surroundings. These novel sensors call for the development of techniques that efficiently exploit their capabilities for autonomous navigation.The first part of this thesis presents a technique for the calibration of 3D lidar devices. The calibration technique is based on the comparison of acquired 3D lidar data to a ground truth model in order to estimate the optimal values of the calibration parameters. The second part of the thesis presents a technique for qualitative localization and loop closure detection for autonomous mobile robots, by extracting and indexing small-sized signatures from 3D lidar data. The signatures are based on histograms of local surface normal information that is efficiently extracted from the lidar data. Experimental results illustrate the developments throughout the manuscript
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Schworer, Ian Josef. "Navigation and Control of an Autonomous Vehicle." Thesis, Virginia Tech, 2005. http://hdl.handle.net/10919/32634.
Full textAbstract:
The navigation and control of an autonomous vehicle is a highly complex task. Making a vehicle intelligent and able to operate â unmannedâ requires extensive theoretical as well as practical knowledge. An autonomous vehicle must be able to make decisions and respond to situations completely on its own. Navigation and control serves as the major limitation of the overall performance, accuracy and robustness of an autonomous vehicle. This thesis will address this problem and propose a unique navigation and control scheme for an autonomous lawn mower (ALM).
Navigation is a key aspect when designing an autonomous vehicle. An autonomous vehicle must be able to sense its location, navigate its way toward its destination, and avoid obstacles it encounters. Since this thesis attempts to automate the lawn mowing process, it will present a navigational algorithm that covers a bounded region in a systematic way, while avoiding obstacles. This algorithm has many applications including search and rescue, floor cleaning, and lawn mowing. Furthermore, the robustness and utility of this algorithm is demonstrated in a 3D simulation.
This thesis will specifically study the dynamics of a two-wheeled differential drive vehicle. Using this dynamic model, various control techniques can then be applied to control the movement of the vehicle. This thesis will consider both open loop and closed loop control schemes. Optimal control, path following, and trajectory tracking are all considered, simulated, and evaluated as practical solutions for control of an ALM.
To design and build an autonomous vehicle requires the integration of many sensors, actuators, and controllers. Software serves as the glue to fuse all these devices together. This thesis will suggest various sensors and actuators that could be used to physically implement an ALM. This thesis will also describe the operation of each sensor and actuator, present the software used to control the system, and discuss physical limitations and constraints that might be encountered while building an ALM.Master of Science
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Hughes, Bradley Evan. "A Navigation Subsystem for an Autonomous Robot Lawn Mower." Case Western Reserve University School of Graduate Studies / OhioLINK, 2011. http://rave.ohiolink.edu/etdc/view?acc_num=case1312391797.
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Corominas, Murtra Andreu. "Map-based localization for urban service mobile robotics." Doctoral thesis, Universitat Politècnica de Catalunya, 2011. http://hdl.handle.net/10803/41555.
Full textAbstract:
Mobile robotics research is currently interested on exporting autonomous navigation results achieved in indoor environments, to more challenging environments, such as, for instance, urban pedestrian areas. Developing mobile robots with autonomous navigation capabilities in such urban environments supposes a basic requirement for a upperlevel service set that could be provided to an users community. However, exporting indoor techniques to outdoor urban pedestrian scenarios is not evident due to the larger size of the environment, the dynamism of the scene due to
pedestrians and other moving obstacles, the sunlight conditions, and the high presence of three dimensional elements such as ramps, steps, curbs or holes. Moreover, GPS-based mobile robot localization has demonstrated insufficient
performance for robust long-term navigation in urban environments.
One of the key modules within autonomous navigation is localization. If localization supposes an a priori map, even if it is not a complete model of the environment, localization is called map-based. This assumption is realistic since current
trends of city councils are on building precise maps of their cities, specially of the most interesting places such as city downtowns. Having robots localized within a map allows for a high-level planning and monitoring, so that robots can
achieve goal points expressed on the map, by following in a deliberative way a previously planned route.
This thesis deals with the mobile robot map-based localization issue in urban pedestrian areas. The thesis approach uses the particle filter algorithm, a well-known and widely used probabilistic and recursive method for data fusion and state estimation. The main contributions of the thesis are divided on four aspects: (1) long-term experiments of mobile robot 2D and 3D position tracking in real urban pedestrian scenarios within a full autonomous navigation framework, (2) developing a fast and accurate technique to compute on-line range observation models in 3D environments, a basic step required by the real-time performance of the developed particle filter, (3) formulation of a particle filter that integrates asynchronous data streams and (4) a theoretical proposal to solve the global localization problem in an active and cooperative way, defining cooperation as either information sharing among the robots or planning joint actions to solve a common goal.Actualment, la recerca en robòtica mòbil té un interés creixent en exportar els resultats de navegació autònoma aconseguits en entorns interiors cap a d'altres tipus d'entorns més exigents, com, per exemple, les àrees urbanes peatonals. Desenvolupar capacitats de navegació autònoma en aquests entorns urbans és un requisit bàsic per poder proporcionar un conjunt de serveis de més alt nivell a una comunitat d'usuaris. Malgrat tot, exportar les tècniques d'interiors cap a entorns exteriors peatonals no és evident, a causa de la major dimensió de l'entorn, del dinamisme de l'escena provocada pels peatons i per altres obstacles en moviment, de la resposta de certs sensors a la il.luminació natural, i de la constant presència d'elements tridimensionals tals com rampes, escales, voreres o forats. D'altra banda, la localització de robots mòbils basada en GPS ha demostrat uns resultats insuficients de cara a una navegació robusta i de llarga durada en entorns urbans. Una de les peces clau en la navegació autònoma és la localització. En el cas que la localització consideri un mapa conegut a priori, encara que no sigui un model complet de l'entorn, parlem d'una localització basada en un mapa. Aquesta assumpció és realista ja que la tendència actual de les administracions locals és de construir mapes precisos de les ciutats, especialment dels llocs d'interés tals com les zones més cèntriques. El fet de tenir els robots localitzats en un mapa permet una planificació i una monitorització d'alt nivell, i així els robots poden arribar a destinacions indicades sobre el mapa, tot seguint de forma deliberativa una ruta prèviament planificada. Aquesta tesi tracta el tema de la localització de robots mòbils, basada en un mapa i per entorns urbans peatonals. La proposta de la tesi utilitza el filtre de partícules, un mètode probabilístic i recursiu, ben conegut i àmpliament utilitzat per la fusió de dades i l'estimació d'estats. Les principals contribucions de la tesi queden dividides en quatre aspectes: (1) experimentació de llarga durada del seguiment de la posició, tant en 2D com en 3D, d'un robot mòbil en entorns urbans reals, en el context de la navegació autònoma, (2) desenvolupament d'una tècnica ràpida i precisa per calcular en temps d'execució els models d'observació de distàncies en entorns 3D, un requisit bàsic pel rendiment del filtre de partícules a temps real, (3) formulació d'un filtre de partícules que integra conjunts de dades asíncrones i (4) proposta teòrica per solucionar la localització global d'una manera activa i cooperativa, entenent la cooperació com el fet de compartir informació, o bé com el de planificar accions conjuntes per solucionar un objectiu comú.
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Gonullu, Muhammet Kasim. "Development Of A Mobile Robot Platform To Be Used In Mobile Robot Research." Master's thesis, METU, 2013. http://etd.lib.metu.edu.tr/upload/12615654/index.pdf.
Full textAbstract:
Robotics is an interdisciplinary subject and combines mechanical, computer and electrical engineering components together to solve different kinds of problems. In order to build robotic systems, these disciplines should be integrated. Therefore, mobile robots can be used as a tool in education for teaching engineering concepts. They can be employed to be used in undergraduate, graduate and doctorate research. Hands on experience on a mobile robot increase motivation of the students on the topic and give them precious practical knowledge. It also delivers students new skills like teamwork, problem solving, creativity, by executing robotic exercises. To be able to fulfill these outcomes, universities and research centers need mobile robot platforms that are modular, easy to build, cheap and flexible. However it should be also powerful and capable of being used in different research studies and hence be customizable depending on the requirements of these topics.
This thesis aims at building an indoor mobile robot that can be used as a platform for developing algorithms involving various sensors incorporated onto a mobile platform. More precisely, it can be used as a base for indoor navigation and localization algorithms, as well as it can be used as platform for developing algorithms for larger autonomous mobile robots. The thesis work involves the design and manufacturing of a mobile robot platform that can potentially facilitate mobile robotics research that involves use of various hardware to develop and test different perception and navigation algorithms.
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Bauman, Cheryl Lynn. "Autonomous Navigation of a Ground Vehicle to Optimize Communication Link Quality." Thesis, Virginia Tech, 2006. http://hdl.handle.net/10919/36302.
Full textAbstract:
The wireless technology of today provides combat systems with the potential to communicate mission critical data to every asset involved in the operation. In such a dynamic environment, the network must be able maintain communication by adapting to subsystems moving relative to each other. A theoretical and experimental foundation is developed that allows an autonomous ground vehicle to serve as an adaptive communication node in a larger network. The vehicle may perform other functions, but its primary role is to constantly reposition itself to maintain optimal link quality for network communication. Experimentation with existing wireless network hardware and software led to the development, implementation, and analysis of two main concepts that provided a signal optimization solution. The first attracts the communication ground vehicle to the network subsystems with weaker links using a vector summation of the signal-to-noise ratio and network subsystem position. This concept continuously generates a desired waypoint for repositioning the ground vehicle. The second concept uses a-priori GIS data to evaluate the desired vehicle waypoint determined by the vector sum. The GIS data is used primarily for evaluating the viewshed, or line-of-sight, between two network subsystems using elevation data. However, infrastructure and ground cover data are also considered in navigation planning. Both concepts prove to be powerful tools for effective autonomous repositioning for maximizing the communication link quality.Master of Science
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Da, Silva Filho José Grimaldo. "Towards natural human-robot collaboration during collision avoidance." Thesis, Université Grenoble Alpes, 2020. http://www.theses.fr/2020GRALM003.
Full textAbstract:
Ces dernières années, la tendance des robots capables de partager des espaces domestiques ou de travail avec des personnes a connu une croissance importante. Du robot guide à l’aspirateur autonome, ces robots dits "de service" sont de plus en plus intégrés dans la vie quotidienne des profanes.Bien que les progrès des logiciels et du matériel aient permis un comportement plus intelligent et plus autonome des robots, la présence plus répandue des robots parmi les gens pose un nouvel ensemble de défis pour la communauté scientifique. Même si les gens ne sont pas que des obstacles ordinaires, les approches classiques de navigation se sont concentrées sur la garantie d’un mouvement sans collision en supposant que les gens sont soit des obstacles statiques, soit des obstacles en mouvement. Traiter les gens comme des obstacles ordinaires signifie qu’un robot est incapable de tenir compte de la réaction d’une personne au mouvement du robot. Pour cette raison, un mouvement donné d’un robot peut être perçu comme dangereux ou inhabituel, ce qui incite les gens à adopter un mouvement plus prudent pendant qu’ils réfléchissent activement aux intentions du robot. Dans ce contexte, notre travail se concentre sur la manière dont un robot doit se déplacer au milieu des gens, ce qu’on appelle un problème de Mouvement homme-robot. Plus précisément, nous nous concentrons sur la reproduction d’une caractéristique de l’interaction homme-homme lors de la prévention des collisions, à savoir le partage mutuel des adaptations effectuées pour résoudre une collision.Etant donné que les situations d’évitement des collisions entre les personnes sont résolues en coopération, cette thèse modélise la manière dont cette coopération se fait afin qu’un robot puisse reproduire leur comportement. Pour ce faire, des centaines de situations où deux personnes ont des trajectoires de croisement ont été analysées. À partir de ces trajectoires humaines impliquant une tâche d’évitement des collisions, nous avons déterminé comment l’effort total est partagé entre chaque agent en fonction de plusieurs facteurs de l’interaction tels que l’angle de croisement, le temps avant collision ainsi que la vitesse. Pour valider notre approche, une preuve de concept est intégrée dans le framework Robot Operating System (ROS) utilisant une version modifiée de Reciprocal Velocity Objects (RVO) afin de répartir l’effort d’évitement des collisions de façon humanoïde.Bien que la modélisation de la manière dont un robot devrait collaborer avec des personnes ait fourni une base de référence importante pour le comportement d’évitement des collisions, la collaboration pendant une collision pourrait éventuellement engendrer de conséquences négatives. En particulier, pour assurer une collaboration efficace lors de la prévention des collisions, il est nécessaire de prévoir si la personne tentera d’éviter la collision en passant du côté gauche ou du côté droit, c’est-à-dire en prenant une décision de classe homotopie. Cependant, à situation ou cette décision de classe d’homotopie n’est pas cohérente pour les gens, le robot est obligé de tenir compte de la possibilité que les deux agents tentent de se croiser d’un côté ou de l’autre et prennent une décision nuisible à la prévention des collisions.Ainsi, dans cette thèse, nous évaluons également ce qui détermine la frontière qui sépare la décision d’éviter la collision d’un côté ou de l’autre. En faisant une approximation de l’incertitude entourant cette limite, nous avons élaboré une stratégie d’évitement des collisions qui tente de résoudre ce problème. Notre approche est basée sur l’idée que le robot doit planifier son mouvement d’évitement des collisions de telle sorte que, même si les agents, dans un premier temps, choisissent à tort de se croiser sur des côtés différents, le robot et la personne soient capables de percevoirClassical approaches for robot navigation among people have focused on guaranteed collision-free motion with the assumption that people are either static or moving obstacles. However, people are not ordinary obstacles. People react to the presence and the motion of a robot. In this context, a robot that behaves in human-like manner has been shown to reduce overall cognitive effort for nearby people as they do not have to actively think about a robot's intentions while moving on its proximity.Our work is focused on replicating a characteristic of human-human interaction during collision avoidance that is the mutual sharing of effort to avoid a collision. Based on hundreds of situations where two people have crossing trajectories, we determined how total effort is shared between agents depending on several factors of the interaction such as crossing angle and time to collision. As a proof of concept our generated model is integrated into gls{rvo}. For validation, the trajectories generated by our approach are compared to the standard gls{rvo} and to our dataset of people with crossing trajectories.Collaboration during collision avoidance is not without its potential negative consequences. For effective collaboration both agents have to pass each other on the same side. However, whenever the decision of which side collision should be avoided from is not consistent for people, the robot should also account for the risk that both agents will attempt to incorrectly cross each other on different sides. Our work first determines the uncertainty around this decision for people. Based on this, a collision avoidance approach is proposed so that, even if agents initially choose to incorrectly attempt to cross each other on different sides, the robot and the person would be able to perceive the side from which collision should be avoided in their following collision avoidance action. To validate our approach, several distinct scenarios where the crossing side decision is ambiguous are presented alongside collision avoidance trajectories generated by our approach in such scenarios
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Sarti, Lorenzo. "Deep Reinforcement Learning for Robot Navigation in Unstructured Environments." Master's thesis, Alma Mater Studiorum - Università di Bologna, 2021.
Find full textAbstract:
This thesis is focused on deep reinforcement learning for mobile robot navigation in unstructured environments. Autonomous navigation has been mainly tackled through map-based algorithms, which are ineffective in many situations like exploration or rescue missions. For mapless scenarios, the simultaneous localization and planning (SLAM) represents a cornerstone on which a wide variety of algorithms are built. However the difficulty of maintaining a map from sensory inputs, typical of these methods, is leading the research community to look for alternatives. Deep reinforcement learning aims at solving the autonomous navigation problem end-to-end, by directly mapping high-dimensional inputs to actions, without the need for a model of the environment.
In this thesis, a model-free reinforcement learning approach is adopted: a variant of the tabular Q-learning algorithm, called deep Q-learning, uses a deep neural network to approximate the action-value function and to map states into velocity commands, without the need of an expert or supervisor. The learning model is trained in simulation on TurtleBot3 and Curiosity mobile robots in two different environments. After that, the neural network trained on TurtleBot3 is transferred on Curiosity and then fine-tuned on new navigation environments. The results are then compared to those obtained by training the model from scratch, with random initialization of the parameters: this comparison shows how, thanks to the pre-training, the rover manages to reach on average a higher number of targets per episode throughout the entire simulation.
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Mudgal, Apurva. "Worst-case robot navigation in deterministic environments." Diss., Georgia Institute of Technology, 2009. http://hdl.handle.net/1853/33924.
Full textAbstract:
We design and analyze algorithms for the following two robot navigation problems:
1. TARGET SEARCH. Given a robot located at a point s in the plane, how will a robot navigate to a goal t in the presence of unknown
obstacles ?
2. LOCALIZATION. A robot is "lost" in an environment with a map of its surroundings. How will it find its true location by traveling the minimum distance ?
Since efficient algorithms for these two problems will make a robot completely autonomous, they have held the interest of both robotics and computer science communities.
Previous work has focussed mainly on designing competitive algorithms where the robot's performance is compared to that of an omniscient adversary. For example, a competitive algorithm for target search will compare the distance traveled by the robot with the shortest path from
s to t.
We analyze these problems from the worst-case perspective, which, in our view, is a more appropriate measure. Our results are :
1. For target search, we analyze an algorithm called Dynamic A*. The robot continuously moves to the goal on the shortest path which it recomputes on the discovery of obstacles. A variant of this algorithm has been employed in Mars Rover prototypes.
We show that D* takes O(n log n) time on planar graphs and also show a comparable bound on arbitrary graphs. Thus, our results show that D* combines the optimistic possibility of reaching the goal very soon while competing with depth-first search within a logarithmic factor.
2. For the localization problem, worst-case analysis compares the performance of the robot with the optimal decision tree over the set of possible locations.
No approximation algorithm has been known. We give a polylogarithmic approximation algorithm and also show a near-tight lower bound for the grid graphs commonly used in practice. The key idea is to plan travel on a "majority-rule map" which eliminates uncertainty and permits a link to the half-Group Steiner problem. We also extend the problem to polygonal maps by discretizing the domain using novel geometric techniques.
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Carbajal, Jhony, Grimaldo Quispe, Heyul Chavez-Arias, Carlos Raymundo-Ibanez, and Francisco Dominguez. "Mobile Robot for the Spraying of Corn Crops with autonomous navigation camera for the Plains of the Andes." Institute of Electrical and Electronics Engineers Inc, 2019. http://hdl.handle.net/10757/656305.
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El texto completo de este trabajo no está disponible en el Repositorio Académico UPC por restricciones de la casa editorial donde ha sido publicado.The incidence of the disease in horticultural crops is one of the important problems that affect the production of fruits, vegetables and flowers. Regular monitoring of crops for early diagnosis and treatment with pesticides or removal of the affected crop is part of the solution to minimize crop loss. The monitoring of crops by human labor is expensive, time consuming, prone to errors due to insufficient knowledge of the disease and highly repetitive at different stages of crop growth. These needs have motivated to design the mobile robot with vision sensors for navigation through the field. The robot has been designed in the Autodesk Inventor software. Programming for navigation is done in the Arduino Mega 2560 tool. Image capture has been performed using the RGB camera. Image processing for the identification of the disease and its representation in a graphical user interface has been performed using an algorithm in MATLAB R2018B that interacts with the Arduino tool through a communication bus. The system developed consists of the design of a prototype that uses simple and cost effective equipment such as Raspberry Pi, RGB camera, two motors and sensors that allow the autonomous fumigation of corn crops.
Revisión por pares
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Lesueur-Grand, Caroline. "Le Robot mobile compagnon : De l'apprentissage interactif vers un modèle d'IHM intuitive." Thesis, Cergy-Pontoise, 2017. http://www.theses.fr/2017CERG0901/document.
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Dans le cadre de cette thèse, nous abordons les problèmes liés à un robot autonome devant apprendre différentes tâches sensori-motrices dans des situations d’interaction et d’imitation. D’un point de vue théorique et dans le cadre des Interactions Homme-Machine (IHM), nous aborderons notamment les notions liées aux phénomènes d’entraînement rythmiques, de coordination interpersonnelle et de synchronisation intentionnelles et non-intentionnelles qui jouent un rôle important dans les interactions sociales. En particulier nous défendons l’hypothèse que des mécanismes d’entrainement rythmiques facilitent grandement l’apprentissage dans des situations d’interactions Homme-Robot. Leur prise en compte dans la conception de nouvelles IHMs est primordiale pour les rendre plus « intuitives ». A long terme, nous aimerions que le robot puisse utiliser ces signaux sociaux pour comprendre les intentions de son partenaire.L’utilisation d’une tâche complexe est ici nécessaire pour que le robot soit confronté à des situations d’échecs qui devront introduire des modifications de comportement non seulement de la part du partenaire mais aussi et surtout de la part du robot. Ces situations introduiront des modifications du rythme dans l’interaction au cours de l'apprentissage. Pour réussir ce pari, le robot devra être capable d’auto évaluer à la fois son comportement vis à vis de la tâche en cours d’exécution (et d’apprentissage) et son comportement d’interaction avec son partenaire.Nous proposons de travailler sur un « robot mobile compagnon » capable d’apprendre de manière interactive (avec son compagnon) à naviguer. L’utilisation de jeux d’interaction et d’imitation comme moyen d’apprentissage mais surtout de communication permet d’envisager de nouveaux principes d’IHM (Interface Homme-Machine) où l’interaction n’est plus considérée comme une « charge », elle devient au contraire plaisanteIn this thesis, we address the issues related to autonomous learning of different sensory-motor tasks using interaction and imitation. From a theoretical point of view and considering Human Machine Interaction (HMI), we will question the concepts linked to rhythmic entrainment, interpersonal coordination, and also intentional and unintentional synchronisations and their contribution to improve social interactions. Particularly, these mechanisms facilitate human-human interactions. Consequently, we defend the idea that taking them into account is essential to build more intuitive HMI. In near future applications, we would like to make the robot able to use these signals to improve its understanding the human partner intentions.Using a complex task is, then, necessary to confront the robot to failures that will introduce behavioral changes for both the human and the robot agents. These situations will introduce interaction rhythm modifications during learning phases. In this aim, the robot should be able to self assess its behavior regarding both the current task to learn and its interaction with its partner.We propose to work on a 'mobile companion robot' able to learn interactively (with its partner) to navigate. Using interaction games and imitation as a medium of learning and above all of communication, allows to consider new principles of HMI (Human Machine Interface) where the interaction is no longer considered as a 'load', it becomes rather pleasant
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Chmelař, Jakub. "Mobilní robot s GNSS navigací." Master's thesis, Vysoké učení technické v Brně. Fakulta elektrotechniky a komunikačních technologií, 2018. http://www.nusl.cz/ntk/nusl-376999.
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The diploma thesis is focused on the topic of global satellite navigation of mobile robots. The paper describes the principle of currently available global satellite navigation systems. The main element of the thesis is the proposal of mobile robot navigation algorithm. An integral part is also the design of a mobile robot to verify the functionality of the navigation algorithm. The robot software program is described. At the end, everything is verified by real experiments.
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Krysl, Jakub. "Návrh a realizace řídících systému pro mobilní robot." Master's thesis, Vysoké učení technické v Brně. Fakulta strojního inženýrství, 2016. http://www.nusl.cz/ntk/nusl-254397.
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This thesis deals with the design and implementation of autonomous robot with using of the platform ROS. Its goal is to get to know the ROS and use it to implement autonomous control of real robot Leela.
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Huang, Henry. "Bearing-only SLAM : a vision-based navigation system for autonomous robots." Queensland University of Technology, 2008. http://eprints.qut.edu.au/28599/.
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To navigate successfully in a previously unexplored environment, a mobile robot must be able to estimate the spatial relationships of the objects of interest accurately. A Simultaneous Localization and Mapping (SLAM) sys- tem employs its sensors to build incrementally a map of its surroundings and to localize itself in the map simultaneously. The aim of this research project is to develop a SLAM system suitable for self propelled household lawnmowers. The proposed bearing-only SLAM system requires only an omnidirec- tional camera and some inexpensive landmarks. The main advantage of an omnidirectional camera is the panoramic view of all the landmarks in the scene. Placing landmarks in a lawn field to define the working domain is much easier and more flexible than installing the perimeter wire required by existing autonomous lawnmowers. The common approach of existing bearing-only SLAM methods relies on a motion model for predicting the robot’s pose and a sensor model for updating the pose. In the motion model, the error on the estimates of object positions is cumulated due mainly to the wheel slippage. Quantifying accu- rately the uncertainty of object positions is a fundamental requirement. In bearing-only SLAM, the Probability Density Function (PDF) of landmark position should be uniform along the observed bearing. Existing methods that approximate the PDF with a Gaussian estimation do not satisfy this uniformity requirement. This thesis introduces both geometric and proba- bilistic methods to address the above problems. The main novel contribu- tions of this thesis are: 1. A bearing-only SLAM method not requiring odometry. The proposed method relies solely on the sensor model (landmark bearings only) without relying on the motion model (odometry). The uncertainty of the estimated landmark positions depends on the vision error only, instead of the combination of both odometry and vision errors. 2. The transformation of the spatial uncertainty of objects. This thesis introduces a novel method for translating the spatial un- certainty of objects estimated from a moving frame attached to the robot into the global frame attached to the static landmarks in the environment. 3. The characterization of an improved PDF for representing landmark position in bearing-only SLAM. The proposed PDF is expressed in polar coordinates, and the marginal probability on range is constrained to be uniform. Compared to the PDF estimated from a mixture of Gaussians, the PDF developed here has far fewer parameters and can be easily adopted in a probabilistic framework, such as a particle filtering system. The main advantages of our proposed bearing-only SLAM system are its lower production cost and flexibility of use. The proposed system can be adopted in other domestic robots as well, such as vacuum cleaners or robotic toys when terrain is essentially 2D.
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Vodrážka, Jakub. "Návrh konstrukce mobilního autonomního robotu." Master's thesis, Vysoké učení technické v Brně. Fakulta strojního inženýrství, 2010. http://www.nusl.cz/ntk/nusl-229186.
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The thesis deals with design of the device for testing the localization techniques for indoor navigation. Autonomous robot was designed as the most appropriate platform for testing. The thesis is divided into three parts. The first one describes various kinds of robots, their possible use and sensors, which could be of use for solving the problem. The second part deals with the design and construction of the robot. The robot is built on the chassis of the differential type with support spur. Two electric motors with a gearbox and output shaft speed sensor represent the drive unit. Coat of the robot was designed for good functionality and attractive overall look. The robot is also used for the presentation of robotics. Thesis provides complete design of chassis and body construction, along with control section and sensorics. The last part describes a statistical model of the robot movement, which was based on several performed experiments. The experiments were realized to find any possible deviations of sensor measurement comparing to the real situation.
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Růžička, Michal. "Návrh a realizace navigačního systému pro autonomní mobilní robot." Master's thesis, Vysoké učení technické v Brně. Fakulta strojního inženýrství, 2012. http://www.nusl.cz/ntk/nusl-230240.
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This thesis deals with design of navigation system for autonomous mobile robots, which is based on the infrared light. The system is based on measuring the relavive angles using landmarks in the enviroment that make the robot can orient and recognize its absolute position in an environment in which it operates.
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Vávra, Patrik. "Využití nástroje ROS pro řízení autonomního mobilního robotu." Master's thesis, Vysoké učení technické v Brně. Fakulta strojního inženýrství, 2019. http://www.nusl.cz/ntk/nusl-402584.
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Tato práce se zabývá vytvořením lokalizačního a navigačního systému mobilního robota pro vnitřní prostředí pomocí frameworku ROS. Stručně je zde představen projekt, v rámci kterého diplomová práce vznikla, a jeho cíle. V rešeršní části je v krátkosti popsán ROS framework, simulační prostředí Gazebo a senzory, kterými robot disponuje. Následuje vytvoření modelu robota a simulačního prostředí, v němž jsou vyzkoušeny lokalizační, navigační a další rutiny. V experimentální části je provedeno testování senzorů a popsáno využití jejich výstupů. Následně jsou upraveny a otestovány algoritmy ze simulace na reálném robotovi. V závěru jsou popsány vytvořené vzdělávací minihry. Hlavním výstupem této práce je funkční stavový automat, který umožňuje manuální ovládání, zadávání cílů pro navigaci a v případě potřeby zajistí autonomní nabití robota.
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Ben, Said Hela. "Navigation autonome et commande référencée capteurs de robots d'assistance à la personne." Thesis, Limoges, 2018. http://www.theses.fr/2018LIMO0016/document.
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L’autonomie d’un agent mobile se définit par sa capacité à naviguer dans un environnement sans intervention humaine. Cette tâche s’avère très demandée pour les robots d’assistance à la personne. C’est pour cela que notre contribution s’est portée en particulier sur l’instrumentation et l’augmentation de l’autonomie d’un fauteuil roulant pour les personnes à mobilité réduite. L’objectif de ce travail est de concevoir des lois de commande qui permettent à un robot de naviguer en temps réel et en toute autonomie dans un environnement inconnu. Un cadre de perception virtuelle unifié est introduit et permet de projeter l’espace navigable obtenu par des observations éventuellement multiples. Une approche de navigation autonome et sûre a été conçue pour se déplacer dans un environnement peu encombré dont la structure peut être assimilée à un couloir (lignes au sol, murs, délimitation herbes, routes...). La problématique a été résolue en utilisant le formalisme de l’asservissement visuel. Les caractéristiques visuelles utilisées dans la loi de commande ont été construites à partir de la représentation virtuelle (à savoir la position du point de fuite et l’orientation de la ligne médiane du couloir). Pour assurer une navigation sûre et lisse, même lorsque ces paramètres ne peuvent pas être extraits, nous avons conçu un observateur d’état pour estimer les caractéristiques visuelles dans le but de maintenir la commande fonctionnelle du robot. Cette approche permet de faire naviguer un robot mobile dans un couloir même en cas de défaillance sensorielle (données non fiables) et/ou de perte de mesure. La première contribution de cette thèse a été étendue en traitant tout type d’environnement encombré statique ou dynamique. Cela a été réalisé en utilisant le diagramme de Voronoï. Le diagramme de Voronoï généralisé, également appelé squelette, est une représentation puissante de l’environnement. Il définit un ensemble de chemins à la distance maximale des obstacles. Dans ce travail, une approche d’asservissement visuel basée sur le squelette extrait en temps réel était proposée pour une navigation autonome et sûre des robots mobiles. La commande est basée sur une approximation du DVG local en utilisant le Delta Medial axis, un algorithme de squelettisation rapide et robuste. Ce dernier produit un squelette filtré de l’espace libre entourant le robot en utilisant un paramètre qui prend en compte la taille du robot. Cette approche peut faire face aux bruits de mesure au niveau de la perception et au niveau de la commande à cause des glissement des roues. C’est pour cela que nous avons conçu une approche d’asservissement visuel sur une prédiction d’une linéarisation du DVG. Une analyse complète a été réalisée pour montrer la stabilité des lois de commandes proposées. Des simulations et des tests expérimentaux valident l’approche proposéeThe autonomy of a mobile agent is defined by its ability to navigate in an environment without human intervention. This task is very required for personal assistance robots. That’s why our contribution has been particularly focused on instrumentation and increasing the autonomy of a wheelchair for reduced mobility peaple. The objective of this work is to design control laws that allow a robot to navigate in real time and independently in an unknown environment. A unified virtual perception framework is introduced and allows to project the navigable space obtained by possibly multiple observations. First we designed an autonomous and safe navigation approach in environment whose structure can be assimilated to a corridor (lines on the ground, walls, delimitation of grasses, roads ...). We have solved this problem by using the formalism of visual servoing. The visual characteristics used in the control law were constructed from the virtual representation (ie the position of the vanishing point and the orientation of the center line of the corridor). To ensure safe and smooth navigation, even when these parameters can not be extracted, we have designed a finite-time state observer to estimate the visual characteristics in order to maintain the robot’s control efficient. This approach let a mobile robot navigate in a corridor even in in the case of sensory failure (unreliable data) and/or loss of measurement. We have extended the first contribution of this work with dealing with any type of static or dynamic environment. This was done using the Voronoi diagram. The Generalized Voronoi Diagram (GVD), also named skeleton, is a powerful environment representation, since, among other reasons, it defines a set of paths at maximal distance from the obstacles. In this work, a real time skeleton based visual servoing approach is proposed for a safe autonomous navigation of mobile robots. The control is based on an approximation of the local GVD using the Delta Medial Axis, a fast and robust skeletonization algorithm. The latter produces a filtered skeleton of the free space surrounding the robot using a pruning parameter that takes into account the robot size. This approach can cope with measurement noises at the perception and control with the wheel slip. This is why we have designed a visual servoing approach on a prediction of a GVD linearization. A complete analysis was performed to show the stability of the proposed control laws. Simulations and experimental tests validate the proposed approach
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Pessin, Gustavo. "Estratégias inteligentes aplicadas em robôs móveis autônomos e em coordenação de grupos de robôs." Universidade de São Paulo, 2013. http://www.teses.usp.br/teses/disponiveis/55/55134/tde-25062013-160156/.
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O contínuo aumento da complexidade no controle de sistemas robóticos, bem como a aplicação de grupos de robôs auxiliando ou substituindo seres humanos em atividades críticas tem gerado uma importante demanda por soluções mais robustas, flexíveis, e eficientes. O desenvolvimento convencional de algoritmos especializados, constituídos de sistemas baseados em regras e de autômatos usados para coordenar estes conjuntos físicos em um ambiente dinâmico é um desafio extremamente complexo. Diversos modelos de desenvolvimento existem, entretanto, muitos desafios da área da robótica móvel autônoma continuam em aberto. Esta tese se insere no contexto da busca por soluções inteligentes a serem aplicadas em robôs móveis autônomos com o objetivo de permitir a operação destes em ambientes dinâmicos. Buscamos, com a investigação e aplicação de estratégias inteligentes por meio de aprendizado de máquina no funcionamento dos robôs, a proposta de soluções originais que permitam uma nova visão sobre a operação de robôs móveis em três dos desafios da área da robótica móvel autônoma, que são: localização, navegação e operações com grupos de robôs. As pesquisas sobre localização e coordenação de grupos apresentam investigação e propostas originais, buscando estender o estado da arte, onde apresentam resultados inovadores. A parte sobre navegação tem como objetivo principal ser um elo entre os conceitos de localização e coordenação de grupos, sendo o foco o desenvolvimento de um veículo autônomo com maior implicação em avanços técnicos. Relacionado com a coordenação de grupos de robôs, fizemos a escolha de trabalhar sobre uma aplicação modelada como o problema de combate a incêndios florestais. Buscamos desenvolver um ambiente de simulação realístico, onde foram avaliadas quatro técnicas para busca de iii estratégias de formação do grupo: Algoritmos Genéticos, Otimização por Enxame de Partículas, Hill Climbing e (iv) Simulated Annealing. Com base nas diversas avaliações realizadas pudemos mostrar quais das técnicas e conjuntos de parâmetros permitem a obtenção de resultados mais acurados que os demais. Além disso, mostramos como uma heurística baseada em populações anteriores pode auxiliar na tolerância a falhas da operação. Relacionado com a tarefa de navegação, apresentamos o desenvolvimento de um veículo autônomo de grande porte funcional para ambientes externos. Buscamos aperfeiçoar uma arquitetura para navegação autônoma, baseada em visão monocular e com capacidade de seguir pontos esparsos de GPS. Mostramos como a simulação e os usos de robôs de pequeno porte auxiliaram no desenvolvimento do veículo de grande porte e apresentamos como as redes neurais podem ser aplicadas nos modelos de navegação autônoma. Na investigação sobre localização, mostramos um método utilizando informação obtida de redes sem fio para prover informação de localização para robôs móveis. As informações obtidas da rede sem fio são utilizadas para aprendizado da posição de um robô móvel por meio de uma rede neural. Diversas avaliações foram realizadas buscando entender o comportamento do sistema com diferentes números de pontos de acesso, com uso de filtros, com diferentes topologias. Os resultados mostram que o modelo usando redes sem fio pode ser um possível método prático e barato para localização de robôs móveis. Esta tese aborda temas relevantes e propostas originais relacionadas com os objetivos propostos, apresentando métodos que provenham autonomia na coordenação de grupos e nas atividades individuais dos mesmos. A busca por altos graus de eficiência na resolução de tarefas em ambientes dinâmicos ainda é um campo que carece de soluções e de um aprofundamento nas pesquisas. Sendo assim, esta pesquisa buscou agregar diversos avanços científicos na área de pesquisa de robôs móveis autônomos e coordenação de grupos, por meio da aplicação de estratégias inteligentesThe constant increasing of the complexity in the control of robotic systems, as well as the application of groups of robots assisting or replacing human beings in critical activities has generated a significant demand for more robust, flexible and efficient solutions. The conventional development of specialized algorithms consisted of rule-based systems and automatas, used to coordinate these physical sets in a dynamic environment is an extremely complex challenge. Although several models of development of robotic issues are currently in use, many challenges in the area remain open. This thesis is related to the search for intelligent strategies to be applied in autonomous mobile robots in order to allow practical operations in dynamic environments. We seek, with the investigation of intelligent strategies by means of the use of machine learning in the robots, to propose original solutions to allow contributions in three challenges of the robotic research area: localization, navigation and coordination of groups of robots. The investigations about localization and groups of robots show novel and original proposals, where we sought to extend the state of the art. The navigation part has as its major objective to be a link between the subjects of localization and navigation, being its aim to help the deployment of a autonomous vehicle implying in greater technical advances. Related to the robotic group coordination, we have made the choice to work on an application modeled as a wildfire combat operation. We have developed a simulation environment in which we have evaluated four techniques to obtain strategies for the group formation: genetic algorithms, particle swarm optimization, hill climbing and simulated annealing. The v results showed that we can have very different accuracy with different techniques and sets of parameters. Furthermore, we show how a heuristic based on the use of past populations can assist in fault tolerant operation. Related to the autonomous navigation task, we present the development of a large autonomous vehicle capable of operating in outdoor environments. We sought to optimize an architecture for autonomous navigation based on monocular vision and with the ability to follow scattered points of GPS.We show how the use of simulation and small robots could assist in the development of large vehicle. Furthermore, we show how neural networks can be applied as a controller to autonomous navigation systems. In the investigation about localization, we presented a method using wireless networks to provide information about localization to mobile robots. The information gathered by the wireless network is used as input in an artificial neural network which learns the position of the robot. Several evaluations were carried out in order to understand the behavior of the proposed system, as using different topologies, different numbers of access points and the use of filters. Results showed that the proposed system, using wireless networks and neural networks, may be a useful and easy to use solution for localization of mobile robots. This thesis has addressed original and relevant topics related to the proposed objectives, showing methods to allow degrees of autonomy in robotic operations. The search for higher degrees of efficiency in tasks solving in dynamic environments is still a field that lacks solutions. Therefore, this study sought to add several scientific contributions in the autonomous mobile robots research area and coordination of groups, by means of the application of intelligent strategies
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Hernandez, Beleño Ruben Dario 1986. "Proposta de uma plataforma de testes para o desenvolvimento de veículos autônomos." [s.n.], 2012. http://repositorio.unicamp.br/jspui/handle/REPOSIP/264960.
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Orientador: Janito Vaqueiro FerreiraDissertação (mestrado) - Universidade Estadual de Campinas, Faculdade de Engenharia Mecânica
Made available in DSpace on 2018-08-20T14:52:32Z (GMT). No. of bitstreams: 1 HernandezBeleno_RubenDario_M.pdf: 6591392 bytes, checksum: fd4c66b4e3769739bb1a4283c418d2d8 (MD5) Previous issue date: 2012
Resumo: Com o avanço da tecnologia refletida nos sistemas eletrônicos e de computação, os métodos do controle de trajetória no sistema de navegação se tornaram importantes nas diversas aplicações de veículos autônomos, como na geração de mapas, desvio de obstáculos e tarefas de posicionamento. Além disso, o controle pode proporcionar um ganho significativo na confiabilidade, versatilidade e precisão das tarefas robóticas, questões cruciais na maioria das aplicações reais. O presente trabalho tem como objetivo principal apresentar a criação de um veículo autônomo em escala. Para tanto foi desenvolvido um sistema de função sensorial que provê informações sobre a posição e orientação do carro a partir de quatro sistemas sensoriais como GPS, acelerômetro, giroscópio e a bussola (IMU), para que o veículo autônomo possa realizar a rota corretamente, de forma eficiente e segura. Neste projeto foi desenvolvido um software que integra os sistemas de controle e de sensoriamento. Além disso, foi projetado um módulo que controla a posição e orientação do veículo. O robô antes de realizar a manobra calcula a distância mínima relacionada ao próximo ponto da coordenada planejada para trocar sua referência de trajetória satisfazendo a orientação do caminho e do veículo. Para fins de avaliação, foram realizados experimentos em ambientes reais onde o carro percorre um conjunto determinado de coordenadas geográficas sem nenhuma intervenção humana, apresentando resultados do seguimento de trajetórias proposto e validando os sistemas sensoriais, além do algoritmo de controle projetado
Abstract: As electronic and computational systems technology advances, the use of path control methods in navigation systems become very important for different autonomous vehicles applications such as generating maps, avoiding obstacles and carrying out positioning tasks. In addition, controls can help increase the reliability, versatility and precision level of programmed tasks, which is exceedingly significant regarding real applications. The first aim of this work is to present the creation of an autonomous scale vehicle. We have developed a sensor system that provides information about the vehicle's position and orientation through four sensor systems such as gps, accelerometer, gyroscope and compass so that it can effectively and safely cover the right route. This project developed a software, which integrates the control and sensors systems. In addition, a control module was projected for the positioning and orientation of the vehicle. Before the robot turns to any direction, it calculates the minimal distance to the next step of the programmed coordinate, in order to change its own referenced trajectory, satisfying the orientation of the trajectory and the vehicle. For the task validation were done experiments in real life scenarios, where the vehicle follows a determined group of geo-coordinates without any human intervention, presenting results of the purposed following trajectories, validating the sensors systems and the control algorithm
Mestrado
Mecanica dos Sólidos e Projeto Mecanico
Mestre em Engenharia Mecânica
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Braga, Arthur Plínio de Souza. "Um agente autônomo baseado em aprendizagem por reforço direcionado à meta." Universidade de São Paulo, 1998. http://www.teses.usp.br/teses/disponiveis/18/18133/tde-31102017-111839/.
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Uma meta procurada em inteligência artificial (IA) é o desenvolvimento de mecanismos inteligentes capazes de cumprir com objetivos preestabelecidos, de forma totalmente independente, em ambientes dinâmicos e complexos. Uma recente vertente das pesquisas em IA, os agentes autônomos, vem conseguindo resultados cada vez mais promissores para o cumprimento desta meta. A motivação deste trabalho é a proposição e implementação de um agente que aprenda a executar tarefas, sem a interferência de um tutor, em um ambiente não estruturado. A tarefa prática proposta para testar o agente é a navegação de um robô móvel em ambientes com diferentes configurações, e cujas estruturas são inicialmente desconhecidas pelo agente. O paradigma de aprendizagem por reforço, através de variações dos métodos de diferença temporal, foi utilizado para implementar o agente descrito nesta pesquisa. O resultado final obtido foi um agente autônomo que utiliza um algoritmo simples para desempenhar propriedades como: aprendizagem a partir de tabula rasa, aprendizagem incremental, planejamento deliberativo, comportamento reativo, capacidade de melhoria do desempenho e habilidade para gerenciar múltiplos objetivos. O agente proposto também apresenta um desempenho promissor em ambientes cuja estrutura se altera com o tempo, porém diante de certas situações seus comportamentos em tais ambientes tendem a se tornar inconsistentes.One of the current goals of research in Artificial Intelligence is the proposition of intelligent entities that are able to reach a particular target in a dynamic and complex environment without help of a tutor. This objective has been becoming reality through the propositions of the autonomous agents. Thus, the main motivation of this work is to propose and implement an autonomous agent that can match the mentioned goals. This agent, a mobile robot, has to navigate in environments which are initially unknown and may have different structures. The agent learns through one of the main reinforcement learning strategies: temporal difference. The proposed autonomous employs a simple learning mechanisms with the following features: learns incrementally from tabula rasa, executes deliberative and reactive planning, improves its performance through interactions with the environment, and manages multiple objectives. The agent presented promising results when moving in a dynamic environment. However, there are situations in which the agent do not follow this last property.
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Herman, David. "Lokální navigace autonomního mobilního robota." Master's thesis, Vysoké učení technické v Brně. Fakulta informačních technologií, 2010. http://www.nusl.cz/ntk/nusl-237248.
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This paper deals with the topic of design of a navigation system for an autonomous mobile robot in a park-like environment. Precisely, designing methods for road detection using available sensoric system, designing a mathematical model for fusion of these data, and suggesting a representation of an environment suitable for planning and local navigation.
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Reverendo, Nelson Almeida. "Indoor autonomous navigation for service robots using beacons." Master's thesis, 2018. http://hdl.handle.net/10773/25892.
Full textAbstract:
Nowadays robots are becoming more present in our daily life performing a variety of on-demand services. In order to perform autonomous tasks the robot should be aware of its environment. To achieve this goal, there are three main problems to solve: mapping, localisation and navigation. During this work, we developed an autonomous welcome robot for the Institute of Electronics and Informatics Engineering of Aveiro ( IEETA ) with the capacity to receive requests from a visitor and guide him to the requested destination. At the end of this task, the robot should return autonomously to its docking station. To accomplish this goal we studied algorithms related to the three referred problems. As an example, a laser-based solution is used for the Simultaneous Localisation and Mapping procedure ( Gmapping ), the adaptive Monte Carlo localisation approach (AMCL) for the robot moving in 2-D and A* as a method for path planning. Improvements have been made regarding the use of these algorithms including in the environment an active localisation system based on the use of ultrasound beacons. The end result is an autonomous agent capable of mapping the building, self-localise in the resulting map and moving from current position to a specified target. It is also capable of path recalculation and minimal real-time collision avoidance while navigating.Hoje em dia, os robôs estão cada vez mais presentes no nosso quotidiano, fornecendo uma variedade de serviços e realizando as mais diversas tarefas, algumas delas de forma completamente autónoma. Para que o robô execute tarefas autónomas deve estar ciente do ambiente que o rodeia e conhecer a sua posição no mesmo. Para atingir esse objetivo, existem três problemas principais a serem resolvidos: mapeamento, localização e navegação. Durante este trabalho desenvolvemos um robô autónomo de boas-vindas para o Instituto de Engenharia Eletrónica e Informática de Aveiro com a capacidade de receber ordens de um visitante e guiá-lo até ao destino solicitado. No final desta tarefa, o robô retorna autonomamente ao seu local de partida, onde retoma a tarefa de carregamento. Para atingir este objetivo estudámos algoritmos relacionados com os três problemas referidos. Como exemplo, o algoritmo GMapping baseado em laser scans é usado para o processo de Mapeamento e Localização Simultânea, a abordagem adaptativa de localização de Monte Carlo é usada para que o robô que se mova no espaço e o algoritmo A* é aplicado para planeamento de um caminho. Foram feitas diversas melhorias em relação ao uso desses algoritmos, incluindo no ambiente um sistema de localização ativa baseado no uso de beacons ultra-som. O resultado final é um agente autónomo capaz de mapear o edifício, localizarse no mapa resultante e mover-se da posição atual para um destino especificado. Também é capaz de recalcular o caminho e evitar colisões mínimas em tempo real durante a navegação.
Mestrado em Engenharia de Computadores e Telemática
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Wei, Po-An, and 韋柏安. "3D SLAM and Autonomous Navigation of an Indoor Omnidirectional Mobile Robot for Unknown Structured Environments." Thesis, 2019. http://ndltd.ncl.edu.tw/cgi-bin/gs32/gsweb.cgi/login?o=dnclcdr&s=id=%22107NCHU5441048%22.&searchmode=basic.
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碩士國立中興大學
電機工程學系所
107
This thesis proposes techniques for 3D simultaneous localization and mapping (SLAM) and autonomous navigation of an indoor Mecanum-wheeled omnidirectional mobile Robot (MWOR) in unknown structured environments. Such an experimental mobile robot is equipped with one Linux-based TX2 computing board, one RealSense RGB-D camera, one LiDAR and an Open-CR control board and ROS software, where the LiDAR is used to achieve obstacle avoidance. For 3D SLAM, this thesis presents an improved complete-coverage exploration algorithm, an improved RRT algorithm, and an existing RGB-D SLAM algorithm to builds its 3D environment map, which will be transmitted to a host computer through topic in ROS via a wireless network. The autonomous navigation control architecture is composed of one adaptive Monte-Carlo localization SLAM module, one global path planning module using Dijstra algorithm, one obstacle avoidance module by fusing the outputs of the existing DWA method and SegNet, and one motion control module for the MWOR. Serval simulations and experimental results are performed to illustrate the effectiveness, usefulness and practicability of the proposed techniques.
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"Indoor mobile robot navigation with continuous localization." 1999. http://library.cuhk.edu.hk/record=b5890009.
Full textAbstract:
by Lam Chin Hung.Thesis (M.Phil.)--Chinese University of Hong Kong, 1999.
Includes bibliographical references (leaves 60-64).
Abstracts in English and Chinese.
Acknowledgments --- p.ii
List of Figures --- p.v
List of Tables --- p.vii
Abstract --- p.viii
Chapter 1 --- Introduction --- p.1
Chapter 2 --- Algorithm Outline --- p.7
Chapter 2.1 --- Assumptions --- p.7
Chapter 2.2 --- Robot Localization --- p.8
Chapter 2.3 --- Algorithm Outline --- p.11
Chapter 3 --- Global and Local Maps --- p.15
Chapter 3.1 --- Feature Selection --- p.17
Chapter 3.2 --- Line Correspondence --- p.18
Chapter 3.3 --- Map Representation --- p.20
Chapter 3.3.1 --- Global Map --- p.21
Chapter 3.3.2 --- Local Map --- p.22
Chapter 3.4 --- Integration of Multiple Local 2D Maps --- p.24
Chapter 4 --- Localization Algorithm --- p.27
Chapter 4.1 --- Robot Orientation --- p.28
Chapter 4.2 --- Robot Position --- p.29
Chapter 4.2.1 --- Match Function --- p.30
Chapter 4.2.2 --- Search Algorithm --- p.31
Chapter 4.3 --- Continuous Localization with Retroactive Pose Update --- p.32
Chapter 5. --- Implementation and Experiments --- p.35
Chapter 5.1 --- Computing Robot Orientation --- p.36
Chapter 5.2 --- Robot Position by Map Registration --- p.42
Chapter 5.2.1 --- Error Analysis --- p.47
Chapter 5.3 --- Discussions --- p.49
Chapter 6. --- Conclusion --- p.52
Appendix --- p.54
Chapter A.l --- Intrinsic and Extrinsic Parameters --- p.54
Chapter A.2 --- Relation Between Cameras (Stereo Camera Calibration) --- p.55
Chapter A.3 --- Wheel-Eyes Calibration --- p.56
Chapter A.4 --- Epipolar Geometry --- p.58
Chapter A.5 --- The Tele-operate Interface --- p.59
References --- p.60
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Chen, Yuon-Hao, and 陳勇豪. "Indoor Navigation System Design of a Mobile Robot." Thesis, 1998. http://ndltd.ncl.edu.tw/handle/19382513986441272618.
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碩士國立交通大學
電機與控制工程學系
86
An indoor navigation system of a mobile robot has been developed. In this system we can make a simple path-planning based-on the natural landmark──lamps on the ceiling . A fuzzy controller has been designed to perform the lamp-tracking task in order to make the mobile robot to follow the pre-defined path. The mobile robot will make fast local path-planning using a hueristic clustering network to prevent from collision when unexpected obstacles are presented on its pre-defined path. A fuzzy fusion agency
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張原華. "Mobile Robot Navigation with Fuzzy Rules in Indoor Environment." Thesis, 2010. http://ndltd.ncl.edu.tw/handle/72656157694073310874.
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碩士國立臺灣師範大學
應用電子科技學系
98
Now mobile robot be used in all kinds of field. For upgrade the quality of life,more and more mobile robots are developed to help people life. In this paper, the navigation is based on fuzzy rules, laser range finder be used to avoid the obstacles, and obtains the direction by compass. There are horizontal obstacle avoidance and ground obstacle avoidance of the mobile robot. The horizontal obstacle avoidance can avoid most of the obstacles. Using ground obstacle avoidance with horizontal mode could raise the safety and accuracy of the navigation task in unknown indoor environment. In the research, the simulations of general environment are in laboratory.The environments are single horizontal obstacle, horizontal obstacle and ground obstacle side by side, horizontal obstacle and can be traversed obstacle and so forth. The effects of angle of start coordinate and goal coordinate, and the length of navigation distance are be discussed to improve the accuracy of the navigation experiment.
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Lin, Chi-Shian, and 林啟賢. "Study on Map-Based Indoor Mobile Robot Vision Navigation." Thesis, 2009. http://ndltd.ncl.edu.tw/handle/41495171926544827476.
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碩士國立成功大學
電機工程學系碩博士班
97
This thesis focuses on the implementation of an autonomous mobile robot moving along the corridors in a building by map-based vision navigation, where a camera is the only sensor in the navigation system to gather environment information. Generally speaking, map-based navigation consists of three steps: Map-building, localization, and path planning. In our system, the map and path planning are highly related to the ceiling images, and those are defined by user. This thesis constructs a topological map to represent the environment in advance. The constructed map is used to help the autonomous mobile robot to move along the corridor like as a patrol robot. A webcam mounted on the mobile robot is used to capture the ceiling images to analyze the features such as distinctive line, ceiling light and corner features. According to the obtained feature and the pre-constructed topological map, the mobile robot can perform localization. A proper moving strategy is designed to guide the mobile robot to successfully move along the corridor. Since the ceiling image is sensitive to the fluctuation in illumination, therefore variation in illumination may result in localization failure. In order to cope with this problem, an adaptive threshold technique is employed to adjust parameter values used in the navigation system. Experimental results show that our autonomous mobile robot successfully moves along the desired path.