Relevant bibliographies by topics / Autonomous robots; Path planning

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  1. Journal articles
  2. Dissertations / Theses
  3. Books
  4. Book chapters
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Academic literature on the topic 'Autonomous robots; Path planning'

Author: Grafiati
Published: 4 June 2021
Last updated: 1 February 2022

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Journal articles on the topic "Autonomous robots; Path planning"

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Elbanhawi, Mohamed, Milan Simic, and Reza Jazar. "Autonomous Robots Path Planning: An Adaptive Roadmap Approach." Applied Mechanics and Materials 373-375 (August 2013): 246–54. http://dx.doi.org/10.4028/www.scientific.net/amm.373-375.246.

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Developing algorithms that allow robots to independently navigate unknown environments is a widely researched area of robotics. The potential for autonomous mobile robots use, in industrial and military applications, is boundless. Path planning entails computing a collision free path from a robots current position to a desired target. The problem of path planning for these robots remains underdeveloped. Computational complexity, path optimization and robustness are some of the issues that arise. Current algorithms do not generate general solutions for different situations and require user experience and optimization. Classical algorithms are computationally extensive. This reduces the possibility of their use in real time applications. Additionally, classical algorithms do not allow for any control over attributes of the generated path. A new roadmap path planning algorithm is proposed in this paper. This method generates waypoints, through which the robot can avoid obstacles and reach its goal. At the heart of this algorithm is a method to control the distance of the waypoints from obstacles, without increasing its computational complexity. Several simulations were run to illustrate the robustness and adaptability of this approach, compared to the most commonly used path planning methods.
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Zhang, Hong Min. "Path Planning Methods of Mobile Robot Based on Soft Computing Technique." Advanced Materials Research 216 (March 2011): 677–80. http://dx.doi.org/10.4028/www.scientific.net/amr.216.677.

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Path planning is one of the most important and challenging problems of mobile robot. It is one of the keys that will make the mobile robots fully autonomous. In this paper, we summarized the application of soft computing approaches in path planning for mobile robot. Finally the future works of path planning for mobile robots are prospected.
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Saleem Sumbal, Muhammad. "Environment Detection and Path Planning Using the E-puck Robot." IAES International Journal of Robotics and Automation (IJRA) 5, no. 3 (2016): 151. http://dx.doi.org/10.11591/ijra.v5i3.pp151-160.

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Automatic path planning is one of the most challenging problems confronted by autonomous robots. Generating optimal paths for autonomous robots are some of the heavily studied subjects in mobile robotics applications. This paper documents the implementation of a path planning project using a mobile robot in a structured environment. The environment is detected through a camera and then a roadmap of the environment is built using some algorithms. Finally a graph search algorithm called A* is implemented that searches through the roadmap and finds an optimal path for robot to move from start position to goal position avoiding obstacles
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Kumar, Rajeev, Laxman Singh, and Rajdev Tiwari. "Path planning for the autonomous robots using modified grey wolf optimization approach." Journal of Intelligent & Fuzzy Systems 40, no. 5 (2021): 9453–70. http://dx.doi.org/10.3233/jifs-201926.

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Path planning for robots plays a vital role to seek the most feasible path due to power requirement, environmental factors and other limitations. The path planning for the autonomous robots is tedious task as the robot needs to locate a suitable path to move between the source and destination points with multifaceted nature. In this paper, we introduced a new technique named modified grey wolf optimization (MGWO) algorithm to solve the path planning problem for multi-robots. MGWO is modified version of conventional grey wolf optimization (GWO) that belongs to the category of metaheuristic algorithms. This has gained wide popularity for an optimization of different parameters in the discrete search space to solve various problems. The prime goal of the proposed methodology is to determine the optimal path while maintaining a sufficient distance from other objects and moving robots. In MGWO method, omega wolves are treated equally as those of delta wolves in exploration process that helps in escalating the convergence speed and minimizing the execution time. The simulation results show that MGWO gives satisfactory performance than other state of art methods for path planning of multiple mobile robots. The performance of the proposed method is compared with the standard evolutionary algorithms viz., Particle Swarm Optimization (PSO), Intelligent BAT Algorithm (IBA), Grey Wolf Optimization (GWO), and Variable Weight Grey Wolf Optimization (VW-GWO) and yielded better results than all of these.
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Valbahs, Edvards, and Peter Grabusts. "Path Planning Usage for Autonomous Agents." Environment. Technology. Resources. Proceedings of the International Scientific and Practical Conference 2 (August 8, 2015): 40. http://dx.doi.org/10.17770/etr2013vol2.867.

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In order to achieve the wide range of the robotic application it is necessary to provide iterative motions among points of the goals. For instance, in the industry mobile robots can replace any components between a storehouse and an assembly department. Ammunition replacement is widely used in military services. Working place is possible in ports, airports, waste site and etc. Mobile agents can be used for monitoring if it is necessary to observe control points in the secret place. The paper deals with path planning programme for mobile robots. The aim of the research paper is to analyse motion-planning algorithms that contain the design of modelling programme. The programme is needed as environment modelling to obtain the simulation data. The simulation data give the possibility to conduct the wide analyses for selected algorithm. Analysis means the simulation data interpretation and comparison with other data obtained using the motion-planning. The results of the careful analysis were considered for optimal path planning algorithms. The experimental evidence was proposed to demonstrate the effectiveness of the algorithm for steady covered space. The results described in this work can be extended in a number of directions, and applied to other algorithms.
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Zanlongo, Sebastián A., Peter Dirksmeier, Philip Long, Taskin Padir, and Leonardo Bobadilla. "Scheduling and Path-Planning for Operator Oversight of Multiple Robots." Robotics 10, no. 2 (2021): 57. http://dx.doi.org/10.3390/robotics10020057.

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There is a need for semi-autonomous systems capable of performing both automated tasks and supervised maneuvers. When dealing with multiple robots or robots with high complexity (such as humanoids), we face the issue of effectively coordinating operators across robots. We build on our previous work to present a methodology for designing trajectories and policies for robots such that a few operators can supervise multiple robots. Specifically, we: (1) Analyze the complexity of the problem, (2) Design a procedure for generating policies allowing operators to oversee many robots, (3) Present a method for designing policies and robot trajectories to allow operators to oversee multiple robots, and (4) Include both simulation and hardware experiments demonstrating our methodologies.
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Liu, Yong-tao, Rui-zhi Sun, Tian-yi Zhang, Xiang-nan Zhang, Li Li, and Guo-qing Shi. "Warehouse-Oriented Optimal Path Planning for Autonomous Mobile Fire-Fighting Robots." Security and Communication Networks 2020 (June 20, 2020): 1–13. http://dx.doi.org/10.1155/2020/6371814.

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In order to achieve the fastest fire-fighting purpose, warehouse autonomous mobile fire-fighting robots need to make an overall optimal planning based on the principle of the shortest time for their traveling path. A∗ algorithm is considered as a very ideal shortest path planning algorithm, but the shortest path is not necessarily the optimal path for robots. Furthermore, the conventional A∗ algorithm is affected by the search neighborhood restriction and the theoretical characteristics, so there are many problems, which are closing to obstacles, more inflection points, more redundant points, larger total turning angle, etc. Therefore, A∗ algorithm is improved in eight ways, and the inflection point prior strategy is adopted to compromise Floyd algorithm and A∗ algorithm in this paper. According to the criterion of the inflection point in this paper, the path inflection point arrays are constructed and traveling all path nodes are replaced by traveling path inflection points for the conventional Floyd algorithm backtracking, so it greatly reduces the backtracking time of the smooth path. In addition, this paper adopts the method of the extended grid map obstacle space in path planning safety distance. According to the relationship between the actual scale of the warehouse grid map and the size of the robot body, the different safe distance between the planning path and the obstacles is obtained, so that the algorithm can be applied to the safe path planning of the different size robots in any map environments. Finally, compared with the conventional A∗ algorithm, the improved algorithm reduces by 7.846% for the path length, reduces by 71.429% for the number of the cumulative turns, and reduces by 75% for the cumulative turning angle through the experiment. The proposed method can ensure robots to move fast on the planning path and ultimately achieve the goal of reducing the number of inflection points, reducing the cumulative turning angle, and reducing the path planning time.
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Urdiales, C., A. Bandera, F. Arrebola, and F. Sandoval. "Multi-level path planning algorithm for autonomous robots." Electronics Letters 34, no. 2 (1998): 223. http://dx.doi.org/10.1049/el:19980204.

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Arokiasami, Willson Amalraj, Prahlad Vadakkepat, Kay Chen Tan, and Dipti Srinivasan. "Real-Time Path-Generation and Path-Following Using an Interoperable Multi-Agent Framework." Unmanned Systems 06, no. 04 (2018): 231–50. http://dx.doi.org/10.1142/s2301385018500061.

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Autonomous unmanned vehicles are preferable in patrolling, surveillance and, search and rescue missions. Multi-agent architectures are commonly used for autonomous control of unmanned vehicles. Existing multi-robot architectures for unmanned aerial and ground robots are generally mission and platform oriented. Collision avoidance, path-planning and tracking are some of the fundamental requirements for autonomous operation of unmanned robots. Though aerial and ground vehicles operate differently, the algorithms for obstacle avoidance, path-planning and path-tracking can be generalized. Service Oriented Interoperable Framework for Robot Autonomy (SOIFRA) proposed in this work is an interoperable multi-agent framework focused on generalizing platform independent algorithms for unmanned aerial and ground vehicles. SOIFRA is behavior-based, modular and interoperable across unmanned aerial and ground vehicles. SOIFRA provides collision avoidance, and, path-planning and tracking behaviors for unmanned aerial and ground vehicles. Vector Directed Path-Generation and Tracking (VDPGT), a vector-based algorithm for real-time path-generation and tracking, is proposed in this work. VDPGT dynamically adopts the shortest path to the destination while minimizing the tracking error. Collision avoidance is performed utilizing Hough transform, Canny contour, Lucas–Kanade sparse optical flow algorithm and expansion of object-based time-to-contact estimation. Simulation and experimental results from Turtlebot and AR Drone show that VDPGT can dynamically generate and track paths, and SOIFRA is interoperable across multiple robotic platforms.
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Masone, Carlo, Mostafa Mohammadi, Paolo Robuffo Giordano, and Antonio Franchi. "Shared planning and control for mobile robots with integral haptic feedback." International Journal of Robotics Research 37, no. 11 (2018): 1395–420. http://dx.doi.org/10.1177/0278364918802006.

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This paper presents a novel bilateral shared framework for online trajectory generation for mobile robots. The robot navigates along a dynamic path, represented as a B-spline, whose parameters are jointly controlled by a human supervisor and an autonomous algorithm. The human steers the reference (ideal) path by acting on the path parameters that are also affected, at the same time, by the autonomous algorithm to ensure: (i) collision avoidance, (ii) path regularity, and (iii) proximity to some points of interest. These goals are achieved by combining a gradient descent-like control action with an automatic algorithm that re-initializes the traveled path (replanning) in cluttered environments to mitigate the effects of local minima. The control actions of both the human and the autonomous algorithm are fused via a filter that preserves a set of local geometrical properties of the path to ease the tracking task of the mobile robot. The bilateral component of the interaction is implemented via a force feedback that accounts for both human and autonomous control actions along the whole path, thus providing information about the mismatch between the reference and traveled path in an integral sense. The proposed framework is validated by means of realistic simulations and actual experiments deploying a quadrotor unmanned aerial vehicle (UAV) supervised by a human operator acting via a force-feedback haptic interface. Finally, a user study is presented to validate the effectiveness of the proposed framework and the usefulness of the provided force cues.
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Dissertations / Theses on the topic "Autonomous robots; Path planning"

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Crous, C. B. "Autonomous robot path planning." Thesis, Stellenbosch : University of Stellenbosch, 2009. http://hdl.handle.net/10019.1/2519.

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Thesis (MSc (Mathematical Sciences. Computer SCience))--University of Stellenbosch, 2009.<br>In this thesis we consider the dynamic path planning problem for robotics. The dynamic path planning problem, in short, is the task of determining an optimal path, in terms of minimising a given cost function, from one location to another within a known environment of moving obstacles. Our goal is to investigate a number of well-known path planning algorithms, to determine for which circumstances a particular algorithm is best suited, and to propose changes to existing algorithms to make them perform better in dynamic environments. At this stage no thorough comparison of theoretical and actual running times of path planning algorithms exist. Our main goal is to address this shortcoming by comparing some of the wellknown path planning algorithms and our own improvements to these path planning algorithms in a simulation environment. We show that the visibility graph representation of the environment combined with the A* algorithm provides very good results for both path length and computational cost, for a relatively small number of obstacles. As for a grid representation of the environment, we show that the A* algorithm produces good paths in terms of length and the amount of rotation and it requires less computation than dynamic algorithms such as D* and D* Lite.
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Schmitt, Paul Richard. "Reactive path shaping : local path planning for autonomous mobile robots in aisles." Thesis, Georgia Institute of Technology, 1996. http://hdl.handle.net/1853/17778.

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balakrishnan, mohanakrishnan. "COVERAGE PATH PLANNING AND CONTROL FOR AUTONOMOUS MOBILE ROBOTS." Master's thesis, University of Central Florida, 2005. http://digital.library.ucf.edu/cdm/ref/collection/ETD/id/2769.

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Coverage control has many applications such as security patrolling, land mine detectors, and automatic vacuum cleaners. This Thesis presents an analytical approach for generation of control inputs for a non-holonomic mobile robot in coverage control. Neural Network approach is used for complete coverage of a given area in the presence of stationary and dynamic obstacles. A complete coverage algorithm is used to determine the sequence of points. Once the sequences of points are determined a smooth trajectory characterized by fifth order polynomial having second order continuity is generated. And the slope of the curve at each point is calculated from which the control inputs are generated analytically. Optimal trajectory is generated using a method given in research literature and a qualitative analysis of the smooth trajectory is done. Cooperative sweeping of multirobots is achieved by dividing the area to be covered into smaller areas depending on the number of robots. Once the area is divided into sub areas, each robot is assigned a sub area for cooperative sweeping.<br>M.S.<br>Department of Electrical and Computer Engineering<br>Engineering and Computer Science<br>Electrical Engineering
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Qin, Caigong. "A computational framework for manipulator motion planning." Thesis, University of Oxford, 1996. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.362068.

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Cowlagi, Raghvendra V. "Hierarchical motion planning for autonomous aerial and terrestrial vehicles." Diss., Georgia Institute of Technology, 2011. http://hdl.handle.net/1853/41066.

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Autonomous mobile robots - both aerial and terrestrial vehicles - have gained immense importance due to the broad spectrum of their potential military and civilian applications. One of the indispensable requirements for the autonomy of a mobile vehicle is the vehicle's capability of planning and executing its motion, that is, finding appropriate control inputs for the vehicle such that the resulting vehicle motion satisfies the requirements of the vehicular task. The motion planning and control problem is inherently complex because it involves two disparate sub-problems: (1) satisfaction of the vehicular task requirements, which requires tools from combinatorics and/or formal methods, and (2) design of the vehicle control laws, which requires tools from dynamical systems and control theory. Accordingly, this problem is usually decomposed and solved over two levels of hierarchy. The higher level, called the geometric path planning level, finds a geometric path that satisfies the vehicular task requirements, e.g., obstacle avoidance. The lower level, called the trajectory planning level, involves sufficient smoothening of this geometric path followed by a suitable time parametrization to obtain a reference trajectory for the vehicle. Although simple and efficient, such hierarchical separation suffers a serious drawback: the geometric path planner has no information of the kinematic and dynamic constraints of the vehicle. Consequently, the geometric planner may produce paths that the trajectory planner cannot transform into a feasible reference trajectory. Two main ideas appear in the literature to remedy this problem: (a) randomized sampling-based planning, which eliminates altogether the geometric planner by planning in the vehicle state space, and (b) geometric planning supported by feedback control laws. The former class of methods suffer from a lack of optimality of the resultant trajectory, while the latter class of methods makes a restrictive assumption concerning the vehicle kinematic model. In this thesis, we propose a hierarchical motion planning framework based on a novel mode of interaction between these two levels of planning. This interaction rests on the solution of a special shortest-path problem on graphs, namely, one using costs defined on multiple edge transitions in the path instead of the usual single edge transition costs. These costs are provided by a local trajectory generation algorithm, which we implement using model predictive control and the concept of effective target sets for simplifying the non-convex constraints involved in the problem. The proposed motion planner ensures "consistency" between the two levels of planning, i.e., a guarantee that the higher level geometric path is always associated with a kinematically and dynamically feasible trajectory. We show that the proposed motion planning approach offers distinct advantages in comparison with the competing approaches of discretization of the state space, of randomized sampling-based motion planning, and of local feedback-based, decoupled hierarchical motion planning. Finally, we propose a multi-resolution implementation of the proposed motion planner, which requires accurate descriptions of the environment and the vehicle only for short-term, local motion planning in the immediate vicinity of the vehicle.
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Hasler, Michael Douglas. "Simulation for Improvement of Dynamic Path Planning in Autonomous Search and Rescue Robots." Thesis, University of Canterbury. Electrical and Computer Engineering, 2009. http://hdl.handle.net/10092/4475.

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To hasten the process of saving lives after disasters in urban areas, autonomous robots are being looked to for providing mapping, hazard identification and casualty location. These robots need to maximise time in the field without having to recharge and without reducing productivity. This project aims to improve autonomous robot navigation through allowing comparison of algorithms with various weightings, in conjunction with the ability to vary physical parameters of the robot and other factors such as error thresholds/limits. The lack of a priori terrain data in disaster sites, means that robots have to dynamically create a representation of the terrain from received sensor range-data in order to path plan. To reduce the resources used, the affect of input data on the terrain model is analysed such that some points may be culled. The issues of identifying hazards within these models are considered with respect to the effect on safe navigation. A modular open-source platform has been created which allows the automated running of experimental trials in conjunction with the implementation and use of other input types, node networks, or algorithms. Varying the terrains, obstacles, initial positions and goals, which a virtual robot is tasked with navigating means that the design, and hence performance, are not tailored to individual situations. Additionally, this demonstrates the variability of scenarios possible. This combination of features allows one to identify the effects of different design decisions, while the use of a game-like graphical interface allows users to readily view and comprehend the scenarios the robot encounters and the paths produced to traverse these environments. The initially planned focus of experimentation lay in testing different algorithms and various weightings, however this was expanded to include different implementations and factors of the input collection, terrain modelling and robot movement. Across a variety of terrain scenarios, the resultant paths and status upon trial completion were analysed and displayed to allow observations to be made. It was found that the path planning algorithms are of less import than initially believed, with other facets of the robotic system having equally significant roles in producing quality paths through a hazardous environment. For fixed view robots, like the choice used in this simulator, it was found that there were issues of incompatibility with A* based algorithms, as the algorithm’s expected knowledge of the areas in all directions regardless of present orientation, and hence they did not perform as they are intended. It is suggested that the behaviour of such algorithms be modified if they are to be used with fixed view systems, in order to gather sufficient data from the surroundings to operate correctly and find paths in difficult terrains. A simulation tool such as this, enables the process of design and testing to be completed with greater ease, and if one can restrain the number of parameters varied, then also with more haste. These benefits will make this simulation tool a valuable addition to the field of USAR research.
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Haight, Timothy A. "Layered path planning for an autonomous mobile robot." Thesis, Monterey, Calif. : Springfield, Va. : Naval Postgraduate School ; Available from National Technical Information Service, 1994. http://handle.dtic.mil/100.2/ADA286138.

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Thesis (M.S. in Computer Science and M.S. in Mathematics) Naval Postgraduate School, September 1994.<br>Thesis advisor(s): Yutaka Kanayama, Craig W. Rasmussen. "September 1994." Bibliography: p. 43-44. Also available online.
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Selin, Magnus. "Efficient Autonomous Exploration Planning of Large-Scale 3D-Environments : A tool for autonomous 3D exploration indoor." Thesis, Linköpings universitet, Artificiell intelligens och integrerade datorsystem, 2019. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-163329.

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Exploration is of interest for autonomous mapping and rescue applications using unmanned vehicles. The objective is to, without any prior information, explore all initially unmapped space. We present a system that can perform fast and efficient exploration of large scale arbitrary 3D environments. We combine frontier exploration planning (FEP) as a global planning strategy, together with receding horizon planning (RH-NBVP) for local planning. This leads to plans that incorporate information gain along the way, but do not get stuck in already explored regions. Furthermore, we make the potential information gain estimation more efficient, through sparse ray-tracing, and caching of already estimated gains. The worked carried out in this thesis has been published as a paper in Robotand Automation letters and presented at the International Conference on Robotics and Automation in Montreal 2019.
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Hernández, Vega Juan David. "Online path planning for autonomous underwater vehicles under motion constraints." Doctoral thesis, Universitat de Girona, 2017. http://hdl.handle.net/10803/457592.

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The most common applications of autonomous underwater vehicles (AUVs) include imaging and inspecting different kinds of structures on the sea. Most of these applications require a priori information of the area or structure to be inspected, either to navigate at a safe and conservative altitude or to 2/2 pre-calculate a survey path. However, there are other applications where it's unlikely that such information is available (e.g., exploring confined natural environments like underwater caves). In this respect, this thesis presents an approach that endows an AUV with the capabilities to move through unexplored environments. To do so, it proposes a computational framework for planning feasible and safe paths online. This approach allows the vehicle to incrementally build a map of the surroundings, while simultaneously (re)plan a feasible path to a specified goal. The framework takes into account motion constraints in planning feasible paths, i.e., those that meet the vehicle's motion capabilities<br>Les aplicacions més comunes dels vehicles autònoms submarins o AUVs són l’obtenció d'imatges i inspecció de diferents tipus d'estructures, com per exemple, cascos de vaixells o estructures naturals en el fons marí. Moltes d'aquestes aplicacions requereixen informació a priori de l'àrea o estructura que es vol inspeccionar. No obstant, existeixen aplicacions similars o noves, com l'exploració d'entorns naturals confinats (e.g., coves submarines), on aquesta informació pot ser inexistent. En aquest sentit, aquesta tesi presenta una alternativa per dotar un AUV amb l'habilitat de moure’s a través d'entorns no explorats. Per aconseguir aquesta fita, aquesta tesi proposa un mètode per calcular en temps real camins factibles i segurs. El mètode proposat permet al vehicle construir de forma incremental un mapa de l'entorn, i al mateix temps replanificar un camí factible cap a l'objectiu establert. El mètode proposat te en compte les restriccions de moviment del vehicle per planificar camins que siguin factibles
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Moletta, Marco. "Path planning for autonomous aerial robots in unknown underground zones optimized for vertical tunnels exploration." Thesis, KTH, Skolan för elektroteknik och datavetenskap (EECS), 2020. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-285574.

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Robotics is revolutionizing the work in dangerous environments like mines and tunnels, making life easier and safer for the workers. The specific case considered in this thesis regards UAVs used for 3D mapping of these zones. However, the use of UAVs in underground mines can be challenging for many reasons, such as reduced visibility, no GPS localization available and limited wireless communication, challenges that can be partially solved by using au- tonomous robots. Precisely for these reasons, this work aims to contribute on this application with the implementation of an autonomous path planning algorithm for aerial vehicles in underground zones.However, the peculiar contribution of this work regards shaft mines, which are vertical or near-vertical tunnels with access from the top and the bottom. This particular scenario is extremely challenging for UAVs, since the length of these tunnels (typically 100-200 m) cause the lost of signal from the con- trol station during the mission. Hence, the implemented algorithm is chosen in order to succeed in shaft scenarios. Then, an optimization of the algorithm has been made in order to decrease the time of the mission, thus increasing the chances of success by saving the battery of the robot.<br>Robotik revolutionerar arbetet i farliga miljöer som gruvor och tunnlar, vilket gör livet enklare och säkrare för arbetarna. Det specifika fallet som behandlas i denna avhandling gäller UAV: er som används för 3D-kartläggning av dessa zoner. Användningen av UAV i underjordiska gruvor kan dock vara utmanan- de av många anledningar, till exempel minskad sikt, ingen GPS-lokalisering tillgänglig och begränsad trådlös kommunikation, utmaningar som delvis kan lösas genom att göra roboten autonom. Just av dessa skäl syftar detta arbe- te till att bidra till denna applikation med implementeringen av en autonom vägplaneringsalgoritm för flygfordon i underjordiska zoner. Det relaterade ar- betet har utvecklats med stöd av Inkonova AB, ett robotföretag i Stockholm. Emellertid gäller det speciella bidraget till detta arbete axelminor, som är ver- tikala eller nästan vertikala tunnlar med åtkomst från toppen och botten. Det- ta speciella scenario är extremt utmanande för UAV: er, eftersom längden på dessa tunnlar (vanligtvis 100-200 m) orsakar förlorad signal från kontroll- stationen under uppdraget. Därför väljs den implementerade algoritmen för att lyckas i axelscenarier. Sedan har en optimering av algoritmen gjorts för att minska uppdragstiden och därmed öka chanserna för framgång genom att spara i robotens batteri.
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Books on the topic "Autonomous robots; Path planning"

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Haight, Timothy A. Layered path planning for an autonomous mobile robot. Naval Postgraduate School, 1994.

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Sukhatme, Gaurav, ed. The Path to Autonomous Robots. Springer US, 2009. http://dx.doi.org/10.1007/978-0-387-85774-9.

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Karamanlis, Vasilios. Mulltivariate motion planning of autonomous robots. Naval Postgraduate School, 1997.

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Nourbakhsh, Illah Reza. Interleaving Planning and Execution for Autonomous Robots. Springer US, 1997.

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Nourbakhsh, Illah Reza. Interleaving Planning and Execution for Autonomous Robots. Springer US, 1997. http://dx.doi.org/10.1007/978-1-4615-6317-4.

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Nourbakhsh, Illah Reza. Interleaving planning and execution for autonomous robots. Kluwer Academic Publishers, 1997.

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Reiter, Alexander. Optimal Path and Trajectory Planning for Serial Robots. Springer Fachmedien Wiesbaden, 2020. http://dx.doi.org/10.1007/978-3-658-28594-4.

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Wahdan, Mahmoud A. New motion planning and real-time localization methods using proximity for autonomous mobile robots. Naval Postgraduate School, 1996.

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Milford, Michael John. Robot navigation from nature: Simultaneous localisation, mapping, and path planning based on hippocampal models. Springer, 2008.

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Bonsignore, Joseph. Underwater multi-dimensional path planning for the Naval Postgraduate School Autonomous Underwater Vehicle II. Naval Postgraduate School, 1991.

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Book chapters on the topic "Autonomous robots; Path planning"

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Vasudevan, C., and K. Ganesan. "Case-Based Path Planning for Autonomous Underwater Vehicles." In Underwater Robots. Springer US, 1996. http://dx.doi.org/10.1007/978-1-4613-1419-6_1.

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Dang, Tung, Frank Mascarich, Shehryar Khattak, Christos Papachristos, and Kostas Alexis. "Autonomous Aerial Robots, Informative Path Planning for." In Encyclopedia of Robotics. Springer Berlin Heidelberg, 2020. http://dx.doi.org/10.1007/978-3-642-41610-1_74-1.

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Kanayama, Yutaka, and Bruce I. Hartman. "Smooth Local Path Planning for Autonomous Vehicles." In Autonomous Robot Vehicles. Springer New York, 1990. http://dx.doi.org/10.1007/978-1-4613-8997-2_6.

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Paull, Liam, Sajad Saeedi, and Howard Li. "Path Planning for Autonomous Underwater Vehicles." In Marine Robot Autonomy. Springer New York, 2012. http://dx.doi.org/10.1007/978-1-4614-5659-9_4.

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Espinosa, Omar, Luisa Castañeda, and Fredy Martínez. "Minimalist Artificial Eye for Autonomous Robots and Path Planning." In Intelligent Data Engineering and Automated Learning – IDEAL 2015. Springer International Publishing, 2015. http://dx.doi.org/10.1007/978-3-319-24834-9_28.

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Doi, Yuki, Yonghoon Ji, Yusuke Tamura, et al. "Robust Path Planning Against Pose Errors for Mobile Robots in Rough Terrain." In Intelligent Autonomous Systems 15. Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-030-01370-7_3.

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Gyagenda, Nasser, Ahmad Kamal Nasir, Hubert Roth, and Vadim Zhmud. "Coverage Path Planning for Large-Scale Aerial Mapping." In Towards Autonomous Robotic Systems. Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-23807-0_21.

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Vadakkepat, Prahlad, Tong-Heng Lee, and Liu Xin. "Evolutionary Artificial Potential Field — Applications to Mobile Robot Path Planning." In Autonomous Robotic Systems. Physica-Verlag HD, 2003. http://dx.doi.org/10.1007/978-3-7908-1767-6_8.

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Koubaa, Anis, Hachemi Bennaceur, Imen Chaari, et al. "Performance Analysis of the MRTA Approaches for Autonomous Mobile Robot." In Robot Path Planning and Cooperation. Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-319-77042-0_8.

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Nalini, K. M., and Raju R. Gondkar. "Path Planning and Controlling of Autonomous Robot." In Emerging Research in Computing, Information, Communication and Applications. Springer India, 2015. http://dx.doi.org/10.1007/978-81-322-2550-8_12.

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Conference papers on the topic "Autonomous robots; Path planning"

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Ronnback, Sven, Simon Westerberg, and Kalle Prorok. "CSE+: Path planning amid circles." In 2009 4th International Conference on Autonomous Robots and Agents. IEEE, 2009. http://dx.doi.org/10.1109/icara.2000.4803947.

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"MOBILE ROBOT - A Complete Framework for 2D-path Planning and Motion Planning." In Special Session on Mobile Robots and Autonomous Systems. SciTePress - Science and and Technology Publications, 2011. http://dx.doi.org/10.5220/0003648504170426.

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Wong, Cuebong, Erfu Yang, Xiu-Tian Yan, and Dongbing Gu. "Dynamic, Anytime Task and Path Planning for Mobile Robots." In 2nd UK-RAS ROBOTICS AND AUTONOMOUS SYSTEMS CONFERENCE, Loughborough, 2019. UK-RAS Network, 2019. http://dx.doi.org/10.31256/ukras19.10.

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Schima, Francis, and Stephen Derby. "Two Robot Arm Cooperative Path Planning Using String Stretching." In ASME 1991 International Computers in Engineering Conference and Exposition. American Society of Mechanical Engineers, 1991. http://dx.doi.org/10.1115/cie1991-0159.

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Abstract Two arm robot path planning has many applications. Potential uses of 2 arm robot path planning include terrestrial and space based construction, and general movement of objects. The U.S. space station will most likely be built using robots so that humans do not have to be put into space regularly at great expense and risk. Control of robots from Earth via telerobotics is not practical because the robots will be so far away that there is a delay in the signals due to the great distance between the robots and the controllers and the fact that the signals are limited by the speed of light. The robot arms could also be controlled remotely from space, but only one at a time could be controlled and thus many people would need to be sent up to control all of the robots. One pair of robot arms can replace one human to manually build a structure. However, there would not be any savings in the number of humans sent into space because each pair of robot arms would require a human operator in space. Thus the robot arms should be autonomous or at least semi-autonomous to reduce the number of humans required in space for construction of the space station.
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Hasan, Kazi Mahmud, Abdullah-Al-Nahid, and Khondker Jahid Reza. "Path planning algorithm development for autonomous vacuum cleaner robots." In 2014 International Conference on Informatics, Electronics & Vision (ICIEV). IEEE, 2014. http://dx.doi.org/10.1109/iciev.2014.6850799.

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Orozco-Rosas, Ulises, Kenia Picos, Oscar Montiel, Roberto Sepúlveda, and Víctor H. Díaz-Ramírez. "Obstacle recognition for path planning in autonomous mobile robots." In SPIE Optical Engineering + Applications, edited by Khan M. Iftekharuddin, Abdul A. S. Awwal, Mireya García Vázquez, Andrés Márquez, and Mohammad A. Matin. SPIE, 2016. http://dx.doi.org/10.1117/12.2237412.

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McKeon, Robert T., Mark Paulik, and Mohan Krishnan. "Lane identification and path planning for autonomous mobile robots." In Optics East 2006, edited by David P. Casasent, Ernest L. Hall, and Juha Röning. SPIE, 2006. http://dx.doi.org/10.1117/12.686278.

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Monaghan, Glen E. "World Modeling And Path Planning For Autonomous Mobile Robots." In 1985 Cambridge Symposium, edited by David P. Casasent. SPIE, 1985. http://dx.doi.org/10.1117/12.950825.

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Kuhnert, Lars, Duong V. Nguyen, Stefan Thamke, and Klaus D. Kuhnert. "Autonomous Explorative Outdoor Path Planning." In Biomechanics / Robotics. ACTAPRESS, 2011. http://dx.doi.org/10.2316/p.2011.752-056.

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Kuhnert, Lars, Duong V. Nguyen, Stefan Thamke, and Klaus D. Kuhnert. "Autonomous Explorative Outdoor Path Planning." In Biomechanics / Robotics. ACTAPRESS, 2012. http://dx.doi.org/10.2316/p.2012.752-056.

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Reports on the topic "Autonomous robots; Path planning"

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EISLER, G. RICHARD. Robust Planning for Autonomous Navigation of Mobile Robots in Unstructured, Dynamic Environments: An LDRD Final Report. Office of Scientific and Technical Information (OSTI), 2002. http://dx.doi.org/10.2172/801404.

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