Relevant bibliographies by topics / Mobile robot mapping

Contents

  1. Journal articles
  2. Dissertations / Theses
  3. Books
  4. Book chapters
  5. Conference papers
  6. Reports

Academic literature on the topic 'Mobile robot mapping'

Author: Grafiati
Published: 14 March 2023
Last updated: 31 July 2025

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Journal articles on the topic "Mobile robot mapping"

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Fu, Yuheng, and Qinyou Zhou. "Analysis and application research of mobile robot navigation related technologies." Applied and Computational Engineering 9, no. 1 (2023): 92–96. http://dx.doi.org/10.54254/2755-2721/9/20230055.

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With social progress and technological development, mobile robots have played an important role in industries, medical care, safety, home and other fields due to their advantages of saving labor costs, reducing personnel work intensity, and avoiding potential job hazards. Especially in indoor environments, such as industrial indoor operations, warehousing and logistics distribution, indoor safety patrols, and other application scenarios, mobile robots have highlighted inestimable application value. Intelligent mobile robot is an important tool in the field of service and automation, and robot
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Tsubouchi, Takashi. "Introduction to Simultaneous Localization and Mapping." Journal of Robotics and Mechatronics 31, no. 3 (2019): 367–74. http://dx.doi.org/10.20965/jrm.2019.p0367.

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Simultaneous localization and mapping (SLAM) forms the core of the technology that supports mobile robots. With SLAM, when a robot is moving in an actual environment, real world information is imported to a computer on the robot via a sensor, and robot’s physical location and a map of its surrounding environment of the robot are created. SLAM is a major topic in mobile robot research. Although the information, supported by a mathematical description, is derived from a space in reality, it is formulated based on a probability theory when being handled. Therefore, this concept contributes not on
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Ridlwan, Hasvienda Mohammad, Sonki Prasetya, and Musli Min. "2D Mapping Lingkungan Indoor Menggunakan Lidar dan ROS untuk Mobile Robot." Jurnal Mekanik Terapan 3, no. 2 (2022): 60–65. http://dx.doi.org/10.32722/jmt.v3i2.4285.

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Currently, the application of control systems has been applied in various scientific fields including mechatronics and robotics. Applications in the branch of robotics are also growing day by day not only with conventional controls but also with intelligent systems. An autonomous robot in carrying out certain missions in an unknown environment requires information about the location itself and the environment through the map. A process to identify a position without a map is called a localization function on the robot. Mobile robots building maps and localization are two fundamental tasks when
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Szeląg, Piotr, Sebastian Dudzik, and Anna Podsiedlik. "Investigation on the Mobile Wheeled Robot in Terms of Energy Consumption, Travelling Time and Path Matching Accuracy." Energies 16, no. 3 (2023): 1210. http://dx.doi.org/10.3390/en16031210.

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The task of controlling a wheeled mobile robot is an important element of navigation algorithms. The control algorithm manages the robot’s movement in accordance with the path determined by the planner module, where the accuracy of mapping the given route is very important. Most often, mobile robots are battery-powered, which makes minimizing energy consumption and shortening travel time an important issue. For this reason, in this work, the mobile robot control algorithm was tested in terms of energy consumption, travel time and path mapping accuracy. During the research, a criterion was deve
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Umetani, Tomohiro, Yuya Kondo, and Takuma Tokuda. "Rapid Development of a Mobile Robot for the Nakanoshima Challenge Using a Robot for Intelligent Environments." Journal of Robotics and Mechatronics 32, no. 6 (2020): 1211–18. http://dx.doi.org/10.20965/jrm.2020.p1211.

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Automated mobile platforms are commonly used to provide services for people in an intelligent environment. Data on the physical position of personal electronic devices or mobile robots are important for information services and robotic applications. Therefore, automated mobile robots are required to reconstruct location data in surveillance tasks. This paper describes the development of an autonomous mobile robot to achieve tasks in intelligent environments. In particular, the robot constructed route maps in outdoor environments using laser imaging detection and ranging (LiDAR), and RGB-D sens
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Jimenez Builes, Jovani Alberto, Gustavo Acosta Amaya, and Julián López Velásquez. "Autonomous navigation and indoor mapping for a service robot." Investigación e Innovación en Ingenierías 11, no. 2 (2023): 28–38. http://dx.doi.org/10.17081/invinno.11.2.6459.

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 Objective: Simultaneous Localization and Mapping (SLAM) is a quite common and interesting problem in mobile robotics. It is the basis of safe autonomous navigation of mobile robots and the entrance to new combined applications with a manipulator for instance. Method: In order to find a solution to the SLAM problem, the ROS middleware and the MRPT were selected. Autonomous navigation was tested using two methods, the MRPT navigation ROS package, which is a reactive navigation method based on Trajectory Parameter Space (TP-Space) transformations, and the ROS navigation stack, a st
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Ganiev, Asilbek, and Kang Hee Lee. "A Study of Autonomous Navigation of a Robot Model based on SLAM, ROS, and Kinect." International Journal of Engineering & Technology 7, no. 3.33 (2018): 28. http://dx.doi.org/10.14419/ijet.v7i3.33.18517.

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In this paper, we used a robot operating system (ROS) that is designed to work with mobile robots. ROS provides us with simultaneous localization and mapping of the environment, and here it is used to autonomously navigate a mobile robot simulator between specified points. Also, when the mobile robot automatically navigates between the starting point and the target point, it bypasses obstacles; and if necessary, sets a new path of the route to reach the goal point.
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Deo, Ankit, Ayush Gupta, Himanshu Khemani, and Rashmi Ranjan Das. "Path tracking mobile robot using steppers." E3S Web of Conferences 87 (2019): 01028. http://dx.doi.org/10.1051/e3sconf/20198701028.

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In control of mobile robots, precision plays a key role in path tracking. In this paper we have intended to use hybrid stepper motors for precise control of the two wheeled robot. A control algorithm was developed to control the robot along different trajectories. We have found that stepper motors are more accurate for path tracking than normal DC motors with wheel encoders and one can obtain the implicit coordinates of the robot in runtime more precisely. Getting the precise coordinates of the robot at runtime can be used in various SLAM and VSLAM techniques for more accurate 3D mapping of th
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Sujan, Vivek Anand, Marco Antonio Meggiolaro, and Felipe Augusto Weilemann Belo. "A new technique in mobile robot simultaneous localization and mapping." Sba: Controle & Automação Sociedade Brasileira de Automatica 17, no. 2 (2006): 189–204. http://dx.doi.org/10.1590/s0103-17592006000200007.

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In field or indoor environments it is usually not possible to provide service robots with detailed a priori environment and task models. In such environments, robots will need to create a dimensionally accurate geometric model by moving around and scanning the surroundings with their sensors, while minimizing the complexity of the required sensing hardware. In this work, an iterative algorithm is proposed to plan the visual exploration strategy of service robots, enabling them to efficiently build a graph model of their environment without the need of costly sensors. In this algorithm, the inf
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Nagla, KS, Moin Uddin, and Dilbag Singh. "Dedicated Filter for Robust Occupancy Grid Mapping." IAES International Journal of Robotics and Automation (IJRA) 4, no. 1 (2014): 82. http://dx.doi.org/10.11591/ijra.v4i1.pp82-92.

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<p>Sensor based perception of the environment is an emerging area of the mobile robot research where sensors play a pivotal role. For autonomous mobile robots, the fundamental requirement is the convergent of the range information in to high level internal representation. Internal representation in the form of occupancy grid is commonly used in autonomous mobile robots due to its various advantages. There are several sensors such as vision sensor, laser rage finder, and ultrasonic and infrared sensors etc. play roles in mapping. However the sensor information failure, sensor inaccuracies
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Dissertations / Theses on the topic "Mobile robot mapping"

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HASSANZADEH, Aidin. "Mobile Robot Wind Mapping." Thesis, Örebro universitet, Institutionen för naturvetenskap och teknik, 2014. http://urn.kb.se/resolve?urn=urn:nbn:se:oru:diva-34606.

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Statistical gas distribution mapping has recently become a prominent research area in the robotics community. Gas distribution mapping using mobile robots aims for building map of gas dispersion in an unknown environment using the sampled gas concentrations accompanied by the corresponding atmospheric variables. In this context, wind is considered as one of the main driving forces and recently exploited as an environmental bias in the the modelling process. However, the existing approaches utilizing the wind data are based on very simple averaging window methods which do not take the specic sp
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Wong, Chee Kit. "Cognitive inspired mapping by an autonomous mobile robot." Click here to access this resource online, 2008. http://hdl.handle.net/10292/427.

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When animals explore a new environment, they do not acquire a precise map of the places visited. In fact, research has shown that learning is a recurring process. Over time, new information helps the animal to update their perception of the locations it has visited. Yet, they are still able to use the fuzzy and often incomplete representation to find their way home. This process has been termed the cognitive mapping process. The work presented in this thesis uses a mobile robot equipped with sonar sensors to investigate the nature of such a process. Specifically, what is the information that i
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WANG, XUAN. "2D Mapping Solutionsfor Low Cost Mobile Robot." Thesis, KTH, Skolan för datavetenskap och kommunikation (CSC), 2013. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-138427.

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Mapping, localization, and path-planning are three fundamental problems of robotic. Robot needs a map to perform actions like path-planning. When positioning system is not available, the map is also used for localization. A lot of researches have been done in this area. And newly emerging ranging sensors, like Kinect and TOF camera, have widen people’s choices and greatly enhanced innovative ideas in robot mapping. The price of these sensors is not very high and the performance is decent, which makes low cost, high performance mobile robot solution possible. In this thesis, different existing
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Nordin, Peter. "Mobile Robot Traversability Mapping : For Outdoor Navigation." Licentiate thesis, Linköpings universitet, Fluida och mekatroniska system, 2012. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-85937.

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To avoid getting stuck or causing damage to a vehicle or its surroundings a driver must be able to identify obstacles and adapt speed to ground conditions. An automatically controlled vehicle must be able to handle these identifications and adjustments by itself using sensors, actuators and control software. By storing properties of the surroundings in a map, a vehicle revisiting an area can benefit from prior information. Rough ground may cause oscillations in the vehicle chassis. These can be measured by on-board motion sensors. For obstacle detection, a representation of the geometry of the
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Deďo, Michal. "Řízení čtyřkolového mobilního robotu." Master's thesis, Vysoké učení technické v Brně. Fakulta strojního inženýrství, 2011. http://www.nusl.cz/ntk/nusl-229688.

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The purpose of this thesis is to design and implement four-wheel mobile robot control which will be used in future in the field of mapping and localization. Concretely, it will be a design of drive control with microcontrollers Xmega, which will also process the signals of the sensors. Communication with the PC will ensure the BlueTooth module. In view of the future use of the robot, there will be designed and carried out modifications of the mechanical part. Correctness and functionality of all parts of the robot will be verified by carrying out basic movements.
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McCoig, Kenneth. "A MOBILE ROBOTIC COMPUTING PLATFORM FOR THREE-DIMENSIONAL INDOOR MAPPI." Master's thesis, University of Central Florida, 2004. http://digital.library.ucf.edu/cdm/ref/collection/ETD/id/2372.

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There are several industries exploring solutions to quickly and accurately digitize unexplored indoor environments, into useable three-dimensional databases. Unfortunately, there are inherent challenges to the indoor mapping process such as, scanning limitations and environment complexity, which require a specific application of tools to map an environment precisely with low cost and high speed. This thesis successfully demonstrates the design and implementation of a low cost mobile robotic computing platform with laser scanner, for quickly mapping with high resolution, urban and/or indoor env
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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
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Casalaro, Giuseppina Lucia, and Giulio Cattivera. "MODEL-DRIVEN ENGINEERING FOR MOBILE ROBOT SYSTEMS: A SYSTEMATIC MAPPING STUDY." Thesis, Mälardalens högskola, Akademin för innovation, design och teknik, 2015. http://urn.kb.se/resolve?urn=urn:nbn:se:mdh:diva-28261.

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The development of autonomous Mobile Robot Systems is attracting nowadays more and moreinterest from both researchers and practitioners, mainly because they may open for a wide rangeof improvements for quality of life. Mobile robots are systems capable of accomplishing missionsby moving in an unknown environment without human supervision. Throughout mechanisms ofdetection, communication and adaptation, they can adapt their behavior according to changes ofthe environment. Individual robots can even join teams of autonomous mobile robots that, throughindividual tasks, accomplish common missions.
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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.

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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. Fr
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ROSA, STEFANO. "Localization and Mapping for Service Robotics Applications." Doctoral thesis, Politecnico di Torino, 2014. http://hdl.handle.net/11583/2542488.

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In this work we address different techniques for autonomous navigation of single and multi-robot systems in unstructured indoor environments. The first problem that we address is the problem of robot localization. We first show how a multi-robot localization approach can speed up the process as well as introducing robustness to failures. At the same time we show the possibility to introduce some sort of insight into the algorithm. We then focus on increasing the robustness of single robot localization, by taking advantage of sensor fusion and by exploiting visual markers embedded in the enviro
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Books on the topic "Mobile robot mapping"

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Mullane, John. Random Finite Sets for Robot Mapping and SLAM: New Concepts in Autonomous Robotic Map Representations. Springer Berlin Heidelberg, 2011.

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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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Kucner, Tomasz Piotr, Achim J. Lilienthal, Martin Magnusson, Luigi Palmieri, and Chittaranjan Srinivas Swaminathan. Probabilistic Mapping of Spatial Motion Patterns for Mobile Robots. Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-41808-3.

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Fernández-Madrigal, Juan-Antonio. Simultaneous localization and mapping for mobile robots: Introduction and methods. Information Science Reference, 2013.

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Bayoud, Fadi Atef. Development of a robotic mobile mapping system by vision-aided inertial navigation: A geomatics approach. Institut für Geodäsie und Photogrammetrie, Eidgenössische Technische Hochschule Zürich, 2006.

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Hafner, Verena Vanessa. Adaptive navigation strategies in biorobotics: Visual homing and cognitive mapping in animals and machines. Shaker, 2004.

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Adaptive Sampling With Mobile Wsn Simultaneous Robot Localisation And Mapping Of Paramagnetic Spatiotemporal Fields. Institution of Engineering & Technology (IET), 2011.

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Lewis, Frank L., Koushil Sreenath, Muhammad F. Mysorewala, and Dan O. Popa. Adaptive Sampling with Mobile WSN: Simultaneous Robot Localisation and Mapping of Paramagnetic Spatio-Temporal Fields. Institution of Engineering & Technology, 2011.

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Milford, Michael John. Robot Navigation from Nature: Simultaneous Localisation, Mapping, and Path Planning Based on Hippocampal Models. Springer London, Limited, 2007.

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Milford, Michael John. Robot Navigation from Nature: Simultaneous Localisation, Mapping, and Path Planning Based on Hippocampal Models. Springer, 2010.

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Book chapters on the topic "Mobile robot mapping"

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Chatterjee, Amitava, Anjan Rakshit, and N. Nirmal Singh. "Simultaneous Localization and Mapping (SLAM) in Mobile Robots." In Vision Based Autonomous Robot Navigation. Springer Berlin Heidelberg, 2013. http://dx.doi.org/10.1007/978-3-642-33965-3_7.

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Krishna, K. Y. V., A. Wadnerkar, G. M. Patel, G. Baluni, A. K. Pandey, and R. M. Suresh Babu. "Indigenous Mobile Robot for Surveillance and Mapping." In Lecture Notes in Mechanical Engineering. Springer Singapore, 2018. http://dx.doi.org/10.1007/978-981-10-8597-0_33.

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Kulich, Miroslav, Petr ŠtŐpán, and Libor Přeučil. "Knowledge Acquisition for Mobile Robot Environment Mapping." In Lecture Notes in Computer Science. Springer Berlin Heidelberg, 1999. http://dx.doi.org/10.1007/3-540-48309-8_11.

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Zelinsky, A. "Environment mapping with a mobile robot using sonar." In AI '88. Springer Berlin Heidelberg, 1990. http://dx.doi.org/10.1007/3-540-52062-7_90.

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Bruno, Giovanni di Dio. "Erwhi Hedgehog: A New Learning Platform for Mobile Robotics." In Makers at School, Educational Robotics and Innovative Learning Environments. Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-77040-2_32.

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AbstractErwhi Hedgehog is one of the smallest mobile robots. It enables mapping and vision analysis, and also displays machine learning features. Behaving like a small, curious animal, eager to explore the surroundings, the robot can be used to test navigation, mapping and localization algorithms, thus allowing the prototyping of new hardware and software for robotics. This application is particularly handy for educational robotics, at both high school and university level. On the one hand, the project is fully open source and open hardware under MIT license and available on Github, so everyon
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Schmidt, Jochen, Chee K. Wong, and Wai K. Yeap. "Localisation and Mapping With a Mobile Robot Using Sparse Range Data." In Autonomous Robots and Agents. Springer Berlin Heidelberg, 2007. http://dx.doi.org/10.1007/978-3-540-73424-6_4.

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Rogers, John G., Alexander J. B. Trevor, Carlos Nieto-Granda, et al. "Effects of Sensory Precision on Mobile Robot Localization and Mapping." In Experimental Robotics. Springer Berlin Heidelberg, 2014. http://dx.doi.org/10.1007/978-3-642-28572-1_30.

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Gu, Chaoyue, Zhenxing Sun, and Wang Ting. "Invariant EKF Based Mobile Robot Simultaneous Localization and Mapping Navigation." In Communications in Computer and Information Science. Springer Nature Singapore, 2022. http://dx.doi.org/10.1007/978-981-19-7946-0_35.

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Mando, Raghad, Eylül Özer, and Burak İnner. "Autonomous Mobile Robot Mapping and Exploration of an Indoor Environment." In Computational Intelligence, Data Analytics and Applications. Springer International Publishing, 2023. http://dx.doi.org/10.1007/978-3-031-27099-4_2.

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Piardi, Luis, José Lima, Paulo Costa, and Thadeu Brito. "Development of a Dynamic Path for a Toxic Substances Mapping Mobile Robot in Industry Environment." In ROBOT 2017: Third Iberian Robotics Conference. Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-70836-2_54.

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Conference papers on the topic "Mobile robot mapping"

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Fatah, Muhammad, Muhammad Rivai, and Ronny Mardiyanto. "Indoor Gas Mapping Using Ultra-Wideband Based Mobile Robot." In 2024 International Seminar on Intelligent Technology and Its Applications (ISITIA). IEEE, 2024. http://dx.doi.org/10.1109/isitia63062.2024.10667771.

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Nguyen, Ngoc Thinh, Niklas Fin Kompe, Nicolas Mandel, Neele Kohle, and Floris Ernst. "Autonomous mapping and monitoring of rumex with mobile robot." In 2024 10th International Conference on Control, Decision and Information Technologies (CoDIT). IEEE, 2024. http://dx.doi.org/10.1109/codit62066.2024.10708540.

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Hou, Jingfu, Ziyan Zhao, Shixin Liu, and Dawei Yang. "Topology Mapping and Connectivity Detection for Autonomous Mobile Robot Systems." In 2024 IEEE 20th International Conference on Automation Science and Engineering (CASE). IEEE, 2024. http://dx.doi.org/10.1109/case59546.2024.10711744.

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Wang, Junlin, Shanshan Sun, Lianxin Hu, et al. "Research and trend of key technology of mining mobile robot mapping." In International Conference on Mechatronics and Mechanical Engineering (ICMME 2024), edited by Yucheng Jiang. SPIE, 2024. http://dx.doi.org/10.1117/12.3037056.

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Prawira, Sandy, Rangga Winantyo, and Eunike Endariahna Surbakti. "Mobile Robot System Design With Mapping Function For Industrial Logistic Management*." In 2024 International Conference on Advanced Robotics and Mechatronics (ICARM). IEEE, 2024. http://dx.doi.org/10.1109/icarm62033.2024.10715951.

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Özkil, Ali Gürcan, and Thomas Howard. "Automatically Annotated Mapping for Indoor Mobile Robot Applications." In ASME 2012 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference. American Society of Mechanical Engineers, 2012. http://dx.doi.org/10.1115/detc2012-71351.

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This paper presents a new and practical method for mapping and annotating indoor environments for mobile robot use. The method makes use of 2D occupancy grid maps for metric representation, and topology maps to indicate the connectivity of the ‘places-of-interests’ in the environment. Novel use of 2D visual tags allows encoding information physically at places-of-interest. Moreover, using physical characteristics of the visual tags (i.e. paper size) is exploited to recover relative poses of the tags in the environment using a simple camera. This method extends tag encoding to simultaneous loca
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Kasetani, Misaki, Tomonobu Noguchi, Hirotake Yamazoe, and Joo-Ho Lee. "Projection mapping by mobile projector robot." In 2015 12th International Conference on Ubiquitous Robots and Ambient Intelligence (URAI). IEEE, 2015. http://dx.doi.org/10.1109/urai.2015.7358918.

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Nitsche, Matias, Pablo de Cristoforis, Miroslav Kulich, and Karel Kosnar. "Hybrid mapping for autonomous mobile robot exploration." In 2011 IEEE 6th International Conference on Intelligent Data Acquisition and Advanced Computing Systems: Technology and Applications (IDAACS). IEEE, 2011. http://dx.doi.org/10.1109/idaacs.2011.6072761.

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Zhang, Nan, Maohai Li, and Bingrong Hong. "Active Mobile Robot Simultaneous Localization and Mapping." In 2006 IEEE International Conference on Robotics and Biomimetics. IEEE, 2006. http://dx.doi.org/10.1109/robio.2006.340218.

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Liu, Haoxin, Yonghui Zhang, and Yibo Cao. "A Mapping Method for Indoor Mobile Robot." In CSAE 2020: The 4th International Conference on Computer Science and Application Engineering. ACM, 2020. http://dx.doi.org/10.1145/3424978.3425050.

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Reports on the topic "Mobile robot mapping"

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Lee, W. S., Victor Alchanatis, and Asher Levi. Innovative yield mapping system using hyperspectral and thermal imaging for precision tree crop management. United States Department of Agriculture, 2014. http://dx.doi.org/10.32747/2014.7598158.bard.

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Original objectives and revisions – The original overall objective was to develop, test and validate a prototype yield mapping system for unit area to increase yield and profit for tree crops. Specific objectives were: (1) to develop a yield mapping system for a static situation, using hyperspectral and thermal imaging independently, (2) to integrate hyperspectral and thermal imaging for improved yield estimation by combining thermal images with hyperspectral images to improve fruit detection, and (3) to expand the system to a mobile platform for a stop-measure- and-go situation. There were no
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Brodie, Katherine, Brittany Bruder, Richard Slocum, and Nicholas Spore. Simultaneous mapping of coastal topography and bathymetry from a lightweight multicamera UAS. Engineer Research and Development Center (U.S.), 2021. http://dx.doi.org/10.21079/11681/41440.

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A low-cost multicamera Unmanned Aircraft System (UAS) is used to simultaneously estimate open-coast topography and bathymetry from a single longitudinal coastal flight. The UAS combines nadir and oblique imagery to create a wide field of view (FOV), which enables collection of mobile, long dwell timeseries of the littoral zone suitable for structure-from motion (SfM), and wave speed inversion algorithms. Resultant digital surface models (DSMs) compare well with terrestrial topographic lidar and bathymetric survey data at Duck, NC, USA, with root-mean-square error (RMSE)/bias of 0.26/–0.05 and
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