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

Author: Grafiati

Published: 4 June 2021

Last updated: 1 February 2022

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1

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 expe

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2

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 posi

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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 algo

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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 motio

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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 me

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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,

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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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9

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

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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 wit

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Vasu, V., and K. Jyothi Kumar. "Optimal Path Planning of an Autonomous Mobile Robot Using Genetic Algorithm." Advanced Materials Research 488-489 (March 2012): 1747–51. http://dx.doi.org/10.4028/www.scientific.net/amr.488-489.1747.

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An autonomous Mobile Robot (AMR) is a machine able to extract information from its environment and move in a meaningful and purposeful manner. Robot Navigation and Obstacle avoidance are the most important problems in mobile robots. In the past, a number of soft computing algorithms have been designed by many researchers for robot navigation problems but very few are actually implementable because they haven’t considered robot size as parameter. This paper presents software simulation and hardware implementation of navigation of a mobile robot avoiding obstacles and selecting optimal path in a

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12

Ma, Xi Pei, Bing Feng Qian, Song Jie Zhang, and Ye Wang. "Research on Technology and Application of Multi-Sensor Data Fusion for Indoor Service Robots." Applied Mechanics and Materials 651-653 (September 2014): 831–34. http://dx.doi.org/10.4028/www.scientific.net/amm.651-653.831.

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The autonomous navigation process of a mobile service robot is usually in uncertain environment. The information only given by sensors has been unable to meet the demand of the modern mobile robots, so multi-sensor data fusion has been widely used in the field of robots. The platform of this project is the achievement of the important 863 Program national research project-a prototype nursing robot. The aim is to study a mobile service robot’s multi-sensor information fusion, path planning and movement control method. It can provide a basis and practical use’s reference for the study of an indo

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13

Fazlollahtabar, Hamed. "An Effective Mathematical Programming Model for Production Automatic Robot Path Planning." Open Transportation Journal 13, no. 1 (2019): 11–16. http://dx.doi.org/10.2174/1874447801913010011.

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Objective: Path planning for production robots has been investigated. The sequence of the orders to be processed in a certain planning horizon has been planned for the production system. Methods: Production automatic robots are employed to carry parts and products among all production stations and machining centers. The combination of machines in stations and autonomous robot evolves a production network. Results: The problem is to assign orders to robots so that paths are obtained to minimize total waiting times of production system and meanwhile provide collision-free paths. Conclusion: The

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14

Pruski, A. "Multivalue coding: application to autonomous robots." Robotica 10, no. 2 (1992): 125–33. http://dx.doi.org/10.1017/s0263574700007542.

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SUMMARYThe paper describes a free space modeling method by multivalue coding. Each code defines some numerical values representing a set of cells from a grid. The idea consists in using the grid as a Karnaugh board whose rows and columns are binary coded rather than Gray coded. This operating method allows to define, for each code, its grid location and allows numerical comparison in order to locate a code relatively to another. This aspect is helpful for path planning. The free space model is represented by a switching function or a tree to which boolean algebra rules and mathematic operation

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Ma, Yingchong, Gang Zheng, Wilfrid Perruquetti, and Zhaopeng Qiu. "Local path planning for mobile robots based on intermediate objectives." Robotica 33, no. 4 (2014): 1017–31. http://dx.doi.org/10.1017/s0263574714000186.

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SUMMARYThis paper presents a path planning algorithm for autonomous navigation of non-holonomic mobile robots in complex environments. The irregular contour of obstacles is represented by segments. The goal of the robot is to move towards a known target while avoiding obstacles. The velocity constraints, robot kinematic model and non-holonomic constraint are considered in the problem. The optimal path planning problem is formulated as a constrained receding horizon planning problem and the trajectory is obtained by solving an optimal control problem with constraints. Local minima are avoided b

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Zhi, Yonghong, and Yan Jiang. "Design of basketball robot based on behavior-based fuzzy control." International Journal of Advanced Robotic Systems 17, no. 2 (2020): 172988142090996. http://dx.doi.org/10.1177/1729881420909965.

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Aiming at the strong dependence on environmental information in traditional algorithms, the path planning of basketball robots in an unknown environment, and improving the safety of autonomous navigation, this article proposes a path planning algorithm based on behavior-based module control. In this article, fuzzy control theory is applied to the behavior control structure, and these two path planning algorithms are combined to solve the path planning problem of basketball robots in an unknown environment. First, the data of each sensor of the basketball robot configuration are simply fused. T

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Hosseininejad, Seyedhadi, and Chitra Dadkhah. "Mobile robot path planning in dynamic environment based on cuckoo optimization algorithm." International Journal of Advanced Robotic Systems 16, no. 2 (2019): 172988141983957. http://dx.doi.org/10.1177/1729881419839575.

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Nowadays, the usage of autonomous mobile robots that fulfill various activities in enormous number of applications without human’s interference in a dynamic environment are thriving. A dynamic environment is the robot’s environment which is comprised of some static obstacles as well as several movable obstacles that their quantity and location change randomly through the time. Efficient path planning is one the significant necessities of these kind of robots to do their tasks effectively. Mobile robot path planning in a dynamic environment is finding a shortest possible path from an arbitrary

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18

Song, Weibo, Wei Wang, Xianjiu Guo, and Fengjiao Jiang. "Autonomous Return Path Planning Method for Small Underwater Robots." Journal of Coastal Research 83, sp1 (2019): 184. http://dx.doi.org/10.2112/si83-028.1.

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19

Volos, Ch K., I. M. Kyprianidis, and I. N. Stouboulos. "A chaotic path planning generator for autonomous mobile robots." Robotics and Autonomous Systems 60, no. 4 (2012): 651–56. http://dx.doi.org/10.1016/j.robot.2012.01.001.

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Azpúrua, Héctor, Gustavo M. Freitas, Douglas G. Macharet, and Mario F. M. Campos. "Multi-robot coverage path planning using hexagonal segmentation for geophysical surveys." Robotica 36, no. 8 (2018): 1144–66. http://dx.doi.org/10.1017/s0263574718000292.

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SUMMARYThe field of robotics has received significant attention in our society due to the extensive use of robotic manipulators; however, recent advances in the research on autonomous vehicles have demonstrated a broader range of applications, such as exploration, surveillance, and environmental monitoring. In this sense, the problem of efficiently building a model of the environment using cooperative mobile robots is critical. Finding routes that are either length or time-optimized is essential for real-world applications of small autonomous robots. This paper addresses the problem of multi-r

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Muñoz, Pablo, María D. R-Moreno, and David F. Barrero. "Unified framework for path-planning and task-planning for autonomous robots." Robotics and Autonomous Systems 82 (August 2016): 1–14. http://dx.doi.org/10.1016/j.robot.2016.04.010.

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22

Alvarez, Gabriela, and Omar Flor. "Desempeño en métodos de navegación autónoma para robots móviles." Minerva 1, no. 2 (2020): 19–29. http://dx.doi.org/10.47460/minerva.v1i2.8.

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En este trabajo se presenta una comparación de los tiempos de respuesta, optimización de la ruta y complejidad del grafo en métodos de planificación de trayectoria para robots móviles autónomos. Se contrastan los desarrollos de Voronoi, Campos potenciales, Roadmap probabilístico y Descomposición en celdas para la navegación en un mismo entorno y validándolos para un número variable de obstáculos. Las evaluaciones demuestran que el método de generación de trayectoria por Campos Potenciales, mejora la navegación respecto de la menor ruta obtenida, el método Rapidly Random Tree genera los grafos

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23

Paull, Liam, Mae Seto, John J. Leonard, and Howard Li. "Probabilistic cooperative mobile robot area coverage and its application to autonomous seabed mapping." International Journal of Robotics Research 37, no. 1 (2017): 21–45. http://dx.doi.org/10.1177/0278364917741969.

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There are many applications that require mobile robots to autonomously cover an entire area with a sensor or end effector. The vast majority of the literature on this subject is focused on addressing path planning for area coverage under the assumption that the robot’s pose is known or that error is bounded. In this work, we remove this assumption and develop a completely probabilistic representation of coverage. We show that coverage is guaranteed as long as the robot pose estimates are consistent, a much milder assumption than zero or bounded error. After formally connecting robot sensor unc

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Lavrenov, Lavrenov, Evgeni Magid, Matsuno Fumitoshi, Mikhail Svinin, and Jackrit Suthakorn. "Development and Implementation of Spline-based Path Planning Algorithm in ROS/Gazebo Environment." SPIIRAS Proceedings 18, no. 1 (2019): 57–84. http://dx.doi.org/10.15622/sp.18.1.57-84.

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Path planning for autonomous mobile robots is an important task within robotics field. It is common to use one of the two classical approaches in path planning: a global approach when an entire map of a working environment is available for a robot or local methods, which require the robot to detect obstacles with a variety of onboard sensors as the robot traverses the environment. In our previous work, a multi-criteria spline algorithm prototype for a global path construction was developed and tested in Matlab environment. The algorithm used the Voronoi graph for computing an initial pat

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Das, Subir Kumar, Ajoy Kumar Dutta, and Subir Kumar Debnath. "OperativeCriticalPointBug algorithm-local path planning of mobile robot avoiding obstacles." Indonesian Journal of Electrical Engineering and Computer Science 18, no. 3 (2020): 1646. http://dx.doi.org/10.11591/ijeecs.v18.i3.pp1646-1656.

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<span>For Autonomous Mobile Robot one of the biggest and interesting issues is path planning. An autonomous mobile robot should be able determine its own path to reach destination. This paper offers a new algorithm for mobile robot to plan a path in local environments with stationary as well as moving obstacles. For movable robots’ path planning OperativeCriticalPointBug (OCPB) algorithm, is a new Bug algorithm. This algorithm is carried out by the robot throughout the movement from source to goal, hence allowing the robot to rectify its way if a new obstacle comes into the route or any

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Ravankar, Abhijeet, Ankit Ravankar, Yukinori Kobayashi, Yohei Hoshino, and Chao-Chung Peng. "Path Smoothing Techniques in Robot Navigation: State-of-the-Art, Current and Future Challenges." Sensors 18, no. 9 (2018): 3170. http://dx.doi.org/10.3390/s18093170.

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Robot navigation is an indispensable component of any mobile service robot. Many path planning algorithms generate a path which has many sharp or angular turns. Such paths are not fit for mobile robot as it has to slow down at these sharp turns. These robots could be carrying delicate, dangerous, or precious items and executing these sharp turns may not be feasible kinematically. On the contrary, smooth trajectories are often desired for robot motion and must be generated while considering the static and dynamic obstacles and other constraints like feasible curvature, robot and lane dimensions

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Ji, Xue Song, Ping Xu, and Guo Chen Niu. "Visual-Based Motion Planning for Autonomous Humanoid Service Robot." Advanced Materials Research 143-144 (October 2010): 1031–35. http://dx.doi.org/10.4028/www.scientific.net/amr.143-144.1031.

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A visual-based autonomous motion planning algorithm is designed to guide the robot to take the elevator autonomously. The floor chosen operation as well as the path planning and motion control for the robot’s in-out elevator are the two critical issues. A visual-based motion regulation method is proposed in this paper, so is a manipulator motion planning algorithm based on image Jacobian Matrix. Fuzzy logic is used to mobile path planning. Experimental results on humanoid service robot proves the validity of this control system.

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Ćurković, Petar, and Lovro Čehulić. "Diversity Maintenance for Efficient Robot Path Planning." Applied Sciences 10, no. 5 (2020): 1721. http://dx.doi.org/10.3390/app10051721.

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Path planning is present in many areas, such as robotics, video games, and unmanned autonomous vehicles. In the case of robots, it is a primary low-level prerequisite for the successful execution of high-level tasks. It is a known and difficult problem to solve, especially in terms of finding optimal paths for robots working in complex environments. Recently, population-based methods for multi-objective optimization, i.e., swarm and evolutionary algorithms successfully perform on different path planning problems. Knowing the nature of the problem is hard for optimization algorithms, it is expe

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Cui, Peng, Weisheng Yan, and Yintao Wang. "Reactive Path Planning Approach for Docking Robots in Unknown Environment." Journal of Advanced Transportation 2017 (2017): 1–11. http://dx.doi.org/10.1155/2017/6716820.

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Autonomous robots need to be recharged and exchange information with the host through docking in the long-distance tasks. Therefore, feasible path is required in the docking process to guide the robot and adjust its pose. However, when there are unknown obstacles in the work area, it becomes difficult to determine the feasible path for docking. This paper presents a reactive path planning approach named Dubins-APF (DAPF) to solve the path planning problem for docking in unknown environment with obstacles. In this proposed approach the Dubins curves are combined with the designed obstacle avoid

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Minh, Vu Trieu. "Nonlinear Model Predictive Controller and Feasible Path Planning for Autonomous Robots." Open Computer Science 6, no. 1 (2016): 178–86. http://dx.doi.org/10.1515/comp-2016-0015.

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AbstractThis paper develops the nonlinear model predictive control (NMPC) algorithm to control autonomous robots tracking feasible paths generated directly from the nonlinear dynamic equations.NMPC algorithm can secure the stability of this dynamic system by imposing additional conditions on the open loop NMPC regulator. The NMPC algorithm maintains a terminal constrained region to the origin and thus, guarantees the stability of the nonlinear system. Simulations show that the NMPC algorithm can minimize the path tracking errors and control the autonomous robots tracking exactly on the feasibl

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31

Yoon, Hee-Sang, and Tae-Hyoung Park. "Path Planning for Autonomous Mobile Robots by Modified Global DWA." Transactions of The Korean Institute of Electrical Engineers 60, no. 2 (2011): 389–97. http://dx.doi.org/10.5370/kiee.2011.60.2.389.

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Santos, Luís Carlos, André Silva Aguiar, Filipe Neves Santos, António Valente, and Marcelo Petry. "Occupancy Grid and Topological Maps Extraction from Satellite Images for Path Planning in Agricultural Robots." Robotics 9, no. 4 (2020): 77. http://dx.doi.org/10.3390/robotics9040077.

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Robotics will significantly impact large sectors of the economy with relatively low productivity, such as Agri-Food production. Deploying agricultural robots on the farm is still a challenging task. When it comes to localising the robot, there is a need for a preliminary map, which is obtained from a first robot visit to the farm. Mapping is a semi-autonomous task that requires a human operator to drive the robot throughout the environment using a control pad. Visual and geometric features are used by Simultaneous Localisation and Mapping (SLAM) Algorithms to model and recognise places, and tr

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Nishitani, Ippei, Tetsuya Matsumura, Mayumi Ozawa, Ayanori Yorozu, and Masaki Takahashi. "3D X-Y-T Space Path Planning for Autonomous Mobile Robots Considering Dynamic Constraints." Applied Mechanics and Materials 490-491 (January 2014): 1163–67. http://dx.doi.org/10.4028/www.scientific.net/amm.490-491.1163.

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An autonomous mobile robot in a human living space should be able to not only realize collision-free motion but also give way to humans depending on the situation. Although various reactive obstacle avoidance methods have been proposed, it is difficult to achieve such motion. On the other hand, 3D X-Y-T space path planning, which takes into account the motion of both the robot and the human in a look-ahead time horizon, is effective. This paper proposes a real-time obstacle avoidance method for an autonomous mobile robot that considers the robots dynamic constraints, the personal space, and hu

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Torres-Sospedra, Joaquín, and Patricio Nebot. "Combining Satellite Images and Cadastral Information for Outdoor Autonomous Mapping and Navigation: A Proof-of-Concept Study in Citric Groves." Algorithms 12, no. 9 (2019): 193. http://dx.doi.org/10.3390/a12090193.

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The development of robotic applications for agricultural environments has several problems which are not present in the robotic systems used for indoor environments. Some of these problems can be solved with an efficient navigation system. In this paper, a new system is introduced to improve the navigation tasks for those robots which operate in agricultural environments. Concretely, the paper focuses on the problem related to the autonomous mapping of agricultural parcels (i.e., an orange grove). The map created by the system will be used to help the robots navigate into the parcel to perform

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Liu, Zai Xin, Long Xiang Yang, and Jin Ge Wang. "Soccer Robot Path Planning Based on Evolutionary Artificial Field." Advanced Materials Research 562-564 (August 2012): 955–58. http://dx.doi.org/10.4028/www.scientific.net/amr.562-564.955.

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To improve the success rate of Soccer Robot Path Planning, artificial potential field is amended, autonomous potential field is presented to solve the path planning problem by analyzing shortcomings of the basic shooting algorithm, the autonomous potential field function centering on the soccer robot is constructed, and the robot’s movement in the new potential field is analyzed, the modified artificial potential field model and autonomous potential field model is contrasted, each vicinal potential energy of the modified artificial potential field model and autonomous potential field model is

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Keerthana, V., C. Kiruthiga, P. Kiruthika, V. Sowmiya, and R. Manikadan. "NAVIGATION OF MOBILE ROBOT- ALGORITHM FOR PATH PLANNING & COLLISION AVOIDANCE- A REVIEW." International Journal of Research -GRANTHAALAYAH 5, no. 1 (2017): 198–205. http://dx.doi.org/10.29121/granthaalayah.v5.i1.2017.1735.

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The ﬁeld of autonomous mobile robotics has recently gained many researchers’ interests. Due to the speciﬁc needs required by various applications of mobile robot systems, especially in navigation, designing a real time obstacle avoidance and path following robot system has become the backbone of controlling robots in unknown environments. The main objective of our project is applications based mobile robot systems, especially in navigation, designing real time obstacle avoidance and path following robot system has become the backbone of controlling robots in unknown environments. The main obje

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Zagradjanin, Novak, Aleksandar Rodic, Dragan Pamucar, and Bojan Pavkovic. "Cloud-Based Multi-Robot Path Planning in Complex and Crowded Environment Using Fuzzy Logic and Online Learning." Information Technology and Control 50, no. 2 (2021): 357–74. http://dx.doi.org/10.5755/j01.itc.50.2.28234.

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This paper considers an autonomous cloud-based multi-robot system designed to execute highly repetitive tasksin a dynamic environment such as a modern megastore. Cloud level is intended for performing the most demandingoperations in order to unload the robots that are users of cloud services in this architecture. For path planningon global level D* Lite algorithm is applied, bearing in mind its high efficiency in dynamic environments. In orderto introduce smart cost map for further improvement of path planning in complex and crowded environment, implementationof fuzzy inference system and lear

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Saeedi, Sajad, Carl Thibault, Michael Trentini, and Howard Li. "3D Mapping for Autonomous Quadrotor Aircraft." Unmanned Systems 05, no. 03 (2017): 181–96. http://dx.doi.org/10.1142/s2301385017400064.

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Autonomous navigation in global positioning system (GPS)-denied environments is one of the challenging problems in robotics. For small flying robots, autonomous navigation is even more challenging. These robots have limitations such as fast dynamics and limited sensor payload. To develop an autonomous robot, many challenges including two-dimensional (2D) and three-dimensional (3D) perception, path planning, exploration, and obstacle avoidance should be addressed in real-time and with limited resources. In this paper, a complete solution for autonomous navigation of a quadrotor rotorcraft is pr

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Cai, Jianxian, Xiaogang Ruan, and Pengxuan Li. "Autonomous Path Planning Scheme Research for Mobile Robot." Cybernetics and Information Technologies 16, no. 4 (2016): 113–25. http://dx.doi.org/10.1515/cait-2016-0072.

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Abstract An autonomous path-planning strategy based on Skinner operant conditioning principle and reinforcement learning principle is developed in this paper. The core strategies are the use of tendency cell and cognitive learning cell, which simulate bionic orientation and asymptotic learning ability. Cognitive learning cell is designed on the base of Boltzmann machine and improved Q-Learning algorithm, which executes operant action learning function to approximate the operative part of robot system. The tendency cell adjusts network weights by the use of information entropy to evaluate the f

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Van Pham, Hai, Farzin Asadi, Nurettin Abut, and Ismet Kandilli. "Hybrid Spiral STC-Hedge Algebras Model in Knowledge Reasonings for Robot Coverage Path Planning and Its Applications." Applied Sciences 9, no. 9 (2019): 1909. http://dx.doi.org/10.3390/app9091909.

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Robotics is a highly developed field in industry, and there is a large research effort in terms of humanoid robotics, including the development of multi-functional empathetic robots as human companions. An important function of a robot is to find an optimal coverage path planning, with obstacle avoidance in dynamic environments for cleaning and monitoring robotics. This paper proposes a novel approach to enable robotic path planning. The proposed approach combines robot reasoning with knowledge reasoning techniques, hedge algebra, and the Spiral Spanning Tree Coverage (STC) algorithm, for a cl

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Lisowski, Józef. "Synthesis of a Path-Planning Algorithm for Autonomous Robots Moving in a Game Environment during Collision Avoidance." Electronics 10, no. 6 (2021): 675. http://dx.doi.org/10.3390/electronics10060675.

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This paper describes and illustrates the optimization of a safe mobile robot control process in collision situations using the model of a multistep matrix game of many participants in the form of a dual linear programming problem. The synthesis of non-cooperative and cooperative game control software was performed in Matlab/Simulink software to determine the safe path of the robot when passing a greater number of other robots and obstacles. The operation of the game motion control algorithm of a mobile robot is illustrated by computer simulations made in the Matlab/Simulink program of two real

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Le, Anh Vu, Nguyen Huu Khanh Nhan, and Rajesh Elara Mohan. "Evolutionary Algorithm-Based Complete Coverage Path Planning for Tetriamond Tiling Robots." Sensors 20, no. 2 (2020): 445. http://dx.doi.org/10.3390/s20020445.

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Tiling robots with fixed morphology face major challenges in terms of covering the cleaning area and generating the optimal trajectory during navigation. Developing a self-reconfigurable autonomous robot is a probable solution to these issues, as it adapts various forms and accesses narrow spaces during navigation. The total navigation energy includes the energy expenditure during locomotion and the shape-shifting of the platform. Thus, during motion planning, the optimal navigation sequence of a self-reconfigurable robot must include the components of the navigation energy and the area covera

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teja, T. Ravi. "Autonomous robot motion path planning using shortest path planning algorithms." IOSR Journal of Engineering 3, no. 01 (2013): 65–69. http://dx.doi.org/10.9790/3021-03116569.

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Karur, Karthik, Nitin Sharma, Chinmay Dharmatti, and Joshua E. Siegel. "A Survey of Path Planning Algorithms for Mobile Robots." Vehicles 3, no. 3 (2021): 448–68. http://dx.doi.org/10.3390/vehicles3030027.

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Path planning algorithms are used by mobile robots, unmanned aerial vehicles, and autonomous cars in order to identify safe, efficient, collision-free, and least-cost travel paths from an origin to a destination. Choosing an appropriate path planning algorithm helps to ensure safe and effective point-to-point navigation, and the optimal algorithm depends on the robot geometry as well as the computing constraints, including static/holonomic and dynamic/non-holonomically-constrained systems, and requires a comprehensive understanding of contemporary solutions. The goal of this paper is to help n

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DAS, SUBIR KUMAR. "Local Path Planning of Mobile Robot Using Critical-PointBug Algorithm Avoiding Static Obstacles." IAES International Journal of Robotics and Automation (IJRA) 5, no. 3 (2016): 182. http://dx.doi.org/10.11591/ijra.v5i3.pp182-189.

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<p align="left">Path planning is an essential task for the navigation of Autonomous Mobile Robot. This is one of the basic problems in robotics. Path planning algorithms are classified as global or local, depending on the knowledge of surrounding environment. In local path planning, the environment is unknown to the robot, and sensors are used to detect the obstacles and to avoid collision. Bug algorithms are one of the frequently used path planning algorithms where a mobile robot moves to the target by detecting the nearest obstacle and avoiding it with limited information about the env

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Lee, Sooyong, and Jae-Bok Song. "Generalized Voronoi Diagram based Path Planning for a Mobile Robot in Dynamic Environment(Autonomous Path Planning,Session: MP1-A)." Abstracts of the international conference on advanced mechatronics : toward evolutionary fusion of IT and mechatronics : ICAM 2004.4 (2004): 25. http://dx.doi.org/10.1299/jsmeicam.2004.4.25_2.

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Le, Anh, Ping-Cheng Ku, Thein Than Tun, Nguyen Huu Khanh Nhan, Yuyao Shi, and Rajesh Mohan. "Realization Energy Optimization of Complete Path Planning in Differential Drive Based Self-Reconfigurable Floor Cleaning Robot." Energies 12, no. 6 (2019): 1136. http://dx.doi.org/10.3390/en12061136.

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The efficiency of energy usage applied to robots that implement autonomous duties such as floor cleaning depends crucially on the adopted path planning strategies. Energy-aware for complete coverage path planning (CCPP) in the reconfigurable robots raises interesting research, since the ability to change the robot’s shape needs the dynamic estimate energy model. In this paper, a CCPP for a predefined workspace by a new floor cleaning platform (hTetro) which can self-reconfigure among seven tetromino shape by the cooperation of hinge-based four blocks with independent differential drive modules

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Xie, Li, Christian Henkel, Karl Stol, and Weiliang Xu. "Power-minimization and energy-reduction autonomous navigation of an omnidirectional Mecanum robot via the dynamic window approach local trajectory planning." International Journal of Advanced Robotic Systems 15, no. 1 (2018): 172988141875456. http://dx.doi.org/10.1177/1729881418754563.

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To improve the energy efficiency of the Mecanum wheel, this article extends the dynamic window approach by adding a new energy-related criterion for minimizing the power consumption of autonomous mobile robots. The energy consumption of the Mecanum robot is first modeled by considering major factors. Then, the model is utilized in the extended dynamic window approach–based local trajectory planner to additionally evaluate the omnidirectional velocities of the robot. Based on the new trajectory planning objective that minimizes power consumption, energy-reduction autonomous navigation is propos

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Lewis, Michael, Huadong Wang, Shih Yi Chien, Prasanna Velagapudi, Paul Scerri, and Katia Sycara. "Process and Performance in Human-Robot Teams." Journal of Cognitive Engineering and Decision Making 5, no. 2 (2011): 186–208. http://dx.doi.org/10.1177/1555343411409323.

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The authors are developing a theory for human control of robot teams based on considering how control difficulty grows with team size. Current work focuses on domains, such as foraging, in which robots perform largely independent tasks. Such tasks are particularly amenable to analysis because effects on performance and cognitive resources are predicted to be additive, and tasks can safely be allocated across operators because of their independence. The present study addresses the interaction between automation and organization of human teams in controlling large robot teams performing an urban

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Ayawli, Ben Beklisi Kwame, Xue Mei, Moquan Shen, Albert Yaw Appiah, and Frimpong Kyeremeh. "Optimized RRT-A* Path Planning Method for Mobile Robots in Partially Known Environment." Information Technology And Control 48, no. 2 (2019): 179–94. http://dx.doi.org/10.5755/j01.itc.48.2.21390.

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This paper presents optimized rapidly exploring random trees A* (ORRT-A*) method to improve the performance of RRT-A* method to compute safe and optimal path with low time complexity for autonomous mobile robots in partially known complex environments. ORRT-A* method combines morphological dilation, goal-biased RRT, A* and cubic spline algorithms. Goal-biased RRT is modified by introducing additional step-size to speed up the generation of the tree towards the goal after which A* is applied to obtain the shortest path. Morphological dilation technique is used to provide safety for the robots w

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