Abstract
In an autonomous multi-mobile robot environment, path planning and collision avoidance are important functions used to perform a given task collaboratively and cooperatively. This study considers these important and challenging problems. The proposed approach is based on a potential field method and fuzzy logic system. First, a global path planner selects the paths of the robots that minimize the potential value from each robot to its own target using a potential field. Then, a local path planner modifies the path and orientation from the global planner to avoid collisions with static and dynamic obstacles using a fuzzy logic system. In this paper, each robot independently selects its destination and considers other robots as dynamic obstacles, and there is no need to predict the motion of obstacles. This process continues until the corresponding target of each robot is found. To test this method, an autonomous multi-mobile robot simulator (AMMRS) is developed, and both simulation-based and experimental results are given. The results show that the path planning and collision avoidance strategies are effective and useful for multi-mobile robot systems.
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Recommended by Editorial Board member Fuchun Sun under the direction of Editor Myotaeg Lim.
The authors would like to thank the support of the AHMCT in UC-Davis and also very grateful to the anonymous reviewers for their valuable comments. This research was supported by Basic Science Research Program through the National Research Foundation of Korea (NRF) funded by the Ministry of Education, Science and Technology (Grant No. 2011-0010579).
Dong W. Kim received his Ph.D. degree in Electrical Engineering from Korea University in 2007. He is an assistant professor of Inha Technical College. His research interests include robotics, advanced robot design, evolutionary multimobile robot system, humanoid robot, soft computing and their application to control.
Ty A. Lasky received his Ph.D. degree in Electrical Engineering from University of California, Davis in 1995. He is a researcher in Mechanical and Aerospace Engineering and Associate Director of Advanced Highway Maintenance and Construction Technology Research Center (AHMCT) of the University of California, Davis. His research interests include mechatronics, robotics and automation, real-time sensing and control, and GPS/GIS.
Steven A. Velinsky received his Ph.D. degree in Theoretical and Applied Mechanics from University of Illinois at Urbana-Champaign in 1981. He is a professor of Mechanical and Aerospace Engineering and Director of Advanced Highway Maintenance and Construction Technology Research Center (AHMCT) of the University of California, Davis. His research interests include mechanical systems analysis and design, vehicle design and dynamics, robotics and automation, machinery for highway maintenance and construction.
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Kim, D.W., Lasky, T.A. & Velinsky, S.A. Autonomous multi-mobile robot system: simulation and implementation using fuzzy logic. Int. J. Control Autom. Syst. 11, 545–554 (2013). https://doi.org/10.1007/s12555-012-0096-z
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DOI: https://doi.org/10.1007/s12555-012-0096-z