On-line Motion Planning of an Autonomous Mobile Robot to Avoid Multiple Moving Obstacles Based on the Prediction of Their Future Trajectories

goal while avoiding multiple moving obstacles such as people and other mobile robots. The future trajectories of the obstacles depend on the future motion of the robot, since each obstacle also avoids other obstacles, including the robot. In other words, each obstacle has its own•emotion principle•fwhich determines its motion from the location of its goal and the motion of other obstacles. In this study, the robot infers the principles of all obstacles in its sensing area from their trajectories observed in real time. This means it can predict their future trajectories, which are influenced

[1]  Oussama Khatib,et al.  Real-Time Obstacle Avoidance for Manipulators and Mobile Robots , 1986 .

[2]  Rodney A. Brooks,et al.  A Robust Layered Control Syste For A Mobile Robot , 2022 .

[3]  Bruce H. Krogh,et al.  Integrated path planning and dynamic steering control for autonomous vehicles , 1986, Proceedings. 1986 IEEE International Conference on Robotics and Automation.

[4]  S. Zucker,et al.  Toward Efficient Trajectory Planning: The Path-Velocity Decomposition , 1986 .

[5]  Steven W. Zucker,et al.  Planning collision-free trajectories in time-varying environments: a two-level hierarchy , 1988, Proceedings. 1988 IEEE International Conference on Robotics and Automation.

[6]  Hiroshi Noborio,et al.  A fast path-planning algorithm by synchronizing modification and search of its path graph (mobile robots) , 1988, Proceedings of the International Workshop on Artificial Intelligence for Industrial Applications.

[7]  Bruce H. Krogh,et al.  Dynamic generation of subgoals for autonomous mobile robots using local feedback information , 1989 .

[8]  P. K. C. Wang Interaction dynamics of multiple mobile robots with simple navigation strategies , 1989, J. Field Robotics.

[9]  John F. Canny,et al.  A motion planner for multiple mobile robots , 1990, Proceedings., IEEE International Conference on Robotics and Automation.

[10]  Yun-Hui Liu,et al.  A flexible algorithm for planning local shortest path of mobile robots based on reachability graph , 1990, EEE International Workshop on Intelligent Robots and Systems, Towards a New Frontier of Applications.

[11]  Fabrice R. Noreils Coordinated execution of trajectories by multiple mobile robots , 1991, Proceedings IROS '91:IEEE/RSJ International Workshop on Intelligent Robots and Systems '91.

[12]  Paul Keng-Chieh Wang Navigation strategies for multiple autonomous mobile robots moving in formation , 1991, J. Field Robotics.

[13]  Ronald C. Arkin,et al.  Behavior-Based Robot Navigation for Extended Domains , 1992, Adapt. Behav..

[14]  Russell J. Clark,et al.  Learning momentum: online performance enhancement for reactive systems , 1992, Proceedings 1992 IEEE International Conference on Robotics and Automation.