Published in Proceedings of the 2003 IEEE International Conference on Robotics & Automation: Taipei, Taiwan, Volume 3, September 14, 2003, pages 4222-4227.
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NOTE: At the time of publication, the author Christopher Clark was not yet affiliated with Cal Poly.
A new motion planning framework is presented that enables multiple mobile robots with limited ranges of sensing and communication to maneuver and achieve goals safely in dynamic environments. To combine the respective advantages of centralized and de-centralized planning, this framework is based on the concept of centralized planning within dynamic robot networks. As the robots move in their environment, localized robot groups form networks, within which world models and robot goals can be shared. Whenever a network is formed, new information then becomes available to all robots in this network. With this new information, each robot uses a fast, centralized planner to compute new coordinated trajectories on the fly. Planning over several robot networks is decentralized and distributed. Both simulated and real-robot experiments have validated the approach.