An evolutionary method for active learning of mobile robot path planning

Byoung-Tak Zhang, Sung-Hoon Kim
Proceedings 1997 IEEE International Symposium on Computational Intelligence in Robotics and Automation CIRA'97. 'Towards New Computational Principles for Robotics and Automation'  
Several evolutionary algorithms have been proposed for robot path planning. Most existing methods f o r evolutionary path planning require a number of generations for finding a satisfactory trajectory and thus are not e@cient enough for real-time applications. In this paper we present a new method for evolutionary path planning whach can be used on-line i n real-time. We use an evolutionary algorithm as a means for active learning of a route map for the path planner. Given a source-destination
more » ... air, the path planner searches the map for a best matching route. I f an acceptable match is not found, the planner uses another evolutionary algorithm to generate on-line a path for the sourcedestination pair. The overall system is an incremental learning planner that gradually expands ats own knowledge suitable for path plannzng i n real-time. Simulatzons huve been performed zn the domazn of robotic soccer to demonstrate the effectiveness of the presented method.
doi:10.1109/cira.1997.613874 dblp:conf/cira/ZhangK97 fatcat:vi6pr3k4rbgxbocwkwxf2yn4ai