Coevolving and cooperating path planner for multiple unmanned air vehicles

Authors:
Changwen Zheng;Mingyue Ding;Chengping Zhou;Lei Li
Affiliations:
Laboratory of General Software, Institute of Software, Chinese Academy of Sciences, Beijing 100080, PR China;Institute of Pattern Recognition and Artificial Intelligence, Huazhong University of Science and Technology, Wuhan 430074, PR China;Institute of Pattern Recognition and Artificial Intelligence, Huazhong University of Science and Technology, Wuhan 430074, PR China;Laboratory of General Software, Institute of Software, Chinese Academy of Sciences, Beijing 100080, PR China
Venue:
Engineering Applications of Artificial Intelligence
Year:
2004

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Abstract

In this paper, the coordinated path planning problem for multiple unmanned air vehicles is studied with the proposal of a novel coevolving and cooperating path planner. In the new planner, potential paths of each vehicle form their own sub-population, and evolve only in their own sub-population, while the interaction among all sub-problems is reflected by the definition of fitness function. Meanwhile, the individual candidates are evaluated with respect to the workspace so that the computation of the configuration space is avoided. By using a problem-specific representation of candidate solutions and genetic operators, our algorithm can take into account different kinds of mission constraints and generate solutions in real time.