NDLI: Path planning of multiple UAVs low-altitude penetration based on improved Multi-agent Coevolutionary Algorithm

Content Provider	IEEE Xplore Digital Library
Author	Peng Zhi-Hong Sun Lin Chen Jie Wu Jin-Ping
Copyright Year	2011
Description	Author affiliation: School of Automation, Beijing Institute of Technology, 100081, China (Peng Zhi-Hong; Sun Lin; Chen Jie; Wu Jin-Ping)
Abstract	In order to solve the multi-UAV cooperative path planning problem of low-altitude penetration, the paper proposes an improved Multi-agent Coevolutionary Algorithm (IMACEA), which introduces co-evolution mechanism based on Multi-agent Genetic Algorithm(MAGA) to find the optimal solution of multi-objective optimization problem by combing the agents' perception and response capabilities of environment, information sharing capacity among multi-agent systems and heuristic search ability of heuristic search. At the same time, we use absolute Cartesian coordinates and relative polar coordinates coding method to reduce the search space and speed up the convergence rate. To adapt to multi-path planning problems of UAVs, new multi-agent co-evolution operators are designed. Finally, the proposed algorithm is used for multiple UAVs offline and online route planning, simulation results show the effectiveness of the algorithm.
Starting Page	4056
Ending Page	4061
File Size	625118
Page Count	6
File Format	PDF
ISBN	9781457706776
ISSN	21612927
e-ISBN	9789881725592
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2011-07-22
Publisher Place	China
Access Restriction	Subscribed
Rights Holder	Chinese Assoc of Automati
Subject Keyword	Algorithm design and analysis Multiagent systems Low-Altitude Penetration Improved Multi-Agent Coevolutionary Algorithm Offline / Online Path Planning Path planning Encoding Nickel Genetic algorithms Manganese Multiple UAVs
Content Type	Text
Resource Type	Article

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