TY - GEN
T1 - Path planning of multiple UAVs low-altitude penetration based on improved Multi-agent Coevolutionary Algorithm
AU - Peng, Zhi Hong
AU - Sun, Lin
AU - Chen, Jie
AU - Wu, Jin Ping
PY - 2011
Y1 - 2011
N2 - 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.
AB - 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.
KW - Improved Multi-Agent Coevolutionary Algorithm
KW - Low-Altitude Penetration
KW - Multiple UAVs
KW - Offline / Online Path Planning
UR - http://www.scopus.com/inward/record.url?scp=80053063680&partnerID=8YFLogxK
M3 - Conference contribution
AN - SCOPUS:80053063680
SN - 9789881725592
T3 - Proceedings of the 30th Chinese Control Conference, CCC 2011
SP - 4056
EP - 4061
BT - Proceedings of the 30th Chinese Control Conference, CCC 2011
T2 - 30th Chinese Control Conference, CCC 2011
Y2 - 22 July 2011 through 24 July 2011
ER -