Path Planning for Multiple UAVs Based on Hybrid Particle Swarm Optimization with Differential Evolution

YU Hongda; WANG Congqing; JIA Feng; LIU Yang

doi:10. 3969/j. issn. 1671-637x. 2018. 05. 005

[3] PEHLIVANOGLU Y V. A new vibrational genetic algorithm enhanced with a Voronoi diagram for path planning of auto-nomous UAV［J］. Aerospace Science and Technology, 2012, 16(1):47-55.

[4] MARTINEZ-ZERON E, ACEVES-FERNANDEZ M A, GORROSTIETA-HURTADO E, et al. Method to improve airborne pollution forecasting by using ant colony optimization and neuro-fuzzy algorithms［J］. International Journal of Intelligence Science, 2014(4)：81-90．

[6] LIN L, GOODRICH M A. Hierarchical heuristic search using a Gaussian mixture model for UAV coverage planning［J］. IEEE Transactions on Cybernetics, 2017, 44(12):2532-2544.

[7] MA P B, FAN Z E, JI J. Cooperative control of multi-UAV with time constraint in the threat environment［C］//The IEEE Chinese Guidance, Navigation and Control Confe-rence, 2014:2424-2428.

[8] AHMED F, DEB K. Multi-objective optimal path planning using elitist non-dominated sorting genetic algorithms［J］. Soft Computing, 2013, 17(7):1283-1299.

[10] LEE D S, PERIAUX J, GONZALEZ L F. UAS Mission Path Planning System (MPPS) using hybrid-game coupled to multi-objective optimizer［J］. Journal of Dynamic Systems, Measurement and Control, 2010, 132(4):1-11.

[11] SAHINGOZ O K. Flyable path planning for a multi-UAV system with genetic algorithms and Bezier curves［C］//International Conference on Unmanned Aircraft Systems, IEEE, 2013:41-48.