LAUSR

In large-scale natural disasters and military supplies, multiple parafoils are more capable of performing actual tasks. The cooperative paths planning for multiple parafoils with different initial positions and headings is an important step in multiple parafoils airdrop, which has to satisfy multiple objectives, namely, parafoils can’t collide with each other, parafoils should rendezvous at same target area, most of parafoils need to keep alignment against wind, and planned paths should be in the range of maneuver performance constraints to ensure that every parafoil’s path is fl yable. Due to more factors need to be considered, it is more diffi cult to plan paths for multiple parafoils than single parafoil. In this paper an improved genetic algorithm is used to solve the multi-objective cooperative paths planning problem of multiple parafoils system. Parafoils’paths are encoded by real matrix, and the cooperative relationship between parafoils is realized by paths fi tness function. The random single point crossover and Gaussian mutation are introduced to accelerate algorithm convergence rate. Finally, a simulation example is given, simulation results show that proposed method can plan feasible paths for all parafoils, meanwhile, it satisfies the requirements of anti-collision, rendezvous to target point, and keep alignment against the wind.