Real-time Path Planning Strategy for UAV Based on Improved Particle Swarm Optimization

Unmanned Aerial Vehicle (UAV) path planning is divided into off-line static path planning and real-time dynamic path planning. The former one is applied to the ideal situation that the terrain has been clear, and there is no unexpected situation in flight. Actually, however, the flight situation is very complex, we have to adopt real-time path planning based on off-line static path planning. To meet the demand of real-time dynamic path planning, this paper proposes a dynamic path planning strategy of adaptive chaotic particle swarm optimization (PSO) algorithm, which owns both good global and local search ability. The simulation shows that the path planning strategy this paper proposes, basically, meets the needs of real-time path planning. Moreover, it has better performance than other algorithm.

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