无人机三维路径规划及避障方法

UAV 3D Path Planning and Obstacle Avoidance Method

  • 摘要: 针对无人机(UAV)在三维环境中如何由起始点到目标点合理地规划路径避开障碍物,提出了一种基于改进粒子群算法与滚动策略相结合的UAV路径规划与避障方法.该方法首先以UAV为中心,通过传感器建立UAV的可视区域模型;其次结合滚动策略滚动探知UAV周围环境信息;最后,利用改进的粒子群算法进行路径搜索,并加入综合转角控制提高路径的平滑性.在传统粒子群算法中加入信息素与启发函数,增强算法的全局搜索能力,并对参数进行特定设计提高算法的收敛速度.仿真结果表明,该方法可以实现实时避障,所规划的路径相对平滑,且改进算法比传统算法具有较高的收敛性.

     

    Abstract: We address the problem of how UAVs in the three-dimensional environment can reasonably plan a path that avoids obstacles from the starting point to a target point. UAV path planning and obstacle avoidance method are proposed, based on the combination of improved particle swarm optimization and rolling strategy methods. First, the proposed method uses the UAV as the center and uses sensors to establish a UAV visual area model.Next, scrolling strategies are combined to obtain information about the environment surrounding the UAV.Lastly, the improved particle swarm algorithm is used to search the path, with the addition of integrated corner control to improve path smoothness. Pheromone and heuristic functions are added to the traditional particle swarm optimization algorithm to enhance the algorithm's global search capability, and the parameters are specifically designed to improve the algorithm's convergence speed. Simulation results show that the proposed method can achieve real-time obstacle avoidance, the planned path is relatively smooth, and the improved algorithm has higher convergence than the traditional algorithm.

     

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