基于综合改进RRT算法的无人机三维航路规划

Three-Dimensional Path Planning for UAV Based on Comprehensive Improved RRT Algorithm

针对复杂飞行环境下的无人机三维航路规划问题,提出了一种基于快速扩展随机树(RRT)的综合改进航路规划算法。根据实际复杂任务环境,建立三维任务空间模型,并考虑无人机性能约束;通过引入基于概率的启发式策略引导节点扩展方向,加入贪婪策略提高终点扩展方向节点生长速度;提出动态引力步长策略在保证节点搜索概率完备性的同时,降低节点扩展方向的随机性;设计平滑度优化方法改善规划航路曲折问题。仿真结果表明,综合改进RRT算法整体性能较好,具有良好的避障特性。

Aiming at the problem of three-dimensional path planning for UAVs in complex flight environments,a comprehensive improved path planning algorithm based on a rapidly-exploring random tree(RRT)is proposed.Based on the actual complex task environment,we established a three-dimensional task space model and consider the UAV performance constraints.The probability-based heuristic strategy was introduced to guide the node expansion direction and adding a greedy strategy to increase the node growth speed in the goal expansion direction.A dynamic gravity step strategy was proposed to reduce the randomness of the node expansion direction while ensuring the completeness of the node search probability.The smoothness optimization method was used to improve the tortuous trajectory problem.The simulation results show that the comprehensive improved RRT algorithm has better overall performance and good obstacle avoidance characteristics.