基于优化A*和MPC融合算法的三维无人机航迹规划

3D UAV trajectory planning based on optimized A*and MPC fusion algorithm

针对传统A*算法在二维无人机(unmanned aerial vehicle,UAV)航迹规划中存在的不足,提出了一种优化A*算法与模型预测控制融合的三维UAV航迹规划方法。通过压缩搜索空间和平滑处理,提出了一种基于三维空间的优化A*算法,综合考虑全局规划与实时避障需求,构建了优化A*算法与模型预测控制的融合算法。仿真验证表明,融合算法能够实现三维复杂环境下UAV实时避障航迹规划,搜索节点少,路径长度短且更加平滑,具有很好的环境适应性。

In view of the shortcomings of the traditional A*algorithm in 2D unmanned aerial vehicle(UAV)trajectory planning,a 3D UAV trajectory planning method that fuses the optimized A*algorithm with model predictive control is proposed.An optimized A*algorithm based on 3D space is proposed by compressing the search space and smoothing operation,and a fusion algorithm of optimised A*algorithm and model predictive control is constructed by considering the global planning and real-time obstacle avoidance requirements.Simulation verification shows that the proposed fusion algorithm can achieve real-time UAV obstacle avoidance trajectory planning in 3D complex environment,with fewer search nodes,shorter and smoother path lengths,and has good environmental adaptability.