基于变步长稀疏A*搜索和MPC的多无人机层次化协同航迹规划

摘要

A hierarchical optimization strategy based on path planning and trajectory planning process is presented in this paper to solve the trajectory planning problem of multiple unmanned aerial vehicles(UAV).Firstly,a model of path planning considering obstacle constrains is established,and a modified Sparse A ? Algorithm(SAS)is proposed to shortcomings of fixed step adaptability to environmental changes. Secondly, The trajectory planning strategy is established based on Decen-tralized Model Predictive Control(DMPC). Lastly, the hierarchic optimization strategy is simulated with MATLAB. Compared with the traditional trajectory optimization methods,the strategy achieves a balance between better solution and re-al-time performance with stronger adaptability.%提出一种路径规划与轨迹规划相结合的多无人机实时航迹规划层次结构.首先,建立了路径规划问题模型,提出了一种连续可变步长稀疏A?算法(Sparse A? Search,SAS)进行求解,克服了固定步长对于环境变化适应性较差的不足;其次,对于任一中间航路段,设计了基于模型预测控制((Decentralized Model Predictive Control, DMPC)思想的轨迹规划问题求解框架,综合考虑UAV飞行运动学约束、避碰约束,建立DMPC单步非线性规划问题模型;最后,对提出的层次化航迹规划方法进行了仿真验证.与传统的航迹规划方法相比,该方案均衡了解质量与实时性要求,并具有更好的适应性.