避障
数学优化
运动规划
计算机科学
障碍物
轨迹优化
占用网格映射
机器人
弹道
同伦
控制理论(社会学)
网格
转弯半径
移动机器人
数学
人工智能
工程类
最优控制
航空航天工程
控制(管理)
物理
天文
法学
纯数学
政治学
几何学
作者
Jinyu Fu,Guanghui Sun,Weiran Yao,Ligang Wu
标识
DOI:10.1109/tits.2022.3195521
摘要
This paper examines a trajectory homotopy optimization framework for multiple unmanned aerial vehicles (multi-UAV) to solve the problem of dynamic penetration mission planning (PMP) with hostile obstacles and perception constraints. Constrained problems are usually more challenging and difficult to solve with some practical constraints and requirements. To improve the efficiency of the solution for the penetration path, a novel variable-time mechanism has been constructed to adapt to the updated delay time of unknown target search (UTS) and dynamic trajectory planning (DTP) two stages. The occupancy grid maps are established by a Gaussian probability field (GPF) for predicting the positions of enemy UAVs. To fully consider the hostile obstacle constraint, a hybrid adaptive obstacle avoidance approach dynamic window PRM (DW-PRM) is designed to shorten the planned path. The penetration strategy algorithm (SG) is developed based on the proposed strategy set and decision tree. To improve the ability of dynamic obstacle avoidance, the multiple coupled penetration homotopy trajectory is addressed with a turning radius constraint. The simulation results indicated that the penetration homotopy framework for multi-constraints can solve the multi-UAV PMP problem.
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