一种地空协同巡检的分层最优路径规划算法

Yuanguang Zhang, Yuhong Zhao, Ziqi Zhao, Weiqi Tang
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摘要

由无人机/地面车辆(UAV/UGV)组成的异构协同系统在许多领域具有巨大的应用潜力。除此之外,无人机可以提供广阔的视野和摄影,而UGV可以提供足够的负载能力并充当中继站。基于实际任务合理规划无人机/UGV路径是需要解决的重要问题。本文提出了一种基于UAV /UGV协调协作的混合无人系统。在该系统中,利用UGV作为移动充电站来解决无人机的能量约束问题。UAV作为一个机器人系统,负责到达目标点和解决UGV的功能约束问题。提出了一种研究两个机器人协同工作的路径规划方法。一种结合经典与现代进化方法的分层路径优化策略。该方法充分利用了各个方法和算法在路径选择和规划方面的优势。仿真结果表明,无人机与UGV协同系统可以提高任务执行效率,分层优化策略可以提高路径规划解的质量和稳定性。
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A hierarchical optimal path planning algorithm for collaborative air-ground inspection
Heterogeneous collaborative systems consisting of unmanned aerial vehicles/ground vehicles (UAV/UGV) have great potential for application in many fields. Among other things, UAV can provide a wide field of view and photography, while UGV can provide sufficient load capacity and act as relay stations. Rational planning of UAV/UGV paths based on actual tasks is an important issue to be addressed. This study proposes a hybrid unmanned system based on coordinated cooperation between UAV /UGV. In this system, the UGV is used as a mobile charging station to solve the UAV energy constraint problem. The UAV is used as a robotic system responsible for reaching the target point and solving the UGV functional constraint problem. We propose a path planning method for the study of two robots working together. A hierarchical path optimization strategy that combines classical and modern evolutionary methods. The method takes full advantage of the strengths of individual methods and algorithms in path selection and planning. Simulation results show that the collaborative UAV and UGV systems can improve the efficiency of performing tasks and that the hierarchical optimization strategy can improve the solution quality and stability of path planning.
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