应急场景通信机器人布放路径规划

Layout path planning for emergency disaster-stricken communication robot base station

针对应急场景通信基站站点布放的路径规划问题,提出了一种改进RRT的基站通信机器人布放路径规划算法。采用目标偏置采样结合剪枝采样的新采样方法,以一定概率将目标点作为采样点进行随机采样,并结合新节点位置约束采样范围。在此基础上引入随机点引力和目标点引力思想来改变局部节点扩展方向,利用权重距离系数实时调整扩展步长。对生成路径进行3次B样条拟合。驱使基站通信机器人安全、高效、稳定地抵达预先规划好的基站位置。与其他几种算法的Matlab仿真对比结果表明:所提方法具有可行性,且改进后的RRT算法在进行基站布放时内存占用率更低,能耗更少,寻路代价更短。

Aiming at the path planning problem of emergency disaster-stricken communication base station site deployment, a path planning algorithm for base station communication robot deployment based on improved RRT is proposed. The algorithm proposes a new sampling method of target bias sampling combined with pruning sampling. The target point is used as a sampling point for random sampling with a certain probability, and the sampling range is constrained by the position of the new node. On this basis, the idea of random point gravity and target point gravity is introduced to change the expansion direction of local nodes, and the expansion step size is adjusted inreal-time by using the weight distance coefficient. The generated path is fitted by a cubic B-spline curve. Drive the base station communication robot to arrive safely, efficiently, and stably at the pre-planned base station location. Finally, the algorithm is verified based on the Matlab platform, which is compared with the traditional RRT algorithm and an existing improved algorithm, and the results show that the proposed method is feasible, and the improved RRT algorithm has lower memory occupation, less energy consumption, and shorter pathfinding cost when the base station is deployed.