基于分层2.5D地图的无人履带车辆路径规划

Path Planning Algorithm Based on Layered 2.5D Map for Unmanned Tracked Vehicle

  • 摘要: 针对越野环境地形下无人履带车辆难以安全、高效规划出一条可通行路径的问题,提出一种考虑地形特征、障碍物以及车辆运动特性的分层式路径规划算法. 算法先通过三维参考路径规划模块改进A*算法节点扩展方式,使用无梯度迭代平滑算法、B样条曲线拟合得到平滑参考路径;然后在多阶段状态空间采样模块中采用自适应采样策略生成候选路径集,采用贪婪策略选出最优路径. 试验结果表明,所提方法在越野环境中的规划结果既保证了可行性、稳定性、实时性,又在稳定车辆姿态上具有优势.

     

    Abstract: A hierarchical path planning algorithm was proposed, considering the factors of terrain features, obstacles and vehicle motion characteristics, to address the problem of finding a safe, efficient and right of way for unmanned tracked vehicles in off-road terrain. Firstly, improving the node expansion mode of A * algorithm with the 3D reference path planning module, a smooth reference path was obtained based on the gradient free iterative smoothing algorithm and B-spline curve fitting. Then, using the adaptive sampling strategy, a candidate path set was generated in the multi-stage state space sampling module, and a greedy strategy was used to select the optimal path. The experimental results show that the proposed method can not only ensure feasibility, stability, and real-time performance in off-road environments, but also have advantages in stabilizing vehicle posture.

     

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