标题： 一种用于具有狭窄通道的构形空间路径规划的改进快速探索随机树算法 显示英文标题

标题： An Improved Rapidly Exploring Random Tree Algorithm for Path Planning in Configuration Spaces with Narrow Channels

摘要： 快速探索随机树（RRT）算法已成功应用于具有挑战性的机器人运动规划和欠驱动非线性控制问题。然而，RRT 方法的一个基本局限性是在配置空间中存在狭窄通道时收敛速度较慢，这是因为在狭窄通道内生成测试点的概率较小。本文提出了一种改进的 RRT 算法，该算法利用初始状态与目标状态之间的狭窄通道，通过改进配置空间中狭窄区域的探索来找到更短的路径。所提出的算法通过检查邻域点是否与不可行集发生碰撞来检测狭窄通道的存在，并尝试以预定的偏向性向狭窄通道内添加点。该方法在多种基准规划问题上与经典的 RRT 及其变体进行了比较。仿真结果表明，本文提出的算法在含有狭窄通道的空间中计算出显著更短的路径。 显示英文摘要

摘要： Rapidly-exploring Random Tree (RRT) algorithms have been applied successfully to challenging robot motion planning and under-actuated nonlinear control problems. However a fundamental limitation of the RRT approach is the slow convergence in configuration spaces with narrow channels because of the small probability of generating test points inside narrow channels. This paper presents an improved RRT algorithm that takes advantage of narrow channels between the initial and goal states to find shorter paths by improving the exploration of narrow regions in the configuration space. The proposed algorithm detects the presence of narrow channel by checking for collision of neighborhood points with the infeasible set and attempts to add points within narrow channels with a predetermined bias. This approach is compared with the classical RRT and its variants on a variety of benchmark planning problems. Simulation results indicate that the algorithm presented in this paper computes a significantly shorter path in spaces with narrow channels.