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Three-dimensional path planning of manipulator based on improved RRT algorithm

机译:基于改进的RRT算法的机械臂三维路径规划

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This paper provides an improved algorithm which is proposed for the deviating optimal solution, non-target and path non-smooth problem of the original Rapidly-exploring Random Trees (RRT). The improved algorithm is based on the new parent node selection method to ensure that the random tree extends the asymptotic optimality of the new node. On this basis, the heuristic value function is introduced according to the Euclidean shortest distance thought, which improves the planning efficiency of the algorithm. In addition, the method of regression analysis is adopted to improve the search ability of the algorithm and solve the local minimum problem caused by the heuristic value function. The Bézier curve fitting method is then used to generate a smooth path, which further reduces the jitter during the 6-DOF manipulator motion. The simulation experiment of improved RRT algorithm is established in MATLAB platform, and the effectiveness and rationality of the algorithm are verified.
机译:本文针对原始快速探索随机树(RRT)的最优解,非目标和路径非光滑问题提出了一种改进的算法。改进的算法基于新的父节点选择方法,以确保随机树扩展新节点的渐近最优性。在此基础上,根据欧几里德最短距离思想引入了启发式价值函数,提高了算法的规划效率。另外,采用回归分析的方法来提高算法的搜索能力,解决由启发式值函数引起的局部极小问题。然后,使用Bézier曲线拟合方法来生成平滑路径,从而进一步减小6自由度机械手运动期间的抖动。在MATLAB平台上建立了改进的RRT算法的仿真实验,验证了该算法的有效性和合理性。

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