基于改进RRT-Connect算法的机械臂路径规划研究

Research on path planning of robotic arm based on improved RRT-Connect algorithm

  • 摘要: 为解决快速遍历随机树算法(rapidly-exploring random tree,RRT-Connect)在复杂凹区域特定场景下收敛速度慢、路径质量差的问题,提出了一种改进的路径规划算法。该算法通过引入优化的搜索范围、自适应步长和路径修剪策略,提高了路径生成的成功率,缩短了路径搜索时间,并缩短了路径的总距离。实验结果表明,改进后的算法在路径生成效率和质量上具有显著优势,平均路径规划时间缩短 11%,平均路径长度缩短 30%。定性和定量结果均验证了该改进算法的有效性和优越性。

     

    Abstract: To address the issues of slow convergence speed and poor path quality of the RRT-Connect algorithm in specific scenarios of complex concave regions, an improved path planning algorithm is proposed. By introducing an optimized search range, adaptive step size, and path pruning strategy, this algorithm increases the success rate of path generation, shortens the path search time, and reduces the total path distance. Experimental results show that the improved algorithm has significant advantages in path generation efficiency and quality, with the average path planning time reduced by 11% and the average path length shortened by 30%. Both qualitative and quantitative results verify the effectiveness and superiority of the improved algorithm.

     

/

返回文章
返回