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基于采样点优化RRT算法的机械臂路径规划

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针对基于随机采样的RRT机械臂路径规划算法在全局工作空间下采样效率低、随机性强等问题,提出一种基于采样点优化RRT算法的机械臂路径规划算法.相对于全局工作空间采样,优化算法首先基于非障碍物空间生成随机采样点,以降低算法碰撞检测概率与冗余节点的生成,再结合一定概率的人工势场法产生启发式采样点,使得机械臂臂体于路径规划采样过程中既能保证随机采样的概率完备,又能使采样点更具目标导向性.其次,为使得路径更加简洁平滑,使用冗余节点删除策略剔除路径中的冗余节点来优化最终路径.最后在二维、三维的仿真环境中对优化算法进行对比实验分析,以验证算法在随机采样路径规划算法中的良好性能,并在IRB 1200-7/0.7机械臂上进行避障规划算法实验.仿真和实验结果都表明,所提出的算法在机械臂路径规划中可以获得更高的规划效率和更优的路径.
Robotic arm path planning based on sampling point optimization RRT algorithm
In order to address the problems of low efficiency and high randomness of the RRT-based arm path planning algorithm based on random sampling in the global workspace,a mechanical arm path planning algorithm based on sample point optimization RRT algorithm is proposed.Compared to global workspace sampling,the optimization algorithm first generates random sampling points based on non-obstacle space to reduce the probability of algorithm collision detection and redundant node generation,and combines with a certain probability of artificial potential field method to generate heuristic sampling points,which can ensure the completeness of random sampling probability and make the sampling points more target-oriented.Secondly,in order to make the path more concise and smooth,a redundant node deletion strategy is used to remove redundant nodes in the path to optimize the final path.Finally,comparative experiments and analysis of the optimized algorithm are carried out in two-dimensional and three-dimensional simulation environments,confirming the good performance of the algorithm in random sampling path planning algorithm,and conducting obstacle avoidance planning algorithm experiments on the IRB 1200-7/0.7 robot arm.The simulation and experimental results both demonstrate that this algorithm can achieve higher planning efficiency and better path in robot arm path planning.

fast random search treenon-obstruction spatial samplingartificial potential field methodheuristic samplingsample point optimizationrobotic arm motion planning

陈丹、谭钦、徐哲壮

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福州大学电气工程与自动化学院,福州 350108

快速随机搜索树 非障碍物空间采样 人工势场法 启发式采样 采样点优化 机械臂运动规划

国家自然科学基金面上项目福建省自然科学基金面上项目

619730852022J01114

2024

10.13195/j.kzyjc.2023.0330

控制与决策
东北大学

控制与决策

CSTPCD北大核心
影响因子：1.227
ISSN：1001-0920
年,卷(期)：2024.39(8)