Abstract: A target area guided RRT* robotic arm path planning algorithm (TA-RRT*) is proposed to address the issues of low planning efficiency, poor path quality, and improper robotic arm pose in the traditional RRT* algorithm for robotic arm path planning. Firstly, with the traditional RRT* algorithm as the foundation, a target bias strategy is introduced and a spherical subset constraint sampling is utilized to narrow the sampling range and guide the expansion of the new node towards the target point, enhancing target orientation. By employing a direct connection strategy for new nodes, the algorithm is enabled to converge faster and the speed of path generation is improved. Secondly, by removing redundant points from the initial planning path and transforming it into a smooth path using a cubic B-spline curve, the quality of the path is improved. Finally, the position of the robotic arm is constrained. The reachability of the robotic arm linkage pose is ultimately determined through the inverse kinematics of the robotic arm, and the envelope box model is used to determine whether the robotic arm is collided with obstacles. Experimental results show that the TA-RRT* algorithm outperforms the RRT* algorithm in terms of sampling frequency, planning time, path length, and smoothness in 2D and 3D scenes, verifying the correctness and feasibility of this method. Both the robotic arm simulation experiments and the test results in real environment demonstrate that when adding pose constraints to the planned trajectory of the robotic arm during operation, the joints of the robotic arm do not collide with obstacles during the execution of the planned paths and exhibit good stability.

Key words: RRT* algorithm, manipulator path planning, target area guide, cubic B-spline curve

摘要： 针对传统RRT*算法在机械臂路径规划的过程中存在规划效率低、路径质量不佳、机械臂位姿不当等问题，提出一种目标区域引导的RRT*机械臂路径规划算法（TA-RRT*）。在传统RRT*算法基础上，引入目标偏向策略并使用球形子集约束采样，缩小采样范围并使新节点朝向目标点扩展，增强目标导向性；对新节点采用直连策略，让算法可以更快地收敛从而提升路径生成速度。对初始规划路径去除冗余点并使用三次B样条曲线转换成平滑路径，优化了路径质量。对机械臂进行位姿约束，通过机械臂逆运动学判断机械臂连杆位姿可达性，并利用包络盒模型判断机械臂是否与障碍物碰撞。实验结果表明，在二维以及三维场景下，TA-RRT*算法在采样次数、规划时间、路径长度以及平滑度等方面的性能均优于RRT*算法，验证了该方法的正确性及可行性。机械臂仿真实验以及在真实环境下的测试结果显示，加入位姿约束后机械臂运行规划好的轨迹时，机械臂各个关节在运行规划路径的过程中并未与障碍物发生碰撞且具有良好的稳定性。

关键词: RRT*算法, 机械臂路径规划, 目标区域引导, 三次B样条曲线