In this paper, an efficient and probabilistic complete planning algorithm called Composite-space RRT is presented to address motion planning with soft constraints for spherical wrist manipulators. Firstly, we propose a novel configuration space termed Composite Configuration Space (“Composite Space” for short), which is composed of the joint space and the task space. Then, collision-free paths are generated in the composite space by the Rapidly-exploring Random Trees (RRT) algorithm. Finally, the planned paths in the composite space are mapped into the corresponding joint-space paths by a local planner. As the analytical inverse kinematics (IK) of the spherical wrist is used in the local planner, the proposed Composite-space RRT algorithm is characterized by high efficiency and no numerical iteration. Moreover, this approach can effectively improve the smoothness of the end-effector orientation path. The effectiveness of the proposed algorithm is demonstrated on the Willow Garage’s PR2 simulation platform with two typical orientation-constrained cases.

中文翻译：

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通过复合配置空间的随机探索进行软约束的操作规划

在本文中，提出了一种称为复合空间 RRT 的有效且概率性的完整规划算法，以解决球形手腕机械手的具有软约束的运动规划问题。首先，我们提出了一种新的配置空间，称为复合配置空间（简称“复合空间”），它由关节空间和任务空间组成。然后，通过快速探索随机树 (RRT) 算法在复合空间中生成无碰撞路径。最后，复合空间中的规划路径被局部规划器映射到相应的关节空间路径。由于局部规划器中使用了球形手腕的解析逆运动学（IK），因此所提出的复合空间RRT算法具有高效且无需数值迭代的特点。而且，这种方法可以有效提高末端执行器定向路径的平滑度。在 Willow Garage 的 PR2 仿真平台上，通过两个典型的方向约束情况证明了所提出算法的有效性。