Purpose

This paper aims to present a method of optimal singularity-free motion planning under multiple objectives and multiple constrains for the 6-DOF parallel manipulator, which is used as an execution mechanism for the automated docking of components.

Design/methodology/approach

First, the distribution characteristics of the Jacobian matrix determinant in local workspace are studied based on the kinematics and a sufficient and necessary condition of singularity-free path planning in local workspace is proposed. Then, a singularity-free motion path of the end-effector is generated by a fifth-order B-spline curve and the corresponding trajectories of each actuator are obtained via the inverse kinematics. Finally, several objective functions are defined to evaluate the motion path and an improved multi-objective particle swarm optimization algorithm-based on the Pareto archive evolution is developed to obtain the optimal singularity-free motion trajectories.

Findings

If the initial pose and the target pose of the end-effector are both singularity-free, a singularity-free motion path can be planned in the local workspace as long as all the values of each pose elements in their own directions are monotonous. The improved multi-objective particle swarm optimization (IMPSO) algorithm is effective and efficient in the optimization of multi-objective motion planning model. The optimal singularity-free motion path of the end-effector is verified in the component docking test. The docking result is that the movable component is in alignment with the fixed one, which proves the feasibility and practicability of the proposed motion path method to some extent.

Originality/value

The proposed method has a certain novelty value in kinematic multi-objective motion planning of parallel manipulators; it also increases the application prospect of parallel manipulators and provides attractive solutions to component assembly for those organizations with limited cost and that want to find an option that is effective to be implemented.

中文翻译：

---

一种六自由度并联机械臂最优无奇异运动规划方法

目的

本文旨在提出一种多目标和多约束下的最优无奇异运动规划方法，用于六自由度并联机械手，用作组件自动对接的执行机制。

设计/方法/方法

首先，基于运动学研究了局部工作空间内雅可比矩阵行列式的分布特征，提出了局部工作空间内无奇异路径规划的充要条件。然后，末端执行器的无奇异运动路径由五阶 B 样条曲线生成，并通过逆运动学获得每个执行器的相应轨迹。最后，定义了几个目标函数来评估运动路径，并开发了一种基于帕累托档案进化的改进的多目标粒子群优化算法，以获得最佳的无奇异运动轨迹。

发现

如果末端执行器的初始位姿和目标位姿都是无奇点的，只要每个位姿元素在各自方向上的所有值都是单调的，就可以在局部工作空间中规划一条无奇点的运动路径。改进的多目标粒子群优化(IMPSO)算法在多目标运动规划模型的优化中是有效且高效的。在组件对接测试中验证了末端执行器的最佳无奇异运动路径。对接结果是可动部件与固定部件对齐，这在一定程度上证明了所提出的运动路径方法的可行性和实用性。

原创性/价值

该方法在并联机械手的运动学多目标运动规划中具有一定的新颖性；它还增加了并联机械手的应用前景，并为那些成本有限并希望找到有效实施方案的组织提供有吸引力的组件组装解决方案。