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首页> 外文期刊>IEEE transactions on industrial informatics >Two Hybrid End-Effector Posture-Maintaining and Obstacle-Limits Avoidance Schemes for Redundant Robot Manipulators
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Two Hybrid End-Effector Posture-Maintaining and Obstacle-Limits Avoidance Schemes for Redundant Robot Manipulators

机译：冗余机器人操纵器的两个混合末端效应姿势和障碍限制避免方案

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摘要

To fulfill path tracking tasks with the end-effector posture controlled in a complex environment, maintaining the robot manipulator end-effector posture and avoiding obstacles are two important issues needed to be considered. In this paper, two hybrid end-effector posture-maintaining and obstacle-limits avoidance (hybrid PM-OLA) schemes are proposed and investigated for motion planning of redundant robot manipulators, which are based on the quadratic programming (QP) framework. The end-effector posture-maintaining, obstacle-avoidance, and the joint-angular-limits are formulated as an equality constraint, inequality constraint, and bound constraint into the QP problem. With these hybrid PM-OLA schemes, the robot manipulator can avoid the obstacle and joint physical limits when executing end-effector tasks. The hybrid PM-OLA schemes are finally transformed into linear variational inequalities and solved by a recurrent neural network. Computer simulations and physical experiments substantiate the effectiveness, accuracy, safety, and the practicability of the proposed hybrid PM-OLA schemes. Comparisons with other schemes show that the proposed hybrid PM-OLA schemes are more suitable for applications.
机译：为了实现具有在复杂环境中控制的端部执行器姿势的路径跟踪任务，维持机器人机械手末端执行器姿势并避免障碍是所需的两个重要问题。在本文中，提出了两个混合末端效应器姿势和避免避免（混合PM-OLA）方案，并研究了冗余机器人操纵器的运动规划，其基于二次编程（QP）框架。最终效应器姿势保持，避免障碍物和关节角度限制作为平等约束，不等式约束以及QP问题的束缚约束。利用这些混合动力PM-OLA方案，机器人操纵器可以避免在执行终端执行器任务时避免障碍和关节物理限制。 Hybrid PM-OLA方案最终转化为线性变分不等式，并由经常性神经网络求解。计算机仿真和物理实验证实了所提出的杂交PM-OLA方案的有效性，准确性，安全性和实用性。与其他方案的比较表明，所提出的杂交PM-OLA方案更适合应用。

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