弹道
机器人末端执行器
路径(计算)
计算机科学
控制理论(社会学)
多目标优化
运动规划
机器人
数学优化
笛卡尔坐标系
分类
串联机械手
并联机械手
数学
人工智能
算法
控制(管理)
物理
天文
几何学
程序设计语言
作者
Jintao Ye,Lina Hao,Hongtai Cheng
出处
期刊:Robotica
[Cambridge University Press]
日期:2024-04-17
卷期号:: 1-20
被引量:1
标识
DOI:10.1017/s0263574724000481
摘要
Abstract In the process of trajectory optimization for robot manipulator, the path that is generated may deviate from the intended path because of the adjustment of trajectory parameters, if there is limitation of end-effector path in Cartesian space for specific tasks, this phenomenon is dangerous. This paper proposes a methodology that is based on the Pareto front to address this issue, and the methodology takes into account both the multi-objective optimization of robotic arm and the quality of end-effector path. Based on dung beetle optimizer, this research proposes improved non-dominated sorting dung beetle optimizer. This paper interpolates manipulator trajectory with quintic B -spline curves, achieves multi-objective trajectory optimization that simultaneously optimizes traveling time, energy consumption, and mean jerk, proposes a trajectory selection strategy that is based on Pareto solution set by introducing the concept of Fréchet distance, and the strategy enables the end-effector to approach the desired path in Cartesian space. Simulation and experimental results validate the effectiveness and practicability of the proposed methodology on the Sawyer robot manipulator.
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