关注末端执行器路径限制的机器人操纵器多目标优化轨迹规划

IF 1.9 4区 计算机科学 Q3 ROBOTICS Robotica Pub Date : 2024-04-17 DOI:10.1017/s0263574724000481
Jintao Ye, Lina Hao, Hongtai Cheng
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引用次数: 0

摘要

在机器人机械手的轨迹优化过程中,由于轨迹参数的调整,生成的路径可能会偏离预定路径,如果特定任务的末端执行器路径在笛卡尔空间存在限制,这种现象就很危险。本文提出了一种基于帕累托前沿的方法来解决这一问题,该方法既考虑了机械臂的多目标优化,又考虑了末端执行器路径的质量。在蜣螂优化器的基础上,本研究提出了改进的非支配排序蜣螂优化器。本文用五次 B-样条曲线对机械手轨迹进行插值,实现了同时优化行走时间、能耗和平均挺举的多目标轨迹优化,并通过引入弗雷谢特距离的概念,提出了一种基于帕累托解集的轨迹选择策略,该策略可使末端执行器在笛卡尔空间中接近所需的路径。仿真和实验结果验证了所提方法在 Sawyer 机器人操纵器上的有效性和实用性。
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Multi-objective optimal trajectory planning for robot manipulator attention to end-effector path limitation
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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来源期刊
Robotica
Robotica 工程技术-机器人学
CiteScore
4.50
自引率
22.20%
发文量
181
审稿时长
9.9 months
期刊介绍: Robotica is a forum for the multidisciplinary subject of robotics and encourages developments, applications and research in this important field of automation and robotics with regard to industry, health, education and economic and social aspects of relevance. Coverage includes activities in hostile environments, applications in the service and manufacturing industries, biological robotics, dynamics and kinematics involved in robot design and uses, on-line robots, robot task planning, rehabilitation robotics, sensory perception, software in the widest sense, particularly in respect of programming languages and links with CAD/CAM systems, telerobotics and various other areas. In addition, interest is focused on various Artificial Intelligence topics of theoretical and practical interest.
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