Problem
Research questions and friction points this paper is trying to address.
kinesthetic teaching
operational performance
collaborative robots
A Unified Dynamic Force Guidance Framework for Performance-Optimized Kinesthetic Teaching
🤖 AI Summary
为解决协作机器人在示教过程中操作性能下降问题，提出一种在线动态力引导方法，结合性能约束与优化机制，通过变顺应控制和虚拟力引导提升机器人操作性能。
📝 Abstract
Collaborative robots are increasingly deployed in industrial scenarios characterized by frequent product changeovers. As an intuitive programming method, kinesthetic teaching facilitates rapid robot deployment. However, users may overlook the configuration of the robot during kinesthetic teaching, leading to degradation in operational performance. Operational performance refers to the capability of the robot to generate motion and can be quantified by the Minimum Singular Value of the Jacobian matrix. To address this issue, this paper proposes an online dynamic force guidance method that integrates performance constraint and optimization mechanisms. Specifically, variable admittance control maintains the operational performance of the robot above a predefined threshold, while a virtual force actively guides the user to drag the robot towards configurations with improved performance. Experiments are conducted on a 6-DOF collaborative robot, comparing three typical paths in the task space. To evaluate the quality of the taught trajectories, trajectory playback experiments are conducted to analyze the relationship between the operational performance of the robot and the work efficiency. The results demonstrate that the proposed method effectively enhances the operational performance of the robot and consequently improves the work efficiency, holding significant value for reducing production takt time in industrial deployment.
Innovation
Methods, ideas, or system contributions that make the work stand out.
dynamic force guidance
performance optimization
variable admittance control
kinesthetic teaching
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2024-09-18arXiv.orgCitations: 2
