基于并行图像的协作式Delta机器人视觉伺服/力控制

Parallel Image-Based Visual Servoing/Force Control of a Collaborative Delta Robot.

作者信息

Zhu Minglei, Huang Cong, Qiu Zhiqiang, Zheng Wei, Gong Dawei

机构信息

School of Mechanical and Electrical Engineering, University of Electronic Science and Technology of China, Chengdu, China.

Science and Technology on Thermal Energy and Power Laboratory, Wuhan Second Ship Design and Research Institute, Wuhan, China.

出版信息

Front Neurorobot. 2022 Jun 1;16:922704. doi: 10.3389/fnbot.2022.922704. eCollection 2022.

DOI:10.3389/fnbot.2022.922704

PMID:35721276

原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC9198459/

Abstract

In this paper, a parallel Image-based visual servoing/force controller is developed in order to solve the interaction problem between the collaborative robot and the environment so that the robot can track the position trajectory and the desired force at the same time. This control methodology is based on the image-based visual servoing (IBVS) dynamic computed torque control and couples the force control feedback in parallel. Simulations are performed on a collaborative Delta robot and two types of image features are tested to determine which one is better for this parallel IBVS/force controller. The results show the efficiency of this controller.

摘要

本文开发了一种基于图像的并行视觉伺服/力控制器，以解决协作机器人与环境之间的交互问题，使机器人能够同时跟踪位置轨迹和所需力。这种控制方法基于基于图像的视觉伺服（IBVS）动态计算转矩控制，并并行耦合力控制反馈。在协作Delta机器人上进行了仿真，并测试了两种类型的图像特征，以确定哪一种更适合这种并行IBVS/力控制器。结果表明了该控制器的有效性。