使用综合摩擦模型的改进迭代法确定协作机器人的动态参数

IF 1.9 4区 计算机科学 Q3 ROBOTICS
Robotica Pub Date : 2024-03-20 DOI:10.1017/s0263574724000341
Zeyu Li, Hongxing Wei, Chengguo Liu, Ye He, Gang Liu, Haochen Zhang, Weiming Li
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引用次数: 0

摘要

协作机器人正在成为工业和日常生活中人类的智能助手。动态模型识别为协作机器人实现精确控制、快速碰撞检测和流畅的前导编程提供了有效途径,因此是一个活跃的课题。本研究提出了一种改进的迭代方法,在考虑关节速度、温度和负载扭矩影响的情况下,利用综合摩擦模型进行协作机器人的动态模型识别。实验在 AUBO I5 协作机器人上进行。采用其他两种现有的识别算法与所提出的方法进行比较。实验证明,与经典的 IRLS 算法相比,所提出的 I-IRLS 算法的平均误差减少了 14% 以上。提出的 I-IRLS 方法可广泛应用于协作机器人的各种应用场景。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
An improved iterative approach with a comprehensive friction model for identifying dynamic parameters of collaborative robots

Collaborative robots are becoming intelligent assistants of human in industrial settings and daily lives. Dynamic model identification is an active topic for collaborative robots because it can provide effective ways to achieve precise control, fast collision detection and smooth lead-through programming. In this research, an improved iterative approach with a comprehensive friction model for dynamic model identification is proposed for collaborative robots when the joint velocity, temperature and load torque effects are considered. Experiments are conducted on the AUBO I5 collaborative robots. Two other existing identification algorithms are adopted to make comparison with the proposed approach. It is verified that the average error of the proposed I-IRLS algorithm is reduced by over 14% than that of the classical IRLS algorithm. The proposed I-IRLS method can be widely used in various application scenarios of collaborative robots.

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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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