Identification of physically consistent dynamics parameter of the ABB IRB 360-6/1600 delta robot and its use for time-optimal motion planning under consideration of constraint forces

IF 4.3 2区计算机科学 Q1 AUTOMATION & CONTROL SYSTEMS

Robotics and Autonomous Systems Pub Date : 2024-10-02 DOI:10.1016/j.robot.2024.104823

Daniel Gnad , Hubert Gattringer , Andreas Müller , Wolfgang Höbarth , Roland Riepl , Lukas Meßner

{"title":"Identification of physically consistent dynamics parameter of the ABB IRB 360-6/1600 delta robot and its use for time-optimal motion planning under consideration of constraint forces","authors":"Daniel Gnad , Hubert Gattringer , Andreas Müller , Wolfgang Höbarth , Roland Riepl , Lukas Meßner","doi":"10.1016/j.robot.2024.104823","DOIUrl":null,"url":null,"abstract":"<div><div>Model-based control schemes, forward dynamics simulations, constraint force computation and time-optimal motion planning have one major thing in common, they all depend on the dynamics parameters of the system. Physical consistency of the dynamics parameters ensures a positive definite mass matrix and correct constraint forces. The most common inverse dynamics identification method – the base-parameters – lack physical consistency. This paper proposes an identification method to identify physically consistent dynamics parameters for Delta-like robots while further showing the effects of friction in passive joints. A tailored model to compute the crucial constraint forces appearing in the mechanism based on the identified dynamics parameters is derived. This model is used to additionally consider constraint forces besides actuation torques for time-optimal motion planning of a typical pick and place task. This is done without any prior CAD data of the robot from the manufacturer.</div></div>","PeriodicalId":49592,"journal":{"name":"Robotics and Autonomous Systems","volume":"182 ","pages":"Article 104823"},"PeriodicalIF":4.3000,"publicationDate":"2024-10-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Robotics and Autonomous Systems","FirstCategoryId":"94","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S0921889024002070","RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"AUTOMATION & CONTROL SYSTEMS","Score":null,"Total":0}

引用次数: 0

Abstract

Model-based control schemes, forward dynamics simulations, constraint force computation and time-optimal motion planning have one major thing in common, they all depend on the dynamics parameters of the system. Physical consistency of the dynamics parameters ensures a positive definite mass matrix and correct constraint forces. The most common inverse dynamics identification method – the base-parameters – lack physical consistency. This paper proposes an identification method to identify physically consistent dynamics parameters for Delta-like robots while further showing the effects of friction in passive joints. A tailored model to compute the crucial constraint forces appearing in the mechanism based on the identified dynamics parameters is derived. This model is used to additionally consider constraint forces besides actuation torques for time-optimal motion planning of a typical pick and place task. This is done without any prior CAD data of the robot from the manufacturer.

查看原文本刊更多论文

识别 ABB IRB 360-6/1600 三角形机器人的物理一致动力学参数，并将其用于考虑约束力的时间最优运动规划

基于模型的控制方案、前向动力学模拟、约束力计算和时间最优运动规划有一个主要共同点，即它们都取决于系统的动力学参数。动力学参数的物理一致性确保了质量矩阵的正定性和约束力的正确性。最常见的逆动力学识别方法--基础参数--缺乏物理一致性。本文提出了一种识别方法，用于识别类似德尔塔机器人的物理一致性动力学参数，同时进一步显示被动关节中摩擦力的影响。根据识别出的动力学参数，推导出一个量身定制的模型，用于计算机械装置中出现的关键约束力。除了执行扭矩外，该模型还用于额外考虑约束力，以对典型的取放任务进行时间优化运动规划。这项工作无需事先从制造商处获得任何机器人的 CAD 数据。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

求助全文

约1分钟内获得全文求助全文

来源期刊

Robotics and Autonomous Systems 工程技术-机器人学

CiteScore

9.00

自引率

7.00%

发文量

164

审稿时长

4.5 months

期刊介绍： Robotics and Autonomous Systems will carry articles describing fundamental developments in the field of robotics, with special emphasis on autonomous systems. An important goal of this journal is to extend the state of the art in both symbolic and sensory based robot control and learning in the context of autonomous systems. Robotics and Autonomous Systems will carry articles on the theoretical, computational and experimental aspects of autonomous systems, or modules of such systems.