An Inverse Kinematics Algorithm With Smooth Task Switching for Redundant Robots

被引：0

作者：

Gamper, Hannes ^{[1
,2
]}

Perez, Laura Rodrigo ^{[1
]}

Mueller, Andreas ^{[2
]}

Rosales, Alejandro Diaz ^{[1
,3
]}

Di Castro, Mario ^{[1
]}

机构：

[1] European Org Nucl Res CERN, CH-1211 Meyrin, Switzerland

[2] Johannes Kepler Univ Linz, Inst Robot, A-4040 Linz, Austria

[3] Delft Univ Technol, Dept Cognit Robot, NL-2628 CD Delft, Netherlands

来源：

IEEE ROBOTICS AND AUTOMATION LETTERS | 2024年 / 9卷 / 05期

关键词：

Task analysis; Switches; Kinematics; Robots; Jacobian matrices; Optimization; Asymptotic stability; redundant robots; motion control;

D O I：

10.1109/LRA.2024.3379860

中图分类号：

TP24 [机器人技术];

学科分类号：

080202 ; 1405 ;

摘要：

This letter presents an inverse kinematics approach that combines two well-known Jacobian based methods, the task-priority framework and an optimization-based approach, such that tracking and optimization tasks can be executed simultaneously. The novelty of the proposed algorithm lies in the ability to smoothly switch between different tasks and thus to allow for a seamless and safe transition during robot operation. This has shown to improve the efficiency and user experience, especially during tele-operated interventions in complex environments.

引用

页码：4527 / 4534

页数：8

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