Operational Space Control: A Theoretical and Empirical Comparison

Author:

Nakanishi Jun1,Cory Rick2,Mistry Michael3,Peters Jan3,Schaal Stefan4

Affiliation:

1. ICORP, Computational Brain Project, Japan Science and Technology Agency, Saitama 332-0012, Japan, ATR Computational Neuroscience Laboratories, Department of Humanoid Robotics and Computational Neuroscience, Kyoto 619-0288, Japan,

2. Computer Science and Artificial Intelligence Laboratory, Massachusetts Institute of Technology, Cambridge, MA 02139, USA,

3. Computer Science & Neuroscience, University of Southern California, Los Angeles, CA 90089-2520, USA,

4. ATR Computational Neuroscience Laboratories, Department of Humanoid Robotics and Computational Neuroscience, Kyoto 619-0288, Japan, Computer Science & Neuroscience, University of Southern California, Los Angeles, CA 90089-2520, USA,

Abstract

Dexterous manipulation with a highly redundant movement system is one of the hallmarks of human motor skills. From numerous behavioral studies, there is strong evidence that humans employ compliant task space control, i.e. they focus control only on task variables while keeping redundant degrees-of-freedom as compliant as possible. This strategy is robust towards unknown disturbances and simultaneously safe for the operator and the environment. The theory of operational space control in robotics aims to achieve similar performance properties. However, despite various compelling theoretical lines of research, advanced operational space control is hardly found in actual robotics implementations, in particular new kinds of robots like humanoids and service robots, which would strongly profit from compliant dexterous manipulation. To analyze the pros and cons of different approaches to operational space control, this paper focuses on a theoretical and empirical evaluation of different methods that have been suggested in the literature, but also some new variants of operational space controllers. We address formulations at the velocity, acceleration, and force levels. First, we formulate all controllers in a common notational framework, including quaternion-based orientation control, and discuss some of their theoretical properties. Second, we present experimental comparisons of these approaches on a seven-degree-of-freedom anthropomorphic robot arm with several benchmark tasks. As an aside, we also introduce a novel parameter estimation algorithm for rigid body dynamics, which ensures physical consistency, as this issue was crucial for our successful robot implementations. Our extensive empirical results demonstrate that one of the simplified acceleration-based approaches can be advantageous in terms of task performance, ease of parameter tuning, and general robustness and compliance in the face of inevitable modeling errors.

Publisher

SAGE Publications

Subject

Applied Mathematics,Artificial Intelligence,Electrical and Electronic Engineering,Mechanical Engineering,Modeling and Simulation,Software

Cited by 214 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Redundancy-Aware Action Spaces for Robot Learning;IEEE Robotics and Automation Letters;2024-08

2. Safe Whole-Body Task Space Control for Humanoid Robots;2024 American Control Conference (ACC);2024-07-10

3. Moving Past Point-Contacts: Extending the ALIP Model to Humanoids with Non-Trivial Feet Using Hierarchical, Full-Body Momentum Control;2024 American Control Conference (ACC);2024-07-10

4. Hybrid OSC-RL Control for Task Optimization of Dual-Arm Robots;2024 13th International Workshop on Robot Motion and Control (RoMoCo);2024-07-02

5. Robot control based on motor primitives: A comparison of two approaches;The International Journal of Robotics Research;2024-06-21

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3