Decentralized and recursive identification for cooperative manipulation of unknown rigid body with local measurements

Taosha Fan; Huan Weng; Todd David Murphey

doi:10.1109/CDC.2017.8264073

Decentralized and recursive identification for cooperative manipulation of unknown rigid body with local measurements

Taosha Fan, Huan Weng, Todd David Murphey

Mechanical Engineering

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

4 Scopus citations

Abstract

This paper proposes a fully decentralized and recursive approach to online identification of unknown kinematic and dynamic parameters for cooperative manipulation of a rigid body based on commonly used local measurements. To the best of our knowledge, this is the first paper addressing the identification problem for 3D rigid body cooperative manipulation, though the approach proposed here applies to the 2D case as well. In this work, we derive truly linear observation models for kinematic and dynamic unknowns whose state-dependent uncertainties can be exactly evaluated. Dynamic consensus in different coordinates and a filter for dual quaternion are developed with which the identification problem can be solved in a distributed way. It can be seen that in our approach all unknowns to be identified are time-invariant constants. Finally, we provide numerical simulation results to illustrate the efficacy of our approach indicating that it can be used for online identification and adaptive control of rigid body cooperative manipulation.

Original language	English (US)
Title of host publication	Proceedings of yhe 2017 IEEE 56th Annual Conference on Decision and Control (CDC)
Publisher	IEEE
Pages	2842-2849
Number of pages	8
ISBN (Electronic)	9781509028733
ISBN (Print)	978-1509028740
DOIs	https://doi.org/10.1109/CDC.2017.8264073
State	Published - Jan 18 2018
Event	56th IEEE Annual Conference on Decision and Control, CDC 2017 - Melbourne, Australia Duration: Dec 12 2017 → Dec 15 2017

Publication series

Name	2017 IEEE 56th Annual Conference on Decision and Control, CDC 2017
Volume	2018-January

Other

Other	56th IEEE Annual Conference on Decision and Control, CDC 2017
Country/Territory	Australia
City	Melbourne
Period	12/12/17 → 12/15/17

Funding

This material is based upon work supported by the National Science Foundation under Grant CNS 1329891. Any opinions, findings and conclusions or recommendations expressed in this material are those of the authors and do not necessarily reflect the views of the National Science Foundation.

Keywords

3D rigid body
Cooperative manipulation
distributed identification
dual quaternion
dynamic consensus

ASJC Scopus subject areas

Decision Sciences (miscellaneous)
Industrial and Manufacturing Engineering
Control and Optimization

Access to Document

10.1109/CDC.2017.8264073

Cite this

Fan, T., Weng, H., & Murphey, T. D. (2018). Decentralized and recursive identification for cooperative manipulation of unknown rigid body with local measurements. In Proceedings of yhe 2017 IEEE 56th Annual Conference on Decision and Control (CDC) (pp. 2842-2849). (2017 IEEE 56th Annual Conference on Decision and Control, CDC 2017; Vol. 2018-January). IEEE. https://doi.org/10.1109/CDC.2017.8264073

@inproceedings{10c16f0d73114d9dbb4fa4cdfa3fa688,

title = "Decentralized and recursive identification for cooperative manipulation of unknown rigid body with local measurements",

abstract = "This paper proposes a fully decentralized and recursive approach to online identification of unknown kinematic and dynamic parameters for cooperative manipulation of a rigid body based on commonly used local measurements. To the best of our knowledge, this is the first paper addressing the identification problem for 3D rigid body cooperative manipulation, though the approach proposed here applies to the 2D case as well. In this work, we derive truly linear observation models for kinematic and dynamic unknowns whose state-dependent uncertainties can be exactly evaluated. Dynamic consensus in different coordinates and a filter for dual quaternion are developed with which the identification problem can be solved in a distributed way. It can be seen that in our approach all unknowns to be identified are time-invariant constants. Finally, we provide numerical simulation results to illustrate the efficacy of our approach indicating that it can be used for online identification and adaptive control of rigid body cooperative manipulation.",

keywords = "3D rigid body, Cooperative manipulation, distributed identification, dual quaternion, dynamic consensus",

author = "Taosha Fan and Huan Weng and Murphey, {Todd David}",

note = " DOI: 10.1109/CDC.2017.8264073 ; 56th IEEE Annual Conference on Decision and Control, CDC 2017 ; Conference date: 12-12-2017 Through 15-12-2017",

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Fan, T, Weng, H & Murphey, TD 2018, Decentralized and recursive identification for cooperative manipulation of unknown rigid body with local measurements. in Proceedings of yhe 2017 IEEE 56th Annual Conference on Decision and Control (CDC) . 2017 IEEE 56th Annual Conference on Decision and Control, CDC 2017, vol. 2018-January, IEEE, pp. 2842-2849, 56th IEEE Annual Conference on Decision and Control, CDC 2017, Melbourne, Australia, 12/12/17. https://doi.org/10.1109/CDC.2017.8264073

Decentralized and recursive identification for cooperative manipulation of unknown rigid body with local measurements. / Fan, Taosha; Weng, Huan; Murphey, Todd David.
Proceedings of yhe 2017 IEEE 56th Annual Conference on Decision and Control (CDC) . IEEE, 2018. p. 2842-2849 (2017 IEEE 56th Annual Conference on Decision and Control, CDC 2017; Vol. 2018-January).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

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N2 - This paper proposes a fully decentralized and recursive approach to online identification of unknown kinematic and dynamic parameters for cooperative manipulation of a rigid body based on commonly used local measurements. To the best of our knowledge, this is the first paper addressing the identification problem for 3D rigid body cooperative manipulation, though the approach proposed here applies to the 2D case as well. In this work, we derive truly linear observation models for kinematic and dynamic unknowns whose state-dependent uncertainties can be exactly evaluated. Dynamic consensus in different coordinates and a filter for dual quaternion are developed with which the identification problem can be solved in a distributed way. It can be seen that in our approach all unknowns to be identified are time-invariant constants. Finally, we provide numerical simulation results to illustrate the efficacy of our approach indicating that it can be used for online identification and adaptive control of rigid body cooperative manipulation.

AB - This paper proposes a fully decentralized and recursive approach to online identification of unknown kinematic and dynamic parameters for cooperative manipulation of a rigid body based on commonly used local measurements. To the best of our knowledge, this is the first paper addressing the identification problem for 3D rigid body cooperative manipulation, though the approach proposed here applies to the 2D case as well. In this work, we derive truly linear observation models for kinematic and dynamic unknowns whose state-dependent uncertainties can be exactly evaluated. Dynamic consensus in different coordinates and a filter for dual quaternion are developed with which the identification problem can be solved in a distributed way. It can be seen that in our approach all unknowns to be identified are time-invariant constants. Finally, we provide numerical simulation results to illustrate the efficacy of our approach indicating that it can be used for online identification and adaptive control of rigid body cooperative manipulation.

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Decentralized and recursive identification for cooperative manipulation of unknown rigid body with local measurements

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