A Convex Optimization Framework for Constrained Concurrent Motion Control of a Hybrid Redundant Surgical System

Farshid Alambeigi, Shahriar Sefati, Mehran Armand

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

We present a constrained motion control framework for a redundant surgical system designed for minimally invasive treatment of pelvic osteolysis. The framework comprises a kinematics model of a six Degrees-of-Freedom (DoF) robotic arm integrated with a one DoF continuum manipulator as well as a novel convex optimization redundancy resolution controller. To resolve the redundancy resolution problem, formulated as a constrained ℓ2-regularized quadratic minimization, we study and evaluate the potential use of an optimally tuned alternating direction method of multipliers (ADMM) algorithm. To this end, we prove global convergence of the algorithm at linear rate and propose expressions for the involved parameters resulting in a fast convergence. Simulations on the robotic system verified our analytical derivations and showed the capability and robustness of the ADMM algorithm in constrained motion control of our redundant surgical system.

Original languageEnglish (US)
Title of host publication2018 Annual American Control Conference, ACC 2018
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages1158-1165
Number of pages8
Volume2018-June
ISBN (Print)9781538654286
DOIs
StatePublished - Aug 9 2018
Event2018 Annual American Control Conference, ACC 2018 - Milwauke, United States
Duration: Jun 27 2018Jun 29 2018

Other

Other2018 Annual American Control Conference, ACC 2018
CountryUnited States
CityMilwauke
Period6/27/186/29/18

Fingerprint

Convex optimization
Motion control
Redundancy
Robotic arms
Degrees of freedom (mechanics)
Manipulators
Kinematics
Robotics
Controllers

ASJC Scopus subject areas

  • Electrical and Electronic Engineering

Cite this

Alambeigi, F., Sefati, S., & Armand, M. (2018). A Convex Optimization Framework for Constrained Concurrent Motion Control of a Hybrid Redundant Surgical System. In 2018 Annual American Control Conference, ACC 2018 (Vol. 2018-June, pp. 1158-1165). [8430983] Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.23919/ACC.2018.8430983

A Convex Optimization Framework for Constrained Concurrent Motion Control of a Hybrid Redundant Surgical System. / Alambeigi, Farshid; Sefati, Shahriar; Armand, Mehran.

2018 Annual American Control Conference, ACC 2018. Vol. 2018-June Institute of Electrical and Electronics Engineers Inc., 2018. p. 1158-1165 8430983.

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Alambeigi, F, Sefati, S & Armand, M 2018, A Convex Optimization Framework for Constrained Concurrent Motion Control of a Hybrid Redundant Surgical System. in 2018 Annual American Control Conference, ACC 2018. vol. 2018-June, 8430983, Institute of Electrical and Electronics Engineers Inc., pp. 1158-1165, 2018 Annual American Control Conference, ACC 2018, Milwauke, United States, 6/27/18. https://doi.org/10.23919/ACC.2018.8430983
Alambeigi F, Sefati S, Armand M. A Convex Optimization Framework for Constrained Concurrent Motion Control of a Hybrid Redundant Surgical System. In 2018 Annual American Control Conference, ACC 2018. Vol. 2018-June. Institute of Electrical and Electronics Engineers Inc. 2018. p. 1158-1165. 8430983 https://doi.org/10.23919/ACC.2018.8430983
Alambeigi, Farshid ; Sefati, Shahriar ; Armand, Mehran. / A Convex Optimization Framework for Constrained Concurrent Motion Control of a Hybrid Redundant Surgical System. 2018 Annual American Control Conference, ACC 2018. Vol. 2018-June Institute of Electrical and Electronics Engineers Inc., 2018. pp. 1158-1165
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