Assistive Optimal Control-on-Request with Application in Standing Balance Therapy and Reinforcement

Anastasia Mavrommati, Alex Ansari, Todd David Murphey

Research output: Chapter in Book/Report/Conference proceedingChapter

Abstract

This chapter develops and applies a new control-on-request (COR) method to improve the capability of existing shared control interfaces. These COR enhanced interfaces allow users to request on-demand bursts of assistive computer control authority when manual/shared control tasks become too challenging. To enable the approach, we take advantage of the short duration of the desired control responses to derive an algebraic solution for the optimal switching control for differentiable nonlinear systems. Simulation studies show how COR interfaces present an opportunity for human–robot collaboration in standing balance therapy . In particular, we use the Robot Operating System (ROS) to show that optimal control-on-request achieves both therapy objectives of active patient participation and safety. Finally, we explore the potential of a COR interface as a vibrotactile feedback generator to dynamically reinforce standing balance through sensory augmentation.
Original languageEnglish (US)
Title of host publicationTrends in Control and Decision-Making for Human–Robot Collaboration Systems
EditorsYue Wang, Fumin Zhang
PublisherSpringer International Publishing
Pages131-151
Number of pages21
ISBN (Electronic)978-3-319-40533-9
ISBN (Print)978-3-319-40532-2
StatePublished - 2017

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Reinforcement
Manual control
Computer control
User interfaces
Interfaces (computer)
Nonlinear systems
Robots
Feedback

Cite this

Mavrommati, A., Ansari, A., & Murphey, T. D. (2017). Assistive Optimal Control-on-Request with Application in Standing Balance Therapy and Reinforcement. In Y. Wang, & F. Zhang (Eds.), Trends in Control and Decision-Making for Human–Robot Collaboration Systems (pp. 131-151). Springer International Publishing.
Mavrommati, Anastasia ; Ansari, Alex ; Murphey, Todd David. / Assistive Optimal Control-on-Request with Application in Standing Balance Therapy and Reinforcement. Trends in Control and Decision-Making for Human–Robot Collaboration Systems. editor / Yue Wang ; Fumin Zhang. Springer International Publishing, 2017. pp. 131-151
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Mavrommati, A, Ansari, A & Murphey, TD 2017, Assistive Optimal Control-on-Request with Application in Standing Balance Therapy and Reinforcement. in Y Wang & F Zhang (eds), Trends in Control and Decision-Making for Human–Robot Collaboration Systems. Springer International Publishing, pp. 131-151.

Assistive Optimal Control-on-Request with Application in Standing Balance Therapy and Reinforcement. / Mavrommati, Anastasia; Ansari, Alex; Murphey, Todd David.

Trends in Control and Decision-Making for Human–Robot Collaboration Systems. ed. / Yue Wang; Fumin Zhang. Springer International Publishing, 2017. p. 131-151.

Research output: Chapter in Book/Report/Conference proceedingChapter

TY - CHAP

T1 - Assistive Optimal Control-on-Request with Application in Standing Balance Therapy and Reinforcement

AU - Mavrommati, Anastasia

AU - Ansari, Alex

AU - Murphey, Todd David

PY - 2017

Y1 - 2017

N2 - This chapter develops and applies a new control-on-request (COR) method to improve the capability of existing shared control interfaces. These COR enhanced interfaces allow users to request on-demand bursts of assistive computer control authority when manual/shared control tasks become too challenging. To enable the approach, we take advantage of the short duration of the desired control responses to derive an algebraic solution for the optimal switching control for differentiable nonlinear systems. Simulation studies show how COR interfaces present an opportunity for human–robot collaboration in standing balance therapy . In particular, we use the Robot Operating System (ROS) to show that optimal control-on-request achieves both therapy objectives of active patient participation and safety. Finally, we explore the potential of a COR interface as a vibrotactile feedback generator to dynamically reinforce standing balance through sensory augmentation.

AB - This chapter develops and applies a new control-on-request (COR) method to improve the capability of existing shared control interfaces. These COR enhanced interfaces allow users to request on-demand bursts of assistive computer control authority when manual/shared control tasks become too challenging. To enable the approach, we take advantage of the short duration of the desired control responses to derive an algebraic solution for the optimal switching control for differentiable nonlinear systems. Simulation studies show how COR interfaces present an opportunity for human–robot collaboration in standing balance therapy . In particular, we use the Robot Operating System (ROS) to show that optimal control-on-request achieves both therapy objectives of active patient participation and safety. Finally, we explore the potential of a COR interface as a vibrotactile feedback generator to dynamically reinforce standing balance through sensory augmentation.

M3 - Chapter

SN - 978-3-319-40532-2

SP - 131

EP - 151

BT - Trends in Control and Decision-Making for Human–Robot Collaboration Systems

A2 - Wang, Yue

A2 - Zhang, Fumin

PB - Springer International Publishing

ER -

Mavrommati A, Ansari A, Murphey TD. Assistive Optimal Control-on-Request with Application in Standing Balance Therapy and Reinforcement. In Wang Y, Zhang F, editors, Trends in Control and Decision-Making for Human–Robot Collaboration Systems. Springer International Publishing. 2017. p. 131-151