Cargando…
A Framework for Human-Robot-Human Physical Interaction Based on N-Player Game Theory
In order to analyze the complex interactive behaviors between the robot and two humans, this paper presents an adaptive optimal control framework for human-robot-human physical interaction. N-player linear quadratic differential game theory is used to describe the system under study. N-player differ...
Autores principales: | , , , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2020
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7506811/ https://www.ncbi.nlm.nih.gov/pubmed/32899335 http://dx.doi.org/10.3390/s20175005 |
_version_ | 1783585099618451456 |
---|---|
author | Zou, Rui Liu, Yubin Zhao, Jie Cai, Hegao |
author_facet | Zou, Rui Liu, Yubin Zhao, Jie Cai, Hegao |
author_sort | Zou, Rui |
collection | PubMed |
description | In order to analyze the complex interactive behaviors between the robot and two humans, this paper presents an adaptive optimal control framework for human-robot-human physical interaction. N-player linear quadratic differential game theory is used to describe the system under study. N-player differential game theory can not be used directly in actual scenerie, since the robot cannot know humans’ control objectives in advance. In order to let the robot know humans’ control objectives, the paper presents an online estimation method to identify unknown humans’ control objectives based on the recursive least squares algorithm. The Nash equilibrium solution of human-robot-human interaction is obtained by solving the coupled Riccati equation. Adaptive optimal control can be achieved during the human-robot-human physical interaction. The effectiveness of the proposed method is demonstrated by rigorous theoretical analysis and simulations. The simulation results show that the proposed controller can achieve adaptive optimal control during the interaction between the robot and two humans. Compared with the LQR controller, the proposed controller has more superior performance. |
format | Online Article Text |
id | pubmed-7506811 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-75068112020-09-26 A Framework for Human-Robot-Human Physical Interaction Based on N-Player Game Theory Zou, Rui Liu, Yubin Zhao, Jie Cai, Hegao Sensors (Basel) Letter In order to analyze the complex interactive behaviors between the robot and two humans, this paper presents an adaptive optimal control framework for human-robot-human physical interaction. N-player linear quadratic differential game theory is used to describe the system under study. N-player differential game theory can not be used directly in actual scenerie, since the robot cannot know humans’ control objectives in advance. In order to let the robot know humans’ control objectives, the paper presents an online estimation method to identify unknown humans’ control objectives based on the recursive least squares algorithm. The Nash equilibrium solution of human-robot-human interaction is obtained by solving the coupled Riccati equation. Adaptive optimal control can be achieved during the human-robot-human physical interaction. The effectiveness of the proposed method is demonstrated by rigorous theoretical analysis and simulations. The simulation results show that the proposed controller can achieve adaptive optimal control during the interaction between the robot and two humans. Compared with the LQR controller, the proposed controller has more superior performance. MDPI 2020-09-03 /pmc/articles/PMC7506811/ /pubmed/32899335 http://dx.doi.org/10.3390/s20175005 Text en © 2020 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Letter Zou, Rui Liu, Yubin Zhao, Jie Cai, Hegao A Framework for Human-Robot-Human Physical Interaction Based on N-Player Game Theory |
title | A Framework for Human-Robot-Human Physical Interaction Based on N-Player Game Theory |
title_full | A Framework for Human-Robot-Human Physical Interaction Based on N-Player Game Theory |
title_fullStr | A Framework for Human-Robot-Human Physical Interaction Based on N-Player Game Theory |
title_full_unstemmed | A Framework for Human-Robot-Human Physical Interaction Based on N-Player Game Theory |
title_short | A Framework for Human-Robot-Human Physical Interaction Based on N-Player Game Theory |
title_sort | framework for human-robot-human physical interaction based on n-player game theory |
topic | Letter |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7506811/ https://www.ncbi.nlm.nih.gov/pubmed/32899335 http://dx.doi.org/10.3390/s20175005 |
work_keys_str_mv | AT zourui aframeworkforhumanrobothumanphysicalinteractionbasedonnplayergametheory AT liuyubin aframeworkforhumanrobothumanphysicalinteractionbasedonnplayergametheory AT zhaojie aframeworkforhumanrobothumanphysicalinteractionbasedonnplayergametheory AT caihegao aframeworkforhumanrobothumanphysicalinteractionbasedonnplayergametheory AT zourui frameworkforhumanrobothumanphysicalinteractionbasedonnplayergametheory AT liuyubin frameworkforhumanrobothumanphysicalinteractionbasedonnplayergametheory AT zhaojie frameworkforhumanrobothumanphysicalinteractionbasedonnplayergametheory AT caihegao frameworkforhumanrobothumanphysicalinteractionbasedonnplayergametheory |