Adaptive optimal control for coordination in physical human-robot interaction

In this paper, we propose an adaptive optimal control for a robot to collaborate with a human. Game theory and policy iteration are employed to analyze the interactive behaviors of the human and the robot in physical interactions. The human's control objective is estimated and it is used to adapt the robot's own objective, such that human-robot coordination can be achieved. An optimal control is developed to guarantee that the robot's control objective is realized. The validity of the proposed method is verified through rigorous analysis and experiment studies.

[1]  Shuzhi Sam Ge,et al.  Human–Robot Collaboration Based on Motion Intention Estimation , 2014, IEEE/ASME Transactions on Mechatronics.

[2]  T. Başar,et al.  Dynamic Noncooperative Game Theory, 2nd Edition , 1998 .

[3]  Sean R Eddy,et al.  What is dynamic programming? , 2004, Nature Biotechnology.

[4]  Hidenori Kimura,et al.  Human-robot collaboration in precise positioning of a three-dimensional object , 2009, Autom..

[5]  Antonio Bicchi,et al.  An atlas of physical human-robot interaction , 2008 .

[6]  E. Burdet,et al.  A Framework to Describe, Analyze and Generate Interactive Motor Behaviors , 2012, PloS one.

[7]  Etienne Burdet,et al.  Slaves no longer: review on role assignment for human–robot joint motor action , 2014, Adapt. Behav..

[8]  Frank L. Lewis,et al.  Online adaptive learning for team strategies in multi-agent systems , 2012 .

[9]  Shuzhi Sam Ge,et al.  Force tracking control for motion synchronization in human-robot collaboration , 2014, Robotica.

[10]  Cagatay Basdogan,et al.  The role of roles: Physical cooperation between humans and robots , 2012, Int. J. Robotics Res..

[11]  Lynne E. Parker,et al.  Distributed Intelligence: Overview of the Field and Its Application in Multi-Robot Systems , 2008, AAAI Fall Symposium: Regarding the Intelligence in Distributed Intelligent Systems.

[12]  Neville Hogan,et al.  Impedance Control: An Approach to Manipulation: Part I—Theory , 1985 .

[13]  Keng Peng Tee,et al.  Continuous Role Adaptation for Human–Robot Shared Control , 2015, IEEE Transactions on Robotics.

[14]  Donald E. Kirk,et al.  Optimal control theory : an introduction , 1970 .

[15]  Derong Liu,et al.  Online Synchronous Approximate Optimal Learning Algorithm for Multi-Player Non-Zero-Sum Games With Unknown Dynamics , 2014, IEEE Transactions on Systems, Man, and Cybernetics: Systems.

[16]  T. Başar,et al.  Dynamic Noncooperative Game Theory , 1982 .

[17]  Frank L. Lewis,et al.  Multi-player non-zero-sum games: Online adaptive learning solution of coupled Hamilton-Jacobi equations , 2011, Autom..

[18]  Aude Billard,et al.  A survey of Tactile Human-Robot Interactions , 2010, Robotics Auton. Syst..