Using haptics to probe human contact control strategies for six degree-of-freedom tasks

Transferring human contact-manipulation skills to robots is complicated by the combinatorial growth in contact state descriptions with object and environment complexity, with no systematic method to characterize the subset of contact states that humans actually control. In this paper, we present an approach to determine whether human subjects control specific contact states. Subjects used a six degree-of-freedom haptic interface to place a box on a plane, and insert L- and S-shaped objects into corresponding holes, while using either their (undetermined) natural strategies or explicitly controlling a pre-specified sequence of contact states. We found that the vast majority of contact states were visited for time periods of less than 40ms, which negates the possibility of human feedback control due to physiological delay limits. Next, using force, moment and velocity trajectories around contact state transitions as a metric, we found that certain states were readily discriminable across natural and explicit control strategies (~ 85%), which indicates that they were not controlled during natural motions. Less discriminable states, in contrast, were likely to have been controlled in both natural and explicit strategies. Our results suggest that humans explicitly control a small subset of contact states, and that their control strategies are reflected in local force and velocity profiles. We thus demonstrate that six degree-of-freedom haptic simulations are effective for characterizing human contact-state invariant control strategies.

[1]  Oussama Khatib,et al.  Haptic display for human interaction with virtual dynamic environments , 2001, J. Field Robotics.

[2]  John Kenneth Salisbury,et al.  A constraint-based god-object method for haptic display , 1995, Proceedings 1995 IEEE/RSJ International Conference on Intelligent Robots and Systems. Human Robot Interaction and Cooperative Robots.

[3]  Xin Zhang,et al.  Configuration-based optimization for six degree-of-freedom haptic rendering for fine manipulation. , 2013, IEEE transactions on haptics.

[4]  Jing Xiao,et al.  Planning Motions Compliant to Complex Contact States , 2001, Int. J. Robotics Res..

[5]  Probal Mitra,et al.  Dynamic proxy objects in haptic simulations , 2004, IEEE Conference on Robotics, Automation and Mechatronics, 2004..

[6]  Oussama Khatib,et al.  A Haptic Teleoperation Approach Based on Contact Force Control , 2006, Int. J. Robotics Res..

[7]  山田 祐,et al.  Open Dynamics Engine を用いたスノーボードロボットシミュレータの開発 , 2007 .

[8]  John Kenneth Salisbury,et al.  Constraint-based six degree-of-freedom haptic rendering of volume-embedded isosurfaces , 2011, 2011 IEEE World Haptics Conference.

[9]  Oussama Khatib,et al.  The Potential Field Approach And Operational Space Formulation In Robot Control , 1986 .

[10]  Ming C. Lin,et al.  A modular haptic rendering algorithm for stable and transparent 6-DOF manipulation , 2006, IEEE Transactions on Robotics.

[11]  Joris De Schutter,et al.  Integration of planning and execution in force controlled compliant motion , 2005, IROS.

[12]  Joris De Schutter,et al.  Contact-State Segmentation Using Particle Filters for Programming by Human Demonstration in Compliant-Motion Tasks , 2007, IEEE Transactions on Robotics.

[13]  Tsutomu Hasegawa,et al.  Generating a contact state graph of polyhedral objects for robotic application , 2010, 2010 IEEE/RSJ International Conference on Intelligent Robots and Systems.

[14]  Joris De Schutter,et al.  Specification of force-controlled actions in the "task frame formalism"-a synthesis , 1996, IEEE Trans. Robotics Autom..