Guiding a Human Follower with Interaction Forces: Implications on Physical Human-Robot Interaction

摘要

This work challenges the common assumption in physical human-robot interaction (pHRI) that the movement intention of a human user can be simply modeled with dynamic equations relating forces to movements, regardless of the user. Studies in physical human-human interaction (pHHI) suggest that interaction forces carry sophisticated information that reveals motor skills and roles in the partnership and even promotes adaptation and motor learning. In this view, simple force-displacement equations often used in pHRI studies may not be sufficient. To test this, this work measured and analyzed the interaction forces (F) between two humans as the leader guided the blindfolded follower on a randomly chosen path. The actual trajectory of the follower was transformed to the velocity commands ( <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">$V$</tex> ) that would allow a hypothetical robot follower to track the same trajectory. Then, possible analytical relationships between <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">$F$</tex> and <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">$V$</tex> were obtained using neural network training. Results suggest that while <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">$F$</tex> helps predict V, the relationship is not straightforward, that seemingly irrelevant components of <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">$F$</tex> may be important, that force-velocity relationships are unique to each human follower, and that human neural control of movement may affect the prediction of the movement intent. It is suggested that user-specific, stereotype-free controllers may more accurately decode human intent in pHRI.