The Motion Grammar for physical human-robot games

Abstract

We introduce the Motion Grammar, a powerful new representation for robot decision making, and validate its properties through the successful implementation of a physical human-robot game. The Motion Grammar is a formal tool for task decomposition and hybrid control in the presence of significant online uncertainty. In this paper, we describe the Motion Grammar, introduce some of the formal guarantees it can provide, and represent the entire game of human-robot chess through a single formal language. This language includes game-play, safe handling of human motion, uncertainty in piece positions, misplaced and collapsed pieces. We demonstrate the simple and effective language formulation through experiments on a 14-DOF manipulator interacting with 32 objects (chess pieces) and an unpredictable human adversary.