Planning for Autonomous Door Opening with a Mobile Manipulator

Abstract

Computing a motion that enables a mobile manipulator to open a door is challenging because it requires tight coordination between the motions of the arm and the base. Hard-coding the motion, on the other hand, is infeasible since doors vary widely in their sizes and types, some doors are opened by pulling and others by pushing, and indoor spaces often contain obstacles that limit the freedom of the mobile manipulator and the degree to which the doors open up. In this paper, we show how to overcome the high-dimensionality of the planning problem by identifying a graph-based representation that is small enough for efficient planning yet rich enough to contain feasible motions that open doors. The use of graph search-based motion planning enables us to handle consistently the wide variance of conditions under which doors need to be open. We demonstrate our approach on the PR2 robot - a mobile manipulator with an omnidirectional base and a 7 degree of freedom arm. The robot was successful in opening a variety of doors both by pulling and pushing.