Environment Reconfiguration Planning for Autonomous Robotic Manipulation to overcome Mobility Constraints

This paper presents a novel strategy for intelligent robotic environment reconfiguration applied to overcome mobility constraints with an autonomously exploring mobile manipulation system. A realistic problem arising during exploration of unknown challenging environments is the encountering of untraversable areas –given the robot’s mobility constraints– resulting in the robot getting stuck. We propose that given manipulation capabilities of an autonomous system, it should be possible to leverage loose entities in its surrounding to reconfigure its environment, and therefore potentially restore traversability to an unreachable region. This work’s contribution is two-fold: first, it proposes a mid-range traversability estimation graph-based backend which also allows early detection of terrain gaps, and secondly, it provides an algorithm for focused environment alteration that ensures stable and valid configurations. The plans of this generic policy are evaluated to decide if they resolve the robot’s problem, and are subsequently applied. The effectiveness of the proposed approach is demonstrated via experimental studies using a relevant autonomous system within a mobility-constrained mock-up environment.