Stable pushing in narrow passage environment using a modified hybrid A* algorithm

Abstract

Pushing is a fundamental ability in mobile robotics for transporting objects when grippers are not applicable. A successful “box-pushing” requires good coordination between model prediction, pushing strategy, and motion planning, therefore presents a well-known challenge in mobile robot transportation community. However, current research often focuses on local planning for altering push direction, while global planning remains inadequate. This can lead to inefficient pushing trajectories, especially in narrow passages where robots may unintentionally push the box into a dead end due to the lack of robust global path. To address this, we propose the use of stable pushing as an effective technique and develop a unique global planning approach based on the hybrid A* algorithm. We enhance the hybrid A* algorithm by modifying the node expansion approach and incorporating a mechanism for predicting push direction, enabling the system to adapt to changing push side behavior and discover optimal pathways. Extensive simulations validate our system’s effectiveness in handling complex scenarios with limited passageways. As a result, our method significantly improves the robot’s capability to generate superior global paths for box-pushing, mitigating wasteful trajectories and enhancing overall performance.