Abstract
Path planning is crucial in numerous robotic applications. Reconfigurable robots possess the capability to alter their shape, enabling access to confined spaces, a task challenging for fixed-shape robots. However, existing path planners for reconfigurable robots are typically designed with predefined motion patterns for reconfiguration, lacking adaptation to space availability and executing reconfiguration only when the robot is static. This reliance on predefined patterns limits the potential of reconfigurable robots to navigate through confined spaces. This paper proposes a novel path-planning approach based on dynamic reconfiguration to address this limitation. The proposed method employs two nested A* algorithms modified to handle reconfiguration and efficient search, termed Dynamic Reconfiguration integrated Nested A* (DRiNA*). Experimental results demonstrate the proposed method's ability to find feasible paths for robot navigation using dynamic reconfigurations in confined spaces, surpassing the capabilities of existing path planners. The scalability of the proposed method to reconfigurable robots with varying numbers of blocks is also confirmed. Additionally, DRiNA* significantly reduces energy consumption compared to existing path planners.