Improved A * Algorithm for Autonomous Vehicle Path Planning under Post-disaster Rescue Scene

Mobile robots play a crucial role in various applications, such as explosion prevention, warning systems, and post-disaster rescue missions, owing to their small size and flexible movement capabilities. Traditional mobile robots often employ a single motion mode, which can be insufficient in adapting to the complex and dynamic post-disaster rescue environments. Composite mobile robots, equipped with multiple motion capabilities, have gained popularity in such scenarios. This paper focuses on wheel-legged robots as carriers and proposes a heuristic function that combines distance and energy consumption constraints to improve the A * algorithm. The goal is to achieve effective global path planning in the challenging post-disaster rescue conditions. The environmental features are represented using distance grid maps and energy grid maps. Experimental results demonstrate that the improved algorithm reduces path planning time and successfully balances optimal path selection with energy-efficient planning in typical post-disaster rescue conditions.