Optimizing Path Planning and Conflict Resolution in High-Density AS/RS With a Multishuttle Cooperative Scheduling Framework

The internal environment of a high-density automated storage and retrieval system (AS/RS) can be characterized as a grid map scenario and is highly complex, due to the narrow space for shuttle movement, restricted alleys, and the need for dynamic obstacle avoidance involving goods. Consequently, the design and optimization of the multi-shuttle scheduling system are crucial for enhancing the overall operational efficiency. Therefore, this study proposes a pioneering framework for a multi-shuttle cooperative scheduling system (MSCSS), which can serve as a widely referenced model for future research on single-shuttle path planning and multi-shuttle conflict avoidance in AS/RS. To address the issues of balancing efficiency with path length, reducing path conflicts in dense goods areas, and minimizing turning points in single-shuttle path planning, a fuzzy minority obstacle side A* (FMOSA*) algorithm is proposed, which combines minimal obstacle side considerations with turning costs. To resolve the problems caused by single avoidance rules, including poor handling of unexpected tasks and resulting shuttle idle time, an adaptive time window algorithm based on grid maps (GMATW) is proposed to improve shuttle and road utilization. Finally, the proposed MSCSS is experimentally validated in both real and simulated warehouse environments. Experimental results indicate that MSCSS not only effectively avoids densely packed goods areas and minimizes shuttle turning times but also ensures the shortest paths and enhances planning efficiency. Moreover, it comprehensively resolves various conflict types within the system, effectively handles unexpected tasks, and reduces idle time for the shuttles. The proposed scheduling system architecture addresses the cooperative scheduling of four-way shuttles in complex environments and offers insights for the development of efficient scheduling systems in high-density automated storage and retrieval systems.