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.

High-density 3D warehousing is the future cornerstone of modern logistics storage. It aims to efficiently manage and store various types of goods by utilizing 3D space and automation technology. The accurate and fast docking algorithm of the four-way shuttles, as a core method of carrying the goods in high-density 3D warehousing, has become an increasingly important technical challenge. Inaccurate docking will result in a failure to change direction, while long docking time will affect the operation efficiency of the four-way shuttle. To overcome these obstacles, this paper presents an accurate and rapid docking algorithm for four-way shuttles. Firstly, the deceleration and jerk of a four-way shuttle in the braking stage are initialized according to the motion parameter set calculated by the docking motion model. Then, the four-way shuttle starts to move until the stop signal has been detected. If the system fails to detect the stop signal, the distance compensation is needed to ensure that the four-way shuttle can arrive at the stop point. Finally, the four-way shuttle stops immediately by way of amplifying the deceleration when reaching the stop point. The result shows that the accuracy of rapid docking is superior to that of direct docking. Compared with crawling docking, rapid docking reduces the braking time by 3.99s and stops at a speed lower than the crawling speed. The rapid docking algorithm not only enhances the throughput of high-density 3D warehousing but also improves the service life of four-way shuttles.