Complete, Scalable, and Robust Prioritized Planning for Multi-Robot Ordered Storage and Retrieval at Maximum Capacity
Researchers have developed a planning algorithm for multiple robots to efficiently store and retrieve items in high-density warehouses. The algorithm prioritizes tasks and coordinates the movements of multiple robots to maximize storage capacity and minimize retrieval time. It achieves near-linear improvement in efficiency with an increasing number of robots, even at full storage density. The approach also accounts for potential uncertainty in departure sequences without sign
Researchers have developed a planning algorithm for multiple robots to efficiently store and retrieve items in high-density warehouses. The algorithm prioritizes tasks and coordinates the movements of multiple robots to maximize storage capacity and minimize retrieval time. It achieves near-linear improvement in efficiency with an increasing number of robots, even at full storage density. The approach also accounts for potential uncertainty in departure sequences without significantly impacting execution times.
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Why it matters: This work matters because it addresses a key challenge in automated warehouses: balancing storage density and retrieval throughput. Efficient planning algorithms like this one can help optimize warehouse operations and improve the overall performance of robotic systems.
Source: https://arxiv.org/abs/2608.07734
This article was originally published at: https://arxiv.org/abs/2608.07734