Path planning for robotic mobile fulfillment systems

Abstract

This paper presents a collection of path planning algorithms for real-time movement of multiple robots across a Robotic Mobile Fullment System (RMFS). Robots are assigned to move storage units to pickers at working stations instead of requiring pickers to go to the storage area. Path planning algorithms aim to find paths for the robots to fulfill the requests without collisions or deadlocks. The state-of-the-art path planning algorithms, including WHCA*, FAR, BCP, OD&ID and CBS, were adapted to suit path planning in RMFS and integrated within a simulation tool to guide the robots from their starting points to their destinations during the storage and retrieval processes. Ten different layouts with a variety of numbers of robots, floors, pods, stations and the sizes of storage areas were considered in the simulation study. Performance metrics of throughput, path length and search time were monitored. Simulation results demonstrate the best algorithm based on each performance metric.

Biography

Prof. Lin Xie is an Assistant Professor in the Institute of Information Systems (IIS) at the Leuphana University of Lüneburg. She received her PhD (with distinction) in the department of Business Information Systems at the University of Paderborn in 2014. In 2010 and 2008, she graduated from the same university with a Master of Science and a Bachelor of Science in Business Information Systems.
The research areas of Lin Xie include operations research, optimization, simulation, decision support systems in various application contexts of business informatics. Areas of application include personnel deployment planning in public transport and hospitals, logistics (especially automated storage facilities).

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