Task-Allocation and Control of a Ground Robots Collective for Warehouse Automation
In the last years, there have been several attempts to deploy Autonomous Guided Vehicles (AGVs) to automate the operation of warehouse environments. The implementation of AGVs has numerous advantages over conventional warehouse automation systems in terms of cost and scalability. In this work, we present the development of a test-bed platform for the utilization of an AGV collective to a warehouse automation system. The system architecture has plug-and-play algorithmic design which makes it extremely modular. In this system, small-scale robotic forklifts are used to transport an arbitrary number of circular pallets to predefined locations. The forklift robots are able to move in the arena without colliding each other due to the implementation of a centralized deconfliction algorithm. A task allocation algorithm prevents the forklift drives from being trapped by a fence of pallets. The performance of the proposed system is validated by both simulation and experimental results.