Decentralized Task Assignment for Multi-item Pickup and Delivery in Logistic Scenarios

Abstract

The Multi-Robot Pickup and Delivery problem has received significant attention from the research community. We focus on such problem and propose a multi-item variant, where robots can pick up multiple items at once and deliver them to their destinations in a single travel. We propose a distributed algorithm based on a Token-Passing approach, where robots handles by themselves the allocation of tasks and generates conflict-free paths requiring weaker assumptions in comparison to previous approaches. We evaluate our approach on two maps, one representing the ICE laboratory, a facility for Industry 4.0 located in Verona. Our approach produces solutions comparable in quality to those produced by a centralized approach and reduces computation times significantly. We also show a synchronization technique to the robots' movements, still based on Token-Passing. This guarantees the absence of collisions in spite of unexpected delays in path execution.