An ETCEN-Based Motion Coordination Strategy Avoiding Active and Passive Deadlocks for Multi-AGV System

Abstract

In recent years, automated guided vehicles (AGV) are widely used to sort and transport parcels in logistics warehouses. The deployment of AGVs can improve storage efficiency and free human labour greatly. However, as the number of AGVs grows, the computational complexity and deadlock occurrence rate increase simultaneously, making it extremely difficult to coordinate AGVs’ movements in real time. In this paper, we first present a hierarchical motion coordination system based on event-triggered colored elementary net (ETCEN). The primary aim of the system is to coordinate AGVs in real time regardless of the system’s scale. Then, we describe deadlocks by the ETCEN model and classify them into two categories - active deadlocks and passive deadlocks. Active deadlocks are prevented dynamically by controlling the movements of AGVs, while passive deadlocks are resolved by an improved path planning strategy. The entire system relies on a two-layer architecture, thereby improving flexibility and scalability. The proposed algorithms are validated by simulations and applications. Experiment results demonstrated that our approach can coordinate multi-AGV systems, avoid collisions and prevent deadlocks effectively. Note to Practitioners—This paper was motivated by the problem of coordinating multi-AGV system in warehouses, especially the tricky problem of preventing deadlocks in large-scale applications. Existing approaches mainly focused on collision-avoiding strategies, while paying less attention to the deadlock-preventing problem. As a result, the feasibility of current deadlock prevention methods strongly depends on the topology of the environment, and the computation time will surge exponentially as the scale of AGVs grows. This paper suggests a general approach towards solving two types of deadlocks (active deadlocks and passive deadlocks) based on Petri net theory. In this paper, a multi-AGV coordination model is presented and described thoroughly. Then we use the model to prove our theories and introduce our collision-avoiding and deadlock-preventing strategies. A two-layer architecture is designed to support the expansion of AGV fleet, making our system highly scalable. Both experiments and applications suggest that this approach is feasible and effective. In future research, we will focus on further optimizing the coordination and routing algorithm to improve the system throughput.