A Control of Collision and Deadlock Avoidance for Automated Guided Vehicles with a Fault-Tolerance Capability

Abstract

Based on a novel discrete-event zone-control model, in our previous papers [1,2], we presented a time-efficient traffic control for automated guided vehicle (AGV) systems to exclude inter-vehicle collisions and system deadlocks, together with a case study on container terminals. The traffic control allows each vehicle in an AGV system to freely choose its routes for any finite sequence of zone-tozone transportation tasks and the routes can be constructed in an online fashion. In this paper, we extended our previous results with two practical goals: (1) to increase the utilization of the workspace area by reducing the minimally allowed area of each zone; (2) to avoid vehicle collisions and deadlocks with the occurrence of vehicle breakdowns. To achieve the first goal, we include one extra vehicle event that allows each vehicle to probe further ahead while it is moving on the guide-path. This leads to an extension of our previous discrete-event model and traffic control rules, which are presented in the first part of the paper. The second part of the paper concerns the second goal, for which an emergency traffic control scheme is designed as supplementary to the normal traffic control rules. As in our previous papers, the improved model and traffic control are applied to a simulation of quayside container transshipment at container terminals; our simulation results are compared with those from two interesting works in the literature.

Control of Automated Guided Vehicles Without Collision by Quantum Annealer and Digital Devices

“…Notice that the DA can solve the QUBO problem with a large number of binary variable compared to D-Wave 2000Q. In the present study, the maximum number of binary variables in the QUBO problem is 60, which is the product of the number of the AGVs (10) and the number of candidates of routes (6). Thus, the number of the binary variables is quite small.…”

Modeling and verification of contingency resolution strategies for multi-robot missions using temporal logic

“…The probability of i 0 u civilian vessels ð0 i 0 u i u Þ still intruding the region is clearly i u i 0 u p i u res . For i u ¼ 2, we consider region R 1 where two civilian vessels were reported and so have the following transition rule for the contingency variable "contingency_type_A [1]." Thus, we must code up similar rules for all possible values of i u and regions of interest, and this is automated using MATLAB.…”

“…Multi-robot systems are increasingly being used to automate complex missions. [1][2][3][4][5][6][7] Many such missions are collections of spatially separated tasks that are executed by multi-robot teams in parallel. Generally, these missions may encounter unexpected situations that can halt or alter mission tasks.…”

Case study: evaluation of the automation of material handling with mobile robots

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