Abstract
This paper presents a novel approach for Multi-Robot Task Allocation (MRTA) that introduces priority policies on preemptive task scheduling and considers dependencies between tasks, and tolerates faults. The approach is referred to as Multi-Robot Preemptive Task Scheduling with Fault Recovery (MRPF). It considers the interaction between running processes and their tasks for management at each new event, prioritizing the more relevant tasks without idleness and latency. The benefit of this approach is the optimization of production in smart factories, where autonomous robots are being employed to improve efficiency and increase flexibility. The evaluation of MRPF is performed through experimentation in small-scale warehouse logistics, referred to as Augmented Reality to Enhanced Experimentation in Smart Warehouses (ARENA). An analysis of priority scheduling, task preemption, and fault recovery is presented to show the benefits of the proposed approach.
Highlights
For the problem of coalition formation and task allocation, we present a new approach to subgroup formation and cooperative accomplishment, which composes the complex logistic process
The Multi-Robot Preemptive Task Scheduling with Fault Recovery (MRPF) approach is focused on distribution during execution, managing
This paper presented MRPF, an approach to designing the distribution of multi-robots, taking into account robot restrictions, task constraints, job priority, and resource dependence
Summary
Vivian Cremer Kalempa 1,2, * , Luis Piardi 1,3 , Marcelo Limeira 1 and André Schneider de Oliveira 1. Research Center in Digitalization and Intelligent Robotics (CeDRI), Instituto Politécnico de Bragança (IPB), Campus de Santa Apolónia, 5300-253 Bragança, Portugal
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