We present the Limited-range Online Routing Problem (LORP), which involves a team of Unmanned Aerial Vehicles (UAVs) with limited communication range that must autonomously coordinate to service task requests. We first show a general approach to cast this dynamic problem as a sequence of decentralized task allocation problems. Then we present two solutions both based on modeling the allocation task as a Markov Random Field to subsequently assess decisions by means of the decentralized Max-Sum algorithm. Our first solution assumes independence between requests, whereas our second solution also considers the UAVs' workloads. A thorough empirical evaluation shows that our workload-based solution consistently outperforms current state-of-the-art methods in a wide range of scenarios, lowering the average service time up to 16%. In the best-case scenario there is no gap between our decentralized solution and centralized techniques. In the worst-case scenario we manage to reduce by 25% the gap between current decentralized and centralized techniques. Thus, our solution becomes the method of choice for our problem.
@article{arxiv.1809.07863,
title = {Decentralized dynamic task allocation for UAVs with limited communication range},
author = {Marc Pujol-Gonzalez and Jesus Cerquides and Pedro Meseguer and Juan A. Rodriguez-Aguilar and Milind Tambe},
journal= {arXiv preprint arXiv:1809.07863},
year = {2018}
}