Reactive UAV Fleet’s Mission Planning in Highly Dynamic and Unpredictable Environments

Grzegorz Radzki, Izabela Nielsen, Paulina Golińska-Dawson, Grzegorz Bocewicz and Zbigniew Banaszak
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Grzegorz Radzki: Faculty of Electronics and Computer Science, Koszalin University of Technology, 75-453 Koszalin, Poland
Izabela Nielsen: Department of Materials and Production, Aalborg University, 9220 Aalborg, Denmark
Paulina Golińska-Dawson: Faculty of Engineering Management, Poznan University of Technology, 60-965 Poznań, Poland
Grzegorz Bocewicz: Faculty of Electronics and Computer Science, Koszalin University of Technology, 75-453 Koszalin, Poland
Zbigniew Banaszak: Faculty of Electronics and Computer Science, Koszalin University of Technology, 75-453 Koszalin, Poland

Sustainability, 2021, vol. 13, issue 9, 1-23

Abstract: Unmanned aerial vehicles (UAVs) create an interesting alternative for establishing more sustainable urban freight deliveries. The substitution of traditional trucks in the last-mile distribution by a UAV fleet can contribute to urban sustainability by reducing air pollution and increasing urban freight efficiency. This paper presents a novel approach to the joint proactive and reactive planning of deliveries by a UAV fleet. We develop a receding horizon-based approach to reactive, online planning for the UAV fleet’s mission. We considered the delivery of goods to spatially dispersed customers over an assumed time horizon. Forecasted weather changes affect the energy consumption of UAVs and limit their range. Therefore, consideration should be given to plans for follow-up tasks, previously unmet needs, and predictions of disturbances over a moving time horizon. We propose a set of reaction rules that can be encountered during delivery in a highly dynamic and unpredictable environment. We implement a constraint programming paradigm, which is well suited to cope with the nonlinearity of the system’s characteristics. The proposed approach to online reactive UAV routing is evaluated in several instances. The computational experiments have shown that the developed model is capable of providing feasible plans for a UAV fleet’s mission that are robust to changes in weather and customer’s orders.

Keywords: reactive planning; vehicle routing problem; unmanned aerial vehicle fleet mission; declarative modeling (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2021
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

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