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

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.

On the Use of Agile Optimization for Efficient Energy Consumption in Smart Cities’s Transportation and Mobility

“…Real-world problems are characterized by uncertainty and dynamicity. Thus, these characteristics should be considered in problem formulation and an approach used to solve it [69].…”

Reactive Planning-Driven Approach to Online UAVs Mission Rerouting and Rescheduling

“…Research conducted in this area is devoted to the application of UAVs in emergency situations where they are used for transport of much-needed water, food, and medical supplies over hazardous (flooded) terrain. This is required due to climate change [29], necessitating the introduction of online UAV mission planning systems [20]. Other studies conducted in this area are devoted to various fields of application, e.g., reconnaissance and mapping [17], package delivery [3], delivery communication capabilities [22], healthcare [24,25], and so on.…”

“…The presented problem has been neither previously addressed nor solved in the existing literature [8][9][10]17,28,[31][32][33][34], thus it is not possible to compare it directly with existing methods. The novelty of the presented approach results from the extension of the declarative model used in our previous works, particularly in [6,7,20,21] by the addition of a function of the UAVs mission resistance to both changes in weather conditions and changes in the times and locations of deliveries. The condition that constitutes this extension allows the UAV's battery depletion to be foreseen in online mode before completing its mission, and thus it can be used in DSS-based planning of the UAVs' fleet mission.…”

“…In this context, the studies presented are a continuation of the previously published work focused on methods for planning UAVs' fleet missions online [20,21]. Previous research has focused on selected planning strategies for UAVs' fleet missions.…”

Proactive Mission Planning of Unmanned Aerial Vehicle Fleets Used in Offshore Wind Farm Maintenance

“…The function F (θ) (used in (59)) represents the forecasted weather conditions during the UAV flight mission [38,39]. A value of this function determines the maximal value of forecasted wind speed vw in direction θ.…”