UAV rendezvous based on Nash bargain

Abstract

Purpose The purpose of this paper is to find a solution for the unmanned aerial vehicle (UAV) rendezvous problem, which should be feasible, optimal and not time consuming. In the existing literatures, the UAV rendezvous problem is always presented as a matter of simultaneous arrival. They focus only on the time consistency. However, the arrival time of UAVs can vary according to the rendezvous position. The authors should determine the best rendezvous position with considering UAVs’ maneuver constraint, so that UAVs can construct a formation in a short time. Design/methodology/approach The authors present a decentralized method in which UAVs negotiate with each other for the best rendezvous positions by using Nash bargain. The authors analyzed the constraints of the rendezvous time and the UAV maneuver, and proposed an objective function that allows UAVs to get to their rendezvous positions as fast as possible. Bezier curve is adopted to generate smooth and feasible flight trajectories. During the rendezvous process, UAVs adjust their speed so that they can arrive at the rendezvous positions simultaneously. Findings The effectiveness of the proposed method is verified by simulation experiments. The proposed method can successfully and efficiently solve the UAV rendezvous problem. Originality/value As far as the authors know, it is the first time Nash bargain is used in the UAV rendezvous problem. The authors modified the Nash bargain method and make it distributed, so that it can be computed easily. The proposed method is much less consuming than ordinary Nash bargain method and ordinary swarm intelligence based methods. It also considers the UAV maneuver constraint, and can be applied online for its fast calculation speed. Simulations demonstrate the effectiveness of the proposed method.

Resource allocation based on overall equipment effectiveness using cooperative game

“…Omrani et al (2015) introduced an integrated approach to evaluate the efficiency of electricity distribution companies by combining the NBS, principal component analysis (PCA) and the DEA. Jiang et al (2018) presented a decentralized method in which unmanned aerial vehicles (UAVs) negotiate with each other for the best rendezvous positions by using the Nash bargain. Yu et al (2017) examined how the formation of international climate agreement (ICAs) and their mitigation efficiency are impacted by the use of the NBS.…”