An Ecological Approach to the Supervisory Control of UAV Swarms. Issue 4 (December 2014)

• Record Type: Journal Article
• Authors: Fuchs, Christian; Borst, Clark; de Croon, Guido C. H. E.; van Paassen, M. M. (René); Mulder, Max
• Is Part Of: International journal of micro air vehicles. Volume 6:Issue 4(2014)
• Page Start: 211
• Page End: 229
• Publication Date: 2014-12
• Subjects: Aerosonde (Drone aircraft) -- Periodicals; Aerospace engineering -- Periodicals; Aerosonde (Drone aircraft); Aerospace engineering; Periodicals; 623.746905
• DOI: 10.1260/1756-8293.6.4.211
• Languages: English
• ISSNs: 1756-8293

Abstract

Advances in miniaturized computer technology have made it possible for a single Unmanned Aerial Vehicle (UAV) to complete its mission autonomously. This also sparked interest in having swarms of UAVs that are cooperating as a team on a single mission. The level of automation involved in the control of UAV swarms will also change the role of the human operator. That is, instead of manually controlling the movements of the individual UAVs, the system operator will need to perform higher-level mission management tasks. However, most ground control stations are still tailored to the control of single UAVs by portraying raw flight status data on cockpit like instruments. In this paper, the ecological interface design paradigm is used to enhance the human-machine interface of a ground control station to support mission management for UAV swarms. As a case study, a generic ground-surveillance mission with four UAVs is envisioned. A preliminary evaluation study with 10 participants showed that the enhanced interface successfully enables operators to control a swarm of four UAVs and to resolve failures during mission execution. The results of the evaluation study showed that the interface enhancements promoted creative problem-solving activities to scenarios that could not have been solved by following a fixed procedure. However, the results also showed that the current interface still required control actions to be performed per single UAV, making it labor intensive to change mission parameters for swarms consisting of more than four UAVs.