Area exploration with a swarm of UAVs combining deterministic chaotic ant colony mobility with position MPC.

Rosalie, Martin; Dentier, Jan E.; Danoy, Grégoire; Bouvry, Pascal; Kannan, Somasundar; Olivares-Mendez, Miguel A.; Voos, Holger

Abstract

The recent advances in Unmanned Aerial Vehicles (UAVs) technology permit to develop new usages for them. One of the current challenges is to operate UAVs as an autonomous swarm. In this domain we already proposed a new mobility model using Ant Colony Algorithms combined with chaotic dynamics (CACOC) to enhance the coverage of an area by a swarm of UAVs. In this paper we propose to consider this mobility model as waypoints for real UAVs. A control model of the UAVs is deployed to test the efficiency of the coverage of an area by the swarm. We have tested our approach in a realistic robotics simulator (V-Rep) which is connected with ROS. We compare the performance in terms of coverage using several metrics to ensure that this mobility model is efficient for real UAVs.

Citation

ROSALIE, M., DENTLER, J.E., DANOY, G., BOUVRY, P., KANNAN, S., OLIVARES-MENDEZ, M.A. and VOOS, H. 2017. Area exploration with a swarm of UAVs combining deterministic chaotic ant colony mobility with position MPC. In Proceedings of 2017 International conference on unmanned aircraft systems (ICUAS 2017), 13-16 June 2017, Miami, USA. Piscataway: IEEE [online], pages 1392-1397. Available from: https://doi.org/10.1109/ICUAS.2017.7991418

• Presentation Conference Type: Conference Paper (published)
• Conference Name: 2017 International conference on unmanned aircraft systems (ICUAS 2017)
• Start Date: Jun 13, 2017
• End Date: Jun 16, 2017
• Acceptance Date: Apr 14, 2017
• Online Publication Date: Jun 16, 2017
• Publication Date: Jul 27, 2017
• Deposit Date: Oct 31, 2022
• Publicly Available Date: Oct 31, 2022
• Publisher: Institute of Electrical and Electronics Engineers (IEEE)
• Peer Reviewed: Peer Reviewed
• Pages: 1392-1397
• ISBN: 9781509044962
• DOI: https://doi.org/10.1109/ICUAS.2017.7991418
• Keywords: Measurement; Heuristic algorithms; Trajectory; Ant colony optimization; Dynamics; Analytical models; Robot sensing systems
• Public URL: https://rgu-repository.worktribe.com/output/1279791