| Literature DB >> 33681299 |
Daniel H Stolfi1, Matthias R Brust1, Grégoire Danoy1,2, Pascal Bouvry1,2.
Abstract
In this paper we present a surveillance system for early detection of escapers from a restricted area based on a new swarming mobility model called CROMM-MS (Chaotic Rössler Mobility Model for Multi-Swarms). CROMM-MS is designed for controlling the trajectories of heterogeneous multi-swarms of aerial, ground and marine unmanned vehicles with important features such as prioritising early detections and success rate. A new Competitive Coevolutionary Genetic Algorithm (CompCGA) is proposed to optimise the vehicles' parameters and escapers' evasion ability using a predator-prey approach. Our results show that CROMM-MS is not only viable for surveillance tasks but also that its results are competitive in regard to the state-of-the-art approaches.Entities:
Keywords: UAV; UGV; UMV; competitive coevolutionary genetic algorithm; mobility model; parameter optimisation; surveillance system; swarm robotics
Year: 2021 PMID: 33681299 PMCID: PMC7933201 DOI: 10.3389/frobt.2021.616950
Source DB: PubMed Journal: Front Robot AI ISSN: 2296-9144