Design of genetic algorithms for topology control of unmanned vehicles. (20th October 2010)

• Record Type: Journal Article
• Authors: Sahin, Cem Safak; Urrea, Elkin; Uyar, M. Umit; Conner, Michael; Bertoli, Giorgio; Pizzo, Christian
• Is Part Of: International journal of applied decision sciences. Volume 3:Number 3(2010)
• Page Start: 221
• Page End: 238
• Publication Date: 2010-10-20
• Subjects: genetic algorithms -- GAs -- artificial intelligence -- mobile ad hoc networks -- MANETs -- bio-inspired algorithms -- unmanned vehicles -- UVs -- topology control -- mobile networks -- decentralised control -- military applications -- simulation -- unknown terrain; Decision making -- Periodicals; Management science -- Periodicals; 658.403005
• Languages: English
• ISSNs: 1755-8077

Abstract

We present genetic algorithms (GAs) as a decentralised topology control mechanism distributed among active running software agents to achieve a uniform spread of terrestrial unmanned vehicles (UVs) over an unknown geographical area. This problem becomes more challenging under the harsh and bandwidth limited conditions of military applications. Using only local neighbour information, a GA guides each UV to select a 'fitter' speed and direction among exponentially large number of choices, converging towards a uniform node distribution. In an observed occurrence of a threat situation during a mission where UVs are to spread uniformly over an unknown terrain, if the number of UVs change with time (e.g., losing assets due to hostile forces), the remaining units should reposition themselves to compensate the loss in area coverage. Our simulation software results show that GAs can be an effective tool for providing a robust solution for topology control of UVs in military applications.