title: Adaptive behaviors in multi-agent source localization using passive sensing.
abstract: In this paper, the role of adaptive group cohesion in a cooperative multi-agent source localization problem is investigated. A distributed source localization algorithm is presented for a homogeneous team of simple agents. An agent uses a single sensor to sense the gradient and two sensors to sense its neighbors. The algorithm is a set of individualistic and social behaviors where the individualistic behavior is as simple as an agent keeping its previous heading and is not self-sufficient in localizing the source. Source localization is achieved as an emergent property through agent's adaptive interactions with the neighbors and the environment. Given a single agent is incapable of localizing the source, maintaining team connectivity at all times is crucial. Two simple temporal sampling behaviors, intensity-based-adaptation and connectivity-based-adaptation, ensure an efficient localization strategy with minimal agent breakaways. The agent behaviors are simultaneously optimized using a two phase evolutionary optimization process. The optimized behaviors are estimated with analytical models and the resulting collective behavior is validated against the agent's sensor and actuator noise, strong multi-path interference due to environment variability, initialization distance sensitivity and loss of source signal.
authors.affiliation: Acoustics Research Laboratory, Tropical Marine Sciences Institute, Singapore.
authors.forename: Mansoor
authors.initials: M
authors.lastname: Shaukat
authors.affiliation: Acoustics Research Laboratory, Tropical Marine Sciences Institute, Singapore.
authors.forename: Mandar
authors.initials: M
authors.lastname: Chitre
keywords: Swarm intelligence; autonomous robots; collective behavior; cooperative source localization; multi-agent systems