Adaptive behaviors in multi-agent source localization using passive sensing. (December 2016)

• Record Type: Journal Article
• Authors: Shaukat, Mansoor; Chitre, Mandar
• Is Part Of: Adaptive behavior. Volume 24:Number 6(2016)
• Page Start: 446
• Page End: 463
• Publication Date: 2016-12
• Subjects: Swarm intelligence -- multi-agent systems -- collective behavior -- cooperative source localization -- autonomous robots; Animal behavior -- Periodicals; Animals -- Adaptation -- Periodicals; Adaptability (Psychology) -- Periodicals; Adaptation, Psychological -- Periodicals; Artificial intelligence -- Periodicals; 591.5
• DOI: 10.1177/1059712316664120
• Languages: English
• ISSNs: 1741-2633

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.