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Open AccessArticle

Intermittent Information-Driven Multi-Agent Area-Restricted Search

by Branko Ristic 1,*,† and Alex Skvortsov 2,†
1
School of Engineering, RMIT University, Melbourne, VIC 3000, Australia
2
Maritime Division, Defence Science and Technology Group, Fishermans Bend, VIC 3207, Australia
*
Author to whom correspondence should be addressed.
These authors contributed equally to this work.
Entropy 2020, 22(6), 635; https://doi.org/10.3390/e22060635
Received: 25 May 2020 / Revised: 2 June 2020 / Accepted: 4 June 2020 / Published: 8 June 2020
(This article belongs to the Section Information Theory, Probability and Statistics)
The problem is a two-dimensional area-restricted search for a target using a coordinated team of autonomous mobile sensing platforms (agents). Sensing is characterised by a range-dependent probability of detection, with a non-zero probability of false alarms. The context is underwater surveillance using a swarm of amphibious drones equipped with active sonars. The paper develops an intermittent information-driven search strategy, which alternates between two phases: the fast and non-receptive displacement phase (called the ballistic phase) with a slow displacement and sensing phase (called the diffusive phase). The proposed multi-agent search strategy is carried out in a decentralised manner, which means that all computations (estimation and motion control) are done locally. Coordination of agents is achieved by exchanging the data with the neighbours only, in a manner which does not require global knowledge of the communication network topology. View Full-Text
Keywords: autonomous search; infotaxis; multi-agent system; decentralised control autonomous search; infotaxis; multi-agent system; decentralised control
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Figure 1

  • Externally hosted supplementary file 1
    Doi: 10.5281/zenodo.3842299
    Description: The movie is a visual demonstration of a search for a target.
MDPI and ACS Style

Ristic, B.; Skvortsov, A. Intermittent Information-Driven Multi-Agent Area-Restricted Search. Entropy 2020, 22, 635.

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