Heterogeneous Swarms for Maritime Dynamic Target Search and Tracking

Current strategies employed for maritime target search and tracking are primarily based on the use of agents following a predetermined path to perform a systematic sweep of a search area. Recently, dynamic Particle Swarm Optimization (PSO) algorithms have been used together with swarming multi-robot...

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Bibliographic Details
Main Authors: Kwa, Hian Lee (Author), Tokic, Grgur (Author), Bouffanais, Roland (Author), Yue, Dick KP (Author)
Format: Article
Language:English
Published: Institute of Electrical and Electronics Engineers (IEEE), 2022-01-27T13:50:31Z.
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Online Access:Get fulltext
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100 1 0 |a Kwa, Hian Lee  |e author 
700 1 0 |a Tokic, Grgur  |e author 
700 1 0 |a Bouffanais, Roland  |e author 
700 1 0 |a Yue, Dick KP  |e author 
245 0 0 |a Heterogeneous Swarms for Maritime Dynamic Target Search and Tracking 
260 |b Institute of Electrical and Electronics Engineers (IEEE),   |c 2022-01-27T13:50:31Z. 
856 |z Get fulltext  |u https://hdl.handle.net/1721.1/139763 
520 |a Current strategies employed for maritime target search and tracking are primarily based on the use of agents following a predetermined path to perform a systematic sweep of a search area. Recently, dynamic Particle Swarm Optimization (PSO) algorithms have been used together with swarming multi-robot systems (MRS), giving search and tracking solutions the added properties of robustness, scalability, and flexibility. Swarming MRS also give the end-user the opportunity to incrementally upgrade the robotic system, inevitably leading to the use of heterogeneous swarming MRS. However, such systems have not been well studied and incorporating upgraded agents into a swarm may result in degraded mission performances. In this paper, we propose a PSO-based strategy using a topological k-nearest neighbor graph with tunable exploration and exploitation dynamics with an adaptive repulsion parameter. This strategy is implemented within a simulated swarm of 50 agents with varying proportions of fast agents tracking a target represented by a fictitious binary function. Through these simulations, we are able to demonstrate an increase in the swarm's collective response level and target tracking performance by substituting in a proportion of fast buoys. 
546 |a en 
655 7 |a Article 
773 |t 10.1109/IEEECONF38699.2020.9389145 
773 |t Global Oceans 2020: Singapore - U.S. Gulf Coast