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Uninterrupted path planning system for Multi-USV sampling mission in a cluttered ocean environment

MahmoudZadeh, S., Abbasi, A., Yazdani, A., Wang, H.ORCID: 0000-0003-2789-9530 and Liu, Y. (2022) Uninterrupted path planning system for Multi-USV sampling mission in a cluttered ocean environment. Ocean Engineering, 254 . Art. 111328.

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This paper presents an uninterrupted collision-free path planning system that facilitates the operational performance of multiple unmanned surface vehicles (USVs) in an ocean sampling mission. The proposed uninterrupted path planning system is developed based on the integration of a novel B-Spline data frame and particle swarm optimization (PSO)-based solver engine. The new B-spline data framing structure provides smart sampling of the candidate spots without needing full stop for completing the sampling tasks. This enables the USVs to encircle the area smoothly while simultaneously correcting the heading angle toward the next spot and preventing sharp changes in the vehicle's heading. Then, the optimization engine generates optimal, smooth, and constraint-aware path curves for multiple USVs to conduct the sampling mission from start point to the rendezvous point. The path generated incorporates controllability over the vehicles' velocity profile to prevent experiencing zero velocity and frequent stop/start switching of the controller. To achieve faster convergence of the optimization routine, a suitable search space decomposition scheme is proposed. Extensive simulation studies emulating a realistic ocean sampling mission are conducted to examine the feasibility and effectiveness of the proposed path planning system. This encapsulates modelling a realistic maritime environment of Indonesian Archipelago in Banda Sea including ocean waves, obstacles, and no-fly zones and introducing several performance indices to benchmark the path planning system performance. This process is accompanied by a comparative study of the proposed path planning system with a well-known state-of-the art piecewise, rapidly exploring random tree (RRT), and differential evolution-based path planning algorithms. The results of the simulation confirm the suitability and robustness of the proposed path planning system for the uninterrupted ocean sampling missions.

Item Type: Journal Article
Murdoch Affiliation(s): Engineering and Energy
Publisher: Elsevier
Copyright: © 2022 Elsevier Ltd.
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