Title: An improved energy-aware and self-adaptive deployment method for autonomous underwater vehicles

Authors: Chunlai Peng; Tao Wang

Addresses: School of Electro-mechanical Engineering, Guangdong University of Technology, Guangzhou, China ' School of Automation, Guangdong University of Technology, Guangzhou, China

Abstract: Autonomous underwater vehicles (AUVs) are special mobile robots travelling underwater and perform dangerous tasks for human in the unknown mission area. However, it suffers from two critical issues when deploying AUVs. First, these algorithms do not optimise the travelling distances of AUVs and hence will lead to excessive energy depletion. Second, these deployment models rarely consider the available energy variations among AUVs in the task execution process. For this reason, an energy-aware and self-adaptive deployment method is presented for a group of AUVs taking collaborative tasks. First, the movement priority of AUVs is considered according to their positions during the deployment process. Second, an improved virtual force algorithm is proposed to obtain the initial deployment scheme. In addition, a self-adaptive deployment strategy is presented for redeploying the AUVs when the available energy of some AUVs has fallen below a certain threshold. Simulation results with ten AUVs demonstrate that the proposed method greatly decreases energy consumption (evaluated by the movement distances of AUVs) by about 30% than its traditional counterpart and it can redeploy AUVs adaptively and rapidly.

Keywords: autonomous underwater vehicles; AUVs; Voronoi diagram; energy-aware; self-adaptive deployment; unknown environment; distributed control; multi-robot.

DOI: 10.1504/IJMIC.2019.098005

International Journal of Modelling, Identification and Control, 2019 Vol.31 No.2, pp.182 - 192

Available online: 19 Feb 2019 *

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