Motion Planning of an Autonomous Underwater Vehicle via the Integrated Design of Detection, Communication and Control
Abstract
Dear Editor, This letter studies the motion planning issue for an autonomous underwater vehicle (AUV) in obstacle environment. We propose a novel integrated detection-communication waveform that enables simultaneous obstacle detection and self-localization. Then, a multi-pseudo Q-learning-based algorithm is designed to drive AUV to avoid obstacles and reach its destination. Major merits lie in two aspects: 1) The integrated design can improve spectrum efficiency and save energy consumption; 2) The multi-pseudo Q-learning-based algorithm can enhance exploration capability and avoid local optimum. To the best of our knowledge, it is the first integrated solution that simultaneously solves detection, communication and control for AUV.
Fields of Study & Subjects
Underwater Vehicles and Communication Systems
Robotic Path Planning Algorithms
Distributed Control Multi-Agent Systems
Publication details
- Journal / source
- IEEE/CAA Journal of Automatica Sinica
- Publisher
- Institute of Electrical and Electronics Engineers (IEEE)
- Volume
- 13
- Issue
- 1
- Pages
- 218–220
- Publication date
- 1 January 2026