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cs.RO2025
Towards Bio-inspired Heuristically Accelerated Reinforcement Learning for Adaptive Underwater Multi-Agents Behaviour
Antoine Vivien, Thomas Chaffre, Matthew Stephenson +4
This paper describes the problem of coordination of an autonomous Multi-Agent System which aims to solve the coverage planning problem in a complex environment. The considered appl…
cs.RO2025
Wake-Informed 3D Path Planning for Autonomous Underwater Vehicles Using A* and Neural Network Approximations
Zachary Cooper-Baldock, Stephen Turnock, Karl Sammut
Autonomous Underwater Vehicles (AUVs) encounter significant energy, control and navigation challenges in complex underwater environments, particularly during close-proximity operat…