13 citations · 15 across the 10 of their papers we have counts for
10 papers
A Unified Causal-Origin Taxonomy of Distributional Shifts in Reinforcement Learning
Ardianto Wibowo, Paulo E Santos, Amer Baghdadi +3
Reinforcement learning (RL) systems often degrade when operating conditions differ from those previously encountered, reflecting distributional shifts in the underlying data-genera…
3D Underwater Path Planning via Generative Flow Field Surrogates
Zachary Cooper-Baldock, Paulo E. Santos, Russell S. A. Brinkworth +1
Autonomous underwater vehicle (AUV) launch and recovery (LAR) into the hull of an advancing host platform requires traversal of a complex, three-dimensional propeller wake whose hy…
WAKESET: A Large-Scale, High-Reynolds Number Flow Dataset for Machine Learning of Turbulent Wake Dynamics
Zachary Cooper-Baldock, Paulo E. Santos, Russell S. A. Brinkworth +1
Machine learning (ML) offers transformative potential for computational fluid dynamics (CFD), promising to accelerate simulations, improve turbulence modelling, and enable real-tim…
Mitigation of multi-path propagation artefacts in acoustic targets with adaptive cepstral filtering
Lucas C. F. Domingos, Russell S. A. Brinkworth, Paulo E. Santos +1
Passive acoustic sensing is a cost-effective solution for monitoring moving targets such as vessels and aircraft, but its performance is hindered by complex propagation effects lik…
Improving Underwater Acoustic Classification Through Learnable Gabor Filter Convolution and Attention Mechanisms
Lucas Cesar Ferreira Domingos, Russell Brinkworth, Paulo Eduardo Santos +1
Remotely detecting and classifying underwater acoustic targets is critical for environmental monitoring and defence. However, the complexity of ship-radiated and environmental nois…
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…
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…
A generalised novel loss function for computational fluid dynamics
Zachary Cooper-Baldock, Paulo E. Santos, Russell S. A. Brinkworth +1
Computational fluid dynamics (CFD) simulations are crucial in automotive, aerospace, maritime and medical applications, but are limited by the complexity, cost and computational re…
Hybrid Navigation Acceptability and Safety
Benoit Clement, Marie Dubromel, Paulo E. Santos +3
Autonomous vessels have emerged as a prominent and accepted solution, particularly in the naval defence sector. However, achieving full autonomy for marine vessels demands the deve…
Sim-to-Real Transfer of Adaptive Control Parameters for AUV Stabilization under Current Disturbance
Thomas Chaffre, Jonathan Wheare, Andrew Lammas +4
Learning-based adaptive control methods hold the premise of enabling autonomous agents to reduce the effect of process variations with minimal human intervention. However, its appl…