4 citations · 4 across the 5 of their papers we have counts for
6 papers
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…
PID Tuning using Cross-Entropy Deep Learning: a Lyapunov Stability Analysis
Hector Kohler, Benoit Clement, Thomas Chaffre +1
Underwater Unmanned Vehicles (UUVs) have to constantly compensate for the external disturbing forces acting on their body. Adaptive Control theory is commonly used there to grant t…
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…
Learning-based vs Model-free Adaptive Control of a MAV under Wind Gust
Thomas Chaffre, Julien Moras, Adrien Chan-Hon-Tong +4
Navigation problems under unknown varying conditions are among the most important and well-studied problems in the control field. Classic model-based adaptive control methods can b…
Sim-to-Real Transfer with Incremental Environment Complexity for Reinforcement Learning of Depth-Based Robot Navigation
Thomas Chaffre, Julien Moras, Adrien Chan-Hon-Tong +1
Transferring learning-based models to the real world remains one of the hardest problems in model-free control theory. Due to the cost of data collection on a real robot and the li…
Exploiting Physical Contacts for Robustness Improvement of a Dot-Painting Mission by a Micro Air Vehicle
Thomas Chaffre, Kevin Tudal, Sylvain Bertrand +1
In this paper we address the problem of dot painting on a wall by a quadrotor Micro Air Vehicle (MAV), using on-board low cost sensors (monocular camera and IMU) for localization.…