Projects with Machine Learning and Control

v.2021

This page is dedicated to the research activities concerning the Machine Learning and Control.

The listed projects are from a team from Lab-STICC and College of Science and Engineering at Flinders University

• Karl Sammut

• Paulo Santos,

• Gilles Le Chenadec

• Benoit Clement

Our main Industrial partnet is Naval Group with Eva Artusi, Estelle Chauveau and Gregory Bartoli.

A short presentation of current project is here.

Projects

• Katell Lagattu PhD

• Yoann Sola PhD

• Thomas Chaffre PhD

• Hector Kohler internship

Recent Publications

• Thomas Chaffre, Jonathan Wheare, Andrew Lammas, Paulo Santos, Gilles Le Chenadec, Karl Sammut, Es­telle Chauveau, and Benoit Clement (2022). Sim­to­real transfer of adaptive control parameters for improved robustness to sea current variations, under review.

• Thomas Chaffre, Paulo E. Santos, Gilles Le Chenadec, Estelle Chauveau, Karl Sammut, and Benoit Clement (2022). Learning Stochastic Adaptive Control using a Bio­Inspired Experience Replay Experience Replay.In TechRxiv.

• Hector Kohler, Benoit Clement, Thomas Chaffre, and Gilles Le Chenadec (2022). PID Tuning using Cross­Entropy DeepLearning: a Lyapunov Stability Analysis. In Proceedings of the 14th IFAC CAMS.

• Thomas Chaffre, Julien Moras, Adrien Chan­Hon­Tong, Julien Marzat, Karl Sammut, Gilles Le Chenadec, and Benoit Clement (2022). Learning­based vs Model­free Adaptive Control of a MAV under Wind Gust. In Informatics in Control, Automation and Robotics pp 362–385, LNEE, SPRINGER.

• Thomas Chaffre, Gilles Le Chenadec, Karl Sammut, Estelle Chauveau, and Benoit Clement (2021). Direct Adaptive Pole­Placement Controller using Deep Reinforcement Learning: Application to AUV Control. In Proceedings of the 13th IFAC Conference on Control Applications in Marine Systems, Robotics and Vehicles (CAMS).

• Thomas Chaffre, Julien Moras, Adrien Chan Hon Tong, and Julien Marzat (2020). Sim­to­Real Transfer with Incremental Environment Complexity for Reinforcement Learning of Depth­Based Robot Navigation., in Proceedings of the 16th ICINCO.

• T. Chaffre, G. Le Chenadec, K. Sammut, E. Chauveau, and B. Clement. Direct adaptive pole-placement controller using deep reinforcement learning: Application to auv. In 13th IFAC Conference on Control Application on Marine Systems, Germany, 2021. (doi)

• Y. Sola, T. Chaffre, K. Sammut, Gilles Le Chenadec, and B. Clement. Robust guidance and controlof autonomous underwater vehicles with deep reinforcement learning. In IEEE Oceans Conference, Singapore, 2020

• Y. Sola, G. Le Chenadec, K. Sammut and B. Clement. Auto-tuning PID controller based on machine learning algorithms for robust control of autonomous underwater vehicles. In IEEE Oceans Conference, Marseille, France, 2019.