Robotics

Online Gain Tuning Using Neural Networks: A Comparative Study
This paper addresses the problem of adapting a control system to unseen conditions, specifically to the problem of trajectory tracking …
Ashley W.D. Hill, Jean Laneurit, Roland Lenain, Eric Lucet
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Online Gain Tuning Using Neural Networks: A Comparative Study
Online Tuning of Control Parameters for Off-Road Mobile Robots: Novel Deterministic and Neural Network-Based Approaches
This paper addresses the problem of the on-line adaptation of control parameters, dedicated to a path tracking problem in off-road …
Ashley W.D. Hill, Jean Laneurit, Roland Lenain, Eric Lucet
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A Novel Gradient Feature Importance Method for Neural Networks: An Application to Controller Gain Tuning for Mobile Robots
In the paper, a novel gradient-based feature importance method for neural networks is described. This method is compared to the …
Ashley W.D. Hill, Eric Lucet, Roland Lenain
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Online velocity fluctuation of off-road wheeled mobile robots: A reinforcement learning approach
During the off-road path following of a wheeled mobile robot in presence of poor grip conditions, the longitudinal velocity should be …
François Gauthier-Clerc, Ashley W.D. Hill, Jean Laneurit, Roland Lenain, Eric Lucet
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Online gain setting method for path tracking using CMA-ES: Application to off-road mobile robot control
This paper proposes a new approach for online control law gains adaptation, through the use of neural networks and the Covariance …
Ashley W.D. Hill, Jean Laneurit, Roland Lenain, Eric Lucet
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A new neural network feature importance method: Application to mobile robots controllers gain tuning
This paper proposes a new approach for feature importance of neural networks and subsequently a methodology to determine useful sensor …
Ashley W.D. Hill, Eric Lucet, Roland Lenain
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CES-IA Reinforcement Learning Class
The CES-IA Reinforcement learning class slides.
Apr 4, 2020 9:00 AM Paris, France
Ashley W.D. Hill
Slides
ICINCO presentation
The presentation of the 2019 ICINCO paper
Jul 29, 2019 12:00 PM Prague, Czech Republic
Ashley W.D. Hill
Slides
Neuroevolution with CMA-ES for real-time gain tuning of a car-like robot controller
This paper proposes a method for dynamically varying the gains of a mobile robot controller that takes into account, not only errors to …
Ashley W.D. Hill, Eric Lucet, Roland Lenain
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Decoupling feature extraction from policy learning: assessing benefits of state representation learning in goal based robotics
Scaling end-to-end reinforcement learning to control real robots from vision presents a series of challenges, in particular in terms of …
Antonin Raffin, Ashley W.D. Hill, René Traoré, Timothée Lesort, Natalia Díaz-Rodríguez, David Filliat
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