Ashley Hill — accepted AI-conference papers

2021

Online velocity fluctuation of off-road wheeled mobile robots: A reinforcement learning approach

François Gauthier-Clerc, Ashley Hill, Jean Laneurit, Roland Lenain, Éric Lucet

ICRA 2021poster

During the off-road path following of a wheeled mobile robot in presence of poor grip conditions, the longitudinal velocity should be limited in order to maintain safe navigation with limited tracking errors, while at the same time being high enough to minimize travel time. Thus, this paper presents…

Cited by 9 Source ↗Scholar ↗

2020

Online gain setting method for path tracking using CMA-ES: Application to off-road mobile robot control

Ashley Hill, Jean Laneurit, Roland Lenain, Eric Lucet

IROS 2020poster

This paper proposes a new approach for online control law gains adaptation, through the use of neural networks and the Covariance Matrix Adaptation Evolution Strategy (CMA-ES) algorithm, in order to optimize the behavior of the robot with respect to an objective function. The neural network consider…

Cited by 9 Source ↗Scholar ↗