157 citations · 221 across the 12 of their papers we have counts for
14 papers
Generalizing deep reinforcement learning across cable-driven parallel robot configurations with actuator-level policies
Abir Bouaouda, Mohamed Boutayeb, François Charpillet +2
Cable-driven parallel robots (CDPRs) present diverse configurations and complex control challenges, which can be addressed by deep reinforcement learning (DRL) by learning their no…
Gradient based Bilevel for Inverse Optimal Control, a Riemannian approach
Ahmed-Manaf Dahmani, Vincent Bonnet, David Daney +1
Inverse Optimal Control (IOC) aims to recover the cost function that explains observed trajectories as solutions of an optimal control problem. Classical IOC formulations rely on b…
PreTR: Spatio-Temporal Non-Autoregressive Trajectory Prediction Transformer
Lina Achaji, Thierno Barry, Thibault Fouqueray +3
Nowadays, our mobility systems are evolving into the era of intelligent vehicles that aim to improve road safety. Due to their vulnerability, pedestrians are the users who will ben…
Is attention to bounding boxes all you need for pedestrian action prediction?
Lina Achaji, Julien Moreau, Thibault Fouqueray +2
The human driver is no longer the only one concerned with the complexity of the driving scenarios. Autonomous vehicles (AV) are similarly becoming involved in the process. Nowadays…
A dataset for complex activity recognition withmicro and macro activities in a cooking scenario
Paula Lago, Shingo Takeda, Sayeda Shamma Alia +4
Complex activity recognition can benefit from understanding the steps that compose them. Current datasets, however, are annotated with one label only, hindering research in this di…
A Variational Time Series Feature Extractor for Action Prediction
Maxime Chaveroche, Adrien Malaisé, Francis Colas +2
We propose a Variational Time Series Feature Extractor (VTSFE), inspired by the VAE-DMP model of Chen et al., to be used for action recognition and prediction. Our method is based…