3 citations · 10 across the 15 of their papers we have counts for
6 papers · 1 filter
Goal-Conditioned Data Augmentation for Offline Reinforcement Learning
Xingshuai Huang, Di Wu, Benoit Boulet
Offline reinforcement learning (RL) enables policy learning from pre-collected offline datasets, relaxing the need to interact directly with the environment. However, limited by th…
Robot Policy Learning with Temporal Optimal Transport Reward
Yuwei Fu, Haichao Zhang, Di Wu +2
Reward specification is one of the most tricky problems in Reinforcement Learning, which usually requires tedious hand engineering in practice. One promising approach to tackle thi…
Trajectory Prediction for Autonomous Driving using Agent-Interaction Graph Embedding
Jilan Samiuddin, Benoit Boulet, Di Wu
Trajectory prediction module in an autonomous driving system is crucial for the decision-making and safety of the autonomous agent car and its surroundings. This work presents a no…
An Online Self-learning Graph-based Lateral Controller for Self-Driving Cars
Jilan Samiuddin, Benoit Boulet, Di Wu
The hype around self-driving cars has been growing over the past years and has sparked much research. Several modules in self-driving cars are thoroughly investigated to ensure saf…
FuRL: Visual-Language Models as Fuzzy Rewards for Reinforcement Learning
Yuwei Fu, Haichao Zhang, Di Wu +2
In this work, we investigate how to leverage pre-trained visual-language models (VLM) for online Reinforcement Learning (RL). In particular, we focus on sparse reward tasks with pr…
An Online Spatial-Temporal Graph Trajectory Planner for Autonomous Vehicles
Jilan Samiuddin, Benoit Boulet, Di Wu
The autonomous driving industry is expected to grow by over 20 times in the coming decade and, thus, motivate researchers to delve into it. The primary focus of their research is t…