1 citations · 1 across the 7 of their papers we have counts for
4 papers · 1 filter
Grounded World Model for Semantically Generalizable Planning
Quanyi Li, Lan Feng, Haonan Zhang +4
In Model Predictive Control (MPC), world models predict the future outcomes of various action proposals, which are then scored to guide the selection of the optimal action. For vis…
OpenNav: Open-World Navigation with Multimodal Large Language Models
Mingfeng Yuan, Letian Wang, Steven L. Waslander
Pre-trained large language models (LLMs) have demonstrated strong common-sense reasoning abilities, making them promising for robotic navigation and planning tasks. However, despit…
Trends in Motion Prediction Toward Deployable and Generalizable Autonomy: A Revisit and Perspectives
Letian Wang, Marc-Antoine Lavoie, Sandro Papais +13
Motion prediction, recently popularized as world models, refers to the anticipation of future agent states or scene evolution, which is rooted in human cognition, bridging percepti…
Accelerating Reinforcement Learning for Autonomous Driving using Task-Agnostic and Ego-Centric Motion Skills
Tong Zhou, Letian Wang, Ruobing Chen +2
Efficient and effective exploration in continuous space is a central problem in applying reinforcement learning (RL) to autonomous driving. Skills learned from expert demonstration…