2 citations · 2 across the 11 of their papers we have counts for
5 papers · 2 filters
UrbanVerse: Scaling Urban Simulation by Watching City-Tour Videos
Mingxuan Liu, Honglin He, Elisa Ricci +2
Urban embodied AI agents, ranging from delivery robots to quadrupeds, are increasingly populating our cities, navigating chaotic streets to provide last-mile connectivity. Training…
From Seeing to Experiencing: Scaling Navigation Foundation Models with Reinforcement Learning
Honglin He, Yukai Ma, Brad Squicciarini +2
Navigation foundation models trained on massive web-scale data enable agents to generalize across diverse environments and embodiments. However, these models, which are trained sol…
Towards Autonomous Micromobility through Scalable Urban Simulation
Wayne Wu, Honglin He, Chaoyuan Zhang +5
Micromobility, which utilizes lightweight mobile machines moving in urban public spaces, such as delivery robots and mobility scooters, emerges as a promising alternative to vehicu…
Vid2Sim: Realistic and Interactive Simulation from Video for Urban Navigation
Ziyang Xie, Zhizheng Liu, Zhenghao Peng +2
Sim-to-real gap has long posed a significant challenge for robot learning in simulation, preventing the deployment of learned models in the real world. Previous work has primarily…
Joint Optimization for 4D Human-Scene Reconstruction in the Wild
Zhizheng Liu, Joe Lin, Wayne Wu +1
Reconstructing human motion and its surrounding environment is crucial for understanding human-scene interaction and predicting human movements in the scene. While much progress ha…