2 citations · 6 across the 20 of their papers we have counts for
25 papers
ChairNav: Cross-Embodiment Pre-training and Personalization for Long-Horizon Wheelchair Navigation
Junhua Huang, Zhizheng Liu, Honglin He +2
Developing autonomous electric wheelchairs capable of long-horizon sidewalk navigation is critical for accessible personal mobility, yet existing approaches either focus on indoor…
Looking Back to Move Forward: Temporal Verification for Generative Robot Policies
Haoxuan Wang, Wayne Wu, Yan Yan +1
Generative policies have emerged as a promising paradigm for robot learning, combining expressive generative action modeling with scalable imitation learning from large demonstrati…
Cue the Flow: Steering Flow-Matching Policies for Open-World Delivery Manipulation
Haoxuan Wang, Griffin Galimi, Junhua Huang +4
Open-world goods delivery requires mobile manipulators to follow free-form user instructions and manipulate potentially novel objects. Existing dual-system approaches use high-leve…
Slow Brain, Fast Planner: Latency-Resilient VLM-Augmented Urban Navigation
Zhenghao "Mark'' Peng, Honglin He, Quanyi Li +2
Learning-based planners for sidewalk navigation can generate diverse candidate trajectories in real time, yet their scoring functions often fail to select the best trajectory in ch…
Monocular 3D Occupancy Perception for Robots on Sidewalks via Hybrid 2D-3D Learning
Yukai Ma, Joe Lin, Liu Liu +5
Sidewalks in the real world are crowded, cluttered, and less structured than roads, making 3D occupancy prediction a key ingredient for the safe navigation of mobile robots such as…
From Imitation to Alignment: Human-Preference Flow Policies for Long-Horizon Sidewalk Navigation
Honglin He, Zhizheng Liu, Yukai Ma +1
Autonomous long-horizon sidewalk navigation is essential for micro-mobility applications such as robotic food delivery and assistive electronic wheelchairs. Unlike autonomous drivi…
Learning Sidewalk Autopilot from Multi-Scale Imitation with Corrective Behavior Expansion
Honglin He, Yukai Ma, Brad Squicciarini +2
Sidewalk micromobility is a promising solution for last-mile transportation, but current learning-based control methods struggle in complex urban environments. Imitation learning (…
DiSCo: Diffusion Sequence Copilots for Shared Autonomy
Andy Wang, Xu Yan, Brandon McMahan +9
Shared autonomy combines human user and AI copilot actions to control complex systems such as robotic arms. When a task is challenging, requires high dimensional control, or is sub…
Predictive Preference Learning from Human Interventions
Haoyuan Cai, Zhenghao Peng, Bolei Zhou
Learning from human involvement aims to incorporate the human subject to monitor and correct agent behavior errors. Although most interactive imitation learning methods focus on co…
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…
Robot-Gated Interactive Imitation Learning with Adaptive Intervention Mechanism
Haoyuan Cai, Zhenghao Peng, Bolei Zhou
Interactive Imitation Learning (IIL) allows agents to acquire desired behaviors through human interventions, but current methods impose high cognitive demands on human supervisors.…
SceneStreamer: Continuous Scenario Generation as Next Token Group Prediction
Zhenghao Peng, Yuxin Liu, Bolei Zhou
Realistic and interactive traffic simulation is essential for training and evaluating autonomous driving systems. However, most existing data-driven simulation methods rely on stat…
Adv-BMT: Bidirectional Motion Transformer for Safety-Critical Traffic Scenario Generation
Yuxin Liu, Zhenghao Peng, Xuanhao Cui +1
Scenario-based testing is essential for validating the performance of autonomous driving (AD) systems. However, such testing is limited by the scarcity of long-tailed, safety-criti…
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…
Data-Efficient Learning from Human Interventions for Mobile Robots
Zhenghao Peng, Zhizheng Liu, Bolei Zhou
Mobile robots are essential in applications such as autonomous delivery and hospitality services. Applying learning-based methods to address mobile robot tasks has gained popularit…
Learning from Active Human Involvement through Proxy Value Propagation
Zhenghao Peng, Wenjie Mo, Chenda Duan +2
Learning from active human involvement enables the human subject to actively intervene and demonstrate to the AI agent during training. The interaction and corrective feedback from…
Embodied Scene Understanding for Vision Language Models via MetaVQA
Weizhen Wang, Chenda Duan, Zhenghao Peng +2
Vision Language Models (VLMs) demonstrate significant potential as embodied AI agents for various mobility applications. However, a standardized, closed-loop benchmark for evaluati…
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…
Learning to Generate Diverse Pedestrian Movements from Web Videos with Noisy Labels
Zhizheng Liu, Joe Lin, Wayne Wu +1
Understanding and modeling pedestrian movements in the real world is crucial for applications like motion forecasting and scene simulation. Many factors influence pedestrian moveme…
Shared Autonomy with IDA: Interventional Diffusion Assistance
Brandon J. McMahan, Zhenghao Peng, Bolei Zhou +1
The rapid development of artificial intelligence (AI) has unearthed the potential to assist humans in controlling advanced technologies. Shared autonomy (SA) facilitates control by…
MetaUrban: An Embodied AI Simulation Platform for Urban Micromobility
Wayne Wu, Honglin He, Jack He +5
Public urban spaces like streetscapes and plazas serve residents and accommodate social life in all its vibrant variations. Recent advances in Robotics and Embodied AI make public…
A Simple Framework Towards Vision-based Traffic Signal Control with Microscopic Simulation
Pan He, Quanyi Li, Xiaoyong Yuan +1
Traffic signal control (TSC) is crucial for reducing traffic congestion leading to smoother traffic flow, reduced idle time, and mitigated CO2 emissions. In this paper, we explore…