2 citations · 6 across the 20 of their papers we have counts for
10 papers · 1 filter
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 (…
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…
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…