10 papers
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…
SidewalkBench: Benchmarking Visual Navigation on Urban Sidewalks
Zhizheng Liu, Honglin He, Vivek Alumootil +4
Urban sidewalk navigation presents significant challenges due to complex structural layouts, dynamic pedestrian behaviors, and long distances. While recent visual navigation models…
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…
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…
AURA: Multimodal Shared Autonomy for Real-World Urban Navigation
Yukai Ma, Honglin He, Selina Song +2
Long-horizon navigation in complex urban environments relies heavily on continuous human operation, which leads to fatigue, reduced efficiency, and safety concerns. Shared autonomy…