36 citations · 44 across the 26 of their papers we have counts for
11 papers · 1 filter
SAGE-Nav: Leveraging LLM Planning and Alignment Fusion for Hierarchical Scene Graph-Guided Navigation
Hao Su, Yuehao Huang, Yukai Ma +2
Object-Goal Navigation (ObjNav) requires embodied agents to autonomously locate specified targets using only egocentric visual observations. Existing monolithic methods struggle wi…
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…
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…
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 (…
SimGenHOI: Physically Realistic Whole-Body Humanoid-Object Interaction via Generative Modeling and Reinforcement Learning
Yuhang Lin, Yijia Xie, Jiahong Xie +5
Generating physically realistic humanoid-object interactions (HOI) is a fundamental challenge in robotics. Existing HOI generation approaches, such as diffusion-based models, often…
DriveArena: A Closed-loop Generative Simulation Platform for Autonomous Driving
Xuemeng Yang, Licheng Wen, Yukai Ma +11
This paper presented DriveArena, the first high-fidelity closed-loop simulation system designed for driving agents navigating in real scenarios. DriveArena features a flexible, mod…
Continuously Learning, Adapting, and Improving: A Dual-Process Approach to Autonomous Driving
Jianbiao Mei, Yukai Ma, Xuemeng Yang +11
Autonomous driving has advanced significantly due to sensors, machine learning, and artificial intelligence improvements. However, prevailing methods struggle with intricate scenar…
Coco-LIC: Continuous-Time Tightly-Coupled LiDAR-Inertial-Camera Odometry using Non-Uniform B-spline
Xiaolei Lang, Chao Chen, Kai Tang +4
In this paper, we propose an efficient continuous-time LiDAR-Inertial-Camera Odometry, utilizing non-uniform B-splines to tightly couple measurements from the LiDAR, IMU, and camer…
Ctrl-VIO: Continuous-Time Visual-Inertial Odometry for Rolling Shutter Cameras
Xiaolei Lang, Jiajun Lv, Jianxin Huang +3
In this paper, we propose a probabilistic continuous-time visual-inertial odometry (VIO) for rolling shutter cameras. The continuous-time trajectory formulation naturally facilitat…