33 citations · 38 across the 7 of their papers we have counts for
7 papers
OmniNav: Robust Long-Horizon Target Navigation in Dynamic Environments
Yujie Tang, Meiling Wang, Jinhao Jiang +4
Long-horizon target navigation requires a robot to sustain task execution across evolving observations, decisions, and physical interactions. This requires three coupled capabiliti…
DINO-CoDT: Multi-class Collaborative Detection and Tracking with Vision Foundation Models
Xunjie He, Christina Dao Wen Lee, Meiling Wang +4
Collaborative perception plays a crucial role in enhancing environmental understanding by expanding the perceptual range and improving robustness against sensor failures, which pri…
OpenIN: Open-Vocabulary Instance-Oriented Navigation in Dynamic Domestic Environments
Yujie Tang, Meiling Wang, Yinan Deng +3
In daily domestic settings, frequently used objects like cups often have unfixed positions and multiple instances within the same category, and their carriers frequently change as…
OpenObject-NAV: Open-Vocabulary Object-Oriented Navigation Based on Dynamic Carrier-Relationship Scene Graph
Yujie Tang, Meiling Wang, Yinan Deng +3
In everyday life, frequently used objects like cups often have unfixed positions and multiple instances within the same category, and their carriers frequently change as well. As a…
Human Demonstrations are Generalizable Knowledge for Robots
Te Cui, Tianxing Zhou, Zicai Peng +6
Learning from human demonstrations is an emerging trend for designing intelligent robotic systems. However, previous methods typically regard videos as instructions, simply dividin…
PointGPT: Auto-regressively Generative Pre-training from Point Clouds
Guangyan Chen, Meiling Wang, Yi Yang +3
Large language models (LLMs) based on the generative pre-training transformer (GPT) have demonstrated remarkable effectiveness across a diverse range of downstream tasks. Inspired…
Full Transformer Framework for Robust Point Cloud Registration with Deep Information Interaction
Guangyan Chen, Meiling Wang, Yufeng Yue +2
Recent Transformer-based methods have achieved advanced performance in point cloud registration by utilizing advantages of the Transformer in order-invariance and modeling dependen…