7 papers
Goal2Pixel: Grounding Goals to Pixels for Vision-Language Navigation
Muyi Bao, Yuxin Cai, Hang Xu +7
Vision-language models (VLMs) have become a common foundation for vision-and-language navigation in continuous environments (VLN-CE). Yet most VLM-based methods cast navigation as…
IntentNav: Learning Spatial-Visual Object Navigation from Human Demonstrations
Yuxin Cai, Zongtai Li, Maonan Wang +9
Object navigation requires a robot to search for an unobserved target in an unknown environment by deciding where to explore next under partial observability. Effective search rese…
ImagiNav: Scalable Embodied Navigation via Generative Visual Prediction and Inverse Dynamics
Jie Chen, Yuxin Cai, Yizhuo Wang +5
Enabling robots to navigate open-world environments via natural language is critical for general-purpose autonomy. Yet, Vision-Language Navigation has relied on end-to-end policies…
SysNav: Multi-Level Systematic Cooperation Enables Real-World, Cross-Embodiment Object Navigation
Haokun Zhu, Zongtai Li, Zihan Liu +8
Object navigation (ObjectNav) in real-world environments is a complex problem that requires simultaneously addressing multiple challenges, including complex spatial structure, long…
Dual-Interaction-Aware Cooperative Control Strategy for Alleviating Mixed Traffic Congestion
Zhengxuan Liu, Yuxin Cai, Yijing Wang +3
As Intelligent Transportation System (ITS) develops, Connected and Automated Vehicles (CAVs) are expected to significantly reduce traffic congestion through cooperative strategies,…
COVLM-RL: Critical Object-Oriented Reasoning for Autonomous Driving Using VLM-Guided Reinforcement Learning
Lin Li, Yuxin Cai, Jianwu Fang +2
End-to-end autonomous driving frameworks face persistent challenges in generalization, training efficiency, and interpretability. While recent methods leverage Vision-Language Mode…