4 papers · 1 filter
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…
CROSS: A Mixture-of-Experts Reinforcement Learning Framework for Generalizable Large-Scale Traffic Signal Control
Xibei Chen, Yifeng Zhang, Yuxiang Xiao +3
Recent advances in robotics, automation, and artificial intelligence have enabled urban traffic systems to operate with increasing autonomy towards future smart cities, powered in…
Real-Time Communication-Aware Ride-Sharing Route Planning for Urban Air Mobility: A Multi-Source Hybrid Attention Reinforcement Learning Approach
Yuejiao Xie, Maonan Wang, Di Zhou +2
Urban Air Mobility (UAM) systems are rapidly emerging as promising solutions to alleviate urban congestion, with path planning becoming a key focus area. Unlike ground transportati…
CL-CoTNav: Closed-Loop Hierarchical Chain-of-Thought for Zero-Shot Object-Goal Navigation with Vision-Language Models
Yuxin Cai, Xiangkun He, Maonan Wang +3
Visual Object Goal Navigation (ObjectNav) requires a robot to locate a target object in an unseen environment using egocentric observations. However, decision-making policies often…