Publications (6)
L3MVN: Leveraging Large Language Models for Visual Target Navigation
Bangguo Yu, Hamidreza Kasaei, Ming Cao
Visual target navigation in unknown environments is a crucial problem in robotics. Despite extensive investigation of classical and learning-based approaches in the past, robots la…
Co-NavGPT: Multi-Robot Cooperative Visual Semantic Navigation Using Vision Language Models
Bangguo Yu, Qihao Yuan, Kailai Li +2
Visual target navigation is a critical capability for autonomous robots operating in unknown environments, particularly in human-robot interaction scenarios. While classical and le…
Frontier Semantic Exploration for Visual Target Navigation
Bangguo Yu, Hamidreza Kasaei, Ming Cao
This work focuses on the problem of visual target navigation, which is very important for autonomous robots as it is closely related to high-level tasks. To find a special object i…
Fairness risk and its privacy-enabled solution in AI-driven robotic applications
Le Liu, Bangguo Yu, Nynke Vellinga +1
Complex decision-making by autonomous machines and algorithms could underpin the foundations of future society. Generative AI is emerging as a powerful engine for such transitions.…
VLN-Game: Vision-Language Equilibrium Search for Zero-Shot Semantic Navigation
Bangguo Yu, Yuzhen Liu, Lei Han +3
Following human instructions to explore and search for a specified target in an unfamiliar environment is a crucial skill for mobile service robots. Most of the previous works on o…
PANav: Toward Privacy-Aware Robot Navigation via Vision-Language Models
Bangguo Yu, Hamidreza Kasaei, Ming Cao
Navigating robots discreetly in human work environments while considering the possible privacy implications of robotic tasks presents significant challenges. Such scenarios are inc…