3 papers
cs.RO2025
Language as Cost: Proactive Hazard Mapping using VLM for Robot Navigation
Mintaek Oh, Chan Kim, Seung-Woo Seo +1
Robots operating in human-centric or hazardous environments must proactively anticipate and mitigate dangers beyond basic obstacle detection. Traditional navigation systems often d…
cs.RO2025
LaMOuR: Leveraging Language Models for Out-of-Distribution Recovery in Reinforcement Learning
Chan Kim, Seung-Woo Seo, Seong-Woo Kim
Deep Reinforcement Learning (DRL) has demonstrated strong performance in robotic control but remains susceptible to out-of-distribution (OOD) states, often resulting in unreliable…
cs.RO2025
E2Map: Experience-and-Emotion Map for Self-Reflective Robot Navigation with Language Models
Chan Kim, Keonwoo Kim, Mintaek Oh +10
Large language models (LLMs) have shown significant potential in guiding embodied agents to execute language instructions across a range of tasks, including robotic manipulation an…