most citedSeRO: Self-Supervised Reinforcement Learning for Recovery from Out-of-Distribution Situations

2 citations · 2 across the 4 of their papers we have counts for

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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.RO2023

LoRCoN-LO: Long-term Recurrent Convolutional Network-based LiDAR Odometry

Donghwi Jung, Jae-Kyung Cho, Younghwa Jung +2

We propose a deep learning-based LiDAR odometry estimation method called LoRCoN-LO that utilizes the long-term recurrent convolutional network (LRCN) structure. The LRCN layer is a…