14 citations · 22 across the 9 of their papers we have counts for
9 papers
Radar-Based NLoS Pedestrian Localization for Darting-Out Scenarios Near Parked Vehicles with Camera-Assisted Point Cloud Interpretation
Hee-Yeun Kim, Byeonggyu Park, Byonghyok Choi +6
The presence of Non-Line-of-Sight (NLoS) blind spots resulting from roadside parking in urban environments poses a significant challenge to road safety, particularly due to the sud…
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…
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…
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…
SeRO: Self-Supervised Reinforcement Learning for Recovery from Out-of-Distribution Situations
Chan Kim, Jaekyung Cho, Christophe Bobda +2
Robotic agents trained using reinforcement learning have the problem of taking unreliable actions in an out-of-distribution (OOD) state. Agents can easily become OOD in real-world…
Scaling of Class-wise Training Losses for Post-hoc Calibration
Seungjin Jung, Seungmo Seo, Yonghyun Jeong +1
The class-wise training losses often diverge as a result of the various levels of intra-class and inter-class appearance variation, and we find that the diverging class-wise traini…
Learning Multi-Task Transferable Rewards via Variational Inverse Reinforcement Learning
Se-Wook Yoo, Seung-Woo Seo
Many robotic tasks are composed of a lot of temporally correlated sub-tasks in a highly complex environment. It is important to discover situational intentions and proper actions b…
GIN: Graph-based Interaction-aware Constraint Policy Optimization for Autonomous Driving
Se-Wook Yoo, Chan Kim, Jin-Woo Choi +2
Applying reinforcement learning to autonomous driving entails particular challenges, primarily due to dynamically changing traffic flows. To address such challenges, it is necessar…
A Robotic Dating Coaching System Leveraging Online Communities Posts
Sihyeon Jo, Donghwi Jung, Keonwoo Kim +6
Can a robot be a personal dating coach? Even with the increasing amount of conversational data on the internet, the implementation of conversational robots remains a challenge. In…