Publications (18)
Evidential Semantic Mapping in Off-road Environments with Uncertainty-aware Bayesian Kernel Inference
Junyoung Kim, Junwon Seo, Jihong Min
Robotic mapping with Bayesian Kernel Inference (BKI) has shown promise in creating semantic maps by effectively leveraging local spatial information. However, existing semantic map…
Collage: Decomposable Rapid Prototyping for Information Extraction on Scientific PDFs
Sireesh Gururaja, Yueheng Zhang, Guannan Tang +6
Recent years in NLP have seen the continued development of domain-specific information extraction tools for scientific documents, alongside the release of increasingly multimodal p…
UFO: Uncertainty-aware LiDAR-image Fusion for Off-road Semantic Terrain Map Estimation
Ohn Kim, Junwon Seo, Seongyong Ahn +1
Autonomous off-road navigation requires an accurate semantic understanding of the environment, often converted into a bird's-eye view (BEV) representation for various downstream ta…
Safe Navigation in Unstructured Environments by Minimizing Uncertainty in Control and Perception
Junwon Seo, Jungwi Mun, Taekyung Kim
Uncertainty in control and perception poses challenges for autonomous vehicle navigation in unstructured environments, leading to navigation failures and potential vehicle damage.…
OW-Rep: Open World Object Detection with Instance Representation Learning
Sunoh Lee, Minsik Jeon, Jihong Min +1
Open World Object Detection(OWOD) addresses realistic scenarios where unseen object classes emerge, enabling detectors trained on known classes to detect unknown objects and increm…
E2-BKI: Evidential Ellipsoidal Bayesian Kernel Inference for Uncertainty-aware Gaussian Semantic Mapping
Junyoung Kim, Minsik Jeon, Jihong Min +2
Semantic mapping aims to construct a 3D semantic representation of the environment, providing essential knowledge for robots operating in complex outdoor settings. While Bayesian K…
Structured Extraction of Process Structure Properties Relationships in Materials Science
Amit K Verma, Zhisong Zhang, Junwon Seo +4
With the advent of large language models (LLMs), the vast unstructured text within millions of academic papers is increasingly accessible for materials discovery, although signific…
DA-RAW: Domain Adaptive Object Detection for Real-World Adverse Weather Conditions
Minsik Jeon, Junwon Seo, Jihong Min
Despite the success of deep learning-based object detection methods in recent years, it is still challenging to make the object detector reliable in adverse weather conditions such…
ScaTE: A Scalable Framework for Self-Supervised Traversability Estimation in Unstructured Environments
Junwon Seo, Taekyung Kim, Kiho Kwak +2
For the safe and successful navigation of autonomous vehicles in unstructured environments, the traversability of terrain should vary based on the driving capabilities of the vehic…
Self-Supervised 3D Traversability Estimation with Proxy Bank Guidance
Jihwan Bae, Junwon Seo, Taekyung Kim +3
Traversability estimation for mobile robots in off-road environments requires more than conventional semantic segmentation used in constrained environments like on-road conditions.…
In Search of a Data Transformation That Accelerates Neural Field Training
Junwon Seo, Sangyoon Lee, Kwang In Kim +1
Neural field is an emerging paradigm in data representation that trains a neural network to approximate the given signal. A key obstacle that prevents its widespread adoption is th…
Learning Off-Road Terrain Traversability with Self-Supervisions Only
Junwon Seo, Sungdae Sim, Inwook Shim
Estimating the traversability of terrain should be reliable and accurate in diverse conditions for autonomous driving in off-road environments. However, learning-based approaches o…
METAVerse: Meta-Learning Traversability Cost Map for Off-Road Navigation
Junwon Seo, Taekyung Kim, Seongyong Ahn +1
Autonomous navigation in off-road conditions requires an accurate estimation of terrain traversability. However, traversability estimation in unstructured environments is subject t…
StressDream: Steering Video World Models for Robust Policy Evaluation and Improvement
Junwon Seo, Sushant Veer, Ran Tian +6
Video world models (WMs) have shown promise for policy evaluation and improvement by imagining realistic future observations conditioned on ego-robot actions. While WMs can model d…
AnySafe: Adapting Latent Safety Filters at Runtime via Safety Constraint Parameterization in the Latent Space
Sankalp Agrawal, Junwon Seo, Kensuke Nakamura +2
Recent works have shown that foundational safe control methods, such as Hamilton-Jacobi (HJ) reachability analysis, can be applied in the latent space of world models. While this e…
Bridging Active Exploration and Uncertainty-Aware Deployment Using Probabilistic Ensemble Neural Network Dynamics
Taekyung Kim, Jungwi Mun, Junwon Seo +2
In recent years, learning-based control in robotics has gained significant attention due to its capability to address complex tasks in real-world environments. With the advances in…
Uncertainty-aware Semantic Mapping in Off-road Environments with Dempster-Shafer Theory of Evidence
Junyoung Kim, Junwon Seo
Semantic mapping with Bayesian Kernel Inference (BKI) has shown promise in providing a richer understanding of environments by effectively leveraging local spatial information. How…
Uncertainty-aware Latent Safety Filters for Avoiding Out-of-Distribution Failures
Junwon Seo, Kensuke Nakamura, Andrea Bajcsy
Recent advances in generative world models have enabled classical safe control methods, such as Hamilton-Jacobi (HJ) reachability, to generalize to complex robotic systems operatin…