9 citations · 18 across the 24 of their papers we have counts for
10 papers · 1 filter
XPRESS: X-Band Radar Place Recognition via Elliptical Scan Shaping
Hyesu Jang, Wooseong Yang, Ayoung Kim +2
X-band radar serves as the primary sensor on maritime vessels, however, its application in autonomous navigation has been limited due to low sensor resolution and insufficient info…
GaRLILEO: Gravity-aligned Radar-Leg-Inertial Enhanced Odometry
Chiyun Noh, Sangwoo Jung, Hanjun Kim +3
Deployment of legged robots for navigating challenging terrains (e.g., stairs, slopes, and unstructured environments) has gained increasing preference over wheel-based platforms. I…
SHeRLoc: Synchronized Heterogeneous Radar Place Recognition for Cross-Modal Localization
Hanjun Kim, Minwoo Jung, Wooseong Yang +1
Despite the growing adoption of radar in robotics, the majority of research has been confined to homogeneous sensor types, overlooking the integration and cross-modality challenges…
The City that Never Settles: Simulation-based LiDAR Dataset for Long-Term Place Recognition Under Extreme Structural Changes
Hyunho Song, Dongjae Lee, Seunghun Oh +2
Large-scale construction and demolition significantly challenge long-term place recognition (PR) by drastically reshaping urban and suburban environments. Existing datasets predomi…
ImLPR: Image-based LiDAR Place Recognition using Vision Foundation Models
Minwoo Jung, Lanke Frank Tarimo Fu, Maurice Fallon +1
LiDAR Place Recognition (LPR) is a key component in robotic localization, enabling robots to align current scans with prior maps of their environment. While Visual Place Recognitio…
Ephemerality meets LiDAR-based Lifelong Mapping
Hyeonjae Gil, Dongjae Lee, Giseop Kim +1
Lifelong mapping is crucial for the long-term deployment of robots in dynamic environments. In this paper, we present ELite, an ephemerality-aided LiDAR-based lifelong mapping fram…
Ground-Optimized 4D Radar-Inertial Odometry via Continuous Velocity Integration using Gaussian Process
Wooseong Yang, Hyesu Jang, Ayoung Kim
Radar ensures robust sensing capabilities in adverse weather conditions, yet challenges remain due to its high inherent noise level. Existing radar odometry has overcome these chal…
GaRLIO: Gravity enhanced Radar-LiDAR-Inertial Odometry
Chiyun Noh, Wooseong Yang, Minwoo Jung +2
Recently, gravity has been highlighted as a crucial constraint for state estimation to alleviate potential vertical drift. Existing online gravity estimation methods rely on pose e…
HeRCULES: Heterogeneous Radar Dataset in Complex Urban Environment for Multi-session Radar SLAM
Hanjun Kim, Minwoo Jung, Chiyun Noh +5
Recently, radars have been widely featured in robotics for their robustness in challenging weather conditions. Two commonly used radar types are spinning radars and phased-array ra…
HeLiOS: Heterogeneous LiDAR Place Recognition via Overlap-based Learning and Local Spherical Transformer
Minwoo Jung, Sangwoo Jung, Hyeonjae Gil +1
LiDAR place recognition is a crucial module in localization that matches the current location with previously observed environments. Most existing approaches in LiDAR place recogni…