6 papers
GR-LIO: A Local Ground-Aware LiDAR-Inertial Odometry System Using Body-to-Ground Height
Zhixin Zhang, Yang Song, Liang Zhao +3
LiDAR-inertial odometry (LIO) is widely used for state estimation in ground-based autonomous mobile robots. However, the geometric constraints provided by the local ground surface…
Dynamic-LIVO: A Dynamic-Aware LiDAR-Inertial-Visual Odometry System Using Spatio-Temporal Normals
Zhixin Zhang, Samuel Ahiwe, Matthew Hale +2
This paper proposes Dynamic-LIVO, a dynamic-aware LiDAR-Inertial-Visual Odometry (LIVO) system for robust state estimation and static colored mapping in dynamic environments. Dynam…
FLARE-BO: Fused Luminance and Adaptive Retinex Enhancement via Bayesian Optimisation for Low-Light Robotic Vision
Nathan Shankar, Pawel Ladosz, Hujun Yin
Reliable visual perception under low illumination remains a core challenge for autonomous robotic systems, where degraded image quality directly compromises navigation, inspection,…
CLEAR-IR: Clarity-Enhanced Active Reconstruction of Infrared Imagery
Nathan Shankar, Pawel Ladosz, Marton Gonczy +1
This paper presents CLEAR-IR (Clarity Enhanced Active Reconstruction of Infrared Imagery), a novel framework for enabling robust robotic perception in dark environments using activ…
PL-VIWO2: A Lightweight, Fast and Robust Visual-Inertial-Wheel Odometry Using Points and Lines
Zhixin Zhang, Liang Zhao, Pawel Ladosz
Vision-based odometry has been widely adopted in autonomous driving owing to its low cost and lightweight setup; however, its performance often degrades in complex outdoor urban en…
PL-VIWO: A Lightweight and Robust Point-Line Monocular Visual Inertial Wheel Odometry
Zhixin Zhang, Wenzhi Bai, Liang Zhao +1
This paper presents a novel tightly coupled Filter-based monocular visual-inertial-wheel odometry (VIWO) system for ground robots, designed to deliver accurate and robust localizat…