12 papers
eKalibr-Inertial: Continuous-Time Spatiotemporal Calibration for Event-Based Visual-Inertial Systems
Shuolong Chen, Xingxing Li, Liu Yuan
The bioinspired event camera, distinguished by its exceptional temporal resolution, high dynamic range, and low power consumption, has been extensively studied in recent years for…
MASt3R-Fusion: Integrating Feed-Forward Visual Model with IMU, GNSS for High-Functionality SLAM
Yuxuan Zhou, Xingxing Li, Shengyu Li +3
Visual SLAM is a cornerstone technique in robotics, autonomous driving and extended reality (XR), yet classical systems often struggle with low-texture environments, scale ambiguit…
S3MOT: Monocular 3D Object Tracking with Selective State Space Model
Zhuohao Yan, Shaoquan Feng, Xingxing Li +3
Accurate and reliable multi-object tracking (MOT) in 3D space is essential for advancing robotics and computer vision applications. However, it remains a significant challenge in m…
eKalibr-Stereo: Continuous-Time Spatiotemporal Calibration for Event-Based Stereo Visual Systems
Shuolong Chen, Xingxing Li, Liu Yuan
The bioinspired event camera, distinguished by its exceptional temporal resolution, high dynamic range, and low power consumption, has been extensively studied in recent years for…
eKalibr: Dynamic Intrinsic Calibration for Event Cameras From First Principles of Events
Shuolong Chen, Xingxing Li, Liu Yuan +1
The bio-inspired event camera has garnered extensive research attention in recent years, owing to its significant potential derived from its high dynamic range and low latency char…
SF-Loc: A Visual Mapping and Geo-Localization System based on Sparse Visual Structure Frames
Yuxuan Zhou, Xingxing Li, Shengyu Li +3
For high-level geo-spatial applications and intelligent robotics, accurate global pose information is of crucial importance. Map-aided localization is a universal approach to overc…
iKalibr-RGBD: Partially-Specialized Target-Free Visual-Inertial Spatiotemporal Calibration For RGBDs via Continuous-Time Velocity Estimation
Shuolong Chen, Xingxing Li, Shengyu Li +1
Visual-inertial systems have been widely studied and applied in the last two decades (from the early 2000s to the present), mainly due to their low cost and power consumption, smal…
Equivariant Filter for Tightly Coupled LiDAR-Inertial Odometry
Anbo Tao, Yarong Luo, Chunxi Xia +2
Pose estimation is a crucial problem in simultaneous localization and mapping (SLAM). However, developing a robust and consistent state estimator remains a significant challenge, a…
RIs-Calib: An Open-Source Spatiotemporal Calibrator for Multiple 3D Radars and IMUs Based on Continuous-Time Estimation
Shuolong Chen, Xingxing Li, Shengyu Li +2
Aided inertial navigation system (INS), typically consisting of an inertial measurement unit (IMU) and an exteroceptive sensor, has been widely accepted as a feasible solution for…
iKalibr: Unified Targetless Spatiotemporal Calibration for Resilient Integrated Inertial Systems
Shuolong Chen, Xingxing Li, Shengyu Li +2
The integrated inertial system, typically integrating an IMU and an exteroceptive sensor such as radar, LiDAR, and camera, has been widely accepted and applied in modern robotic ap…
DBA-Fusion: Tightly Integrating Deep Dense Visual Bundle Adjustment with Multiple Sensors for Large-Scale Localization and Mapping
Yuxuan Zhou, Xingxing Li, Shengyu Li +3
Visual simultaneous localization and mapping (VSLAM) has broad applications, with state-of-the-art methods leveraging deep neural networks for better robustness and applicability.…
Ground-VIO: Monocular Visual-Inertial Odometry with Online Calibration of Camera-Ground Geometric Parameters
Yuxuan Zhou, Xingxing Li, Shengyu Li +2
Monocular visual-inertial odometry (VIO) is a low-cost solution to provide high-accuracy, low-drifting pose estimation. However, it has been meeting challenges in vehicular scenari…