activity
20172026
most citedCoco-LIC: Continuous-Time Tightly-Coupled LiDAR-Inertial-Camera Odometry using Non-Uniform B-spline

36 citations · 107 across the 29 of their papers we have counts for

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18 papers · 1 filter

cs.RO2026

FlowHOI: Flow-based Semantics-Grounded Generation of Hand-Object Interactions for Dexterous Robot Manipulation

Huajian Zeng, Lingyun Chen, Jiaqi Yang +4

Recent vision-language-action (VLA) models can generate plausible end-effector motions, yet they often fail in long-horizon, contact-rich tasks because the underlying hand-object i…

cs.RO2025

SimGenHOI: Physically Realistic Whole-Body Humanoid-Object Interaction via Generative Modeling and Reinforcement Learning

Yuhang Lin, Yijia Xie, Jiahong Xie +5

Generating physically realistic humanoid-object interactions (HOI) is a fundamental challenge in robotics. Existing HOI generation approaches, such as diffusion-based models, often…

cs.RO2025

Gaussian-LIC2: LiDAR-Inertial-Camera Gaussian Splatting SLAM

Xiaolei Lang, Jiajun Lv, Kai Tang +5

This paper presents the first photo-realistic LiDAR-Inertial-Camera Gaussian Splatting SLAM system that simultaneously addresses visual quality, geometric accuracy, and real-time p…

cs.RO2024★ 3 cited

Gaussian-LIC: Real-Time Photo-Realistic SLAM with Gaussian Splatting and LiDAR-Inertial-Camera Fusion

Xiaolei Lang, Laijian Li, Chenming Wu +5

In this paper, we present a real-time photo-realistic SLAM method based on marrying Gaussian Splatting with LiDAR-Inertial-Camera SLAM. Most existing radiance-field-based SLAM syst…

cs.RO2023★ 36 cited

Coco-LIC: Continuous-Time Tightly-Coupled LiDAR-Inertial-Camera Odometry using Non-Uniform B-spline

Xiaolei Lang, Chao Chen, Kai Tang +4

In this paper, we propose an efficient continuous-time LiDAR-Inertial-Camera Odometry, utilizing non-uniform B-splines to tightly couple measurements from the LiDAR, IMU, and camer…

cs.RO2023

Continuous-Time Fixed-Lag Smoothing for LiDAR-Inertial-Camera SLAM

Jiajun Lv, Xiaolei Lang, Jinhong Xu +3

Localization and mapping with heterogeneous multi-sensor fusion have been prevalent in recent years. To adequately fuse multi-modal sensor measurements received at different time i…

cs.RO2022★ 1 cited

Ctrl-VIO: Continuous-Time Visual-Inertial Odometry for Rolling Shutter Cameras

Xiaolei Lang, Jiajun Lv, Jianxin Huang +3

In this paper, we propose a probabilistic continuous-time visual-inertial odometry (VIO) for rolling shutter cameras. The continuous-time trajectory formulation naturally facilitat…

cs.RO2022★ 1 cited

Visual-Inertial SLAM with Tightly-Coupled Dropout-Tolerant GPS Fusion

Simon Boche, Xingxing Zuo, Simon Schaefer +1

Robotic applications are continuously striving towards higher levels of autonomy. To achieve that goal, a highly robust and accurate state estimation is indispensable. Combining vi…

cs.RO2022

Observability-Aware Intrinsic and Extrinsic Calibration of LiDAR-IMU Systems

Jiajun Lv, Xingxing Zuo, Kewei Hu +3

Accurate and reliable sensor calibration is essential to fuse LiDAR and inertial measurements, which are usually available in robotic applications. In this paper, we propose a nove…

cs.RO2022★ 3 cited

Symmetry and Uncertainty-Aware Object SLAM for 6DoF Object Pose Estimation

Nathaniel Merrill, Yuliang Guo, Xingxing Zuo +5

We propose a keypoint-based object-level SLAM framework that can provide globally consistent 6DoF pose estimates for symmetric and asymmetric objects alike. To the best of our know…

cs.RO2022★ 6 cited

Online Self-Calibration for Visual-Inertial Navigation Systems: Models, Analysis and Degeneracy

Yulin Yang, Patrick Geneva, Xingxing Zuo +1

In this paper, we study in-depth the problem of online self-calibration for robust and accurate visual-inertial state estimation. In particular, we first perform a complete observa…

cs.RO2021★ 1 cited

CLINS: Continuous-Time Trajectory Estimation for LiDAR-Inertial System

Jiajun Lv, Kewei Hu, Jinhong Xu +3

In this paper, we propose a highly accurate continuous-time trajectory estimation framework dedicated to SLAM (Simultaneous Localization and Mapping) applications, which enables fu…

cs.RO2020★ 5 cited

LIC-Fusion 2.0: LiDAR-Inertial-Camera Odometry with Sliding-Window Plane-Feature Tracking

Xingxing Zuo, Yulin Yang, Patrick Geneva +4

Multi-sensor fusion of multi-modal measurements from commodity inertial, visual and LiDAR sensors to provide robust and accurate 6DOF pose estimation holds great potential in robot…

cs.RO2020★ 5 cited

Targetless Calibration of LiDAR-IMU System Based on Continuous-time Batch Estimation

Jiajun Lv, Jinhong Xu, Kewei Hu +2

Sensor calibration is the fundamental block for a multi-sensor fusion system. This paper presents an accurate and repeatable LiDAR-IMU calibration method (termed LI-Calib), to cali…

cs.RO2020

Visual-based Kinematics and Pose Estimation for Skid-Steering Robots

Xingxing Zuo, Mingming Zhang, Mengmeng Wang +4

To build commercial robots, skid-steering mechanical design is of increased popularity due to its manufacturing simplicity and unique mechanism. However, these also cause significa…

cs.RO2019★ 4 cited

Visual-Inertial Localization for Skid-Steering Robots with Kinematic Constraints

Xingxing Zuo, Mingming Zhang, Yiming Chen +3

While visual localization or SLAM has witnessed great progress in past decades, when deploying it on a mobile robot in practice, few works have explicitly considered the kinematic…

cs.RO2019★ 10 cited

LIC-Fusion: LiDAR-Inertial-Camera Odometry

Xingxing Zuo, Patrick Geneva, Woosik Lee +2

This paper presents a tightly-coupled multi-sensor fusion algorithm termed LiDAR-inertial-camera fusion (LIC-Fusion), which efficiently fuses IMU measurements, sparse visual featur…

cs.RO2019★ 9 cited

Pose Estimation for Ground Robots: On Manifold Representation, Integration, Re-Parameterization, and Optimization

Mingming Zhang, Xingxing Zuo, Yiming Chen +2

In this paper, we focus on motion estimation dedicated for non-holonomic ground robots, by probabilistically fusing measurements from the wheel odometer and exteroceptive sensors.…