46 citations · 182 across the 24 of their papers we have counts for
24 papers
DIFTA-3D: Depth-Consistent Instance-Level Feature Transfer and Adaptation of DINOv3 for 3D Detection
Linman Wang, ZiFei Zhang, Chunran Zheng +2
RGB-D 3D instance detectors benefit from visual semantics, but the task-specific Faster R-CNN/ResNet branch used by IIFNet3D couples feature extraction to a separately trained 2D d…
SparseNav: Instruction-conditioned Sparse Semantic Perception for Training-Free Vision-Language Navigation
Quanhua Chen, Juhan Kang, Runfeng Lin +5
Map-based vision-language navigation (VLN) relies on persistent spatial representations to connect language understanding with geometric planning. However, acquiring semantics beyo…
From Routes to Steps: Separating Semantic Progress from Local Execution in Vision-and-Language Navigation
Xiangyun Huang, Xiangchen Wang, Runfeng Lin +5
Vision-and-Language Navigation (VLN) requires an agent to follow a route-level instruction by executing its constituent steps from egocentric visual observations. Existing VLM-base…
Mesh-Learner: Texturing Mesh with Spherical Harmonics
Yunfei Wan, Jianheng Liu, Chunran Zheng +2
In this paper, we present a 3D reconstruction and rendering framework termed Mesh-Learner that is natively compatible with traditional rasterization pipelines. It integrates mesh a…
An End-to-End Learning-Based Multi-Sensor Fusion for Autonomous Vehicle Localization
Changhong Lin, Jiarong Lin, Zhiqiang Sui +4
Multi-sensor fusion is essential for autonomous vehicle localization, as it is capable of integrating data from various sources for enhanced accuracy and reliability. The accuracy…
GS-SDF: LiDAR-Augmented Gaussian Splatting and Neural SDF for Geometrically Consistent Rendering and Reconstruction
Jianheng Liu, Yunfei Wan, Bowen Wang +3
Digital twins are fundamental to the development of autonomous driving and embodied artificial intelligence. However, achieving high-granularity surface reconstruction and high-fid…
Voxel-SLAM: A Complete, Accurate, and Versatile LiDAR-Inertial SLAM System
Zheng Liu, Haotian Li, Chongjian Yuan +7
In this work, we present Voxel-SLAM: a complete, accurate, and versatile LiDAR-inertial SLAM system that fully utilizes short-term, mid-term, long-term, and multi-map data associat…
LVBA: LiDAR-Visual Bundle Adjustment for RGB Point Cloud Mapping
Rundong Li, Xiyuan Liu, Haotian Li +4
Point cloud maps with accurate color are crucial in robotics and mapping applications. Existing approaches for producing RGB-colorized maps are primarily based on real-time localiz…
FAST-LIVO2: Fast, Direct LiDAR-Inertial-Visual Odometry
Chunran Zheng, Wei Xu, Zuhao Zou +11
This paper proposes FAST-LIVO2: a fast, direct LiDAR-inertial-visual odometry framework to achieve accurate and robust state estimation in SLAM tasks and provide great potential in…
Visual Localization in 3D Maps: Comparing Point Cloud, Mesh, and NeRF Representations
Lintong Zhang, Yifu Tao, Jiarong Lin +2
Recent advances in mapping techniques have enabled the creation of highly accurate dense 3D maps during robotic missions, such as point clouds, meshes, or NeRF-based representation…
Occupancy Grid Mapping without Ray-Casting for High-resolution LiDAR Sensors
Yixi Cai, Fanze Kong, Yunfan Ren +3
Occupancy mapping is a fundamental component of robotic systems to reason about the unknown and known regions of the environment. This article presents an efficient occupancy mappi…
ImMesh: An Immediate LiDAR Localization and Meshing Framework
Jiarong Lin, Chongjiang Yuan, Yixi Cai +5
In this paper, we propose a novel LiDAR(-inertial) odometry and mapping framework to achieve the goal of simultaneous localization and meshing in real-time. This proposed framework…
MARSIM: A light-weight point-realistic simulator for LiDAR-based UAVs
Fanze Kong, Xiyuan Liu, Benxu Tang +6
The emergence of low-cost, small form factor and light-weight solid-state LiDAR sensors have brought new opportunities for autonomous unmanned aerial vehicles (UAVs) by advancing n…
RLIVE++: A Robust, Real-time, Radiance reconstruction package with a tightly-coupled LiDAR-Inertial-Visual state Estimator
Jiarong Lin, Fu Zhang
Simultaneous localization and mapping (SLAM) are crucial for autonomous robots (e.g., self-driving cars, autonomous drones), 3D mapping systems, and AR/VR applications. This work p…
STD: Stable Triangle Descriptor for 3D place recognition
Chongjian Yuan, Jiarong Lin, Zuhao Zou +2
In this work, we present a novel global descriptor termed stable triangle descriptor (STD) for 3D place recognition. For a triangle, its shape is uniquely determined by the length…
Fast 3D Sparse Topological Skeleton Graph Generation for Mobile Robot Global Planning
Xinyi Chen, Boyu Zhou, Jiarong Lin +3
In recent years, mobile robots are becoming ambitious and deployed in large-scale scenarios. Serving as a high-level understanding of environments, a sparse skeleton graph is benef…
R3LIVE: A Robust, Real-time, RGB-colored, LiDAR-Inertial-Visual tightly-coupled state Estimation and mapping package
Jiarong Lin, Fu Zhang
In this letter, we propose a novel LiDAR-Inertial-Visual sensor fusion framework termed R3LIVE, which takes advantage of measurement of LiDAR, inertial, and visual sensors to achie…
FAST-LIO2: Fast Direct LiDAR-inertial Odometry
Wei Xu, Yixi Cai, Dongjiao He +2
This paper presents FAST-LIO2: a fast, robust, and versatile LiDAR-inertial odometry framework. Building on a highly efficient tightly-coupled iterated Kalman filter, FAST-LIO2 has…
R2LIVE: A Robust, Real-time, LiDAR-Inertial-Visual tightly-coupled state Estimator and mapping
Jiarong Lin, Chunran Zheng, Wei Xu +1
In this letter, we propose a robust, real-time tightly-coupled multi-sensor fusion framework, which fuses measurement from LiDAR, inertial sensor, and visual camera to achieve robu…
A decentralized framework for simultaneous calibration, localization and mapping with multiple LiDARs
Jiarong Lin, Xiyuan Liu, Fu Zhang
LiDAR is playing a more and more essential role in autonomous driving vehicles for objection detection, self localization and mapping. A single LiDAR frequently suffers from hardwa…
A fast, complete, point cloud based loop closure for LiDAR odometry and mapping
Jiarong Lin, Fu Zhang
This paper presents a loop closure method to correct the long-term drift in LiDAR odometry and mapping (LOAM). Our proposed method computes the 2D histogram of keyframes, a local m…
Loam_livox: A fast, robust, high-precision LiDAR odometry and mapping package for LiDARs of small FoV
Jiarong Lin, Fu Zhang
LiDAR odometry and mapping (LOAM) has been playing an important role in autonomous vehicles, due to its ability to simultaneously localize the robot's pose and build high-precision…
Full Attitude Control of an Efficient Quadrotor Tail-sitter VTOL UAV with Flexible Modes
Wei Xu, Haowei Gu, Youming Qing +2
In this paper, we present a full attitude control of an efficient quadrotor tail-sitter VTOL UAV with flexible modes. This control system is working in all flight modes without any…
Flying through a narrow gap using neural network: an end-to-end planning and control approach
Jiarong Lin, Luqi Wang, Fei Gao +2
In this paper, we investigate the problem of enabling a drone to fly through a tilted narrow gap, without a traditional planning and control pipeline. To this end, we propose an en…