Pinned Repositories
100-gdb-tips
A collection of gdb tips. 100 maybe just mean many here.
2D-3D-pose-tracking
Monocular Camera Localization in Prior LiDAR Maps with 2D-3D Line Correspondences
allan_variance_ros
ROS compatible tool to generate Allan Deviation plots
Apollo-Note
Note for Apollo 3.0 perception, prediction and planning modules
autonomous_exploration_development_environment
Leveraging system development and robot deployment for ground-based autonomous navigation and exploration.
Awesome-DeepLearning-500FAQ
深度学习500问，以问答形式对常用的概率知识、线性代数、机器学习、深度学习、计算机视觉等热点问题进行阐述，以帮助自己及有需要的读者。 全书分为18个章节，50余万字。声明：所有内容来自（仅供学习）：https://github.com/scutan90/DeepLearning-500-questions
BALM
cartographer_detailed_comments_ws
cartographer work space with detailed comments
ccm_slam
CCM-SLAM: Robust and Efficient Centralized Collaborative Monocular SLAM for Robotic Teams
convex-hkust
香港科技大学 凸优化
jsYangCode's Repositories
jsYangCode/100-gdb-tips
A collection of gdb tips. 100 maybe just mean many here.
jsYangCode/allan_variance_ros
ROS compatible tool to generate Allan Deviation plots
jsYangCode/cartographer_detailed_comments_ws
cartographer work space with detailed comments
jsYangCode/ccm_slam
CCM-SLAM: Robust and Efficient Centralized Collaborative Monocular SLAM for Robotic Teams
jsYangCode/covins
jsYangCode/ct-lio
CT-LIO: Continuous-Time LiDAR-Inertial Odometry
jsYangCode/DSP-SLAM
[3DV 2021] DSP-SLAM: Object Oriented SLAM with Deep Shape Priors
jsYangCode/EPro-PnP
[CVPR 2022 Oral, Best Student Paper] EPro-PnP: Generalized End-to-End Probabilistic Perspective-n-Points for Monocular Object Pose Estimation
jsYangCode/faster-lio
Faster-LIO: Lightweight Tightly Coupled Lidar-inertial Odometry using Parallel Sparse Incremental Voxels
jsYangCode/GVINS
Tightly coupled GNSS-Visual-Inertial system for locally smooth and globally consistent state estimation in complex environment.
jsYangCode/leetcode_101
LeetCode 101：和你一起你轻松刷题（C++）
jsYangCode/lili-om
LiLi-OM is a tightly-coupled, keyframe-based LiDAR-inertial odometry and mapping system for both solid-state-LiDAR and conventional LiDARs.
jsYangCode/LIMO-Velo
A real-time, direct and tightly-coupled LiDAR-Inertial SLAM for high velocities with spinning LiDARs
jsYangCode/LIO-Livox
A Robust LiDAR-Inertial Odometry for Livox LiDAR
jsYangCode/liosam
jsYangCode/Livox-Localization
A simple localization framework that can re-localize in one point-cloud map.
jsYangCode/Livox-Mapping
An all-in-one and ready-to-use LiDAR-inertial odometry system for Livox LiDAR
jsYangCode/LVI-SAM
LVI-SAM: Tightly-coupled Lidar-Visual-Inertial Odometry via Smoothing and Mapping
jsYangCode/lvio_fusion
Lvio-Fusion: A Self-adaptive Multi-sensor Fusion SLAM Framework Using Actor-critic Method (IROS 2021)
jsYangCode/MULLS
MULLS: Versatile LiDAR SLAM via Multi-metric Linear Least Square [ICRA '21]
jsYangCode/ORB_SLAM3
ORB-SLAM3: An Accurate Open-Source Library for Visual, Visual-Inertial and Multi-Map SLAM
jsYangCode/PL-SLAM
PL-SLAM: The method is implemented in《PL-SLAM:Real-time Monocular Visual SLAM with Points and Lines》
jsYangCode/r2live
R2LIVE is a robust, real-time tightly-coupled multi-sensor fusion framework, which fuses the measurement from the LiDAR, inertial sensor, visual camera to achieve robust, accurate state estimation.
jsYangCode/range-mcl
Range Image-based LiDAR Localization for Autonomous Vehicles Using Mesh Maps (chen2021icra)
jsYangCode/rpg_svo_pro_open
jsYangCode/sensor-fusion-for-localization-and-mapping
深蓝学院 多传感器定位融合第四期 学习笔记
jsYangCode/tandem
[CoRL 21'] TANDEM: Tracking and Dense Mapping in Real-time using Deep Multi-view Stereo
jsYangCode/VIW-Fusion
Visual-inertial-wheel fusion odometry, better performance in scenes with drastic changes in light
jsYangCode/xmind
jsYangCode/ZhangZhengYou
张正友标定法的数学原理以及python源码实现（详细）