hp-ekko's starred repositories
Navigation-Learning
我的导航学习笔记,内容涵盖导航定位开源程序的源码解读 ( 包括:RTKLIB、GAMP、GINav、Ginan、PSINS、SoftGNSS、KF-GINS、ORB-SLAM3、GICI-Lib 等)、各种导航设备的使用方式、书籍讲义、博客翻译、开源项目梳理、常用网站记录、Linux/Vim/Git/ROS/VSCode 常用命令;本仓库会长期更新,分享出来,跟大家做个交流,也激励着自己坚持学下去;所有内容都可以随意转载,可用于任何目的,不必征求我的意见;如果您觉得内容有价值,推荐用 Github-Desktop 下载并保持更新。
Multi_Sensor_Fusion
Multi-Sensor Fusion (GNSS, IMU, Camera) 多源多传感器融合定位 GPS/INS组合导航 PPP/INS紧组合
algorithms
Algorithms & Data structures in C++.
PythonRobotics
Python sample codes for robotics algorithms.
Tracking-Navigation-and-SLAM
The exercises are all part of a typical application theme, namely tracking, navigation and SLAM: • Bayesian estimation applied to beacon based measurement systems • Kinematic and dynamic models for tracking • Tracking based on discrete Kalman filtering for linear-Gaussian systems • Tracking with extended Kalman filtering in nonlinear systems • Tracking with particle filtering in nonlinear systems • Slam As such the exercises cover the following theoretical subjects: 1. Fundamentals of parameter estimation; static and scalar case 2. Unbiased linear minimum mean square estimation; static and scalar case 3. Unbiased linear minimum mean square estimation; static and vectorial case 4. Propagation of uncertainty in Gaussian-linear systems; prediction 5. Discrete Kalman filtering 6. Extended Kalman filtering 7. Particle filtering 8. SLAM
Face-Tracking-Particle-Filter
A color-based particle filter with a self-updating tracking window to track faces in image sequences.
ObjectTracking
Particle filter to track object in video
Face-Tracking-PF
face tracker using an integration of color-based and moment-based particle filters
SLAM-particle-filter
Particle-filter based SLAM.
robotics-filters
Kalman, Particle and SLAM Filters implemented for the 2012/2013 Robotics exam.
particle-filter-prototype
Particle Filter Implementations in Python and C++, with lecture notes and visualizations
GPSTk
ATTENTION: This repository has been moved and is for archival purposes only. GPSTk toolkit has been renamed to GNSSTK and has been split into two new separate repositories. GNSSTK now only contains libraries while the other repository GNSSTK-APPS contains only applications. The rename and split into libraries and applications started with version v12.0.0 on September 2021. GPSTk --> GNSSTK at https://gitlab.com/sgl-ut/gnsstk --> GNSSTK-APPS at https://gitlab.com/sgl-ut/gnsstk-apps
Visual-GPS-SLAM
This is a repo for my master thesis research about the Fusion of Visual SLAM and GPS. It contains the research paper, code and other interesting data.
L5-SBAS-MOPS-Ephemeris-Fitting-Algorithm
This matlab code fits the L5 SBAS MOPS ephemeris message parameters to precision orbit data. It also performs fit error analysis and evaluates the message performance. Specificially, this looks at the corner cases that can cause problems with the fitting algorithm convergence. This implements the algorithms outlined in Appendix B of my PhD thesis undertaken in the GPS Research Lab in the Department of Aeronautics and Astronautics at Stanford University, entitled, "Orbital Diversity for Global Navigation Satellite Systems"
gps-stack-sim
Simulation of the full GPS stack, from satellites' transmission to position calculation at receivers
gnss-ins-sim
Open-source GNSS + inertial navigation, sensor fusion simulator. Motion trajectory generator, sensor models, and navigation
face_recognition
The world's simplest facial recognition api for Python and the command line
lihang-code
《统计学习方法》的代码实现
Recent_SLAM_Research
Track Advancement of SLAM 跟踪SLAM前沿动态【2021 version】業務調整,暫停更新
interview_internal_reference
2023年最新总结,阿里,腾讯,百度,美团,头条等技术面试题目,以及答案,专家出题人分析汇总。
matplotlib-cheatsheet
Matplotlib 3.1 cheat sheet.