@CHH3213
github

CHH3213

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  • Stars
    star
    1,017
  • Global Rank 30,089 (Top 2 %)
  • Followers 329
  • Following 18
  • Registered over 4 years ago
  • Most used languages
    Python
         47.4 %
    C++
         26.3 %
    Jupyter Notebook
         15.8 %
    TeX
         5.3 %
    HTML
         5.3 %

Top repositories

1

chhRobotics_CPP

自动驾驶规划控制常用算法c++代码实现
C++
450
star
2

chhRobotics

自动驾驶规划控制python代码实现
Jupyter Notebook
309
star
3

Books

书籍资料汇总
C++
167
star
4

chhRL

Reinforcement learning algorithm by pytorch
Python
21
star
5

clash-for-windows-backup

clash for windows v 0.20.39 版本备份，原库的archive镜像：https://web.archive.org/web/20231025075452/https://github.com/Fndroid/clash_for_windows_pkg/releases
16
star
6

chhCpp

c++仓库，包括某些数学理论的实现（最优化、方程求根等），一些简单项目的实现（机房预约系统等）。
C++
12
star
7

testCPP

cppad+Ipopt demo以及OSQP demo程序
C++
8
star
8

safeRL-CBF

新增一个CBF层，并将其结合进actor网络中，得到safe RL框架。后续验证中发现这种做法并没有实质性的用处，所以不再继续这个项目
Python
5
star
9

Autonomous_driving-bilibili

Jupyter Notebook
3
star
10

chh-MachineLearning

机器学习经典算法实现
Python
3
star
11

multiagent-envs-ML

哈工大深圳2021秋季机器学习课程（熊昊）课设作业环境
Python
3
star
12

Math_Geometry

These are Pratical Math and Geometry Algorithms!
C++
3
star
13

chhTricks

一些小tricks项目
Python
2
star
14

CHH3213

Config files for my GitHub profile.
2
star
15

CHH3213.github.io

个人博客生成文件地址
HTML
2
star
16

rcdpr

Xiong, H., Cao, H., Zeng, W., Huang, J., Diao, X., Lu, W., and Lou, Y. (September 6, 2022). "Real-Time Reconfiguration Planning for the Dynamic Control of Reconfigurable Cable-Driven Parallel Robots." ASME. J. Mechanisms Robotics. December 2022; 14(6): 060913. https://doi.org/10.1115/1.4055255
Python
2
star
17

diagrams_flow-chart

This is Source File of the flows chart
1
star
18

loggers_multiobjective

multiobjective tasks--pursuit-evasion,reach target,avoid obstacles
1
star
19

PX4-fork

zh文件夹可细看
TeX
1
star
20

chhML

借助sklearn库实现经典机器学习方法
Jupyter Notebook
1
star
21

uav_rl

uav control via reinforcement learning.
Python
1
star
22

uav_energy

Xiong, Hao et al. “Load Estimation and Optimal Energy Efficiency Configuration Determination of an Aerial Cable Towed Robot: A Preliminary Study.” 2022 International Conference on Machine Learning, Control, and Robotics (MLCR) (2022): 143-147.
Python
1
star
23

Project_XPlane

H. Cao et al., "Two-Stage Strategy to Achieve a Reinforcement Learning-Based Upset Recovery Policy for Aircraft," 2021 China Automation Congress (CAC), Beijing, China, 2021, pp. 2080-2085, doi: 10.1109/CAC53003.2021.9727381.
Python
1
star