CHH3213/multiagent-envs-ML

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CHH3213/multiagent-envs-ML

CHH3213

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哈工大深圳2021秋季机器学习课程（熊昊）课设作业环境

chhRobotics_CPP

自动驾驶规划控制常用算法c++代码实现

chhRobotics

自动驾驶规划控制python代码实现

Jupyter Notebook

Books

书籍资料汇总

chhRL

Reinforcement learning algorithm by pytorch

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

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）。

testCPP

cppad+Ipopt demo以及OSQP demo程序

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

Autonomous_driving-bilibili

Jupyter Notebook

chh-MachineLearning

机器学习经典算法实现

Math_Geometry

These are Pratical Math and Geometry Algorithms!

chhTricks

一些小tricks项目

CHH3213

Config files for my GitHub profile.

CHH3213.github.io

个人博客生成文件地址

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

diagrams_flow-chart

This is Source File of the flows chart

loggers_multiobjective

multiobjective tasks--pursuit-evasion,reach target,avoid obstacles

PX4-fork

zh文件夹可细看

chhML

借助sklearn库实现经典机器学习方法

Jupyter Notebook

uav_rl

uav control via reinforcement learning.

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.

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.