xiangshengcn's repositories
Deep_reinforcement_learning_Course
Implementations from the free course Deep Reinforcement Learning with Tensorflow
2DQuadSim
Matlab simulation of 2D quadrotor systems
academic-drawing
This is a project providing source codes (including Matlab and Python) for presenting experiment results.
architect-awesome
后端架构师技术图谱
awesome-autonomous-vehicle
无人驾驶的资源列表中文版
awesome-model-based-reinforcement-learning
A curated list of awesome Model-based reinforcement learning resources
awesome-reinforcement-learning-zh
中文整理的强化学习资料（Reinforcement Learning）
deep-learning
Repo for the Deep Learning Nanodegree Foundations program.
delta-robot-pybullet
Implementing Delta Robot in PyBullet
drake
A planning, control, and analysis toolbox for nonlinear dynamical systems. More info at
Dynamic-Movement-Primitives-and-Imitation-Learning-Robotics
Dynamic movement primitives (DMPs) are a method of trajectory control/planning from Stefan Schaal’s lab. Complex movements have long been thought to be composed of sets of primitive action ‘building blocks’ executed in sequence and \ or in parallel, and DMPs are a proposed mathematical formalization of these primitives. The difference between DMPs and previously proposed building blocks is that each DMP is a nonlinear dynamical system. The basic idea is that you take a dynamical system with well specified, stable behavior and add another term that makes it follow some interesting trajectory as it goes about its business. The DMP differential equations (Transformation System, Canonical System, Non-linear Function) realize a general way of generating point-to-point movements. Imitation learning using linear regression is performed to compute the weight factor W from a demonstrated trajectory dataset, given by a teacher. The quality of the imitation is evaluated by comparing the training data with the data generated by the DMP.
frost-dev
Fast Robot Optimization and Simulation Toolkit (FROST)
icra19-lfd-tutorial-exercises
Set of exercises accompanying the ICRA 2019 Tutorial on Dynamical System based Learning from Demonstration: https://epfl-lasa.github.io/TutorialICRA2019.io/
leetcode
LeetCode Solutions: A Record of My Problem Solving Journey.( leetcode题解，记录自己的leetcode解题之路。)
LeetCodeAnimation
Demonstrate all the questions on LeetCode in the form of animation.（用动画的形式呈现解LeetCode题目的思路）
matlab-tree
A MATLAB class to represent the tree data structure.
ModernRobotics
Modern Robotics: Mechanics, Planning, and Control Code Library --- The primary purpose of the provided software is to be easy to read and educational, reinforcing the concepts in the book. The code is optimized neither for efficiency nor robustness.
ModernRoboticsCpp
Modern Robotics: Mechanics, Planning, and Control C++ Library --- The primary purpose of the provided software is to be easy to read and educational, reinforcing the concepts in the book. The code is optimized neither for efficiency nor robustness. http://modernrobotics.org/
MPC-mobile-robot-Path-following
Design and simulation model predictive control for path following with mobile robot.
mujoco-py
MuJoCo is a physics engine for detailed, efficient rigid body simulations with contacts. mujoco-py allows using MuJoCo from Python 3.
phd-bibliography
References on Optimal Control, Reinforcement Learning and Motion Planning
Simulink-Arduino-Serial
How to connect Arduino and Simulink