jkwwwwow

v2rayN

A GUI client for Windows, support Xray core and v2fly core and others

Hitomi-Downloader

:cake: Desktop utility to download images/videos/music/text from various websites, and more.

vulhub

Pre-Built Vulnerable Environments Based on Docker-Compose

xray

一款完善的安全评估工具，支持常见 web 安全问题扫描和自定义 poc | 使用之前务必先阅读文档

HighwayEnv

A minimalist environment for decision-making in autonomous driving

spline

c++ cubic spline library

Miniworld

Simple and easily configurable 3D FPS-game-like environments for reinforcement learning

robotics-rl-srl

S-RL Toolbox: Reinforcement Learning (RL) and State Representation Learning (SRL) for Robotics

My_Bibliography_for_Research_on_Autonomous_Driving

Personal notes about scientific and research works on "Decision-Making for Autonomous Driving"

rl-collision-avoidance

Implementation of the paper "Towards Optimally Decentralized Multi-Robot Collision Avoidance via Deep Reinforcement Learning"

macad-gym

Multi-Agent Connected Autonomous Driving (MACAD) Gym environments for Deep RL. Code for the paper presented in the Machine Learning for Autonomous Driving Workshop at NeurIPS 2019:

bark

Open-Source Framework for Development, Simulation and Benchmarking of Behavior Planning Algorithms for Autonomous Driving

DRL_Path_Planning

This is a DRL(Deep Reinforcement Learning) platform built with Gazebo for the purpose of robot's adaptive path planning.

rl_CARLA

Use Reinforcement Learning to train an autonomous driving agent in CARLA Simulator

motion-planner-reinforcement-learning

End to end motion planner using Deep Deterministic Policy Gradient (DDPG) in gazebo

pyastar2d

A very simple A* implementation in C++ callable from Python for pathfinding on a two-dimensional grid.

RL-ROBOT

Reinforcement Learning framework for Robotics

Lane-Change-Simulation

This is an C++ implementation of lane change decision making in simulated autonomous driving, path planning and markov decision process as well as particle filters are considered

IV19

My 10 takeaways from the 2019 Intelligent Vehicle Symposium

f110_rrt_star

RRT Star path planning for dynamic obstacle avoidance for the F110 Autonomous Car

BayesianRLForAutonomousDriving

Recurrent-Multiagent-Deep-Deterministic-Policy-Gradient-with-Difference-Rewards

Deep Reinforcement Learning (DRL) algorithms have been successfully applied to a range of challenging simulated continuous control single agent tasks. These methods have further been extended to multiagent domains in cooperative, competitive or mixed environments. This paper primarily focuses on multiagent cooperative settings which can be modeled for several real world problems such as coordination of autonomous vehicles and warehouse robots. However, these systems suffer from several challenges such as, structural credit assignment and partial observability. In this paper, we propose Recurrent Multiagent Deep Deterministic Policy Gradient (RMADDPG) algorithm which extends Multiagent Deep Determinisitic Policy Gradient algorithm - MADDPG \cite{lowe2017multi} by using a recurrent neural network for the actor policy. This helps to address partial observability by maintaining a sequence of past observations which networks learn to preserve in order to solve the POMDP. In addition, we use reward shaping through difference rewards to address structural credit assignment in a partially observed environment. We evaluate the performance of MADDPG and R-MADDPG with and without reward shaping in a Multiagent Particle Environment. We further show that reward shaped RMADDPG outperforms the baseline algorithm MADDPG in a partially observable environmental setting.

Autonomous_Parking_ROS

16-782 Planning & Decision-making for Robotics final project

autonomous_golf_cart

This is our attempt at replicating the results of the famous ICRA 2015 paper on Intention aware Online POMDP planning for autonomous systems. This project is a part of the course ASEN6519 - Decision Making Under Uncertainty that we took in Spring 2020.

RL-environnement-for-autonomous-car

In this repo, I used some math and image manipulation skills to create my own reinforcement learning environnement for autonomous car

POMDPIDMModel.jl

Decision-Making at Intersections based on POMDP and IDM Model

RLRobotSimulation

Autonomous-Car-RL-Env

autonomous_car_rl

Code for Autonomous Car with Reinforcement Learning

rlrobot

Reinforcement learning framework for robotics