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Basic Arm RL
ChainerRL is a deep reinforcement learning library built on top of Chainer.
利用深度强化学习的方法实现多智能体间离散无交流的障碍避免。其中强化学习算法训练模型所需的数据集由最优互惠碰撞避免(Optimal Reciprocal Collision Avoidance, ORCA)算法生成。
吴恩达老师的机器学习课程个人笔记
Control Synthesis from Linear Temporal Logic Specifications using Model-Free Reinforcement Learning
An implementation of the Deep Deterministic Policy Gradient (DDPG) algorithm using Keras/Tensorflow with the robot simulated using ROS/Gazebo/MoveIt!
DDPG for the robot Poppy Ergo Jr. throwing a ball in the air.
Robot Grasping in Cluttered Environment with DDPG&Affordance
Implementation of Deep Deterministic Policy Gradient (DDPG) with Prioritized Experience Replay (PER)
DDPG with VREP
[CoRL 2020] Learning a Decentralized Multiarm Motion Planner
PyTorch implementations of deep reinforcement learning algorithms and environments
Imlementation of DQN agent to teach the robotic arm simulated in gazebo to touch the cylinder object with certain parts: gripper, the whole arm.
deeplearning.ai(吴恩达老师的深度学习课程笔记及资源)
Deep Reinforcement Learning applied to robotic arm
The DM Control Suite and Package is a tool for developing and testing reinforcement learning agents for the MuJoCo physics engine.
Deep Reinforcement Learning Algorithm Implementing in ROS (virtualenv with Python3)
DRLib:A concise deep reinforcement learning library, integrating HER and PER for almost off policy RL algos.
Application of reinforcement learning to a simulated ROS based robotic arm, to allow it to move to a desired point in 3D space. This repo differs from the previous one in that it is redone using ROS Noetic and Python 3.
DDPG + HER implementation in PyTorch for FetchSlide Robot
Refer to https://github.com/AcutronicRobotics/gym-gazebo2 for the new version
build a reinforcement environment like openai gym based on V-rep for a dual-arm robot
RL based learning for a robotic arm to imitate a given hand in a image feed
This is the pytorch implementation of Hindsight Experience Replay (HER) - Experiment on all fetch robotic environments.
Code for CoRL 2019 paper: HRL4IN: Hierarchical Reinforcement Learning for Interactive Navigation with Mobile Manipulators
Deep Reinforcement Learning for Keras.
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