Using Catalyst.RL to train a robot to perform peg-in-hole insertion in simulation.

This project provides a framework for manipulation and robotic vision tasks, focusing on active perception and imitation learning. It is designed to train and test reinforcement learning (RL) model…

Robotic Arm Manipulation - PPO RL

Reinforcement Learning with Robot Arm

Robotics-Deep Reinforcement Learning Project: Deep RL Arm Manipulation by using DQN (Deep Q-Learning Network) agent simulated on ROS-Gazebo with C++ API.

Asynchronous Reinforcement Learning for UR5 Robotic Arm

Old simulation environment for the cap-the-bottle dual-arm peg-in-hole task

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

Deep reinforcement learning on NVIDIA Jetson tx2 with PyTorch, OpenAI Gym, and Gazebo robotics simulator.

Peg and Hole insertion by Franka Emica

Simulation and training a UR5 robot to accurately insert a pin into a hole using the CoppeliaSim simulator and catalyst-rl reinforcement library

https://hrl.boyuai.com/

PyTorch implementations of deep reinforcement learning algorithms and environments

This is a project about robotic manipulation motion planning using deep reinforcement learning based on ROS and Gazebo simulation

【深度强化学习社区】一个资料与学习内容最全的服务平台

A hotchpotch of tools for DMP learning, dataglove calibration, motion-capture data processing, similarity network training set construction, etc.

Dynamic Movement Primitive based Motion Retargeting, along with the sign language robot constituted by ABB's YuMi dual-arm collaborative robot and Inspire Robotics' multi-fingered hands.

Vision-Based Lego Detection, Localization, and Assembly Using UR5 Robot Arm

✏️ Simulation of UR5 robot assembly using vrep and python

In the env, you can control UR5 robot to achieve the assembly between shaft and hole by Reinforcement Learning.

轴孔装配仿真

基于XMake的C++项目，实现opencv的相机标定与apriltag的识别姿态估计

协作型机器人控制与操作实验 自适应夹取代码

AI-IMU Dead-Reckoning

Convolutional Neural Networks for Denoising Gyroscopes of Low-Cost IMUs

A C++ project designed to implement dynamic positioning using Inertial Measurement Unit (IMU) data.

Estimates pose, velocity, and accelerometer / gyroscope biases by fusing GPS position and/or 6DOF pose with IMU data. The fusion is done using GTSAM's sparse nonlinear incremental optimization (ISA…

A training code for data fusion. States (world frame): position, orientation(Euler angles, ZXY), velocity, gyroscope bais, acceleration bais.