A MuJoCo/Gym environment for robot control using Reinforcement Learning. The task of agents in this environment is pixel-wise prediction of grasp success chances.

Easy to use and accurate hand eye calibration which has been working reliably for years (2016-present) with kinect, kinectv2, rgbd cameras, optical trackers, and several robots including the ur5 and kuka iiwa.

Universal Robot (UR5) Pick and Place Simulation in ROS-Gazebo with a USB Cam and Vacuum Grippers

(deprecated) ROS 1 driver for CB1 and CB2 controllers with UR5 or UR10 robots from Universal Robots

ROS2 URDF description for Universal Robots

Gym-Styled UR5 arm with Robotiq-85 / 140 gripper in Bullet simulator

Python wrapper over OpenRave's IKFast inverse kinematics solver for a UR5 robot arm.

Python IKFast library for Universal Robots

Simulate the iteration of a UR5 robot with Lego bricks

ROS-based Universal Robots (e.g., UR3/e UR5/5, ...) with simulation in Gazebo.

基于 ROS2 与 MoveIt2 框架，集成深度相机感知与OctoMap建图，实现 UR5e机械臂在动态环境中的自主避障与智能抓取。 适用于机器人动态操作、智能制造、人机协作等应用场景。 🚀 深度感知 | 🧠 智能抓取 | 🛡️ 动态避障

Reinforcement learning using rlkit, UR5, Robotiq gripper on ROS(Robot Operating System)

UR5 Robot with a Robotiq gripper

ur5+robotiq_85_gripper gazebo grasping

[CoRL 2021 Best System Paper] This repository contains code for training and evaluating FlingBot in both simulation and real-world settings on a dual-UR5 robot arm setup for Ubuntu 18.04

This Repository is the complete workspace of a project that realizes force-controlled object manipulation with a dual-arm-robot (UR5 and UR10)

Several controllers to move Ridgeback mobile-robot and UR5 robotic-arm.

using TCP/IP network comunication to control UR5 robot with a RG2 gripper

UR10 Reacher Reinforcement Learning Sim2Real Environment for Omniverse Isaac Gym/Sim

This repository contains ROS2 packages for controlling a UR5 robot with a Robotiq gripper, facilitating precise pick and place operations using MoveIt and providing a comprehensive toolkit for ROS2-based UR5 manipulation.

This package enables an UR5 arm with a Robotiq 85 Gripper to be used with ros_control and MoveIt!. A Microsoft Kinect is used to create an Octomap.

Force controlled assembly process. In real and simulated environment. Using Universal Robots UR5, ROS, Gazebo.

No description available

Use ROS2 and Gazebo to simulate 2 UR5 assembling objects.

Simulator of UR5 robotic arm with Robotiq gripper, built with MuJoCo

ROS Nodes to extract image features and move the robot using IBVS(eye in hand)

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

A custom PyBullet environment for UR5 pick-and-place task. Trained using the SAC algorithm from Stable-Baselines3 for continuous control and robotic manipulation.

Integrating learning and task planning for robots with Keras, including simulation, real robot, and multiple dataset support.

A Mujoco Gymnasium Environment for manipulating flexible objects with a UR5e robot arm and Robotiq 2F-85 gripper. Experiment with joint effort, velocity, position, and operational space controllers. Teleoperate in task space and visualize in GUI. Note: Experimental, not actively maintained.