ROS-based project for Robot Control and Simulation course at Warsaw University of Technology.
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Updated
Feb 20, 2023 - Python
ROS-based project for Robot Control and Simulation course at Warsaw University of Technology.
This work builds on top of mujoco-powered robosuite framework, and is designed for learning object-agnostic control policy for pick-and-place operations on a novel 6-DoF parallel manipulator using deep reinforcement learning. This pipeline utilizes DDPG combined with HER algorithm for training a robust manipulation policy.
Robot that can play Checkers.
Exploring Generalization in Deep Reinforcement Learning algorithms for different tasks using Gymnasium, Gymnasium-Robotics and MuJoCo
Convert your Altium Designer pick and place exports to importable data for your Neoden 4 pick and place machine
A collection of useful scripts for the operation of the Baxter Research Robot.
A pick-and-place application with the Franka Panda robot simulated in ROS and Gazebo.
Simulation source code and examples for applying machine learning on Sawyer Robot
Code for reproducing experiments for the paper "Pick-and-Place With Uncertain Object Instance Segmentation and Shape Completion".
A ROS package that makes picking and placing objects with MoveIt and GraspIt, easier than ever! 🤖
A Collision Avoidance and Path Planning Framework implemented for a dual arm Pick and Place robot task simulation. Velocity Obstacles and RRTStar Motion Planner are used in the algorithm to plan dynamic collisionless trajectories.
myGym enables fast prototyping of RL in the area of robotic manipulation and navigation.You can train different robots, in several environments on various tasks. There is automatic evaluation and benchmark tool. From version 2.1 there is support for multi-step tasks, multi-reward training and multi-network architectures.
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.
Universal Robot (UR5) Pick and Place Simulation in ROS-Gazebo with a USB Cam and Vacuum Grippers
Train robotic agents to learn pick and place with deep learning for vision-based manipulation in PyBullet. Transporter Nets, CoRL 2020.
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