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Train robotic agents to learn pick and place with deep learning for vision-based manipulation in PyBullet. Transporter Nets, CoRL 2020.

Mujoco_rl_ur5 ⭐ 171

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.

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.

Rapid Transport ⭐ 11

Open-Source Pick and Place Machines

Easy Baxter ⭐ 7

A collection of useful scripts for the operation of the Baxter Research Robot.

Velocity Obstacle And Motion Planning ⭐ 6

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.

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