OpenAI Gym environments for a quadruped robot

The goal of this project is to train an open-source 3D printed quadruped robot exploring Reinforcement Learning and OpenAI Gym. The aim is to let the robot learns domestic and generic tasks in the simulations and then successfully transfer the knowledge (Control Policies) on the real robot without any other manual tuning.

The robot used for this first experiment is the Spotmicro made by Deok-yeon Kim.

I've printed the components using a Creality Ender3 3D printer, with PLA and TPU+.

The hardware used is listed in this wiki.

The idea is to extend the robot adding components like a robotic arm on the top of the rack and a LiDAR sensor in the next versions alongside fixing some design issue to support a better (and easier) calibration and more reliable servo motors.