Insight for training a small bipedal robot using Mujoco Playground #97
Unanswered
ParadoxRobotics
asked this question in
Q&A
Replies: 0 comments
Sign up for free
to join this conversation on GitHub.
Already have an account?
Sign in to comment
Uh oh!
There was an error while loading. Please reload this page.
-
I'm Quentin Munch, a robotics and computer vision engineer. During my free time, I've been developing a small 3D printed bipedal robot that looks like the BDX droid from disney research.

My BD-5 uses the same dynamixel servos as the Robotis OP3 and it's equipped with a 9Dof IMU and Raspberry Pi zeros 2W.
I managed to integrate the robot in the mujoco playground framework and train it to obtain a walking policy following the berkeley / T1 / OP3 joystick task and description.
However, my current policy (see video attachment) is not very optimal : the robot doesn't lift its feet and the backward walk is faster than the forward one.
In this matter, I have the following questions :
My code is a fork of the original repo, the bd5 is in _src/locomotion folder if you want to look. Also I've modified play_joystick code in the experimental/sim2sim folder.
link : https://github.com/ParadoxRobotics/mujoco_playground
Thank you for your help !
Best regards,
Quentin.
prettygoodpolicy.webm
Beta Was this translation helpful? Give feedback.
All reactions