Whole Body Control for Humanoid Robots
Avideh Zakhor, Professor
Electrical Engineering and Computer Science
Open. Apprentices needed for the Fall semester. Enter your application online beginning August 22nd. The deadline to apply is Tuesday, September 2nd, 4pm.
In this project, we will develop methods to enable a Unitree G1 robot to walk, run, and perform whole body tasks such as bending over to pick up boxes. Some of the techniques we will investigate include Reinforcement Learning.
Role: * Read the literature on humanoid autonomy; This is at least 20 or so relevant papers.
* Come up with innovate algorithms to achieve human body control using RL or alternatives
* Implement the algorithm in simulation to verify performance
* Run it on the actual robot ( sim to real transfer) to verify performance on the robot.
Qualifications: * Must have taken the RL course or gone through the entire CS 285 online course.
* Familiar with deep learning frameworks such as Pytorch.
* Experience with actual hardware is a plus.
* Extensive programming and software development experience.
* Preference will be given to students who can continue the project over the spring semester.
Hours: 12 or more hours
Related website: https://www-video.eecs.berkeley.edu/papers/tomsonqu2/IROS_2024___march_revision_final.pdf
Related website: https://www-video.eecs.berkeley.edu/papers/zixianzang/hexapod_IROS_2023_final.pdf