Hi, I'm Brian. I'm a robotics researcher interested in making dynamic robots do real things in the real world. My current research focuses on designing walking controllers for bipedal robots which leverage terrain information from vision. I've designed and impelemented several walking controllers and deployed them on the bipedal robot Cassie.
I'm a PhD student in the DAIR Lab at the University of Pennsylvania, where I'm advised by Michael Posa and supported by the NSF GRFP.
Before coming to Penn, I received my Bachelor’s degree in Mechanical Engineering from Purdue. I have also worked as a controls engineering intern at John Deere and Intuitive Surgical.
@inproceedings{Acosta2023,
title = {Bipedal Walking on Constrained Footholds with MPC Footstep Control},
author = {Acosta, Brian and Posa, Michael},
year = {2023},
booktitle = {IEEE-RAS International Conference on Humanoid Robotics},
doi = {10.1109/Humanoids57100.2023.10375170}
}
It turns out that a straightforward ADMM implementation is surprisingly performant for solving whole body control QPs that arise in optimization based control of legged robots. As a bonus, we can use the full lorentz-cone constraint for the friction cone, instead of the common pyramidal approximation.
Check out the github repo of my implementation here.