Pieter Abbeel is Professor and Director of the Robot Learning Lab at UC Berkeley [2008- ], Co-Founder of covariant.ai [2017- ], Co-Founder of Gradescope [2014- ], Advisor to OpenAI, Founding Faculty Partner AI@TheHouse, Advisor to many AI/Robotics start-ups. He works in machine learning and robotics. In particular his research focuses on making robots learn from people (apprenticeship learning), how to make robots learn through their own trial and error (reinforcement learning), and how to speed up skill acquisition through learning-to-learn (meta-learning). His robots have learned advanced helicopter aerobatics, knot-tying, basic assembly, organizing laundry, locomotion, and vision-based robotic manipulation. He has won numerous awards, including best paper awards at ICML, NIPS and ICRA, early career awards from NSF, Darpa, ONR, AFOSR, Sloan, TR35, IEEE, and the Presidential Early Career Award for Scientists and Engineers (PECASE). Pieter's work is frequently featured in the popular press, including New York Times, BBC, Bloomberg, Wall Street Journal, Wired, Forbes, Tech Review, NPR.
In the News
Robots today must be programmed by writing computer code, but imagine donning a VR headset and virtually guiding a robot through a task, like you would move the
Bakar Fellow Pieter Abbeel studies deep learning in robots. The robot BRETT (Berkeley Robot for Elimination of Tedious Tasks) has mastered a range of skills, including folding laundry, knot-tying, and basic assembly.
Three UC Berkeley faculty members named as recipients of the Presidential Early Career Awards for Scientists and Engineers, the highest honor bestowed by the U.S. government on science and engineering professionals in the early stages of their independent research careers.
UC Berkeley researchers have developed algorithms that enable robots to learn motor tasks through trial and error using a process that more closely approximates the way humans learn, marking a major milestone in the field of artificial intelligence.
What if robots and humans, working together, were able to perform tasks in surgery and manufacturing that neither can do alone? That’s the question driving new research by UC Berkeley robotics experts Ken Goldberg and Pieter Abbeel and colleagues from four other universities, who were awarded a $3.5 million grant from the National Science Foundation.
Pieter Abbeel, a UC Berkeley, professor known for his novel work in the field of machine learning in robotics – including robots that can fold laundry – has been named to a prestigious list of 35 of the world’s top young innovators by Technology Review magazine.
Folding laundry may seem mundane, but for a robot, identifying a 3-D object and manipulating it correctly, it’s an exercise that requires intelligence that humans may take for granted. Pieter Abbeel and his team of engineers are developing increasingly efficient strategies and algorithms to help robots fold towels, forming the foundation for the next generation.
Four UC Berkeley faculty members have been awarded prestigious Sloan Research Fellowships, given annually by the Alfred P. Sloan Foundation to scientists, mathematicians and economists at an early stage of their careers.
A team from Berkeley's Electrical Engineering and Computer Sciences department has figured out how to get a robot to fold previously unseen towels of different sizes. Their approach solves a key problem in robotics -- how to deal with flexible, or "deformable," objects.