Pieter Abbeel

Pieter Abbeel

Title
Professor
Department
Division of Computer Science/EECS
Research Expertise and Interest
robotics, machine learning, artificial intelligence, Deep Learning
Research Description

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

April 14, 2020

Learning to learn

When children play with toys, they learn about the world around them — and today’s robots aren’t all that different. At UC Berkeley’s Robot Learning Lab, groups of robots are working to master the same kinds of tasks that kids do: placing wood blocks in the correct slot of a shape-sorting cube, connecting one plastic Lego brick to another, attaching stray parts to a toy airplane.
April 9, 2019

Meet Blue, the low-cost, human-friendly robot designed for AI

Enter Blue, a new low-cost, human-friendly robot conceived and built by a team of researchers at the University of California, Berkeley. Blue was designed to use recent advances in artificial intelligence (AI) and deep reinforcement learning to master intricate human tasks, all while remaining affordable and safe enough that every artificial intelligence researcher — and eventually every home — could have one.
November 7, 2017

Berkeley startup to train robots like puppets

Robots today must be programmed by writing computer code, but imagine donning a VR headset and virtually guiding a robot through a task and then letting the robot take it from there.
February 22, 2016

“Deep Learning”: A Giant Step for Robots

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.

February 19, 2016

Three young faculty members honored by White House

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.

December 17, 2012

Big NSF grant funds research into training robots to work with humans

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.

June 29, 2011

Laundry duty getting you down? Robots to the rescue!

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.

April 2, 2010

Researchers enable a robot to fold towels

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.

In the News

April 14, 2020

Learning to learn

When children play with toys, they learn about the world around them — and today’s robots aren’t all that different. At UC Berkeley’s Robot Learning Lab, groups of robots are working to master the same kinds of tasks that kids do: placing wood blocks in the correct slot of a shape-sorting cube, connecting one plastic Lego brick to another, attaching stray parts to a toy airplane.
April 9, 2019

Meet Blue, the low-cost, human-friendly robot designed for AI

Enter Blue, a new low-cost, human-friendly robot conceived and built by a team of researchers at the University of California, Berkeley. Blue was designed to use recent advances in artificial intelligence (AI) and deep reinforcement learning to master intricate human tasks, all while remaining affordable and safe enough that every artificial intelligence researcher — and eventually every home — could have one.
November 7, 2017

Berkeley startup to train robots like puppets

Robots today must be programmed by writing computer code, but imagine donning a VR headset and virtually guiding a robot through a task and then letting the robot take it from there.
February 22, 2016

“Deep Learning”: A Giant Step for Robots

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.

February 19, 2016

Three young faculty members honored by White House

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.

December 17, 2012

Big NSF grant funds research into training robots to work with humans

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.

June 29, 2011

Laundry duty getting you down? Robots to the rescue!

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.

April 2, 2010

Researchers enable a robot to fold towels

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.

Featured in the Media

Please note: The views and opinions expressed in these articles are those of the authors and do not necessarily reflect the official policy or positions of UC Berkeley.
May 6, 2020
Jennifer Smith
Covariant, an AI startup co-founded by electrical engineering and computer sciences professor Pieter Abbeel, director of the Berkeley Robot Learning Lab and co-director of the Berkeley Artificial Intelligence Research (BAIR) lab, and building upon Berkeley research, has raised $40 million to boost hiring and adapt its AI robotics software to new industries. "What we've built is a universal brain for robotic manipulation tasks," says Covariant co-founder and CEO Peter Chen, a Berkeley alum and doctoral student in Professor Abbeel's lab. The COVID-19 pandemic has raised interest in robotics to help companies cope with dramatic shifts in consumer demand and to accommodate new limits on workplace operations, like spacing workers further apart. Stories on this topic have appeared in dozens of sources, including Venture Beat, TechCrunch, Robot Report, and Crunchbase News.
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May 5, 2020
Khari Johnson
A group of Berkeley researchers, including electrical engineering and computer sciences professor Pieter Abbeel, director of the Berkeley Robot Learning Lab and co-director of the Berkeley Artificial Intelligence Research (BAIR) lab, has released a state-of-the-art open-sourced Reinforcement Learning with Augmented Data (RAD) module. The reinforcement learning algorithm, used in machine learning for robotics, beats prior modules, including Google AI's PlaNet, DeepMind's Dreamer, and SLAC from Berkeley and DeepMind.
March 18, 2020
Eugene Demaitre
Berkeley researchers have developed a mobile robot called BADGR, which learns to navigate independently. "Most mobile robots think purely in terms of geometry; they detect where obstacles are, and plan paths around these perceived obstacles in order to reach the goal," says doctoral electrical engineering and computer sciences student Gregory Kahn, one of the study's co-authors. "This purely geometric view of the world is insufficient for many navigation problems." Kahn worked on the robot with electrical engineering and computer sciences professor Pieter Abbeel, director of the Berkeley Robot Learning Lab and co-director of the Berkeley Artificial Intelligence Research (BAIR) lab, and assistant electrical engineering and computer sciences professor Sergey Levine. With just 42 hours of autonomously collected data, BADGR outperformed Simultaneous Localization and Mapping (SLAM) approaches in a test, and it had less data to work with than other navigation methods, according to the researchers. Link to video.
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