Pulkit Agrawal
Pulkit Agrawal is an Associate Professor in the Department of Electrical Engineering and Computer Science at MIT, where he leads the Improbable AI Lab as part of the Computer Science and Artificial Intelligence Laboratory (CSAIL). His research focuses on computational sensorimotor learning, encompassing perception, control, reinforcement learning, and sim-to-real robotic training for agile locomotion and dexterous manipulation. He is known for pioneering force-centric approaches to robotic manipulation and using simulation-based training to enable robots to operate reliably in real-world environments. He holds a Ph.D. from UC Berkeley and an undergraduate degree from IIT Kanpur, and has co-founded companies including SafelyYou Inc. and Eka Robotics Inc.
“Pulkit Agrawal played a role in paper writing and high-level advising”
Source→“The same force a robot needs to lift your dinner plate is enough to break your hand. That's not a bug. It's physics. And it's the one thing standing between robots and your living room.”
Source→“Learning trained robots usually understand where they should move their hands and legs. They have trained to mimic a wide variety of motions like dancing in many many different ways but they're so focused on replicating that motion that they don't account for how much force they're applying. It can damage the object, injure me or break itself.”
Source→“Our lab has pursued this approach of training robots in a simulation. The digital replica of the physical world, where robots can be collecting data in a digital equivalent of reality. In just a few hours, we can collect hundreds of days' worth of data.”
Source→“Our robots not only follow the motions that we command them to be, but also they are smart about how much force they exert. For example, if the robot is carrying a cup of tea but it hits a table, the robot will adjust and absorb the shock.”
Source→“One thing we haven't done is to make robots trained with machine learning be compliant. We came up with this new approach that we call soft mimic.”
Source→AI-extracted from podcast / newsletter / paper summaries. May contain errors.