I am a PhD student at the Computer Science and Artificial Intelligence Laboratory (CSAIL) at MIT, advised by Pulkit Agrawal. I study learned control as a component of complete robotic systems. Previously, I received my BS ('20) and MEng ('21) degrees at MIT.
Updates
- Oct '24 - Gave a talk at Michigan AI Symposium on Learning Proprioceptive Intelligence.
- Aug '24 - I was a summer intern on the Atlas team at Boston Dynamics supervised by Michael Lutter and Scott Kuindersma.
- May '24 - I co-organized two workshops at ICRA 2024 in Yokohama: Agile Robotics on Monday and Loco-Manipulation on Friday.
- Nov '23 - I shared our work on learning to actively sense terrain properties during locomotion at CoRL '23.
- Apr '23 - Our sim-to-real soccer ball manipulation project, DribbleBot, was covered by MIT News.
- Dec '22 - Our open-source codebase for sim2real transfer of continuously parameterized structured gaits to Unitree Go1 is now released, accompanying our CoRL 2022 paper. Try it out here.
- Dec '22 - I co-organized the Workshop on Sim-to-Real Robot Learning: Locomotion and Beyond at the 2022 Conference on Robot Learning. Thanks to all who participated! The full recording is now available here.
- Jun '22 - I presented our work on teaching robots to run fast at the Robotics: Science and Systems conference in New York City. At the conference banquet, our robot hit the dance floor.
Research
Position: Automatic Environment Shaping is the Next Frontier in RL
Younghyo Park*, Gabriel B. Margolis*, Pulkit Agrawal
International Conference on Machine Learning (ICML), 2024 (Oral Presentation)
To generalize the successes of reinforcement learning, we need research on the interaction between environment shaping and learning dynamics.
Learning Force Control for Legged Manipulation
Tifanny Portela, Gabriel B. Margolis, Yandong Ji, Pulkit Agrawal
International Conference on Robotics and Automation (ICRA), 2024
Learn to control the force at the end effector of a quadruped robot with an arm for compliant and forceful manipulation.
Maximizing Quadruped Velocity by Minimizing Energy
Srinath Mahankali*, Chi-Chang Lee*, Gabriel B. Margolis, Zhang-Wei Hong, Pulkit Agrawal
International Conference on Robotics and Automation (ICRA), 2024
Balance energy and velocity through constrained optimization for agile running with minimal reward shaping.
Learning to See Physical Properties with Active Sensing Motor Policies
Gabriel B. Margolis, Xiang Fu, Yandong Ji, Pulkit Agrawal
Conference on Robot Learning (CoRL), 2023
Learn to see how terrains feel by collecting self-supervised data with information-maximizing motor skills.
DribbleBot: Dynamic Legged Manipulation in the Wild
Yandong Ji*, Gabriel B. Margolis*, Pulkit Agrawal
International Conference on Robotics and Automation (ICRA), 2023
Dynamic object manipulation with the legs, using onboard computation and sensing.
Walk These Ways: Tuning Robot Control for Generalization with Multiplicity of Behavior
Gabriel B. Margolis, Pulkit Agrawal
Conference on Robot Learning (CoRL), 2022 (Oral Presentation)
One learned policy embodies parameterized dynamic behaviors useful for different tasks.
Rapid Locomotion via Reinforcement Learning
Gabriel B. Margolis*, Ge Yang*, Kartik Paigwar, Tao Chen, Pulkit Agrawal
Robotics: Science and Systems (RSS), 2022
High-speed running and spinning on diverse terrains with a single neural network.
Learning to Jump from Pixels
Gabriel B. Margolis, Tao Chen, Kartik Paigwar, Xiang Fu, Donghyun Kim, Sangbae Kim, Pulkit Agrawal
Conference on Robot Learning (CoRL), 2021
A hierarchical control framework for dynamic vision-aware locomotion.