Sumeet Singh
Bio
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I am a Research Scientist at Google Brain Robotics in NYC. I recently completed my Ph.D. in the Autonomous Systems Lab in the Aeronautics and Astronautics Department at Stanford. |
Defense
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I recently passed my PhD defense. Click on photo for video link. Additional quadrotor videos can be found here. |
Research Overview
Broadly, I design algorithms for robot planning and control by combining tools from nonlinear control theory and reinforcement learning. Specifically, I am interested in (i) how to use control theory to stabilize and make robust, in a learning and operational sense, model-based reinforcement learning (RL), (ii) how to merge model-based and model-free RL algorithms in such a way as to alleviate issues such as high sample complexity and bias-induced errors, and (iii) rigorously evaluating novel algorithms within challenging experimental domains including aerial & wheeled ground vehicles, dexterous manipulation, and agile locomotion.
Some topics that I studied during my Ph.D. are listed below:
Robust motion planning for constrained nonlinear systems: Design of nonlinear control and planning algorithms for online generation of robust motion plans with guaranteed margins of safety for constrained robotic systems in cluttered environments (ICRA, WAFR, IJRR Preprint).
Control-Theoretic model-based Reinforcement Learning: Infusing model-based reinforcement learning algorithms with concepts drawn from nonlinear control theory, such as stabilizability and robustness (WAFR, IJRR Preprint).
Risk-sensitive inference and decision-making: Development and analysis of flexible risk-sensitive human behavior models and the design of stochastic control algorithms leveraging these models within a risk-sensitive dynamic game framework (IJRR, TAC, RSS).
News
Oct, 2019: Started research scientist position at Google Brain Robotics in NYC!
Sep, 2019: Paper on Robust Feedback Motion Planning submitted to IJRR. Videos of hardware experiments can be found here.
July, 2019: Invited paper on Learning Stabilizable Dynamics submitted to IJRR. Videos of hardware experiments can be found here.
July, 2019: PhD Defense Scheduled! July 18, 10:45am - 12pm. Live stream link.
Apr, 2019: WAFR 2018 conference paper on Stabilizable Dynamics Learning invited for special issue of IJRR.
Feb, 2019: Paper on Reduced Order MPC accepted to ECC 2019.
Invited Talks
Oct, 2019: NSF Robot Learning Workshop, Lehigh University.
May, 2019: ICRA 2019 Workshop: Toward Online Optimal Control of Dynamic Robots
May, 2019: ICME Xpo Research Symposium, Stanford University
May, 2019: MIT CSAIL
Apr, 2019: CITRIS/CPAR Control Theory and Automation Symposium, UC Berkeley
Apr, 2019: Google Brain Robotics (NYC)
Apr, 2019: USC Electrical and Computer Engineering
Mar, 2019: AAAI Spring Symposium - Verification of Neural Networks, Stanford University
Mar, 2019: MIT Mechanical Engineering
Oct, 2018: Stanford Robotics Seminar
Aug, 2018: UC Berkeley Semi-Autonomous Group
Feb, 2017: MIT CSAIL Robotics Seminar
Contact
Email: ssingh19@stanford.edu