Learning Accurate Long-term Dynamics for Model-based Reinforcement Learning
Dec 16, 2020
|
Arxiv
Trying to reframe the MBRL framework with long-term predictions instead of one-step predictions!
Full PageRobotics
←All ResearchEmbodied intelligence, today!
Robotics is likely the biggest category of my work. It encompasses everything from hardware development to algorithmic studies all with the central goal of creating agents that can better interact with our physical world (even in indirect ways, like traffic lights).
I have so many open areas of research here, and am open to inquiries.
Learning for Microrobot Exploration: Model-based Locomotion, Robust Navigation, and Low-Power Deep Classification
Jul 13, 2020
|
Conference on Manipulation, Automation and Robotics at Small Scales (MARSS)
A collections of steps towards a data-driven autonomous microrobot.
Full Page
Learning Generalizable Locomotion Skills with Hierarchical Reinforcement Learning
Sep 26, 2019
|
2020 IEEE International Conference on Robotics and Automation (ICRA)
Learning how to walk with a real-world hexapod using a hierarchy of model-free RL for basic motion primitives with model-based RL for higher level planning.
Full Page
Low Level Control of a Quadrotor with Deep Model-Based Reinforcement Learning
Jan 11, 2019
|
IEEE Robotics and Automation Letters
We used deep model-based reinforcement learning to have a quadrotor learn to hover from less than 5 minutes of all experimental training data.
Full Page
Toward Controlled Flight of the Ionocraft: A Flying Microrobot Using Electrohydrodynamic Thrust With Onboard Sensing and No Moving Parts
Jul 18, 2018
|
IEEE Robotics and Automation Letters
A collection of steps towards controlled flight of The Ionocraft, a completely silent microrobot with ion thrust!
Full Page