Excited to announce that our paper "Blending MPC and Value Function Approximation for Efficient Reinforcement Learning" recently got accepted to #ICLR2021! arxiv.org/abs/2012.05909 Thanks to my co-authors Sanjiban Choudhary Sanjiban Choudhury and Byron Boots for making this work possible.

Announcing another exciting #CoRL2021 tutorial: "Machine Learning Perspectives on Model Predictive Control" from Byron Boots of #UWAllen Allen School @uw Reminder- submissions close June 18th: robot-learning.org #robots #learning #machinelearning #robotics #conference #robot

We would all like our robots to live and work alongside fellow humans. But how should robots imitate us? In this 10-part series, I dive deep into imitation learning, and build up a general framework. A journey through feedback, interventions and more!🧵bit.ly/3Bxv80m 1/

I have been working on a series that revisits core concepts in robotics in a contemporary light. Starting with imitation learning and how it shows up in self-driving, on the simplest of problems! youtu.be/GDmhrAHxgQE

Really excited to present our paper STORM: An Integrated Framework for Fast Joint Space MPC for Reactive Manipulation at Conference on Robot Learning! Checkout our oral talk on Thurs 10am GMT. arxiv.org/abs/2104.13542

Excited about sampling-based MPC but tired of assuming everything is a Gaussian and unsure about the right way to adapt the distribution online? Check out our #CoRL2022 paper on "Learning Sampling Distributions for Model Predictive Control"! (1/8) Paper: arxiv.org/abs/2212.02587

Full version of our NeurIPS Conference 2023 paper titled Adversarial Model for Offline Reinforcement Learning is now available on arxiv arxiv.org/abs/2302.11048 Joint work with Tengyang Xie , Nan Jiang, Byron Boots and Ching-An Cheng. Open source code coming soon!

Cooking in kitchens is fun. BUT doing it collaboratively with two robots is even more satisfying! We introduce MOSAIC, a modular framework that coordinates multiple robots to closely collaborate and cook with humans via natural language interaction and a repository of skills.

Really excited to share that I successfully defended my PhD thesis at Allen School earlier this month! My deepest gratitude to my committee and everyone who helped me along this 5 year journey!

Slightly belated life update: In April I started as a Research Scientist in the Atlas team at Boston Dynamics. Really excited to continue research in learning and manipulation with this amazing team and our shiny new humanoid!

Come over to the poster session 4 at L4DC Conference today if you're interested in learning more about our work on controlling a complex fluid dynamical system with RL directly in the real world. proceedings.mlr.press/v242/bhardwaj2…

Atlas doing a quick warm up before work.

Atlas is autonomously moving engine covers between supplier containers and a mobile sequencing dolly, using ML to detect and localize the environment fixtures and individual bin. There are no prescribed or teleoperated movements. youtu.be/F_7IPm7f1vI

Wishing you a holiday season full of light and laughter as we flip over into the new year!

Our work with Boston Dynamics on RL training workflows for Atlas (upper torso) manipulation. An amazing team to work with! Gina Fey, Mohak Bhardwaj Michael Lutter, Alberto Rodriguez Ritvik Singh, Karl Van Wyk, Ankur Handa

Boston Dynamics collaborated with NVIDIA to demonstrate DextrAH-RGB, a workflow for dexterous grasping from stereo RGB input. The end-to-end policy for Atlas robot, trained entirely in NVIDIA Isaac Lab, transfers zero-shot from simulation to the real robot.

Some more 'cherry' picked field test adventures with Spot! :)