Fei Xia
I'm a Research Scientist at Google Research where I work on the Robotics team. My mission is to build intelligent embodied agents that can interact with complex and unstructured real-world environments, with applications to home robotics. I have been approaching this problem from 3 aspects: 1) Large scale and transferrable simulation for Robotics. 2) Learning algorithms for long-horizon tasks. 3) Combining geometric and semantic representation for environments. Most recently, I have been exploring using foundation models for robot decision making.
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Google
Learning Model Predictive Controllers with Real-Time Attention for Real-World Navigation
Anthony G. Francis
Dmitry Kalashnikov
Edward Lee
Jake Varley
Leila Takayama
Mikael Persson
Peng Xu
Stephen Tu
Xuesu Xiao
Conference on Robot Learning (2022) (to appear)
Robotic table wiping via whole-body trajectory optimizationand reinforcement learning
Benjie Holson
Jeffrey Bingham
Jonathan Weisz
Mario Prats
Peng Xu
Thomas Lew
Xiaohan Zhang
Yao Lu
ICRA (2022)
Do As I Can, Not As I Say: Grounding Language in Robotic Affordances
Alexander Herzog
Alexander Toshkov Toshev
Andy Zeng
Anthony Brohan
Brian Andrew Ichter
Byron David
Chelsea Finn
Clayton Tan
Diego Reyes
Dmitry Kalashnikov
Eric Victor Jang
Jarek Liam Rettinghouse
Jornell Lacanlale Quiambao
Julian Ibarz
Karol Hausman
Kyle Alan Jeffrey
Linda Luu
Mengyuan Yan
Michael Soogil Ahn
Nicolas Sievers
Noah Brown
Omar Eduardo Escareno Cortes
Peng Xu
Peter Pastor Sampedro
Rosario Jauregui Ruano
Sally Augusta Jesmonth
Sergey Levine
Steve Xu
Yao Lu
Yevgen Chebotar
Yuheng Kuang
Conference on Robot Learning (CoRL) (2022)
A Contextual Bandit Approach for Learning to Plan in Environments with Probabilistic Goal Configurations
Sohan Rudra
Saksham Goel
Gaurav Aggarwal
NeurIPS 5th Robot Learning Workshop: Trustworthy Robotics (2022) (to appear)
InnerMonologue: Embodied Reasoning through Planning with Language Models
Wenlong Huang
Harris Chan
Jacky Liang
Pete Florence
Andy Zeng
Igor Mordatch
Yevgen Chebotar
Noah Brown
Tomas Jackson
Linda Luu
Sergey Levine
Karol Hausman
Brian Andrew Ichter
Conference on Robot Learning (2022) (to appear)
