Pete Florence: Dense Visual Representations, NeRFs, and LLMs for Robotics
On how robotics can benefit from dense visual representations, neural radiance fields, and large language models
Note: this was recorded 2 months ago. Andrey should be getting back to putting out some episodes next year.
Pete Florence is a Research Scientist at Google Research on the Robotics at Google team inside Brain Team in Google Research. His research focuses on topics in robotics, computer vision, and natural language -- including 3D learning, self-supervised learning, and policy learning in robotics. Before Google, he finished his PhD in Computer Science at MIT with Russ Tedrake.
(00:01:16) Start in AI
(00:04:15) PhD Work with Quadcopters
(00:08:40) Dense Visual Representations
(00:22:00) NeRFs for Robotics
(00:39:00) Language Models for Robotics
(00:57:00) Talking to Robots in Real Time
Dense Object Nets: Learning Dense Visual Object Descriptors By and For Robotic Manipulation. (Best Paper Award, CoRL 2018)
Self-Supervised Correspondence in Visuomotor Policy Learning (Best Paper Award, RA-L 2020 )