Enes Erciyes
@eneserciyes.bsky.social
Working on home robotics and mobile manipulation @ NYU CILVR | Fulbrighter
eneserciyes.github.io
eneserciyes.github.io
Reposted by Enes Erciyes
Since we are nearing the end of the year, I'll revisit some of our work I'm most excited about from the last year and maybe a sneak peek of what we are up to next.
To start of, Robot Utility Models, which enables zero-shot deployment. In the video below, the robot hasnt seen these doors before.
To start of, Robot Utility Models, which enables zero-shot deployment. In the video below, the robot hasnt seen these doors before.
December 8, 2024 at 2:32 AM
Since we are nearing the end of the year, I'll revisit some of our work I'm most excited about from the last year and maybe a sneak peek of what we are up to next.
To start of, Robot Utility Models, which enables zero-shot deployment. In the video below, the robot hasnt seen these doors before.
To start of, Robot Utility Models, which enables zero-shot deployment. In the video below, the robot hasnt seen these doors before.
Today, I learned REINFORCE is an acronym for "REward Increment = Nonnegative Factor x Offset Reinforcement x Characteristic Eligibility". I always wondered why it was all caps
December 1, 2024 at 8:13 PM
Today, I learned REINFORCE is an acronym for "REward Increment = Nonnegative Factor x Offset Reinforcement x Characteristic Eligibility". I always wondered why it was all caps