Loading...
Market
How many major robotics research papers will cite UC Berkeley's BoT architecture by the end of 2024?
2
Resolution / Starting Odds
0-5 papers • 25%
6-10 papers • 25%
11-15 papers • 25%
16 or more papers • 25%
Citations in peer-reviewed robotics journals or conferences
Story
UC Berkeley Unveils Body Transformer for Enhanced Robot Learning
Aug 13, 2024, 04:38 PM
Researchers at UC Berkeley have introduced the Body Transformer (BoT), an innovative architecture designed to enhance robot learning by leveraging robot embodiment. The BoT architecture integrates a novel masking technique that treats the robot as a graph of sensors and actuators, improving the efficiency and intuitiveness of robot policy learning. This development is seen as a significant step towards creating robots that understand their physical selves as deeply as humans do.
View original story
Similar markets
Less than 10 • 25%
10 to 50 • 25%
51 to 100 • 25%
More than 100 • 25%
Less than 50 • 25%
50 to 100 • 25%
100 to 150 • 25%
More than 150 • 25%
Less than 50 • 25%
50-100 • 25%
101-200 • 25%
More than 200 • 25%
Less than 50 • 25%
50 to 100 • 25%
101 to 200 • 25%
More than 200 • 25%
Yes • 50%
No • 50%
Less than 50 • 33%
50-100 • 33%
More than 100 • 34%
Yes • 50%
No • 50%
