February 16, 2024
Shuran Song of Stanford University
What do we need to take robot learning to the 'next level?' Is it better algorithms, improved policy representations, or is it advancements in affordable robot hardware? While all of these factors are undoubtedly important, however, what I really wish for is something that underpins all these aspects - the right data. In particular, we need data that is scalable, reusable, and robot-complete. While ‘scale’ often takes center stage in machine learning today; I would argue that in robotics, having data that is also both reusable and complete can be just as important. Focusing on sheer quantity and neglecting these properties make it difficult for robot learning to benefit from the same scaling trend that other machine learning fields have enjoyed. In this talk, we will explore potential solutions to such data challenges, shed light on some of the often-overlooked hidden costs associated with each approach, and more importantly, how to potentially bypass these obstacles.
About the speaker: shurans.github.io/
More about the course can be found here: stanfordasl.github.io/robotic...
View the entire AA289 Stanford Robotics and Autonomous Systems Seminar playlist: • Stanford AA289 - Robot...
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4 мар 2024
