Improving data efficiency and accessibility for general robotic manipulation

Speaker: Hao-Shu Fang , CSAIL MIT

Date: Thursday, April 18, 2024

Time: 4:00 PM to 4:30 PM Note: all times are in the Eastern Time Zone

Public: Yes

Location: Room 32-370

Event Type: Seminar

Room Description: Room 32-370

Host: Thien Le, CSAIL MIT

Contact: Thien Le, thienle@csail.mit.edu

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Reminders to: mitml@mit.edu, lids-seminars@mit.edu, seminars@csail.mit.edu

Reminder Subject: TALK: Improving data efficiency and accessibility for general robotic manipulation

Abstract: How can data-driven approaches endow robots with diverse manipulative skills and robust performance in unstructured environments? Despite recent progress, many open questions remain in this area, such as: (1) How can we define and model the data distribution for robotic systems? (2) In light of data scarcity, what strategies can algorithms employ to enhance performance? (3) What is the best way to scale up robotic data collection? In this talk, Hao-Shu Fang will share his research on enhancing the efficiency of robot learning algorithms and democratizing access to large-scale robotic manipulation data. He will also discuss several open questions in data-driven robotic manipulation, offering insights to the challenges posed.

Bio: Hao-Shu Fang is a postdoctoral researcher collaborating with Pulkit Agrawal and Edward Adelson. His research focuses on general robotic manipulation. Recently, he has been investigating how to integrate visual-tactile perception for improved manipulation and how to train a multi-task robotic foundation behavioral model.

Research Areas:
Robotics

Impact Areas:

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Created by Thien Le at Tuesday, April 16, 2024 at 1:44 AM.