Events

Representations in Robot Manipulation: Learning to Manipulate Cables, Fabrics, Bags, Liquids, and Plants

Speaker: Daniel Seita

Location: 60 Fifth Avenue, Room 150
Videoconference link: https://nyu.zoom.us/j/97773738828

Date: Monday, March 13, 2023

The robotics community has seen significant progress in applying machine learning for robot manipulation. However, much manipulation research focuses on rigid objects instead of highly deformable objects such as cables, fabrics, bags, liquids, and plants, which pose challenges due to their complex configuration spaces, dynamics, and self-occlusions. To achieve greater progress in robot manipulation of such diverse deformable objects, I advocate for an increased focus on learning and developing appropriate representations for robot manipulation. In this talk, I show how novel action-centric representations can lead to better imitation learning for manipulation of diverse deformable objects. I will show how such representations can be learned from color images, depth images, or point cloud observational data. My research demonstrates how novel representations can lead to an exciting new era for robot manipulation of complex objects.