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GRASP Special Seminar: Andreas ten Pas, Northeastern University, “Machine Learning for Grasp Pose Detection and Beyond”

February 22, 2018 @ 9:30 am - 10:30 am


We present a grasp detection method that can be used to localize robotic grasp configurations directly from sensor data without estimating object pose. Our method takes a point cloud from an RGBD-camera, like the Microsoft Kinect, as input and produces 6-DOF grasp pose estimates. We use an algorithmic framework that first generates a large number of grasp candidates and then uses machine learning to predict if a candidate is a viable grasp. Our method is evaluated on both challenging tabletop scenarios and an assistive mobile manipulator. Beyond using machine learning for grasp perception, we explore how to extend this approach to pick and place problems where we have to reason about an object’s orientation.


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Andreas ten Pas is currently a Ph.D. candidate in the Helping Hands Lab in the College of Computer and Information Science at Northeastern University, advised by Professor Robert Platt. His main interests are in the field of perception for robotic grasping and manipulation. Andreas is the author of several ROS packages that allow to efficiently grasp objects in cluttered environments. These packages have been used by both academic labs and industrial companies.

Andreas has a M.Sc. in Artificial Intelligence and a B.Sc. in Knowledge Engineering and Computer Science from Maastricht University, The Netherlands. He worked as an intern at the Jet Propulsion Laboratory. Andreas also served as a reviewer for IROS, ICRA, and Humanoids.


February 22, 2018
9:30 am - 10:30 am