IEEE ICMA 2019 Conference

Plenary Talk III

The New Wave in Robot Grasping

Ken Goldberg, Ph.D.
Professor and Director
William S. Floyd Jr. Distinguished Chair in Engineering
Department Chair, Industrial Engineering / Operations Research (IEOR)
Director, AUTOLAB and CITRIS "People and Robots" Initiative Founding Member,
Berkeley AI Research (BAIR) Lab Joint Appointments: EECS, Art Practice, School of
Information (UC Berkeley) and Radiation Oncology (UC San Francisco Medical School).
University of California, Berkeley
E-mail: goldberg@berkeley.edu
hhttp://goldberg.berkeley.edu

Abstract:

Robots are about to become far more dextrous based on a new wave in research that combines classical mechanics, stochastic, and deep learning.
Despite 50 years of research, robots remain remarkably clumsy, limiting their reliability for warehouse order fulfillment, robot-assisted surgery, and home decluttering. The First Wave of grasping research is purely analytical, applying variations of screw theory to exact knowledge of pose, shape, and contact mechanics. The Second Wave is purely empirical: end-to-end hyperparametric function approximation (aka Deep Learning) based on human demonstrations or time-consuming self-exploration. A "New Wave" of research considers hybrid methods that combine analytic models with stochastic sampling and Deep Learning models. I'll present this history with new results from our lab on grasping diverse and previously-unknown objects and discuss exciting future research including cloud and fog robotics.

Prof. Ken Goldberg is an artist, inventor, and UC Berkeley Professor focusing on robotics. He was appointed the William S. Floyd Jr Distinguished Chair in Engineering and serves as Chair of the Industrial Engineering and Operations Research Department. He has secondary appointments in EECS, Art Practice, the School of Information, and Radiation Oncology at the UCSF Medical School. Ken is Director of the CITRIS "People and Robots" Initiative and the UC Berkeley AUTOLAB where he and his students pursue research in machine learning for robotics and automation in warehouses, homes, and operating rooms. Ken developed the first provably complete algorithms for part feeding and part fixturing and the first robot on the Internet. Despite agonizingly slow progress, he persists in trying to make robots less clumsy. He has over 250 peer-reviewed publications and 8 U.S. Patents. He co-founded and served as Editor-in-Chief of the IEEE Transactions on Automation Science and Engineering. Ken's artwork has appeared in 70 exhibits including the Whitney Biennial and films he has co-written have been selected for Sundance and nominated for an Emmy Award. Ken was awarded the NSF PECASE (Presidential Faculty Fellowship) from President Bill Clinton in 1995, elected IEEE Fellow in 2005 and selected by the IEEE Robotics and Automation Society for the George Saridis Leadership Award in 2016.
More information can be obtained in http://goldberg.berkeley.edu.