List of Speakers

Workshop Schedule

Time (CET)*Time (PDST)*NamesTheme
16:00 – 16:1008:00 – 08:10Arne, Elmar, KimWelcome & Agenda
16:10 – 16:3008:10 – 08:30Jan PetersRobot Learning Lessons from Motor Skill Learning
16:30 – 16:5008:30 – 08:50Freek StulpCommon-sense exploration for Robotic Learning
16:50 – 17:1008:50 – 09:10Marc ToussaintLearning to do as planned
17:10 – 17:3009:10 – 09:30Georg v. WichertCombining Machine Learning and first principle models
17:30 – 17:4009:30 – 09:40BREAK
17:40 – 18:0009:40 – 10:00Patrick van der SmagtLearning models in models
18:00 – 18:2010:00 – 10:20Dileep GeorgeData-efficient learning for robotics
18:20 – 18:4010:20 – 10:40Sergey LevineData-driven Reinforcement Learning for Robotics
18:40 – 19:0010:40 – 11:00Pieter AbbeelRobot learning for the real world
19:00 – 19:3011:00 – 11:30Open panelWhat is the future of Robot Learning and what will it bring for society, industry etc.?
19:30 – 20:0011:30 – 12:00Virtual AperoGet together with Music and chatting (among the organizers and speakers)
*Europe will switch to from DST to „winter time“ already on Oct 25, while the US will switch no earlier than Nov 1st => time diff for the workshop will be -8 h (instead of the normal -9 h)

Workshop Summary

Robot learning combines the challenges of understanding, modeling and applying dynamical systems with task learning from rewards, through human robot interaction or from intrinsic motivation signals. While outstanding results using machine and deep learning have been generated in robot learning in the last years, current challenges in industrial applications are underrepresented. The goal of this workshop is to go beyond discussing potential industrial applications like in related past workshops.

The core elements of this event are industrial specific challenges, novel machine and deep learning approaches and unsolved complex problems. For that we will bring together leading experts from academia and industry to discuss current and future challenges in the application of learning mechanisms in industry. We try to have a problem-based look on robot learning: which methods would really help to advance robot learning applications and what are the demands from industry in the first place. Spiced with a discussion between various industrial as well as academic leaders this is unmatched by any classical conference session.

Organizers

Dr. Kim Daniel Listmann, Head of ABB Future Labs Switzerland, kim.listmann@ch.abb.com, +41 79 325 9946

ABB Switzerland Ltd, Segelhofstrasse 1K, 5405 Baden-Dättwil, Switzerland.

Prof. Dr. Elmar Rueckert, Professor at the Institute for Robotics and Cognitive Systems, rueckert@rob.uniluebeck.de, +49 451 310 15 209

University of Luebeck, Ratzeburger Allee 160, 23562 Luebeck, Germany.

arne_wahrburg_200

Dr. Arne Wahrburg, Senior Principal Scientist, ABB Corporate Research Germany,  arne.wahrburg@de.abb.com, +49 6203 716166

ABB AG, Wallstadter Str. 59, 68526 Ladenburg, Germany.