Back to the program.
Advances in massively distributed robotics and machine learning
Roderich Gross
Natural Robotics Lab; Department of Automatic Control and Systems Engineering; The University of Sheffield
UK
r.gross@sheffield.ac.uk

Abstract

In the first part of the talk, we look at how distributed robotic systems that lack the ability to compute arithmetically can accomplish tasks such as aggregation, object clustering, transport, and shepherding. In the second part of the talk, we look at Turing Learning - a novel system identification method, which does not rely on pre-defined metrics - and test its ability to infer the behavior.

Bio:
Roderich Gross received a Computer Science degree from TU Dortmund University in 2001 and a PhD degree from the Universite libre de Bruxelles in 2007. From 2005 to 2009 he was a JSPS Fellow at Tokyo Institute of Technology, a Research Associate at University of Bristol, a Marie Curie Fellow at Unilever, and a Marie Curie Fellow at EPFL. Since 2010, he has been with the Department of Automatic Control and Systems Engineering at the University of Sheffield, where he is currently a Senior Lecturer. His research interests include distributed robotics and machine learning. He has authored 70 publications on these topics, which have been cited 2000 times (h-index 24). Dr Gross serves/has served as the General Chair of DARS 2016, Editor of IROS 2015 - 2017, Associate Editor of ICRA 2014 - 2015, Program Co-Chair of AAMAS 2016 (robotics track), ANTS 2012, and TAROS 2011, Part Editor of the Springer Handbook of Computational Intelligence, and Associate Editor of Swarm Intelligence, IEEE Robotics and Automation Letters, and IEEE Computational Intelligence Magazine.

Keywords

swarm robotics, self-organized aggregation, turing learning