New Research Paradigms in Robotics and AI

Introduction

Deep Learning and more traditional AI paradigms are implicitly based on Descartes’ idea of mind body separation. The very fact that we have two distinct disciplines one for the body (Robotics) and one for the mind (AI) is hard to accept from a philosophical and epistemological standpoint. In particular, the application to physical systems and in particular robotic systems of current Machine/Deep Learning approaches is not straightforward, as usually the data coming from robot sensors are in comparatively limited amounts and the robots interact and affect their environment making for example real time object recognition more problematic. As a matter of fact, the principles of organization of natural intelligent and cognitive agents are rather different from the mainstream design principles of intelligent autonomous systems. In nature, cognition and intelligence are usually embedded in a physical system (a body), emerging bottom-up from the interaction of large numbers of loosely coupled components and is usually associated to Life, while the ‘mechatronics paradigm’ used to build mainstream robots, implements top-down controls, keeping well divided the body (usually a complex mechanical structure, made of rigid parts actuated by electric motors with sophisticated sensors and actuators) from the mind (a set of complex algorithms running on microprocessors arrays).


Modeling and control of intelligent autonomous systems capable to enable the design of complex physical intelligent systems still raise nontrivial research challenges.

Coping with those challenges is necessary if we aim to develop artificial intelligent systems with levels of robustness and adaptivity on par with the natural ones and understand natural intelligence, cognition and life itself.


In this workshop we will analyze strengths and weaknesses of current and novel methods and discuss how to move forward in research and applications of AI to Robotics, more precisely in Physical AI

Invited speakers

Toshio Fukuda

Mejio University

Yannis Aloiminos

University of Maryland

Josh Bongard

University of Vermont

Fabio Bonsignorio

University of Zagreb Faculty of Electrical Engineering and Computing

Paper Submission

  • Maximum of 4 pages IAS template

  • Submit using one of the available templates

  • When submitting your paper please choose an option "New Research Paradigms in Robotics and AI" under "Other Information and Files" card.

  • Accepted papers will be published on the workshop website.

  • Accepted papers will not be published in the conference proceedings

  • Authors will be asked to present a poster at the conference workshop

  • Posters will be published to the workshop website after the conference.

Important dates

  • Paper submission deadline: May 13 May 20

  • Notification of acceptance: May 16 May 23

  • Poster submission: May 27

  • Workshop date: June 13th

Program timeline (June 13, 2022)

Sponsors

For more information visit the conference sponsoring page.

Organizing committee

Fabio Bonsignorio

ERA Chair in AI for Robotics

University of Zagreb Faculty of Electrical Engineering and Computing

Heron Robots s.r.l.

Workshop Chair