Robohub Podcast – Presented work at IROS 2018 (Part 1 of 3), with Alexandros Kogkas, Katie Driggs-Campbell, and Martin Karlsson

Listen in to another good podcast from the team at Robohub. More podcasts from them can be found here.

In this episode, Audrow Nash interviews Alexandros Kogkas, Katie Driggs-Campbell, and Martin Karlsson about the work they presented at the 2018 International Conference on Intelligent Robots and Systems (IROS) in Madrid, Spain.

Alexandros Kogkas is a PhD Candidate at the Imperial College London and he speaks about an eye-tracking framework to understand where a person is looking.  This framework can be used to understand a person’s intentions, for example, to hand a surgeon the correct tool or helping a person who is paraplegic. Kogkas discusses how the framework works, possible applications, and his future plans for this framework.

Katie Driggs-Campbell is a Post Doctoral Researcher at Stanford’s Intelligent System Laboratory and is—soon to be—an Assistant Professor at the University of Illinois Urbana-Champaign (UIUC). She speaks about making inferences about the world from human actions, specifically in the context of autonomous cars. In the work she discusses, they use a model of a human driver that they use to infer what is happening in the world, for example, a human using a crosswalk. Driggs-Campbell talks about how they evaluate this work.

Martin Karlsson is a PhD student at Lund University in Sweden, and he speaks about a haptic interface to mirror robotic arms that require no force sensing.  He discusses a feedback law that allows a mirroring of forces and his future work to deal with joint friction.