Robohub.org
ep.

257

podcast
 

Learning Robot Objectives from Physical Human Interaction with Andrea Bajcsy and Dylan P. Losey


by
31 March 2018



share this:




In this interview, Audrow speaks with Andrea Bajcsy and Dylan P. Losey about a method that allows robots to infer a human’s objective through physical interaction. They discuss their approach, the challenges of learning complex tasks, and their experience collaborating between different universities.

Some examples of people working with the more typical impedance control (left) and Bajcsy and Losey’s learning method (right).


To learn more, see this post on Robohub from the Berkeley Artificial Intelligence Research (BAIR) Lab.

Andrea Bajcsy
Andrea Bajcsy is a Ph.D. student in Electrical Engineering and Computer Sciences at the University of California Berkeley. She received her B.S. degree in Computer Science at the University of Maryland and was awarded the NSF Graduate Research Fellowship in 2016. At Berkeley, she works in the Interactive Autonomy and Collaborative Technologies Laboratory researching physical human-robot interaction.

Dylan P. Losey


Dylan P. Losey received the B.S. degree in mechanical engineering from Vanderbilt University, Nashville, TN, USA, in 2014, and the M.S. degree in mechanical engineering from Rice University, Houston, TX, USA, in 2016.

He is currently working towards the Ph.D. degree in mechanical engineering at Rice University, where he has been a member of the Mechatronics and Haptic Interfaces Laboratory since 2014.  In addition, between May and August 2017, he was a visiting scholar in the Interactive Autonomy and Collaborative Technologies Laboratory at the University of California, Berkeley.  He researches physical human-robot interaction; in particular, how robots can learn from and adapt to human corrections.

Mr. Losey received an NSF Graduate Research Fellowship in 2014, and the 2016 IEEE/ASME Transactions on Mechatronics Best Paper Award as a first author.

Links



tags: , , , , , ,


Audrow Nash is a Software Engineer at Open Robotics and the host of the Sense Think Act Podcast
Audrow Nash is a Software Engineer at Open Robotics and the host of the Sense Think Act Podcast

            AUAI is supported by:



Subscribe to Robohub newsletter on substack



Related posts :

AIhub coffee corner: Are humanoids the future of embodied AI?

  09 Nov 2026
The AIhub coffee corner captures the musings of AI experts over a short conversation.

Robot Talk Episode 169 – Robot sensing inspired by nature, with Dexter Shepherd

  06 Nov 2026
In the latest episode of the Robot Talk podcast, Claire chatted to Dexter Shepherd from the University of Sussex about using artificial intelligence to help robots understand and adapt to their environment.

Robots in society, business and culture: October 2026

We showcase a selection of robotics stories from society, business, research and culture.

Muscle coordination can be mimicked by electric motors – it could lead to improved robots

  02 Nov 2026
Researchers built a physical model using ordinary electric motors to try and simulate how muscles may perform tasks.

Robot Talk Episode 168 – Advancing robotics with novel electronics, with Zlatka Stoeva

  30 Oct 2026
In the latest episode of the Robot Talk podcast, Claire chatted to Zlatka Stoeva from DZP Technologies about flexible, stretchable and soft printed electronics for dexterous robots.

Competing in RoboCup@Home and winning the 2026 best paper award: an interview with Raphael Memmesheimer

and   28 Oct 2026
Hear more about Raphael's research and his involvement in the RoboCup@Home league.

Robots in society, business and culture: September 2026

We showcase a selection of robotics stories from society, business, research and culture.

Robot Talk Episode 167 – Automating construction, with Jan Petrš

  23 Oct 2026
In the latest episode of the Robot Talk podcast, Claire chatted to Jan Petrš from École Polytechnique Fédérale de Lausanne about novel robot designs for construction and architecture.


↑


AUAI is supported by:







Subscribe to Robohub newsletter on substack




 















©2026.05 - Association for the Understanding of Artificial Intelligence