Robohub.org
 

Nikolas Martelaro’s talk – Remote user research for human-robot interaction – with video


by
15 December 2020



share this:

On Friday the 11th of December, Nikolas Martelaro (Assistant Professor at Carnegie Mellon’s Human-Computer Interaction Institute) gave an online seminar on ways robot design teams can do remote user research now (in these COVID-19 times) and in the future. If you missed it, you can now watch the recorded livestream.

About the speaker

Nikolas Martelaro

Nikolas Martelaro is an Assistant Professor at Carnegie Mellon’s Human-Computer Interaction Institute. Martelaro’s lab focuses on augmenting designer’s capabilities through the use of new technology and design methods. Martelaro’s interest in developing new ways to support designers stems from my interest in creating interactive and intelligent products. Martelaro blends a background in product design methods, interaction design, human-robot interaction, and mechatronic engineering to build tools and methods that allow designers to understand people better and to create more human-centered products. Before moving to the HCII, Nikolas Martelaro was a researcher in the Digital Experiences group at the Accenture Technology Labs. Martelaro graduated with a Ph.D. in Mechanical Engineering from Stanford’s Center for Design Research where he was co-advised by Larry Leifer and Wendy Ju.

Abstract

COVID-19 has led to decreases in in-person user research. While designers who work on software can shift to using all digital remote research methods, people who work on hardware systems, including robots, are left with limited options. In this talk, I will discuss some ways the robot design teams can do remote user research now and in the future. I will draw on past work in human-computer interaction as well as my own work in creating systems to allow remote design teams to conduct remote observation and interaction prototyping. While things can be challenging for the user researcher team today, I believe that with some creative new methods, we can expand our abilities to do user research for robotics from anywhere in the world.

Papers covered during the talk



tags: ,


Talking Robotics

            AUAI is supported by:



Subscribe to Robohub newsletter on substack



Related posts :

AI system learns to keep warehouse robot traffic running smoothly

  20 Apr 2026
This new approach adapts to decide which robots should get the right of way at every moment, avoiding congestion and increasing throughput.

Robot Talk Episode 152 – Dexterous robot hands, with Rich Walker

  17 Apr 2026
In the latest episode of the Robot Talk podcast, Claire chatted to Rich Walker from Shadow Robot Company about their advanced robotic hands for research and industry.

What I’ve learned from 25 years of automated science, and what the future holds: an interview with Ross King

and   14 Apr 2026
Ross King created the first robot scientist back in 2009. He spoke to us about the nature of scientific discovery, the role AI has to play, and his recent work in DNA computing.

Robot Talk Episode 151 – Robots to study the ocean, with Simona Aracri

  10 Apr 2026
In the latest episode of the Robot Talk podcast, Claire chatted to Simona Aracri from National Research Council of Italy about innovative robot designs for oceanography and environmental monitoring.

Generative AI improves a wireless vision system that sees through obstructions

  08 Apr 2026
With this new technique, a robot could more accurately detect hidden objects or understand an indoor scene using reflected Wi-Fi signals.

Resource-constrained image generation and visual understanding: an interview with Aniket Roy

  07 Apr 2026
Aniket tells us about his research exploring how modern generative models can be adapted to operate efficiently while maintaining strong performance.

Back to school: robots learn from factory workers

  02 Apr 2026
A Czech startup is making factory automation easier by letting workers teach robots new tasks through simple demonstrations instead of complex coding.

Resource-sharing boosts robotic resilience

  31 Mar 2026
When a modular robot shares power, sensing, and communication resources among its individual units, it is significantly more resistant to failure than traditional robotic systems.



AUAI is supported by:







Subscribe to Robohub newsletter on substack




 















©2026.02 - Association for the Understanding of Artificial Intelligence