Author
Listed:
- Patrick Slade
(Harvard University)
- Christopher Atkeson
(Carnegie Mellon University)
- J. Maxwell Donelan
(Simon Fraser University)
- Han Houdijk
(University of Groningen)
- Kimberly A. Ingraham
(University of Washington)
- Myunghee Kim
(University of Illinois Chicago)
- Kyoungchul Kong
(Korea Advanced Institute of Science and Technology (KAIST))
- Katherine L. Poggensee
(Erasmus Medical Center
Delft University of Technology)
- Robert Riener
(ETH Zurich
University of Zurich)
- Martin Steinert
(Norwegian University of Science and Technology (NTNU))
- Juanjuan Zhang
(Nankai University)
- Steven H. Collins
(Stanford University)
Abstract
From industrial exoskeletons to implantable medical devices, robots that interact closely with people are poised to improve every aspect of our lives. Yet designing these systems is very challenging; humans are incredibly complex and, in many cases, we respond to robotic devices in ways that cannot be modelled or predicted with sufficient accuracy. A new approach, human-in-the-loop optimization, can overcome these challenges by systematically and empirically identifying the device characteristics that result in the best objective performance for a specific user and application. This approach has enabled substantial improvements in human–robot performance in research settings and has the potential to speed development and enhance products. In this Perspective, we describe methods for applying human-in-the-loop optimization to new human–robot interaction problems, addressing each key decision in a variety of contexts. We also identify opportunities to develop new optimization techniques and answer underlying scientific questions. We anticipate that our readers will advance human-in-the-loop optimization and use it to design robotic devices that truly enhance the human experience.
Suggested Citation
Patrick Slade & Christopher Atkeson & J. Maxwell Donelan & Han Houdijk & Kimberly A. Ingraham & Myunghee Kim & Kyoungchul Kong & Katherine L. Poggensee & Robert Riener & Martin Steinert & Juanjuan Zha, 2024.
"On human-in-the-loop optimization of human–robot interaction,"
Nature, Nature, vol. 633(8031), pages 779-788, September.
Handle:
RePEc:nat:nature:v:633:y:2024:i:8031:d:10.1038_s41586-024-07697-2
DOI: 10.1038/s41586-024-07697-2
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