Patrick Slade, Christopher Atkeson, J. Maxwell Donelan, Han Houdijk, Kimberly A. Ingraham, Myunghee Kim, Kyoungchul Kong, Katherine L. Poggensee, Robert Riener, Martin Steinert, Juanjuan Zhang, Steven H. Collins
{"title":"On human-in-the-loop optimization of human–robot interaction","authors":"Patrick Slade, Christopher Atkeson, J. Maxwell Donelan, Han Houdijk, Kimberly A. Ingraham, Myunghee Kim, Kyoungchul Kong, Katherine L. Poggensee, Robert Riener, Martin Steinert, Juanjuan Zhang, Steven H. Collins","doi":"10.1038/s41586-024-07697-2","DOIUrl":null,"url":null,"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. A new approach to designing robotic systems that interact closely with people, called human-in-the-loop optimization, can improve human–robot interaction, but many important research questions remain before it can reach its full potential.","PeriodicalId":18787,"journal":{"name":"Nature","volume":null,"pages":null},"PeriodicalIF":50.5000,"publicationDate":"2024-09-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Nature","FirstCategoryId":"103","ListUrlMain":"https://www.nature.com/articles/s41586-024-07697-2","RegionNum":1,"RegionCategory":"综合性期刊","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"MULTIDISCIPLINARY SCIENCES","Score":null,"Total":0}
引用次数: 0
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. A new approach to designing robotic systems that interact closely with people, called human-in-the-loop optimization, can improve human–robot interaction, but many important research questions remain before it can reach its full potential.
期刊介绍:
Nature is a prestigious international journal that publishes peer-reviewed research in various scientific and technological fields. The selection of articles is based on criteria such as originality, importance, interdisciplinary relevance, timeliness, accessibility, elegance, and surprising conclusions. In addition to showcasing significant scientific advances, Nature delivers rapid, authoritative, insightful news, and interpretation of current and upcoming trends impacting science, scientists, and the broader public. The journal serves a dual purpose: firstly, to promptly share noteworthy scientific advances and foster discussions among scientists, and secondly, to ensure the swift dissemination of scientific results globally, emphasizing their significance for knowledge, culture, and daily life.