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A manifesto for Sustainability Robotics

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dc.contributor.author Song, S. -
dc.contributor.author Mazzolai, B. -
dc.contributor.author Kovač, M. -
dc.date.accessioned 2026-09-29T14:10:16Z -
dc.date.available 2026-09-29T14:10:16Z -
dc.date.created 2026-07-24 -
dc.date.issued 2026-07 -
dc.identifier.issn 2522-5839 -
dc.identifier.uri https://scholar.dgist.ac.kr/handle/20.500.11750/60898 -
dc.description.abstract Sustainability spans environmental, societal and economic challenges, from climate change to healthcare and education. Robotics holds substantial promise for addressing these issues, yet current developments remain fragmented and lack a unifying framework. This fragmentation risks unintended consequences, including unequal access to technology and missed opportunities for broader impact. Here we advocate for a new discipline, Sustainability Robotics, structured around three guiding principles: robots should be minimally invasive, reducing disruption to ecosystems and socio-economic systems; universally accessible, extending benefits to underserved communities and extreme environments; and symbiotic, generating mutually beneficial outcomes for humans and nature. We define two complementary dimensions. The first, sustainable robot design, focuses on minimizing environmental impact through materials, energy and manufacturing. The second, robotic solutions for sustainability, leverages robotics to address environmental, social and economic challenges. By integrating perspectives from science, engineering, economics, ethics and policy, Sustainability Robotics provides a foundation for coordinated research, education and innovation. This framework aims to align robotics development with global sustainability goals, enabling more equitable and effective technological impact. -
dc.language English -
dc.publisher NATURE PORTFOLIO -
dc.title A manifesto for Sustainability Robotics -
dc.type Article -
dc.identifier.doi 10.1038/s42256-026-01260-6 -
dc.identifier.wosid 001818235100001 -
dc.identifier.scopusid 2-s2.0-105044458826 -
dc.identifier.bibliographicCitation NATURE MACHINE INTELLIGENCE, v.8, no.7, pp.1038 - 1044 -
dc.description.isOpenAccess FALSE -
dc.subject.keywordPlus FUTURE -
dc.subject.keywordPlus CO2 -
dc.citation.endPage 1044 -
dc.citation.number 7 -
dc.citation.startPage 1038 -
dc.citation.title NATURE MACHINE INTELLIGENCE -
dc.citation.volume 8 -
dc.description.journalRegisteredClass scie -
dc.description.journalRegisteredClass scopus -
dc.relation.journalResearchArea Computer Science -
dc.relation.journalWebOfScienceCategory Computer Science, Artificial Intelligence; Computer Science, Interdisciplinary Applications -
dc.type.docType Review -
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