Categorizing robots by performance fitness into the tree of robots

IF 18.8 1区 计算机科学 Q1 COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE Nature Machine Intelligence Pub Date : 2025-02-21 DOI:10.1038/s42256-025-00995-y
Robin Jeanne Kirschner, Kübra Karacan, Alessandro Melone, Sami Haddadin
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Abstract

Robots are typically classified based on specific morphological features, like their kinematic structure. However, a complex interplay between morphology and intelligence shapes how well a robot performs processes. Just as delicate surgical procedures demand high dexterity and tactile precision, manual warehouse or construction work requires strength and endurance. These process requirements necessitate robot systems that provide a level of performance fitting the process. In this work, we introduce the tree of robots as a taxonomy to bridge the gap between morphological classification and process-based performance. It classifies robots based on their fitness to perform, for example, physical interaction processes. Using 11 industrial manipulators, we constructed the first part of the tree of robots based on a carefully deduced set of metrics reflecting fundamental robot capabilities for various industrial physical interaction processes. Through significance analysis, we identified substantial differences between the systems, grouping them via an expectation-maximization algorithm to create a fitness-based robot classification that is open for contributions and accessible.

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CiteScore
36.90
自引率
2.10%
发文量
127
期刊介绍: Nature Machine Intelligence is a distinguished publication that presents original research and reviews on various topics in machine learning, robotics, and AI. Our focus extends beyond these fields, exploring their profound impact on other scientific disciplines, as well as societal and industrial aspects. We recognize limitless possibilities wherein machine intelligence can augment human capabilities and knowledge in domains like scientific exploration, healthcare, medical diagnostics, and the creation of safe and sustainable cities, transportation, and agriculture. Simultaneously, we acknowledge the emergence of ethical, social, and legal concerns due to the rapid pace of advancements. To foster interdisciplinary discussions on these far-reaching implications, Nature Machine Intelligence serves as a platform for dialogue facilitated through Comments, News Features, News & Views articles, and Correspondence. Our goal is to encourage a comprehensive examination of these subjects. Similar to all Nature-branded journals, Nature Machine Intelligence operates under the guidance of a team of skilled editors. We adhere to a fair and rigorous peer-review process, ensuring high standards of copy-editing and production, swift publication, and editorial independence.
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