{"title":"From conventional to programmable matter systems: A review of design, materials, and technologies","authors":"Ahmed Amine Chafik, Jaafar Gaber, Souad Tayane, Mohamed Ennaji, Julien Bourgeois, Tarek El-Ghazawi","doi":"10.1145/3653671","DOIUrl":null,"url":null,"abstract":"<p>Programmable matter represents a system of elements whose interactions can be programmed for a certain behavior to emerge (e.g. color, shape) upon suitable commands (e.g., instruction, stimuli) by altering its physical characteristics. Even though its appellation may refer to a morphable physical material, programmable matter has been represented through several approaches from different perspectives (e.g., robots, smart materials) that seek the same objective: controllable behavior such as smart shape alteration. Researchers, engineers, and artists have expressed interest in the development of smart modeling clay as a novel alternative to conventional matter and classical means of prototyping. Henceforth, users will be able to do/undo/redo forms based on computed data (CAD) or interactions (sensors), which will help them unlock more features and increase the usefulness of their products. However, with such a promising technology, many challenges need to be addressed, as programmable matter relies on energy consumption, data transmission, stimuli control, and shape formation mechanisms. Furthermore, numerous devices and technologies are created under the name of programmable matter, which may pose ambiguity to the control strategies. In this study, we determine the basic operations required to form a shape, then review different realizations using the shape shifting ability of programmable matter, their fitting classifications, and finally discuss potential challenges.</p>","PeriodicalId":50926,"journal":{"name":"ACM Computing Surveys","volume":null,"pages":null},"PeriodicalIF":23.8000,"publicationDate":"2024-03-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"ACM Computing Surveys","FirstCategoryId":"94","ListUrlMain":"https://doi.org/10.1145/3653671","RegionNum":1,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"COMPUTER SCIENCE, THEORY & METHODS","Score":null,"Total":0}
引用次数: 0
Abstract
Programmable matter represents a system of elements whose interactions can be programmed for a certain behavior to emerge (e.g. color, shape) upon suitable commands (e.g., instruction, stimuli) by altering its physical characteristics. Even though its appellation may refer to a morphable physical material, programmable matter has been represented through several approaches from different perspectives (e.g., robots, smart materials) that seek the same objective: controllable behavior such as smart shape alteration. Researchers, engineers, and artists have expressed interest in the development of smart modeling clay as a novel alternative to conventional matter and classical means of prototyping. Henceforth, users will be able to do/undo/redo forms based on computed data (CAD) or interactions (sensors), which will help them unlock more features and increase the usefulness of their products. However, with such a promising technology, many challenges need to be addressed, as programmable matter relies on energy consumption, data transmission, stimuli control, and shape formation mechanisms. Furthermore, numerous devices and technologies are created under the name of programmable matter, which may pose ambiguity to the control strategies. In this study, we determine the basic operations required to form a shape, then review different realizations using the shape shifting ability of programmable matter, their fitting classifications, and finally discuss potential challenges.
期刊介绍:
ACM Computing Surveys is an academic journal that focuses on publishing surveys and tutorials on various areas of computing research and practice. The journal aims to provide comprehensive and easily understandable articles that guide readers through the literature and help them understand topics outside their specialties. In terms of impact, CSUR has a high reputation with a 2022 Impact Factor of 16.6. It is ranked 3rd out of 111 journals in the field of Computer Science Theory & Methods.
ACM Computing Surveys is indexed and abstracted in various services, including AI2 Semantic Scholar, Baidu, Clarivate/ISI: JCR, CNKI, DeepDyve, DTU, EBSCO: EDS/HOST, and IET Inspec, among others.