An interaction-aware, perceptual model for non-linear elastic objects
Everyone, from a shopper buying shoes to a doctor palpating a growth, uses their sense of touch to learn about the world. 3D printing is a powerful technology because it gives us the ability to control the haptic impression an object creates. This is critical for both replicating existing, real-worl...
| Main Authors: | , , , , , , , |
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| Other Authors: | |
| Format: | Article |
| Language: | en_US |
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Association for Computing Machinery (ACM)
2017
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| Online Access: | http://hdl.handle.net/1721.1/111686 https://orcid.org/0000-0003-2336-6235 https://orcid.org/0000-0003-0212-5643 |
| _version_ | 1826212927629164544 |
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| author | Piovarči, Michal Levin, David I. W. Rebello, Jason Chen, Desai Ďurikovič, Roman Pfister, Hanspeter Matusik, Wojciech Didyk, Piotr |
| author2 | Massachusetts Institute of Technology. Computer Science and Artificial Intelligence Laboratory |
| author_facet | Massachusetts Institute of Technology. Computer Science and Artificial Intelligence Laboratory Piovarči, Michal Levin, David I. W. Rebello, Jason Chen, Desai Ďurikovič, Roman Pfister, Hanspeter Matusik, Wojciech Didyk, Piotr |
| author_sort | Piovarči, Michal |
| collection | MIT |
| description | Everyone, from a shopper buying shoes to a doctor palpating a growth, uses their sense of touch to learn about the world. 3D printing is a powerful technology because it gives us the ability to control the haptic impression an object creates. This is critical for both replicating existing, real-world constructs and designing novel ones. However, each 3D printer has different capabilities and supports different materials, leaving us to ask: How can we best replicate a given haptic result on a particular output device? In this work, we address the problem of mapping a real-world material to its nearest 3D printable counterpart by constructing a perceptual model for the compliance of nonlinearly elastic objects. We begin by building a perceptual space from experimentally obtained user comparisons of twelve 3D-printed metamaterials. By comparing this space to a number of hypothetical computational models, we identify those that can be used to accurately and efficiently evaluate human-perceived differences in nonlinear stiffness. Furthermore, we demonstrate how such models can be applied to complex geometries in an interaction-aware way where the compliance is influenced not only by the material properties from which the object is made but also its geometry. We demonstrate several applications of our method in the context of fabrication and evaluate them in a series of user experiments. |
| first_indexed | 2024-09-23T15:40:23Z |
| format | Article |
| id | mit-1721.1/111686 |
| institution | Massachusetts Institute of Technology |
| language | en_US |
| last_indexed | 2024-09-23T15:40:23Z |
| publishDate | 2017 |
| publisher | Association for Computing Machinery (ACM) |
| record_format | dspace |
| spelling | mit-1721.1/1116862022-09-29T15:25:32Z An interaction-aware, perceptual model for non-linear elastic objects Piovarči, Michal Levin, David I. W. Rebello, Jason Chen, Desai Ďurikovič, Roman Pfister, Hanspeter Matusik, Wojciech Didyk, Piotr Massachusetts Institute of Technology. Computer Science and Artificial Intelligence Laboratory Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science Chen, Desai Matusik, Wojciech Everyone, from a shopper buying shoes to a doctor palpating a growth, uses their sense of touch to learn about the world. 3D printing is a powerful technology because it gives us the ability to control the haptic impression an object creates. This is critical for both replicating existing, real-world constructs and designing novel ones. However, each 3D printer has different capabilities and supports different materials, leaving us to ask: How can we best replicate a given haptic result on a particular output device? In this work, we address the problem of mapping a real-world material to its nearest 3D printable counterpart by constructing a perceptual model for the compliance of nonlinearly elastic objects. We begin by building a perceptual space from experimentally obtained user comparisons of twelve 3D-printed metamaterials. By comparing this space to a number of hypothetical computational models, we identify those that can be used to accurately and efficiently evaluate human-perceived differences in nonlinear stiffness. Furthermore, we demonstrate how such models can be applied to complex geometries in an interaction-aware way where the compliance is influenced not only by the material properties from which the object is made but also its geometry. We demonstrate several applications of our method in the context of fabrication and evaluate them in a series of user experiments. 2017-10-03T19:05:41Z 2017-10-03T19:05:41Z 2016-07 Article http://purl.org/eprint/type/ConferencePaper 0730-0301 http://hdl.handle.net/1721.1/111686 Piovarči, Michal et al. “An Interaction-Aware, Perceptual Model for Non-Linear Elastic Objects.” ACM Transactions on Graphics 35, 4 (July 2016): 1–13 © 2016 The Author(s) https://orcid.org/0000-0003-2336-6235 https://orcid.org/0000-0003-0212-5643 en_US http://dx.doi.org/10.1145/2897824.2925885 ACM Transactions on Graphics Creative Commons Attribution-Noncommercial-Share Alike http://creativecommons.org/licenses/by-nc-sa/4.0/ application/pdf Association for Computing Machinery (ACM) Other univ. web domain |
| spellingShingle | Piovarči, Michal Levin, David I. W. Rebello, Jason Chen, Desai Ďurikovič, Roman Pfister, Hanspeter Matusik, Wojciech Didyk, Piotr An interaction-aware, perceptual model for non-linear elastic objects |
| title | An interaction-aware, perceptual model for non-linear elastic objects |
| title_full | An interaction-aware, perceptual model for non-linear elastic objects |
| title_fullStr | An interaction-aware, perceptual model for non-linear elastic objects |
| title_full_unstemmed | An interaction-aware, perceptual model for non-linear elastic objects |
| title_short | An interaction-aware, perceptual model for non-linear elastic objects |
| title_sort | interaction aware perceptual model for non linear elastic objects |
| url | http://hdl.handle.net/1721.1/111686 https://orcid.org/0000-0003-2336-6235 https://orcid.org/0000-0003-0212-5643 |
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