Bionic Design Model for Co-creative Product Innovation Based on Deep Generative and BID
Abstract Bio-inspired design (BID) is an abstract process, if we can visualize the process of fusing abstract biological inspiration with figurative product shapes, and combine it with artificial intelligence technology to express the designer’s creativity, it will greatly improve the efficiency and...
| Main Authors: | , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Springer
2023-02-01
|
| Series: | International Journal of Computational Intelligence Systems |
| Subjects: | |
| Online Access: | https://doi.org/10.1007/s44196-023-00187-9 |
| _version_ | 1811165705825943552 |
|---|---|
| author | ZhengGen Deng Jian Lv Xiang Liu YuKang Hou |
| author_facet | ZhengGen Deng Jian Lv Xiang Liu YuKang Hou |
| author_sort | ZhengGen Deng |
| collection | DOAJ |
| description | Abstract Bio-inspired design (BID) is an abstract process, if we can visualize the process of fusing abstract biological inspiration with figurative product shapes, and combine it with artificial intelligence technology to express the designer’s creativity, it will greatly improve the efficiency and accuracy of product shape bionic design. To address this problem, we combine BID with deep generative (DG) model to build a co-creative deep generative bio-inspired design (DGBID) model. Firstly, the designers used perceptual engineering and eye-movement experiments to select the bionic creature that best fits the bionic product and the suitable bionic product and bionic image, respectively. Then, the images are embedded into the potential space of StyleGAN, and the potential relationship between the two is visualized using StyleGAN’s image morphing technique, which generates a new bionic fusion scheme. Finally, the contour lines of the solution are extracted as a reference, the designer is involved in the optimization of the scheme as a sketch, and the hand-drawn sketch is transformed into a real product solution using style migration techniques. The entire bionic design experiment process is a co-creative approach with artificial intelligence technology as the lead and designer participation. The feasibility of the method is verified using the side view of a car as a bionic product. The results show that the integration of bionic technology with deep generative model technology can accelerate the innovation and development of bionic products and provide designers with design references and rapid-generation tools. |
| first_indexed | 2024-04-10T15:42:06Z |
| format | Article |
| id | doaj.art-7724d3a00453431aa5620bd96d9a09b9 |
| institution | Directory Open Access Journal |
| issn | 1875-6883 |
| language | English |
| last_indexed | 2024-04-10T15:42:06Z |
| publishDate | 2023-02-01 |
| publisher | Springer |
| record_format | Article |
| series | International Journal of Computational Intelligence Systems |
| spelling | doaj.art-7724d3a00453431aa5620bd96d9a09b92023-02-12T12:22:18ZengSpringerInternational Journal of Computational Intelligence Systems1875-68832023-02-0116111510.1007/s44196-023-00187-9Bionic Design Model for Co-creative Product Innovation Based on Deep Generative and BIDZhengGen Deng0Jian Lv1Xiang Liu2YuKang Hou3Key Laboratory of Advanced Manufacturing Technology of the Ministry of Education, Guizhou UniversityKey Laboratory of Advanced Manufacturing Technology of the Ministry of Education, Guizhou UniversityKey Laboratory of Advanced Manufacturing Technology of the Ministry of Education, Guizhou UniversityKey Laboratory of Advanced Manufacturing Technology of the Ministry of Education, Guizhou UniversityAbstract Bio-inspired design (BID) is an abstract process, if we can visualize the process of fusing abstract biological inspiration with figurative product shapes, and combine it with artificial intelligence technology to express the designer’s creativity, it will greatly improve the efficiency and accuracy of product shape bionic design. To address this problem, we combine BID with deep generative (DG) model to build a co-creative deep generative bio-inspired design (DGBID) model. Firstly, the designers used perceptual engineering and eye-movement experiments to select the bionic creature that best fits the bionic product and the suitable bionic product and bionic image, respectively. Then, the images are embedded into the potential space of StyleGAN, and the potential relationship between the two is visualized using StyleGAN’s image morphing technique, which generates a new bionic fusion scheme. Finally, the contour lines of the solution are extracted as a reference, the designer is involved in the optimization of the scheme as a sketch, and the hand-drawn sketch is transformed into a real product solution using style migration techniques. The entire bionic design experiment process is a co-creative approach with artificial intelligence technology as the lead and designer participation. The feasibility of the method is verified using the side view of a car as a bionic product. The results show that the integration of bionic technology with deep generative model technology can accelerate the innovation and development of bionic products and provide designers with design references and rapid-generation tools.https://doi.org/10.1007/s44196-023-00187-9Bionic designDeep generativeProduct designImage generationStyleGAN |
| spellingShingle | ZhengGen Deng Jian Lv Xiang Liu YuKang Hou Bionic Design Model for Co-creative Product Innovation Based on Deep Generative and BID International Journal of Computational Intelligence Systems Bionic design Deep generative Product design Image generation StyleGAN |
| title | Bionic Design Model for Co-creative Product Innovation Based on Deep Generative and BID |
| title_full | Bionic Design Model for Co-creative Product Innovation Based on Deep Generative and BID |
| title_fullStr | Bionic Design Model for Co-creative Product Innovation Based on Deep Generative and BID |
| title_full_unstemmed | Bionic Design Model for Co-creative Product Innovation Based on Deep Generative and BID |
| title_short | Bionic Design Model for Co-creative Product Innovation Based on Deep Generative and BID |
| title_sort | bionic design model for co creative product innovation based on deep generative and bid |
| topic | Bionic design Deep generative Product design Image generation StyleGAN |
| url | https://doi.org/10.1007/s44196-023-00187-9 |
| work_keys_str_mv | AT zhenggendeng bionicdesignmodelforcocreativeproductinnovationbasedondeepgenerativeandbid AT jianlv bionicdesignmodelforcocreativeproductinnovationbasedondeepgenerativeandbid AT xiangliu bionicdesignmodelforcocreativeproductinnovationbasedondeepgenerativeandbid AT yukanghou bionicdesignmodelforcocreativeproductinnovationbasedondeepgenerativeandbid |