Computational synthesis of locomotive soft robots by topology optimization
Fuente:
arXiv
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| Autori principali: | , , , , , , , , , |
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| Natura: | Preprint |
| Pubblicazione: |
2023
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| Soggetti: | |
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| _version_ | 1866910540502138880 |
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| author | Kobayashi, Hiroki Gholami, Farzad Montgomery, S. Macrae Tanaka, Masato Yue, Liang Yuhn, Changyoung Sato, Yuki Kawamoto, Atsushi Qi, H. Jerry Nomura, Tsuyoshi |
| author_facet | Kobayashi, Hiroki Gholami, Farzad Montgomery, S. Macrae Tanaka, Masato Yue, Liang Yuhn, Changyoung Sato, Yuki Kawamoto, Atsushi Qi, H. Jerry Nomura, Tsuyoshi |
| contents | Locomotive soft robots (SoRos) have gained prominence due to their adaptability. Traditional locomotive SoRo design is based on limb structures inspired by biological organisms and requires human intervention. Evolutionary robotics, designed using evolutionary algorithms (EAs), have shown potential for automatic design. However, EA-based methods face the challenge of high computational cost when considering multiphysics in locomotion, including materials, actuations, and interactions with environments. Here, we present a design approach for pneumatic SoRos that integrates gradient-based topology optimization with multiphysics material point method (MPM) simulations. This approach starts with a simple initial shape (a cube with a central cavity). The topology optimization with MPM then automatically and iteratively designs the SoRo shape. We design two SoRos, one for walking and one for climbing. These SoRos are 3D printed and exhibit the same locomotion features as in the simulations. This study presents an efficient strategy for designing SoRos, demonstrating that a purely mathematical process can produce limb-like structures seen in biological organisms. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2310_10985 |
| institution | arXiv |
| publishDate | 2023 |
| record_format | arxiv |
| spellingShingle | Computational synthesis of locomotive soft robots by topology optimization Kobayashi, Hiroki Gholami, Farzad Montgomery, S. Macrae Tanaka, Masato Yue, Liang Yuhn, Changyoung Sato, Yuki Kawamoto, Atsushi Qi, H. Jerry Nomura, Tsuyoshi Computational Engineering, Finance, and Science Locomotive soft robots (SoRos) have gained prominence due to their adaptability. Traditional locomotive SoRo design is based on limb structures inspired by biological organisms and requires human intervention. Evolutionary robotics, designed using evolutionary algorithms (EAs), have shown potential for automatic design. However, EA-based methods face the challenge of high computational cost when considering multiphysics in locomotion, including materials, actuations, and interactions with environments. Here, we present a design approach for pneumatic SoRos that integrates gradient-based topology optimization with multiphysics material point method (MPM) simulations. This approach starts with a simple initial shape (a cube with a central cavity). The topology optimization with MPM then automatically and iteratively designs the SoRo shape. We design two SoRos, one for walking and one for climbing. These SoRos are 3D printed and exhibit the same locomotion features as in the simulations. This study presents an efficient strategy for designing SoRos, demonstrating that a purely mathematical process can produce limb-like structures seen in biological organisms. |
| title | Computational synthesis of locomotive soft robots by topology optimization |
| topic | Computational Engineering, Finance, and Science |
| url | https://arxiv.org/abs/2310.10985 |