Harnessing natural embodied intelligence for spontaneous jellyfish cyborgs
Abstract Jellyfish cyborgs present a promising avenue for soft robotic systems, leveraging the natural energy-efficiency and adaptability of biological systems. Here we present an approach for predicting and controlling jellyfish locomotion by harnessing the natural embodied intelligence of these an...
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| Format: | Article |
| Language: | English |
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Nature Portfolio
2025-05-01
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| Series: | Nature Communications |
| Online Access: | https://doi.org/10.1038/s41467-025-59889-7 |
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| _version_ | 1850127889860657152 |
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| author | Dai Owaki Max Austin Shuhei Ikeda Kazuya Okuizumi Kohei Nakajima |
| author_facet | Dai Owaki Max Austin Shuhei Ikeda Kazuya Okuizumi Kohei Nakajima |
| author_sort | Dai Owaki |
| collection | DOAJ |
| description | Abstract Jellyfish cyborgs present a promising avenue for soft robotic systems, leveraging the natural energy-efficiency and adaptability of biological systems. Here we present an approach for predicting and controlling jellyfish locomotion by harnessing the natural embodied intelligence of these animals. We developed an integrated muscle electrostimulation and 3D motion capture system to quantify both spontaneous and stimulus-induced behaviors in Aurelia coerulea jellyfish. Our key findings include an investigation of self-organized criticality in jellyfish swimming motions and the identification of optimal periods of electro-stimulus input signal (1.5 and 2.0 seconds) for eliciting coherent and predictable swimming behaviors. Furthermore, using Reservoir Computing, a machine learning framework, we successfully predicted future movements of the stimulated jellyfish, which also characterizes how the jellyfish swimming motions are synchronized with the electro-stimulus. Our findings provide a foundation for developing jellyfish cyborgs capable of autonomous navigation and environmental exploration, with potential applications in ocean monitoring and pollution management. |
| format | Article |
| id | doaj-art-66d9b9056f1a401b82d3f2a7f636ade1 |
| institution | OA Journals |
| issn | 2041-1723 |
| language | English |
| publishDate | 2025-05-01 |
| publisher | Nature Portfolio |
| record_format | Article |
| series | Nature Communications |
| spelling | doaj-art-66d9b9056f1a401b82d3f2a7f636ade12025-08-20T02:33:32ZengNature PortfolioNature Communications2041-17232025-05-0116111710.1038/s41467-025-59889-7Harnessing natural embodied intelligence for spontaneous jellyfish cyborgsDai Owaki0Max Austin1Shuhei Ikeda2Kazuya Okuizumi3Kohei Nakajima4Department of Robotics, Graduate School of Engineering, Tohoku UniversityGraduate School of Information Science and Technology, The University of TokyoKamo AquariumKamo AquariumGraduate School of Information Science and Technology, The University of TokyoAbstract Jellyfish cyborgs present a promising avenue for soft robotic systems, leveraging the natural energy-efficiency and adaptability of biological systems. Here we present an approach for predicting and controlling jellyfish locomotion by harnessing the natural embodied intelligence of these animals. We developed an integrated muscle electrostimulation and 3D motion capture system to quantify both spontaneous and stimulus-induced behaviors in Aurelia coerulea jellyfish. Our key findings include an investigation of self-organized criticality in jellyfish swimming motions and the identification of optimal periods of electro-stimulus input signal (1.5 and 2.0 seconds) for eliciting coherent and predictable swimming behaviors. Furthermore, using Reservoir Computing, a machine learning framework, we successfully predicted future movements of the stimulated jellyfish, which also characterizes how the jellyfish swimming motions are synchronized with the electro-stimulus. Our findings provide a foundation for developing jellyfish cyborgs capable of autonomous navigation and environmental exploration, with potential applications in ocean monitoring and pollution management.https://doi.org/10.1038/s41467-025-59889-7 |
| spellingShingle | Dai Owaki Max Austin Shuhei Ikeda Kazuya Okuizumi Kohei Nakajima Harnessing natural embodied intelligence for spontaneous jellyfish cyborgs Nature Communications |
| title | Harnessing natural embodied intelligence for spontaneous jellyfish cyborgs |
| title_full | Harnessing natural embodied intelligence for spontaneous jellyfish cyborgs |
| title_fullStr | Harnessing natural embodied intelligence for spontaneous jellyfish cyborgs |
| title_full_unstemmed | Harnessing natural embodied intelligence for spontaneous jellyfish cyborgs |
| title_short | Harnessing natural embodied intelligence for spontaneous jellyfish cyborgs |
| title_sort | harnessing natural embodied intelligence for spontaneous jellyfish cyborgs |
| url | https://doi.org/10.1038/s41467-025-59889-7 |
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