Inversion of Biological Strategies in Engineering Technology: A Case Study of the Underwater Soft Robot
Bio-inspired design, a paradigm-shifting methodology that translates evolutionary mechanisms into engineering solutions, has established itself as a cornerstone for pioneering innovation in multifaceted technological systems. Despite its promise, the inherent complexity of biological systems and int...
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| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2025-06-01
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| Series: | Biomimetics |
| Subjects: | |
| Online Access: | https://www.mdpi.com/2313-7673/10/6/362 |
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| Summary: | Bio-inspired design, a paradigm-shifting methodology that translates evolutionary mechanisms into engineering solutions, has established itself as a cornerstone for pioneering innovation in multifaceted technological systems. Despite its promise, the inherent complexity of biological systems and interdisciplinary knowledge gaps hinder the effective translation of biological principles into practical engineering solutions. This study introduces a structured framework integrating large language models (LLMs) with a function–behavior–characteristic–environment (F-B-C-E) paradigm to systematize biomimetic design processes. We propose a standardized F-B-C-E knowledge model to formalize biological strategy representations, coupled with a BERT-based pipeline for automated inversion of biological strategies into engineering applications. To optimize strategy selection, a hybrid decision-making methodology combining VIKOR multi-criteria analysis and rank correlation is developed. The framework’s functional robustness is validated via aquatic robotic system implementations, wherein three biomimetic propulsion modalities—oscillatory caudal propulsion, pulsed hydrodynamic thrust generation, and autonomous peristaltic locomotion—demonstrate quantifiable enhancements in locomotion efficiency and environmental adaptability metrics. These results underscore the robustness of the proposed inversion methodology in resolving intricate engineering problems through systematic biomimetic translation. |
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| ISSN: | 2313-7673 |