This paper proposes a biomimetic design framework based on biological strategy inversion, aiming to systematically map solutions evolved in nature to the engineering field. By constructing a "Function-Behavior-Feature-Environment" (F-B-Cs in E) knowledge model, combined with natural language processing (NLP) and multi-criteria decision-making methods, it achieves efficient conversion from biological strategies to engineering solutions. Using underwater soft robot design as a case study, the effectiveness of the framework in optimizing drive mechanisms, power distribution, and motion pattern design is verified. This research provides scalable methodological support for interdisciplinary biomimetic innovation.
@article{arxiv.2504.11722,
title = {Inversion of biological strategies in engineering technology: in case underwater soft robot},
author = {Siqing Chen and He Xua and Xueyu Zhang and Zhen Ma},
journal= {arXiv preprint arXiv:2504.11722},
year = {2025}
}