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--> [Submitted on 14 Aug 2026] Title:Modeling and Control of an Eel-Inspired Soft Robot for Design Optimization View a PDF of the paper titled Modeling and Control of an Eel-Inspired Soft Robot for Design Optimization, by Zhangjingyi Jiang and 1 other authors View PDF HTML (experimental) Abstract:Anguilliform locomotion is a highly efficient swimming mode; the advent of new materials for soft robots enables the development of an eel-inspired soft robot. This paper presents a simulation model of an eel-inspired soft robot designed for anguilliform swimming. This model can aid in design optimization and the development of model-based estimation, reasoning, and control systems. A Finite Element Method (FEM) model of an elastic rod is used to capture the soft materials of the robotic fish, which makes it particularly amenable to variation over time as the material properties change. The material model is coupled with a hydrodynamic force model to simulate the behavior of a soft, elongated robot in water. The model is used to demonstrate the effectiveness of the proposed control approaches in achieving desired swimming behaviors. It also provides insights into design decisions, including the robustness of different system configurations and the impact of material degradation and failure. The results show that slightly asymmetric designs are advantageous, offering comparable swimming velocities but greater maneuverability. This model can be used to guide future robotic design decisions aimed at optimizing performance for specific tasks. Subjects: Robotics (cs.RO) Cite as: arXiv:2608.14860 [cs.RO] (or arXiv:2608.14860v1 [cs.RO] for this version) https://doi.org/10.48550/arXiv.2608.14860 arXiv-issued DOI via DataCite (pending registration) Related DOI: https://doi.org/10.1109/CASE59546.2024.10711519 DOI(s) linking to related resources Submission history From: Zhangjingyi Jiang [view email] [v1] Fri, 14 Aug 2026 19:54:40 UTC (2,407 KB) Full-text links: Access Paper: View a PDF of the paper titled Modeling and Control of an Eel-Inspired Soft Robot for Design Optimization, by Zhangjingyi Jiang and 1 other authors View PDF HTML (experimental) TeX Source view license Current browse context: cs.RO new | recent | 2026-08 Change to browse by: cs References & Citations NASA ADS Google Scholar Semantic Scholar Loading... Data provided by: Bibliographic Tools Bibliographic and Citation Tools Bibliographic Explorer Toggle Bibliographic Explorer (What is the Explorer?) Connected Papers Toggle Connected Papers (What is Connected Papers?) Litmaps Toggle Litmaps (What is Litmaps?) scite.ai Toggle scite Smart Citations (What are Smart Citations?) Code, Data, Media Code, Data and Media Associated with this Article alphaXiv Toggle alphaXiv (What is alphaXiv?) Links to Code Toggle CatalyzeX Code Finder for Papers (What is CatalyzeX?) DagsHub Toggle DagsHub (What is DagsHub?) GotitPub Toggle Gotit.pub (What is GotitPub?) Huggingface Toggle Hugging Face (What is Huggingface?) ScienceCast Toggle ScienceCast (What is ScienceCast?) Demos Demos Replicate Toggle Replicate (What is Replicate?) Spaces Toggle Hugging Face Spaces (What is Spaces?) Spaces Toggle TXYZ.AI (What is TXYZ.AI?) Related Papers Recommenders and Search Tools Link to Influence Flower Influence Flower (What are Influence Flowers?) Core recommender toggle CORE Recommender (What is CORE?) Author Venue Institution Topic About arXivLabs arXivLabs: experimental projects with community collaborators arXivLabs is a framework that allows collaborators to develop and share new arXiv features directly on our website. Both individuals and organizations that work with arXivLabs have embraced and accepted our values of openness, community, excellence, and user data privacy. arXiv is committed to these values and only works with partners that adhere to them. Have an idea for a project that will add value for arXiv's community? Learn more about arXivLabs. Which authors of this paper are endorsers? | Disable MathJax (What is MathJax?)