ArticleScience advances2025
A forward-engineered, muscle-driven soft robotic swimmer.
Article in Science advances, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
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Who cites it
3 citing papers in PubMed.
- 2D Skeletal Muscle Thin Film Actuators Enhance Efficiency of Biohybrid Robots.bioRxiv : the preprint server for biology · 2026Article
- Fast-swimming biohybrid OstraBot with self-trained high-strength muscles.Nature communications · 2026Article
- Biohybrid living robotics: A comprehensive review of recent advances, technological innovation, and future prospects.npj Robotics · 2025Article
Corrections and comments
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Authors and funding
11 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The field of biohybrid robotics focuses on using biological actuators to study the emergent properties of tissues and the locomotion of living organisms. On the basis of models of swimming at small size scales, we designed and fabricated a muscle-powered, flagellate swimmer. We investigate the design of a compliant mechanism based on nonlinear mechanics and its mechanical integration with a muscle ring and motor neurons. We find that within a range of anchor stiffnesses around 1 micronewton per micrometer, the homeostatic tension in muscle is insensitive to stiffness, offering greater design flexibility. The proximity of motor neurons results in a fourfold improvement in muscle contractility. Improved contractility and nonlinear design allow for a peak swimming speed about two orders of magnitude higher than previous biohybrid flagellate swimmers, reaching 0.58 body lengths per minute (86.8 micrometers per second), by a mechanism involving inertia that we verify through flow field imaging. This swimmer opens the door for a class of intermediate-Reynolds number swimmers.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.