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Fast-swimming biohybrid OstraBot with self-trained high-strength muscles
Pengyu Chen1, Xuchen Wang1, Jinrun Zhou1
1Department of Mechanical Engineering, College of Design and Engineering, National University of Singapore, Singapore, Singapore.
Nature Communications
|March 19, 2026
Summary
Researchers developed a self-training platform to strengthen skeletal muscle tissues, creating high-force muscle actuators. This enabled a biohybrid swimming robot, OstraBot, to achieve record speeds, outperforming previous muscle-powered robots.
Area of Science:
- Biohybrid robotics
- Tissue engineering
- Biomechanical engineering
Background:
- Skeletal muscle force generation is a key limitation in biohybrid robot performance.
- Existing biohybrid robots powered by muscle tissue have shown limited force output and speed.
Purpose of the Study:
- To develop an autonomous platform for enhancing skeletal muscle actuator strength.
- To design and optimize a muscle-powered swimming robot using a physiology-based model.
Main Methods:
- Utilized a self-training platform to strengthen C2C12 skeletal muscle tissues via spontaneous contractions.
- Developed a physiology-based muscle contraction model to guide robot design.
- Integrated muscle actuators into a twin-tail ostraciiform swimming robot (OstraBot).
Main Results:
- Achieved muscle actuators with a maximum force of 7.05 mN and stress of 8.51 mN/mm², the highest reported for C2C12-derived actuators.
- OstraBot reached a top speed of 467 mm/min (15.6 body lengths/min), significantly exceeding previous biohybrid robots.
- Demonstrated precise on-off control via sound-triggered clapping.
Conclusions:
- The self-training platform effectively produces high-strength skeletal muscle actuators.
- Physiology-based modeling enables quantitative design guidance for high-performance biohybrid robots.
- This work advances the development of advanced biohybrid robotic systems.
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