Soft Robotic Engines with Non‐Reciprocal Motion by Physical Intelligence
Movement is essential for living systems, enabling access to food, habitats, or escape from threats. Across scales, a key unifying principle is symmetry breaking to achieve non-reciprocal motion and accumulate work. In soft robotics, many actuators mimic biological responsiveness, but they typically exhibit reciprocal motion, where forward work is canceled in the return stroke - preventing work accumulation in cyclic operation. Here, a simple and broadly applicable hydrogel engine concept is presented that overcomes this limitation by encoding kinetic asymmetry into swelling and deswelling transitions. This hard-coded asymmetry yields non-reciprocal motion trajectories, enabling continuous mechanical work extraction under a single, uniform stimulus - without complex external control. The strategy embodies a material-based ratchet mechanism rooted in physical intelligence, independent of geometry or scale, and generalizable across stimuli. This hydrogel engine is implemented in soft robotic systems, including artificial cilia for fluid pumping and conveyor belts for object transport. Starting from macroscopic thermoresponsive systems, the design is extended to microscale formats via 3D printing and to other stimuli-responsive materials. This approach shifts the paradigm in soft robotics - from increasing chemical complexity to leveraging intrinsic material properties for emergent function - paving the way for scalable, autonomous systems driven by physical intelligence.
Authors
- Viacheslav Slesarenko (ORCID: https://orcid.org/0000-0003-2689-9918)
- Giulia Vozzolo
- Brigitta Dúzs (ORCID: https://orcid.org/0000-0002-0909-2808)
- Christoph Drees (ORCID: https://orcid.org/0000-0001-6083-3205)
- Giorgio Fusi (ORCID: https://orcid.org/0000-0003-1006-5951)
- Marcos Masukawa (ORCID: https://orcid.org/0000-0003-3814-2744)
- Andreas Walther (ORCID: https://orcid.org/0000-0003-2170-3306)
- Jacqueline Figueiredo da Silva (ORCID: https://orcid.org/0009-0003-4659-1678)
- Oliver Skarsetz (ORCID: https://orcid.org/0000-0002-1540-1873)
- Piet J. M. Swinkels (ORCID: https://orcid.org/0000-0002-6118-9746)
- Yanis Lassiat (ORCID: https://orcid.org/0009-0009-9883-687X)
Institutions
- University of Freiburg (DE)
- Johannes Gutenberg University Mainz (DE)
- Max Planck Institute for Polymer Research (DE)
- Polymat (ES)
Publication Details
- Journal
- Advanced Materials
- Published
- 2025-09-01
- DOI
- https://doi.org/10.1002/adma.202511630
- Citations
- 1
- Primary Topic
- Micro and Nano Robotics
- Type
- article
- Field-Weighted Citation Impact
- 1.26
Funders
- Alexander von Humboldt-Stiftung
- Deutsche Forschungsgemeinschaft
- FP7 Ideas: European Research Council