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Operationalising reproducibility in soft robotics
1CSIRO Robotics, Brisbane, QLD, Australia.
Frontiers in Robotics and AI
|February 26, 2026
Summary
Ensuring reproducibility is vital for advancing soft robotics. This perspective outlines three key goals for data sharing, standardized testing, and quantifying embodied intelligence to foster a more reliable and progressive field.
Area of Science:
- Robotics
- Materials Science
- Computer Science
Background:
- Reproducibility is a significant challenge hindering the development and maturation of soft robotics.
- Establishing reproducible methods is crucial for scientific rigor and field advancement.
Purpose of the Study:
- To define reproducibility in the context of soft robotics.
- To propose actionable strategies and "moonshot" goals for enhancing reproducibility in the field.
- To outline a path towards a more reliable and progressive future for soft robotics research.
Main Methods:
- Literature review and synthesis of existing reproducibility frameworks.
- Analysis of current testing and data-sharing practices in soft robotics.
- Exploration of interdisciplinary testing methodologies from other scientific fields.
- Identification of needs for quantitative comparison of embodied intelligence.
Main Results:
- Defined reproducibility and its critical importance for soft robotics.
- Proposed three "moonshot" goals: improved data sharing and testing methods, adoption of interdisciplinary testing procedures, and development of quantitative metrics for embodied intelligence.
- Highlighted the necessity of these advancements for the field's future development.
Conclusions:
- Achieving these goals will significantly enhance the reliability and progress of soft robotics.
- Standardized data sharing, robust testing protocols, and quantitative evaluation of embodied intelligence are key to a reproducible future.
- The proposed framework provides a roadmap for the maturation of the soft robotics field.
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