# Operationalising reproducibility in soft robotics

## TL;DR

This paper discusses how to make soft robotics research more reproducible by setting clear goals for testing, data sharing, and comparing intelligent systems.

## Contribution

The paper introduces three moonshot goals to improve reproducibility in soft robotics.

## Key findings

- Testing and data-sharing methods are essential for reproducibility in soft robotics.
- Testing procedures from other fields can be adapted for soft robotics.
- Quantitative methods are needed to compare embodied intelligence in soft robots.

## Abstract

Reproducibility is a particular challenge for soft robotics, yet remains a core part of its development and maturation as a field. This perspective dives into reproducibility: what it is, what it means, and how it can be applied to soft robotics. We first discuss reproducibility and delineate why it is a critical consideration for the field. Following this, our core contributions are in defining three moonshot goals that collectively chart a path towards a reproducible future for soft robotics. First, methods for testing and sharing data are discussed. Second, we show how testing procedures from other scientific disciplines can provide broad coverage over different types of soft robotics tests that we might want to complete. Finally, we highlight the need for methods to quantitatively compare the embodied intelligence that lies at the heart of soft robotics research. If successful, these steps would put the field in an excellent position to develop into the future.