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April 27, 2026Advanced Intelligent Systems1 citationsOpen Access

Design‐for‐Benchmarking in Soft Robotics: Navigating Component‐System Dichotomy

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MPMatteo Lo PretiMNMuhammad Sunny NazeerJPJosh Pinskier

Key Points

  • This research aims to address the challenges of benchmarking in soft robotics by analyzing the performance gap between individual components and integrated systems.
  • Conducted a quantitative analysis of performance across sensing, actuation, and control modules.
  • Proposed a hierarchical evaluation framework for consistent reporting of system-level efficiency.
  • Advocated for a 'Design for Benchmarking' approach integrated into the design process.
  • Identified critical gaps in current benchmarking practices affecting reproducibility.
  • Highlighted the importance of long-term durability and system-level efficiency in evaluations.
  • Suggested that adopting transparent protocols could enhance innovation and real-world impact.

Abstract

Soft robotics has advanced significantly by integrating highly deformable and compliant materials, endowing robots with unparalleled adaptability for operation in dynamic and unstructured environments. However, the absence of commonly accepted benchmarking frameworks presents challenges for reproducibility and complicates the comparison of different technologies. This paper addresses this challenge by analyzing the Component‐System Dichotomy, i.e., the performance gap between isolated components and integrated systems, as a key and previously underexplored factor in evaluation. Through a quantitative analysis across sensing, actuation, and control, we identify opportunities to improve current practice, particularly in the consistent reporting of system‐level efficiency and long‐term durability. To address these challenges, we propose a hierarchical evaluation framework and advocate for the consideration of a “Design for Benchmarking” methodology, where testability is integrated into the design process itself. By fostering a culture of transparent comparison built on shared protocols and open‐source tools, the soft robotics community can reduce effort duplication, accelerate innovation, and build the foundation for verifiable, real‐world impact.

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Cite This Study

Preti et al. (2026) studied this question.

synapsesocial.com/papers/69eefd9bfede9185760d455ahttps://doi.org/10.1002/aisy.202600002
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