Soft Robotic Sensing and Modeling: From Proprioception to Physiology-Informed Validation

Soft robotics has emerged as a transformative paradigm where compliance, adaptability, and embodied intelligence are achieved through material and structural design. A critical frontier in this field is the integration of multimodal sensing with advanced modeling frameworks, enabling robots to perceive their own state (proprioception), interact safely with humans, and operate reliably in diverse environments. This Research Topic seeks contributions that advance the sensing–modeling–validation pipeline for soft robotic systems. We invite work that demonstrates how embedded sensing modalities, physics-based and data-driven models, and standardized validation approaches can together ensure reproducibility, robustness, and physiological relevance.Topics of interest include:• Multimodal soft sensing: Hall-effect sensors, electromagnetic resonance, suction/tactile arrays, printable stiffness gradients, and hybrid sensing architectures.• Morphology-driven modeling: Cosserat-rod formulations, strain-based dynamic models, reduced-order modeling (MOR), and autoencoder frameworks for compliant body dynamics.• Validation pipelines: Imaging-based quality control (micro-CT, densitometry), reproducibility protocols, and standardized benchmarking for soft robotic systems.• Physiology-informed approaches: Translating biological proprioception and tactile sensing into robotic architectures for assistive, medical, and rehabilitation applications.• Control interfaces: Bridging sensing and modeling with intuitive human–robot interaction, particularly in assistive and wearable devices.By uniting multimodal sensing, morphological modeling, and physiology-informed validation, this Research Topic will establish new standards for reproducibility and sustainability in soft robotics. The collection aims to highlight how sensing and modeling can jointly enable soft robots to achieve reliable proprioception, extended operational lifetimes, and safe integration into human-centered environments. Topic editors: Anup Teejo Mathew, Francesco Visentin, Luigi BIBBO', Laura Mecozzi Source: https://www.frontiersin.org/research-topics/80751/soft-robotic-sensing-and-modeling-from-proprioception-to-physiology-informed-validation