What is this collection about?

Advances in distributed sensing across soft, deformable, and bio-integrated materials are transforming how intelligent systems perceive, interpret, and interact with their environment. Technologies such as Electrical Impedance Tomography (EIT), capacitive imaging, optical tomography, and field reconstruction are redefining the interface between materials, electronics, and intelligence. These approaches enable the reconstruction and mapping of spatially distributed information from indirect measurements, opening new pathways toward adaptive, self-sensing, and intelligent systems.

Specifically, this Collection showcases innovations in:

• Materials Science: Novel sensing materials, composites, and transducers that combine softness, stretchability, and high sensitivity.
• Design and Optimization: New electrode architectures and structural morphologies for improved resolution, robustness, and scalability.
• Perception Algorithms: Advanced reconstruction, calibration, and inference approaches, ranging from physics-based modelling to data-driven deep learning.
• Emerging Capabilities: Integration of distributed sensing technologies into robotic, haptic, and human-interactive platforms for enhanced perception and control.

Why is this collection important?

Distributed sensing technologies have far-reaching implications for next-generation systems, from autonomous technologies and human–robot interaction to medical wearables and bio-integrated devices, where robust, high-resolution sensing is essential for safe, adaptive, and intelligent operation.

By uniting contributions across materials science, field reconstruction, computational methods, and embodied applications, this Collection aims to define the frontier of distributed sensing and support the development of intelligent, interactive systems.

Why submit to a collection?

Collections like this one help promote high-quality science. They are led by Guest Editors and In-House Editors who are experts in their fields and supported by a dedicated team of Commissioning Editors and Managing Editors at Springer Nature. Collection manuscripts typically see higher citations, downloads, and Altmetric scores, and provide a one-stop-shop on a cutting-edge topic of interest.

Who is involved?

David Hardman, PhD, University of Cambridge, United Kingdom

Dr David Hardman received his PhD in Engineering from the University of Cambridge, UK, in 2024. He is now a Junior Research Fellow and Affiliated Lecturer in Cambridge’s Bio-Inspired Robotics Lab, where he works on soft robotics and tactile perception.

Josie Hughes, PhD, EPFL, Switzerland

Dr Josie Hughes is an Assistant Professor at EPFL where she established the CREATE Lab in the Institute of Mechanical Engineering in 2021. Her research focuses on developing novel design paradigms for designing robot structures that exploit their physicality and interactions with the environment. This includes the development of robotic hands, soft manipulators and automation systems for applications focused on sustainability and science.

Fumiya Iida, PhD, University of Tokyo, Japan and University of Cambridge, United Kingdom

Dr Fumiya Iida is a Professor at Graduate School of Engineering, the University of Tokyo, and Research Professor at University of Cambridge, and the director of Bio-Inspired Robotics Laboratory. His research interest includes biologically inspired robotics, embodied artificial intelligence, and biomechanics, where he was involved in a number of research projects related to dynamic legged locomotion, dextrous and adaptive manipulation, human-machine interactions, and evolutionary robotics. 

Kiyanoush Nazari, PhD, University College London, United Kingdom

Dr Kiyanoush Nazari is a postdoctoral researcher in robotics, specializing in data-driven control for intelligent robotic manipulation. His research focuses on tactile sensing and real-time learning-based control methods for slip prevention and adaptive interaction, with experience spanning deep learning, multi-modal sensing, and deployment on physical robotic systems.

Thomas George Thuruthel, PhD, University College London, United Kingdom

Dr Thomas George Thuruthel is a lecturer in Robotics and AI in the Department of Computer Science at University College London. His research interests include modelling and control of soft bodied systems, soft sensing technologies, dexterous manipulation, and applications of AI in robotic systems.

Communications Engineering is edited by both in-house professional editors and Editorial Board Members.

How can I submit my paper?

Visit the Collection page to find out more about this collection and submit your article.