Self-Healing and Damage Resilience in Soft Robots

The intrinsic compliance of soft robots makes them vulnerable to various types of damage and operational failures. They are susceptible to cuts, fatigue, and overstraining. Such vulnerabilities can drastically shorten the operational lifespan and reliability of soft robotic systems, rendering them economically and ecologically uncompetitive. Over the past decade, materials scientists and roboticists have joined forces to address these challenges by creating soft robots made from self-healing materials, endowing them with the remarkable ability to recover from damage.

While this new generation of self-healing soft robots has driven rapid technical progress, significant challenges remain before these robots can autonomously recover from diverse types of damage in varying conditions, in a robust and efficient way, allowing them to unlock their full industrial and societal potential. This Research Topic aims to advance damage resilience in soft robotics by emphasizing not only the material aspects of healing capability but also addressing the broader dimensions of the self-healing process at the system level. Advancing damage resilience in soft robotics requires progress on multiple fronts. This includes developing self-healing materials—ranging from synthetic to biohybrid and biomaterials—tailored for soft robotics applications with improved toughness and reduced creep properties as well as processing. Additionally, research on physical intelligence through smart and stimuli-responsive materials, as well as embodied intelligence via healing-assistive mechanisms, is essential for achieving fully autonomous self-healing systems. A comprehensive self-healing process also requires further evaluation, including validation, standardization, lifecycle assessment, and energy consumption studies. Moreover, advancements in damage adaptability—ranging from software-based adaptivity to hardware-based solutions—could significantly contribute to making robots more damage-resilient.

This Research Topic seeks manuscripts from a wide range of topics related to self-healing and damage resilient strategies for soft robotics, from improving self-healing material properties tailored for soft robotics applications to advances in self-healing at the system level:

• Self-healing material innovations, their processing and manufacturing of self-healing soft robots
• Damage detection and health monitoring systems designed to facilitate autonomous operation of self-healing or resilience strategies
• Self-closing or self-sealing mechanisms to enable healing from large and/or gaping damage
• Dirt and contamination sensors and self-cleaning strategies
• Assistive mechanisms for activating or enhancing self-healing processes
• Design, testing and validation of self-healing and resilient soft robots
• Damage resilience via redundancy, adaptation and compensation, implemented via software and/or hardware solutions
• Bio-hybrid robots with self-healing capabilities
• Comprehensive studies on damage modes, lifetime estimation, and life cycle assessment of self-healing and resilient robots

This Research Topic is related to the workshop of the same name at the 2024 International Conference on Intelligent Robots and Systems (IROS) conference. Papers which were previously published as conference proceedings should be extended to include at least 30% original content. We encourage contributions from the workshop, as well as other relevant research articles, review or perspective papers and viewpoint letters.

Keywords: Soft robots, Self-healing, Damage resilience, Damage sensors, Smart materials, Damage adaptation, Reconfiguration

Important note: All contributions to this Research Topic must be within the scope of the section and journal to which they are submitted, as defined in their mission statements. Frontiers reserves the right to guide an out-of-scope manuscript to a more suitable section or journal at any stage of peer review.