Toward Autonomous Self-Healing in Soft Robotics: A Review and Perspective for Future Research

Recent advances in dynamic and reversible polymer networks have led to self-healing soft robots that can restore their physical and electrical properties after damage. However, in most cases, human intervention remains essential for the healing process. This poses a challenge, especially in working environments with limited human access or where human involvement cand hinder efficiency. To address this gap, in this article, first, the different phases of the healing process in soft robotics are discussed and then the technologies that are or can be integrated into self-healing soft robots to allow each individual phase to be performed autonomously with minimal human involvement are reviewed. Finally, in this article, the challenges of integrating all phases into self-healing soft robots are discussed and the perspectives on achieving fully autonomous self-healing in the future are offered. These phases are classified into five: damage detection, damage cleaning, damage closure, stimulus-triggered material healing, and recovery assessment. Achieving these attributes requires employing physical intelligence at the material level through the use of stimuli-responsive materials or utilizing embodied intelligence at the system level by integrating healing-assistive subsystems or a synergistic combination of both. Consequently, self-healing soft robots can achieve self-sufficiency in their healing capabilities, rendering them a sustainable solution for broader applications.