Kashef Tabrizian Seyedreza, Terryn Seppe, Vanderborght Bram
Brubotics Vrije Universiteit Brussel and imec 1050 Brussels Belgium.
Adv Intell Syst. 2025 Aug;7(8):2400790. doi: 10.1002/aisy.202400790. Epub 2025 Feb 17.
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.
动态可逆聚合物网络的最新进展催生了自修复软机器人，这种机器人在受损后能够恢复其物理和电气性能。然而，在大多数情况下，愈合过程仍离不开人工干预。这带来了挑战，尤其是在人员难以进入的工作环境中，或者人员参与可能会妨碍效率的情况下。为了弥补这一差距，本文首先讨论了软机器人技术中愈合过程的不同阶段，然后回顾了那些已经或可以集成到自修复软机器人中、使每个阶段能够在最少人工干预的情况下自主进行的技术。最后，本文讨论了将所有阶段集成到自修复软机器人中的挑战，并展望了未来实现完全自主自修复的前景。这些阶段分为五类：损伤检测、损伤清理、损伤闭合、刺激触发材料愈合和恢复评估。要实现这些特性，需要通过使用刺激响应材料在材料层面运用物理智能，或者通过集成愈合辅助子系统在系统层面利用具身智能，或者两者协同结合。因此，自修复软机器人能够在愈合能力方面实现自给自足，使其成为更广泛应用的可持续解决方案。
