Liang Minshi, Zhu Jiaqi, Ke Xingxing, Chai Zhiping, Ding Han, Wu Zhigang
State Key Laboratory of Intelligent Manufacturing Equipment and Technology, School of Mechanical Science and Engineering, Huazhong University of Science and Technology, Wuhan 430074, People's Republic of China.
School of Mechanical Engineering and Automation, Fuzhou University, Fuzhou 350108, People's Republic of China.
Bioinspir Biomim. 2025 May 9;20(3). doi: 10.1088/1748-3190/add1a6.
In nature, organisms have evolved diverse grasping mechanisms to perform vital functions such as hunting and self-defence. These time-tested biological structures, including the arms of octopuses and the trunks of elephants, offer valuable inspiration for designing multimodal soft grippers that can tackle diverse tasks in various environments. Similar to their biological counterparts, these grippers must adapt to dynamic working conditions to enhance their performance. This adaptation process involves multiple factors, including grasping mechanisms, structural design, materials, and application scenarios, with biomimetic strategies offering numerous innovative examples. Despite the significant potential of bio-inspired designs, it lacks comprehensive reviews that explore how these strategies can enhance the development of multimodal soft grippers. This review seeks to address this gap by providing a systematic review of how bioinspired approaches contribute to the advancement of multimodal grippers. It focuses on coupling strategies, integration methods, performance improvements, and application scenarios. Finally, the review explores how future biomimetic insights could address current challenges and further improve the functionality of multimodal grippers.
在自然界中，生物体进化出了多种多样的抓取机制来执行诸如捕猎和自卫等重要功能。这些经过时间考验的生物结构，包括章鱼的触手和大象的鼻子，为设计能够在各种环境中完成各种任务的多模态软抓手提供了宝贵的灵感。与它们的生物同类相似，这些抓手必须适应动态的工作条件以提高其性能。这个适应过程涉及多个因素，包括抓取机制、结构设计、材料和应用场景，仿生策略提供了许多创新实例。尽管受生物启发的设计具有巨大潜力，但缺乏全面的综述来探讨这些策略如何促进多模态软抓手的发展。本综述旨在通过系统回顾受生物启发的方法如何推动多模态抓手的进步来填补这一空白。它侧重于耦合策略、集成方法、性能提升和应用场景。最后，本综述探讨了未来的仿生见解如何应对当前的挑战并进一步提高多模态抓手的功能。
