Fang Zhonggui, Tang Shaowu, Su Yinyin, Liu Xiaohuang, Liu Sicong, Yi Juan, Wang Zheng, Dai Jian S
Department of Mechanical and Energy Engineering, Southern University of Science and Technology, Shenzhen, 518000, China.
Department of Mechanical Engineering, The University of Hong Kong, Hong Kong, 999077, China.
Adv Sci (Weinh). 2025 Jan;12(3):e2409060. doi: 10.1002/advs.202409060. Epub 2024 Nov 26.
The human muscle bundle generates versatile movements with synchronous neurosensory, enabling human to undertake complex tasks, which inspires researches into functional integration of motions and sensing in actuators for robots. Although soft actuators have developed diverse motion capabilities utilizing the inherent compliance, the simultaneous-sensing approaches typically involve adding sensing components or embedding certain-signal-field substrates, resulting in structural complexity and discrepant deformations between the actuation parts with high-dimensional motions and the sensing parts with heterogeneous stiffnesses. Inspired by the muscle-bundle multifiber mechanism, a multicavity functional integration (McFI) approach is proposed for soft pneumatic actuators to simultaneously realize multidimensional motions and sensing by separating and coordinating active and passive cavities. A bio-inspired interweaving foldable endomysium (BIFE) is introduced to construct and reinforce the multicavity chamber with optimized purposive foldability, enabling 3D printing single-material fabrication. Performing elongation, contraction, and bidirectional bending, the McFI actuator senses its spatial position, orientation, and axial force, based on the kinematic and sensing models built on multi-cavity pressures. Two McFI-actuator-driven robots are built: a soft crawling robot with path reconstruction and a narrow-maneuverable soft gripper with object exteroception, validating the practicality in stand-alone use of the actuator and the potential for intelligent soft robotic innovation of the McFI approach.
人类肌肉束通过同步神经传感产生多种运动,使人类能够承担复杂任务,这激发了对机器人执行器中运动与传感功能集成的研究。尽管软驱动器利用其固有的柔顺性发展出了多样的运动能力,但同时传感方法通常涉及添加传感组件或嵌入特定信号场基板,这导致了结构复杂性以及具有高维运动的驱动部件与具有不同刚度的传感部件之间的变形差异。受肌肉束多纤维机制的启发,提出了一种多腔功能集成(McFI)方法,用于软气动执行器,通过分离和协调主动腔和被动腔来同时实现多维运动和传感。引入了一种受生物启发的交织可折叠肌内膜(BIFE),以构建和加固具有优化的目标可折叠性的多腔室,实现3D打印单材料制造。通过执行伸长、收缩和双向弯曲,McFI执行器基于多腔压力建立的运动学和传感模型来感知其空间位置、方向和轴向力。构建了两个由McFI执行器驱动的机器人:一个具有路径重建功能的软爬行机器人和一个具有物体外部感知功能的窄操纵软夹爪,验证了该执行器单独使用的实用性以及McFI方法在智能软机器人创新方面的潜力。