机器人
人工肌肉
形状记忆合金*
计算机科学
软机器人
形状记忆合金
收缩(语法)
灵活性(工程)
机器人运动
仿生学
水下
适应性
模拟
肌肉收缩
爬行
气动人工肌肉
人工智能
神经生理学
执行机构
地面运动
机器人学
人工神经网络
带宽(计算)
生物力学
外骨骼
测距
作者
Zhenyi Chai,Wei Gao,Jingwen Kong,Qiqiang Hu,Yiming Ouyang,Lei Zhang,Mengli Sui,Erbao Dong,Weihua Li,Hu Jin,Shibo Liu
标识
DOI:10.1177/21695172251406493
摘要
Muscles, with broad contraction response bandwidth from milliseconds to seconds, are symmetrically distributed on both sides of the fish’s body. By employing these symmetrical muscles with different contraction response combinations, fish are capable of multimodal locomotion including crawling, jumping, rolling, escaping, and swimming. These locomotion modes, ranging from water to land, enable fish with simple body structure to have strong survival abilities. This work proposes a teleost-inspired multimodal locomotion soft robot, named TMSR, which is capable of multimodal locomotion in both underwater and terrestrial environments. The TMSR features a fish-like simple structure with two shape memory alloy (SMA) artificial muscles, each with different contraction response bandwidths, asymmetrically arranged along its central plane. A series of contraction response combinations using these two SMA artificial muscles were developed for the multimodal locomotion of TMSR. Through performance experiments and mechanical models, the driving characteristics of the SMA artificial muscles and the key factors influencing their contraction responses were explored. The TMSR exhibits excellent adaptability and adjustability across various terrains, achieving five different modes of locomotion similar to the movement behaviors of fish through a lightweight and simple biomimetic structural design, including the unique escape movement, which is uncommon in current soft locomotion robots. This design endows the TMSR with a lower mass–mode ratio and higher flexibility and multifunctionality compared with similar robots. This research contributes to broadening the application prospects of such robots in diverse environments.
科研通智能强力驱动
Strongly Powered by AbleSci AI