A Biomimetic Adhesive Disc for Robotic Adhesion Sliding Inspired by the Net-Winged Midge Larva.

Journal: Soft robotics
PMID: 39411787

Abstract

Net-winged midge larvae (Blephariceridae) are known for their remarkable ability to adhere to and crawl on the slippery surfaces of rocks in fast-flowing and turbulent alpine streams, waterfalls, and rivers. This remarkable performance can be attributed to the larvae's powerful ventral suckers. In this article, we first develop a theoretical model of the piston-driven sucker that considers the lubricated state of the contact area. We then implement a piston-driven robotic sucker featuring a V-shaped notch to explore the adhesion-sliding mechanism. Each biomimetic larval sucker has the unique feature of an anterior-facing V-shaped notch on its soft disc rim; it slides along the shear direction while the entire disc surface maintains powerful adhesion on the benthic substrate, just like the biological counterpart. We found that this biomimetic sucker can reversibly transit between "high friction" (4.26 ± 0.34 kPa) and "low friction" (0.41 ± 0.02 kPa) states due to the piston movement, resulting in a frictional enhancement of up to 93.9%. We also elucidate the frictional anisotropy (forward/backward force ratio: 0.81) caused by the V-shaped notch. To demonstrate the robotic application of this adhesion-sliding mechanism, we designed an underwater crawling robot Adhesion Sliding Robot-1 (ASR-1) equipped with two biomimetic ventral suckers. This robot can successfully crawl on a variety of substrates such as curved surfaces, sidewalls, and overhangs and against turbulent water currents with a flow speed of 2.4 m/s. In addition, we implemented a fixed-wing aircraft Adhesion Sliding Robot-2 (ASR-2) featuring midge larva-inspired suckers, enabling transit from rapid water surface gliding to adhesion sliding in an aquatic environment. This adhesion-sliding mechanism inspired by net-winged midge larvae may pave the way for future robots with long-term observation, monitoring, and tracking capabilities in a wide variety of aerial and aquatic environments.

Authors

  • Haoyuan Xu
    School of Mechanical Engineering and Automation, Beihang University, Beijing, China.
  • Jiale Zhi
    CENTRALE PEKIN/School of General Engineering, Beihang University, Beijing, China.
  • Bohan Chen
  • Shuyong Zhao
    School of Mechanical Engineering and Automation, Beihang University, Beijing, China.
  • Jie Huang
    Department of Critical Medicine, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai 200025, China.
  • Chongze Bi
    School of Mechanical Engineering and Automation, Beihang University, Beijing, China.
  • Lei Li
    Department of Thoracic Surgery, The Affiliated Huaian No.1 People's Hospital of Nanjing Medical University, Huai'an, China.
  • Bochen Tian
    School of Mechanical Engineering and Automation, Beihang University, Beijing, China.
  • Yuchen Liu
    Department of Internal Medicine, Peking Union Medical College Hospital, Beijing, China.
  • Yiyuan Zhang
    Department of Joint Surgery, the Second Hospital of Fuzhou, Teaching Hospital of Xiamen University, Fuzhou Fujian, 350001, P.R.China.972133982@qq.com.
  • JinXi Duan
    School of Mechanical Engineering and Automation, Beihang University, Beijing, China.
  • Fuqiang Yang
    School of Mechanical Engineering and Automation, Beihang University, Beijing, China.
  • Xia He
    Department of Radiation Oncology, Jiangsu Cancer Hospital, Jiangsu Institute of Cancer Research, The Affiliated Cancer Hospital of Nanjing Medical University, Nanjing, China.
  • Kun Xu
    Department of Hygienic Inspection, School of Public Health, Jilin University 1163 Xinmin Street Changchun 130021 Jilin China songxiuling@jlu.edu.cn li_juan@jlu.edu.cn jinmh@jlu.edu.cn +86 43185619441.
  • Ke Wu
    Shanghai Medical Aid Team in Wuhan, Shanghai General Hospital, Shanghai Jiao Tong University, School of Medicine, Shanghai, China.
  • Tianmiao Wang
  • Nguyen Pham
    Key Centre for Polymers and Colloids, School of Chemistry and University of Sydney Nano Institute, The University of Sydney, Sydney, New South Wales, Australia.
  • Xilun Ding
    School of Mechanical Engineering and Automation, Beihang University, Beijing 100191, China.
  • Li Wen

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