JOURNAL ARTICLE

Spines and Inclines: Bioinspired Spines on an Insect-Scale Robot Facilitate Locomotion on Rough and Inclined Terrain.

  • Published In: Integrative & Comparative Biology, 2024, v. 64, n. 5. P. 1371 1 of 3

  • Database: Academic Search Ultimate 2 of 3

  • Authored By: Hernandez, Alyssa M; Schiebel, Perrin E; Shum, Jennifer; Wood, Robert J 3 of 3

Abstract

This article investigates the diversity and functional significance of tarsal spines on the hind legs of ground beetles (family Carabidae) and their role in facilitating locomotion across rough and inclined terrains. By measuring spine morphometrics such as aspect ratio and orientation angle across four beetle species, the study identified key parameters influencing shear force generation during substrate interaction. Bioinspired spines fabricated from stainless steel were tested on 3D-printed rough surfaces using a motorized shear setup, revealing that spines angled at approximately 50° produced higher shear forces than those at 90°, likely due to more effective frictional interlocking with surface asperities. These findings were corroborated by locomotion experiments deploying the spines on an insect-scale robot, where 50° spines enhanced speed and stability on inclined and rough surfaces compared to 90° spines or spineless legs. The research highlights the importance of spine geometry in insect attachment and locomotion, demonstrating the utility of physical models and robotic platforms for comparative biomechanical studies relevant to ecological adaptations.

Additional Information

  • Source:Integrative & Comparative Biology. 2024/11, Vol. 64, Issue 5, p1371
  • Document Type:Article
  • Subject Area:Zoology
  • Publication Date:2024
  • ISSN:1540-7063
  • DOI:10.1093/icb/icae145
  • Accession Number:181030434
  • Copyright Statement:Copyright of Integrative & Comparative Biology is the property of Oxford University Press / USA and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

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