ArticleBiomimetics (Basel, Switzerland)2026
Tribological Behavior and Attachment Force Regulation of Bioinspired Claw-Spines.
Article in Biomimetics (Basel, Switzerland), 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
This study investigates the tribological behavior of the attachment force between bio-inspired claw-spines and rough surfaces and conducts theoretical and model-based analyses of the corresponding attachment mechanism. Based on critical interfacial tribological theory, a frictional mechanics model for a single claw-spine interacting with an arbitrary rough surface was developed. Furthermore, a stiffness-matrix-based mechanical model of bio-inspired claw-spine attachment to arbitrary surfaces was established, together with a contact interaction model between the claw-spine and the contact surface. The force distribution during the contact and attachment of the claw-spine to arbitrary surfaces was analyzed in detail. Criteria for determining stable claw-spine attachment were formulated, and the safe range of frame displacement variation under the corresponding conditions was identified. Based on these analytical results, a test platform for the bio-inspired claw-spine attachment structure was designed. In the experiments, the developed attachment-force measurement system was used to measure and analyze the frictional attachment forces generated by the claw-spine foot on different rough surfaces. After the claw-spine entered the stable attachment stage, the maximum claw-spine attachment forces measured on 60-grit, 80-grit, and 120-grit sandpaper surfaces were 0.62 N, 0.54 N, and 0.61 N, respectively. The corresponding maximum attachment forces measured on horizontal and vertical brick surfaces were 0.92 and 0.99 N, respectively. The results provide a basis for the mechanical analysis and force sensing of bio-inspired claw-spine attachment states and establish theoretical and experimental foundations for subsequent research on attachment-state recognition and motion control based on attachment-force feedback.
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