Locomotion characteristics of foxtail and foxtail type robot according to acting force

Lee, Minsu; Kim, Yeonghyeok; Leem, Sang-Huyck; Park, Jong-Oh; Park, Sukho; Kim, Byung Kyu

doi:10.1109/biorob.2010.5627752

Cited by 1 publication

(1 citation statement)

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“…This phenomenon, known as frictional anisotropy, is the key principle that enables the propulsion of foxtail robots. Various operation methods for foxtail robots have been proposed, including the use of external forces ( Figure 3 a–c) such as horizontal external forces [ 2 , 3 ], vertical external forces [ 4 , 5 , 6 ], and pipe height changes [ 7 ]. Internal actuation mechanisms ( Figure 3 d–f) such as the inchworm [ 8 , 9 ], phase-difference [ 10 ], and carangiform locomotion [ 1 ] have also been studied.…”

Section: Introductionmentioning

confidence: 99%

Dynamic Analysis of the Locomotion Mechanism in Foxtail Robots: Frictional Anisotropy and Bristle Diversity

Lee,

Jeong,

Kim

et al. 2024

Biomimetics

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This study investigated the locomotion mechanism of foxtail robots, focusing on the frictional anisotropy of tilted bristles under the same friction coefficient and propulsion strategy using bristle diversity. Through dynamic analysis and simulations, we confirmed the frictional anisotropy of tilted bristles and elucidated the role of bristle diversity in generating propulsive force. The interaction between contact nonuniformity and frictional anisotropy was identified as the core principle enabling foxtail locomotion. Simulations of foxtail robots with multiple bristles demonstrated that variations in bristle length, angle, and deformation contribute to propulsive force generation and environmental adaptability. In addition, this study analyzed the influence of major design parameters on frictional anisotropy, highlighting the critical roles of body height, bristle length, stiffness, reference angle, and friction coefficient. The proposed guidelines for designing foxtail robots emphasize securing bristle nonuniformity and inducing contact nonuniformity. The simulation framework presented enables the quantitative prediction and optimization of foxtail robot performance. This research provides valuable insights into foxtail robot locomotion and lays a foundation for the development of efficient and adaptive next-generation robots for diverse environments.

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