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<p>Serpentine locomotion in snake robots is inherently susceptible to lateral slip induced by environmental interactions, leading to propulsion efficiency degradation and trajectory deviations. To address these tribodynamic coupling challenges, this study systematically investigates slip dynamics and parametric optimization strategies for high-efficiency serpentine propulsion. First, a hybrid Coulomb-viscous friction model is developed to characterize anisotropic contact constraints while ensuring numerical convergence. Based on this formulation, a generalized multibody dynamics framework incorporating passive wheel position parameters is established using planar rigid-body motion theorems. Numerical simulations comprehensively evaluate the sensitivity of frictional anisotropy, propulsion loss coefficient, and propulsion velocity to distinct control parameters. Subsequently, a genetic algorithm (GA) optimization framework is employed to determine optimal gait parameters, yielding an explicit empirical mapping between optimal initial angles and friction coefficient ratios to facilitate terrain-dependent parameter selection. Crucially, experimental validation on a physical prototype confirms the theoretical trends across varying friction conditions. Demonstrating significant enhancements in locomotion stability and efficiency, the proposed framework provides quantitative design guidelines and a theoretical basis for robust terrain-adaptive control of snake robots in unstructured environments.</p>

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Hybrid tribodynamic modeling and multi-parametric genetic optimization for serpentine propulsion in snake robots

  • 期刊论文

  • 发表日期：

    2026年8月4日

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  • Peng Zhang,
  • Xupeng Liu,
  • Zhiying Gao,
  • Ben Guan,
  • Yong Zang

摘要

Serpentine locomotion in snake robots is inherently susceptible to lateral slip induced by environmental interactions, leading to propulsion efficiency degradation and trajectory deviations. To address these tribodynamic coupling challenges, this study systematically investigates slip dynamics and parametric optimization strategies for high-efficiency serpentine propulsion. First, a hybrid Coulomb-viscous friction model is developed to characterize anisotropic contact constraints while ensuring numerical convergence. Based on this formulation, a generalized multibody dynamics framework incorporating passive wheel position parameters is established using planar rigid-body motion theorems. Numerical simulations comprehensively evaluate the sensitivity of frictional anisotropy, propulsion loss coefficient, and propulsion velocity to distinct control parameters. Subsequently, a genetic algorithm (GA) optimization framework is employed to determine optimal gait parameters, yielding an explicit empirical mapping between optimal initial angles and friction coefficient ratios to facilitate terrain-dependent parameter selection. Crucially, experimental validation on a physical prototype confirms the theoretical trends across varying friction conditions. Demonstrating significant enhancements in locomotion stability and efficiency, the proposed framework provides quantitative design guidelines and a theoretical basis for robust terrain-adaptive control of snake robots in unstructured environments.