arXiv:2602.12199cs.ROcs.NA2026-02

用几何方法建模细长生物的最优运动,兼顾环境阻力与自身变形能耗。

Sub--Riemannian boundary value problems for Optimal Geometric Locomotion

  • 基于子黎曼测地线构建能量耗散最小化边界问题。
  • 能计算三种边界条件下的最优形变步态,结果符合真实生物运动轨迹。
  • 适合研究生物运动机理或仿生机器人设计的学者使用。

我们提出一种几何模型,用于描述细长运动体(如在沙地上滑行的蛇)通过形状变化实现的最优运动。在这些场景中,物体在世界坐标系中的运动完全由其经历的一系列形状决定。具体而言,我们将拉格朗日最小耗散原理表述为边界值问题,其解为子黎曼测地线。值得注意的是,该几何模型不仅考虑了物体在环境中移动时的能量耗散,还纳入了生物代谢或机器人执行器为诱导形变(如弯曲、拉伸)所消耗的能量,从而捕捉整体运动效率。我们的连续模型结合一致的时间与空间离散化,可数值求解三类边界条件下的子黎曼测地线:固定初始与目标体位、限制为循环运动,或仅规定体位与朝向的位移。所得最优形变步态在定性上匹配蛇类、精子等生物的真实运动轨迹,也符合低维系统(如Purcell游泳器)已知的最优性结果。相比以往框架,本模型几何灵活性更高,为广义Purcell游泳器的运动机制提供了新见解。代码已公开。

原文摘要 · Abstract (English)

We propose a geometric model for optimal shape-change-induced motions of slender locomotors, e.g., snakes slithering on sand. In these scenarios, the motion of a body in world coordinates is completely determined by the sequence of shapes it assumes. Specifically, we formulate Lagrangian least-dissipation principles as boundary value problems whose solutions are given by sub-Riemannian geodesics. Notably, our geometric model accounts not only for the energy dissipated by the body's displacement through the environment, but also for the energy dissipated by the animal's metabolism or a robot's actuators to induce shape changes such as bending and stretching, thus capturing overall locomotion efficiency. Our continuous model, together with a consistent time and space discretization, enables numerical computation of sub-Riemannian geodesics for three different types of boundary conditions, i.e., fixing initial and target body, restricting to cyclic motion, or solely prescribing body displacement and orientation. The resulting optimal deformation gaits qualitatively match observed motion trajectories of organisms such as snakes and spermatozoa, as well as known optimality results for low-dimensional systems such as Purcell's swimmers. Moreover, being geometrically less rigid than previous frameworks, our model enables new insights into locomotion mechanisms of, e.g., generalized Purcell's swimmers. The code is publicly available.

生物运动几何建模最优控制仿生学

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