We optimize three-dimensional snake kinematics for locomotor efficiency. We assume a general space-curve representation of the snake backbone with small-to-moderate lifting off the ground and negligible body inertia. The cost of locomotion includes work against friction and internal viscous dissipation. When restricted to planar kinematics, our population-based optimization method finds the same types of optima as a previous Newton-based method. A few types of optimal motions prevail. We find an s-shaped body with alternating lifting of the middle and ends for small-to-moderate transverse friction. For large transverse friction, curling and sliding motions are typical with small viscous dissipation, replaced by large-amplitude bending with large viscous dissipation. With small viscous dissipation we find local optima that resemble sidewinding motions across friction coefficient space. They are always suboptimal to alternating lifting motions, with average input power 10--100\% higher.
翻译:我们优化了三维蛇感官学,以优化叶质运动效率。 我们假设蛇脊具有一般的空间曲线代表, 以小到中等的升降和可忽略的体性惯性。 移动成本包括对抗摩擦和内部粘度消散的工作。 我们的人口优化方法与先前的牛顿法相同。 少数类型的最佳动作占上风。 我们发现一个成形体, 中间和尾端交替提升, 用于小到中位的反向摩擦。 对于大型反向摩擦, 曲曲和滑动运动通常以小粘度消散为典型, 代之以大粘度弯曲, 并用大粘度消散。 随着小粘度消化, 我们发现本地的优化方法类似于摩擦系数空间的侧向运动。 它们总是比交替升动更差, 平均输入功率为10- 100 ⁇ 高。