内部阻尼对摩擦环境中运动的影响
The Effect of Internal Damping on Locomotion in Frictional Environments
AI总结：
本文研究内部阻尼对连续粘弹性非线性梁模型爬行器运动性能的影响，发现调节内部阻尼可改变步态和运动方向，并确定最优阻尼以实现最大爬行速度。
摘要：
波动动物的步态源于其中枢神经系统、肌肉、结缔组织、骨骼和环境之间的复杂相互作用。作为一种简化假设，许多先前的研究通常假定有足够的内部力来产生观测到的运动学，因此并未重点关注量化肌肉用力、身体形状和外部反作用力之间的相互联系。然而，这种相互作用对爬行动物的运动性能至关重要，尤其是当伴随身体粘弹性时。此外，在仿生机器人应用中，身体的内部阻尼确实是设计者可以调节的参数。尽管如此，内部阻尼的影响仍未得到充分理解。本研究探讨了内部阻尼如何影响具有连续、粘弹性、非线性梁模型的爬行器的运动性能。爬行器的肌肉驱动被建模为沿身体向后传播的弯曲力矩行波。与蛇和无肢蜥蜴鳞片的摩擦特性一致，环境力使用各向异性库仑摩擦进行建模。研究发现，通过改变爬行器身体的内部阻尼，可以改变爬行器的性能，并且可以实现不同的步态，包括将净运动方向从向前改变为向后。我们将讨论这种向前和向后控制，并确定实现最大爬行速度的最优内部阻尼。
英文摘要：
The gaits of undulating animals arise from a complex interaction of their central nervous system, muscle, connective tissue, bone, and environment. As a simplifying assumption, many previous studies have often assumed that sufficient internal force is available to produce observed kinematics, thus not focusing on quantifying the interconnection between muscle effort, body shape, and external reaction forces. This interplay, however, is critical to locomotion performance in crawling animals, especially when accompanied by body viscoelasticity. Moreover, in bio-inspired robotic applications, the body's internal damping is indeed a parameter that the designer can tune. Still, the effect of internal damping is not well understood. This study explores how internal damping affects the locomotion performance of a crawler with a continuous, visco-elastic, nonlinear beam model. Crawler muscle actuation is modeled as a traveling wave of bending moment propagating posteriorly along the body. Consistent with the friction properties of the scales of snakes and limbless lizards, environmental forces are modeled using anisotropic Coulomb friction. It is found that by varying the crawler body's internal damping, the crawler's performance can be altered, and distinct gaits could be achieved, including changing the net locomotion direction from forward to back. We will discuss this forward and backward control and identify the optimal internal damping for peak crawling speed.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
