Embodied AI and Neurorobotics Lab, Centre for BioRobotics, The Mærsk Mc-Kinney Møller Institute, University of Southern Denmark, Odense M, DK-5230, Denmark.
Bernstein Center for Computational Neuroscience (BCCN), The Third Institute of Physics, Georg-August-Universität Göttingen, Göttingen, D-37077, Germany.
Sci Rep. 2016 Dec 23;6:39455. doi: 10.1038/srep39455.
Based on the principles of morphological computation, we propose a novel approach that exploits the interaction between a passive anisotropic scale-like material (e.g., shark skin) and a non-smooth substrate to enhance locomotion efficiency of a robot walking on inclines. Real robot experiments show that passive tribologically-enhanced surfaces of the robot belly or foot allow the robot to grip on specific surfaces and move effectively with reduced energy consumption. Supplementing the robot experiments, we investigated tribological properties of the shark skin as well as its mechanical stability. It shows high frictional anisotropy due to an array of sloped denticles. The orientation of the denticles to the underlying collagenous material also strongly influences their mechanical interlocking with the substrate. This study not only opens up a new way of achieving energy-efficient legged robot locomotion but also provides a better understanding of the functionalities and mechanical properties of anisotropic surfaces. That understanding will assist developing new types of material for other real-world applications.
基于形态计算原理,我们提出了一种新方法,利用被动各向异性鳞片材料(如鲨鱼皮)与非光滑基底之间的相互作用,来提高机器人在倾斜表面上的运动效率。真实机器人实验表明,机器人腹部或脚部的被动摩擦增强表面允许机器人在特定表面上抓握,并以较低的能耗有效地移动。作为机器人实验的补充,我们研究了鲨鱼皮的摩擦学特性及其机械稳定性。由于存在一系列倾斜的齿状突起,它表现出很高的摩擦各向异性。齿状突起相对于下面的胶原材料的方向也强烈影响它们与基底的机械互锁。这项研究不仅为实现节能的腿式机器人运动开辟了新途径,还加深了我们对各向异性表面的功能和机械特性的理解。这种理解将有助于开发用于其他实际应用的新型材料。