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形态智能可防止沙漠蝗虫和动态机器人脚部打滑。

Morphological intelligence counters foot slipping in the desert locust and dynamic robots.

机构信息

Physical Intelligence Department, Max Planck Institute for Intelligent Systems, 70569 Stuttgart, Germany.

Physical Intelligence Department, Max Planck Institute for Intelligent Systems, 70569 Stuttgart, Germany

出版信息

Proc Natl Acad Sci U S A. 2018 Sep 4;115(36):E8358-E8367. doi: 10.1073/pnas.1804239115. Epub 2018 Aug 22.

Abstract

During dynamic terrestrial locomotion, animals use complex multifunctional feet to extract friction from the environment. However, whether roboticists assume sufficient surface friction for locomotion or actively compensate for slipping, they use relatively simple point-contact feet. We seek to understand and extract the morphological adaptations of animal feet that contribute to enhancing friction on diverse surfaces, such as the desert locust () [Bennet-Clark HC (1975) 63:53-83], which has both wet adhesive pads and spines. A buckling region in their knee to accommodate slipping [Bayley TG, Sutton GP, Burrows M (2012) 215:1151-1161], slow nerve conduction velocity (0.5-3 m/s) [Pearson KG, Stein RB, Malhotra SK (1970) 53:299-316], and an ecological pressure to enhance jumping performance for survival [Hawlena D, Kress H, Dufresne ER, Schmitz OJ (2011) 25:279-288] further suggest that the locust operates near the limits of its surface friction, but without sufficient time to actively control its feet. Therefore, all surface adaptation must be through passive mechanics (morphological intelligence), which are unknown. Here, we report the slipping behavior, dynamic attachment, passive mechanics, and interplay between the spines and adhesive pads, studied through both biological and robotic experiments, which contribute to the locust's ability to jump robustly from diverse surfaces. We found slipping to be surface-dependent and common (e.g., wood 1.32 ± 1.19 slips per jump), yet the morphological intelligence of the feet produces a significant chance to reengage the surface (e.g., wood 1.10 ± 1.13 reengagements per jump). Additionally, a discovered noncontact-type jump, further studied robotically, broadens the applicability of the morphological adaptations to both static and dynamic attachment.

摘要

在动态陆地运动中,动物使用复杂的多功能脚从环境中提取摩擦力。然而,无论是机器人专家假设足够的表面摩擦力进行运动,还是主动补偿滑动,他们都使用相对简单的点接触脚。我们试图了解和提取动物脚的形态适应,这些适应有助于提高在不同表面上的摩擦力,例如沙漠蝗虫[Bennet-Clark HC(1975)63:53-83],它既有湿粘性垫又有刺。它们膝盖的屈曲区域可适应滑动[Bayley TG,Sutton GP,Burrows M(2012)215:1151-1161],神经传导速度较慢(0.5-3 m/s)[Pearson KG,Stein RB,Malhotra SK(1970)53:299-316],以及为了生存而增强跳跃性能的生态压力[Hawlena D,Kress H,Dufresne ER,Schmitz OJ(2011)25:279-288]进一步表明,蝗虫的运作接近其表面摩擦力的极限,但没有足够的时间主动控制其脚。因此,所有表面适应都必须通过被动力学(形态智能)来实现,而这是未知的。在这里,我们通过生物和机器人实验报告了滑动行为、动态附着、被动力学以及刺和粘性垫之间的相互作用,这些行为和相互作用有助于蝗虫从不同表面稳健地跳跃。我们发现滑动是依赖于表面的,而且很常见(例如,在木材上每跳 1.32±1.19 次滑动),但脚的形态智能提供了一个重新与表面接触的重要机会(例如,在木材上每跳 1.10±1.13 次重新接触)。此外,进一步在机器人上研究发现的非接触式跳跃,拓宽了形态适应在静态和动态附着中的适用性。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c4fd/6130395/8d4238e420e3/pnas.1804239115fig01.jpg

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