Corucci Francesco, Cheney Nick, Giorgio-Serchi Francesco, Bongard Josh, Laschi Cecilia
1 The BioRobotics Institute , Scuola Superiore Sant'Anna, Pisa, Italy .
2 Morphology, Evolution and Cognition Lab, University of Vermont , Burlington, Vermont.
Soft Robot. 2018 Aug;5(4):475-495. doi: 10.1089/soro.2017.0055. Epub 2018 Jul 9.
Designing soft robots poses considerable challenges; automated design approaches may be particularly appealing in this field, as they promise to optimize complex multimaterial machines with very little or no human intervention. Evolutionary soft robotics is concerned with the application of optimization algorithms inspired by natural evolution to let soft robots (both their morphologies and controllers) spontaneously evolve within physically realistic simulated environments, figuring out how to satisfy a set of objectives defined by human designers. In this article, a powerful evolutionary system is put in place to perform a broad investigation on the free-form evolution of simulated walking and swimming soft robots in different environments. Three sets of experiments are reported, tackling different aspects of the evolution of soft locomotion. The first two explore the effects of different material properties on the evolution of terrestrial and aquatic soft locomotion: particularly, we show how different materials lead to the evolution of different morphologies, behaviors, and energy-performance trade-offs. It is found that within our simplified physics world, stiffer robots evolve more sophisticated and effective gaits and morphologies on land, while softer ones tend to perform better in water. The third set of experiments starts investigating the effect and potential benefits of major environmental transitions (land↔water) during evolution. Results provide interesting morphological exaptation phenomena and point out a potential asymmetry between land→water and water→land transitions: while the first type of transition appears to be detrimental, the second one seems to have some beneficial effects.
设计软体机器人面临着诸多挑战;自动化设计方法在该领域可能特别具有吸引力,因为它们有望在极少或无需人工干预的情况下优化复杂的多材料机器。进化软体机器人学关注受自然进化启发的优化算法的应用,以使软体机器人(包括其形态和控制器)在物理上逼真的模拟环境中自发进化,从而找出如何满足人类设计师定义的一组目标。在本文中,我们建立了一个强大的进化系统,对不同环境下模拟行走和游泳的软体机器人的自由形式进化进行广泛研究。报告了三组实验,涉及软体运动进化的不同方面。前两组实验探讨了不同材料属性对陆地和水生软体运动进化的影响:具体而言,我们展示了不同材料如何导致不同形态、行为以及能量性能权衡的进化。研究发现,在我们简化的物理世界中,更硬的机器人在陆地上进化出更复杂、有效的步态和形态,而更软的机器人在水中往往表现更好。第三组实验开始研究进化过程中主要环境转变(陆地↔水)的影响和潜在益处。结果提供了有趣的形态预适应现象,并指出了陆地→水和水→陆转变之间可能存在的不对称性:虽然第一种转变似乎有害,但第二种转变似乎有一些有益影响。