Ayali Amir, Kaminka Gal A
School of Zoology, Sagol School of Neuroscience, Tel Aviv University, Tel-Aviv, Israel.
Department of Computer Science and Gonda Brain Research Center, Bar-Ilan University, Ramat Gan, Israel.
Front Neurorobot. 2023 Jul 14;17:1215085. doi: 10.3389/fnbot.2023.1215085. eCollection 2023.
Swarming or collective motion is ubiquitous in natural systems, and instrumental in many technological applications. Accordingly, research interest in this phenomenon is crossing discipline boundaries. A common major question is that of the intricate interactions between the individual, the group, and the environment. There are, however, major gaps in our understanding of swarming systems, very often due to the theoretical difficulty of relating embodied properties to the physical agents-individual animals or robots. Recently, there has been much progress in exploiting the complementary nature of the two disciplines: biology and robotics. This, unfortunately, is still uncommon in swarm research. Specifically, there are very few examples of joint research programs that investigate multiple biological and synthetic agents concomitantly. Here we present a novel research tool, enabling a unique, tightly integrated, bio-inspired, and robot-assisted study of major questions in swarm collective motion. Utilizing a quintessential model of collective behavior-locust nymphs and our recently developed Nymbots (locust-inspired robots)-we focus on fundamental questions and gaps in the scientific understanding of swarms, providing novel interdisciplinary insights and sharing ideas disciplines. The Nymbot-Locust bio-hybrid swarm enables the investigation of biology hypotheses that would be otherwise difficult, or even impossible to test, and to discover technological insights that might otherwise remain hidden from view.
群体运动或集体运动在自然系统中无处不在，并且在许多技术应用中发挥着重要作用。因此，对这一现象的研究兴趣正在跨越学科界限。一个常见的主要问题是个体、群体和环境之间复杂的相互作用。然而，我们对群体系统的理解存在重大差距，这往往是由于将具体特性与物理主体（个体动物或机器人）联系起来存在理论困难。最近，在利用生物学和机器人学这两个学科的互补性质方面取得了很大进展。不幸的是，这在群体研究中仍然并不常见。具体而言，很少有联合研究项目同时研究多种生物和合成主体的例子。在此，我们展示一种新颖的研究工具，它能够对群体集体运动中的主要问题进行独特、紧密整合、受生物启发且由机器人辅助的研究。利用集体行为的一个典型模型——蝗虫若虫以及我们最近开发的Nymbots（受蝗虫启发的机器人），我们聚焦于群体科学理解中的基本问题和差距，提供新颖的跨学科见解并在不同学科间分享观点。Nymbot - 蝗虫生物混合群体能够对那些否则将难以甚至无法测试的生物学假设进行研究，并发现那些可能否则仍会隐藏不见的技术见解。
