Elongating, entwining, and dragging: mechanism for adaptive locomotion of tubificine worm blobs in a confined environment.

IF 2.6 4区 计算机科学 Q3 COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE
Taishi Mikami, Daiki Wakita, Ryo Kobayashi, Akio Ishiguro, Takeshi Kano
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引用次数: 0

Abstract

Worms often aggregate through physical connections and exhibit remarkable functions such as efficient migration, survival under environmental changes, and defense against predators. In particular, entangled blobs demonstrate versatile behaviors for their survival; they form spherical blobs and migrate collectively by flexibly changing their shape in response to the environment. In contrast to previous studies on the collective behavior of worm blobs that focused on locomotion in a flat environment, we investigated the mechanisms underlying their adaptive motion in confined environments, focusing on tubificine worm collectives. We first performed several behavioral experiments to observe the aggregation process, collective response to aversive stimuli, the motion of a few worms, and blob motion in confined spaces with and without pegs. We found the blob deformed and passed through a narrow passage using environmental heterogeneities. Based on these behavioral findings, we constructed a simple two-dimensional agent-based model wherein the flexible body of a worm was described as a cross-shaped agent that could deform, rotate, and translate. The simulations demonstrated that the behavioral findings were well-reproduced. Our findings aid in understanding how physical interactions contribute to generating adaptive collective behaviors in real-world environments as well as in designing novel swarm robotic systems consisting of soft agents.

拉长、缠绕和拖拽:管状蠕虫在受限环境中的自适应运动机制。
蠕虫通常通过物理连接聚集在一起,并表现出诸如高效迁移、在环境变化中生存和防御捕食者等显著功能。特别是,纠缠的斑点表现出多种生存行为;它们形成球形,并根据环境灵活地改变形状,集体迁移。与以往关于蠕虫集体行为的研究不同,我们研究了它们在受限环境中自适应运动的机制,重点研究了管状蠕虫集体。我们首先进行了几个行为实验来观察聚集过程,对厌恶刺激的集体反应,一些蠕虫的运动,以及在有和没有钉子的密闭空间中的斑点运动。我们发现斑点变形,并通过一个狭窄的通道利用环境的异质性。基于这些行为发现,我们构建了一个简单的二维智能体模型,其中蠕虫的柔性体被描述为一个可以变形、旋转和平移的十字形智能体。模拟表明,这些行为发现被很好地再现了。我们的发现有助于理解物理相互作用如何在现实环境中产生适应性集体行为,以及设计由软代理组成的新型群体机器人系统。
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来源期刊
Frontiers in Neurorobotics
Frontiers in Neurorobotics COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCER-ROBOTICS
CiteScore
5.20
自引率
6.50%
发文量
250
审稿时长
14 weeks
期刊介绍: Frontiers in Neurorobotics publishes rigorously peer-reviewed research in the science and technology of embodied autonomous neural systems. Specialty Chief Editors Alois C. Knoll and Florian Röhrbein at the Technische Universität München are supported by an outstanding Editorial Board of international experts. This multidisciplinary open-access journal is at the forefront of disseminating and communicating scientific knowledge and impactful discoveries to researchers, academics and the public worldwide. Neural systems include brain-inspired algorithms (e.g. connectionist networks), computational models of biological neural networks (e.g. artificial spiking neural nets, large-scale simulations of neural microcircuits) and actual biological systems (e.g. in vivo and in vitro neural nets). The focus of the journal is the embodiment of such neural systems in artificial software and hardware devices, machines, robots or any other form of physical actuation. This also includes prosthetic devices, brain machine interfaces, wearable systems, micro-machines, furniture, home appliances, as well as systems for managing micro and macro infrastructures. Frontiers in Neurorobotics also aims to publish radically new tools and methods to study plasticity and development of autonomous self-learning systems that are capable of acquiring knowledge in an open-ended manner. Models complemented with experimental studies revealing self-organizing principles of embodied neural systems are welcome. Our journal also publishes on the micro and macro engineering and mechatronics of robotic devices driven by neural systems, as well as studies on the impact that such systems will have on our daily life.
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