海洋藻类启发的具有二元感知信息的蜂群机器人的散布

IF 5 2区 计算机科学 Q1 COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE
Zhao Zhang, Xiaokang Lei, Xingguang Peng
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引用次数: 0

摘要

蜂群机器人系统的动力学非常复杂,而且往往是非线性的。其中一个关键问题是如何设计大量简单、低成本机器人的控制器,以便能够观察到它们的出现。本文受藻类中观察到的机制启发,为蜂群机器人系统提出了一种传感器和计算友好型控制器。其目的是通过模仿在海洋藻类系统中观察到的圆周运动,实现机器人的均匀分散。提议的控制器利用二元感官信息(即看到或看不到)来引导机器人运动。通过圆周运动并根据对视线内其他机器人的感知切换半径,机器人模仿了在藻类中观察到的排斥行为。控制器完全依赖于二元状态的感觉输入,无需额外的内存或通信。多达 1024 个模拟机器人被用来验证分散控制器的有效性,而 30 个物理机器人的实验则证明了建议方法的可行性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

Marine algae inspired dispersion of swarm robots with binary sensory information

Marine algae inspired dispersion of swarm robots with binary sensory information

The dynamics of swarm robotic systems are complex and often nonlinear. One key issue is to design the controllers of a large number of simple, low-cost robots so that emergence can be observed. This paper presents a sensor and computation-friendly controller for swarm robotic systems inspired by the mechanisms observed in algae. The aim is to achieve uniform dispersion of robots by mimicking the circular movement observed in marine algae systems. The proposed controller utilizes binary sensory information (i.e., see or not see) to guide the robots’ motion. By moving circularly and switching the radii based on the perception of other robots in their line of sight, the robots imitate the repulsion behavior observed in algae. The controller relies solely on binary-state sensory input, eliminating the need for additional memory or communication. Up to 1024 simulated robots are used to validate the effectiveness of the dispersion controller, while experiments with 30 physical robots demonstrate the feasibility of the proposed approach.

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来源期刊
Complex & Intelligent Systems
Complex & Intelligent Systems COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE-
CiteScore
9.60
自引率
10.30%
发文量
297
期刊介绍: Complex & Intelligent Systems aims to provide a forum for presenting and discussing novel approaches, tools and techniques meant for attaining a cross-fertilization between the broad fields of complex systems, computational simulation, and intelligent analytics and visualization. The transdisciplinary research that the journal focuses on will expand the boundaries of our understanding by investigating the principles and processes that underlie many of the most profound problems facing society today.
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