Investigating the impact of initial parameters on autonomous robot swarm movement strategies for enhanced exploration efficiency: a comprehensive study.

IF 3.1 3区 计算机科学 Q1 ENGINEERING, MULTIDISCIPLINARY
Kübra Karadağ, Özgür Tamer
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Abstract

Swarm robots are frequently preferred for the exploration of harsh environments and search and rescue operations. This study explores the factors that influence the movement strategies of autonomous robot swarms and their impact on swarm distribution in the field, employing simulation-based analysis. The research consists of two parts: initially, robots undergo free-fall as passive entities, followed by a phase where they employ predefined movement strategies from their fall positions. The study aims to investigate how the initial position and related parameters affect movement characteristics and the ultimate swarm distribution. To achieve this objective, four parameters-radius, height, mass, and the Coefficient of Restitution-were identified, each assigned three different values. The study observes the effects of these parameters on robot motion, considering motion strategies such as Random Walk, Levy Walk, Markov Process, and Brownian Motion. Results indicate that increasing parameter values induce changes in the position values of the free-falling swarm in the first part, which is the initial position for the second part, influencing movement strategies in diverse ways. The outcomes are analyzed concerning the radial and angular spread of the robots. Radial spread measures how far swarm elements spread from their initial positions, while angular spread indicates how homogeneously the robots are distributed according to the polar angle. The study comprehensively investigates how the movement strategies of autonomous robot swarms are impacted by parameters and how these effects manifest in the results. The findings are anticipated to enhance the effective utilization of autonomous robot swarms in exploration missions.

探究初始参数对自主机器人蜂群运动策略的影响以提高探索效率:一项综合研究
在恶劣环境的探索和搜救行动中,蜂群机器人经常受到青睐。本研究采用基于仿真的分析方法,探讨了影响自主 机器人群运动策略的因素及其对机器人群在野外分布的影响。 研究由两部分组成:首先,机器人作为被动实体进行自由落体运动,然后是一个 阶段,机器人从落体位置开始采用预定义的运动策略。研究旨在探讨初始位置和相关参数如何影响运动特性和最终的蜂群分布。为了实现这一目标,我们确定了四个参数--半径、高度、质量和恢复系数,每个参数都有三个不同的值。研究观察了这些参数对机器人运动的影响,并考虑了随机行走、列维行走、马尔可夫过程和布朗运动等运动策略。结果表明,参数值的增加会引起自由落体蜂群在第一部分(即第二部分的初始 位置)的位置值发生变化,从而对运动策略产生不同的影响。分析结果涉及机器人的径向和角向散布。径向散布衡量的是蜂群元素从初始位置向外散布的程度,而角度散布则表示机器人根据极角分布的均匀程度。该研究全面探讨了自主机器人群的运动策略如何受到参数的影响,以及这些影响如何在结果中体现出来。研究结果有望提高自主机器人群在探索任务中的有效利用:蜂群机器人、自主机器人、随机行走、列维行走、布朗运动、马尔可夫 过程。
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来源期刊
Bioinspiration & Biomimetics
Bioinspiration & Biomimetics 工程技术-材料科学:生物材料
CiteScore
5.90
自引率
14.70%
发文量
132
审稿时长
3 months
期刊介绍: Bioinspiration & Biomimetics publishes research involving the study and distillation of principles and functions found in biological systems that have been developed through evolution, and application of this knowledge to produce novel and exciting basic technologies and new approaches to solving scientific problems. It provides a forum for interdisciplinary research which acts as a pipeline, facilitating the two-way flow of ideas and understanding between the extensive bodies of knowledge of the different disciplines. It has two principal aims: to draw on biology to enrich engineering and to draw from engineering to enrich biology. The journal aims to include input from across all intersecting areas of both fields. In biology, this would include work in all fields from physiology to ecology, with either zoological or botanical focus. In engineering, this would include both design and practical application of biomimetic or bioinspired devices and systems. Typical areas of interest include: Systems, designs and structure Communication and navigation Cooperative behaviour Self-organizing biological systems Self-healing and self-assembly Aerial locomotion and aerospace applications of biomimetics Biomorphic surface and subsurface systems Marine dynamics: swimming and underwater dynamics Applications of novel materials Biomechanics; including movement, locomotion, fluidics Cellular behaviour Sensors and senses Biomimetic or bioinformed approaches to geological exploration.
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