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SUNDER:Self-organized grouping and entrapping method for swarms in multitarget environments

Defence Technology（防务技术） 2023年第8期26卷 68-83页

作者： Yutong Yuan Zhun Fan Xiaomin Zhu Li Ma Ji Ouyang Weidong Bao Ji Wang Zhaojun Wang College of Systems Engineer National University of Defense TechnologyChangsha 410073China School of Electrical and Information Engineering Shantou UniversityShantou 515063China Strategic Assessments and Consultation Institute Academy of Military ScienceBeijing 100097China

For swarm robots moving in a harsh or uncharted outdoor environment without GPS guidance and global communication,algorithms that rely on global-based information are infeasible.Typically,traditional gene regulatory networks(GRNs)that achieve superior performance in forming trapping pattern towards targets require accurate global positional information to guide swarm robots.This article presents a gene regulatory network with Self-organized grouping and entrapping method for swarms(SUNDER-GRN)to achieve adequate trapping performance with a large-scale swarm in a confined multitarget environment with access to only local information.A hierarchical self-organized grouping method(HSG)is proposed to structure subswarms in a distributed way.In addition,a modified distributed controller,with a relative coordinate system that is established to relieve the need for global information,is leveraged to facilitate subswarms entrapment toward different targets,thus improving the global multi-target entrapping performance.The results demonstrate the superiority of SUNDERGRN in the performance of structuring subswarms and entrapping 10 targets with 200 robots in an environment confined by obstacles and with only local information accessible.

关键词： swarm robots Local information Gene regulatory network swarm grouping Trapping pattern Confined multitarget environment

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Circle Flocking of swarm robots Based on Relative Position Measurement

Circle Flocking of Swarm Robots Based on Relative Position M...

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第40届中国控制会议

作者： Baolin Zhang Jieyi Yan Donghai Wang Yu Liu Shuping Guo Huanli Gao He Cai School of Automation Science and Engineering South China University of Technology

Inspired by the self-organized behaviors of social animals, swarm robots have been investigated from the perspective of both scientific discoveries and engineering studies in a decentralized way. It is shown that simple rules and local interactions will surprisingly lead to collective behaviors for a large number of robots. Nevertheless, most of the existing results for practical applications relies on absolute position measurements of the robots. In this paper, based on the classic leaderless consensus algorithm, a novel control approach is proposed for circle flocking of swarm robots based on relative position measurement.Comprehensive case studies are provided to evaluate the proposed control approach.

关键词： circle flocking multiagent system relative position measurement swarm robots

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Research on distributed positioning algorithm of swarm robots based on UWB ranging

Research on distributed positioning algorithm of swarm robot...

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第十一届中国卫星导航年会

作者： Jiahao Yang Zhongliang Deng School of Electronic Engineering Beijing University of Posts and Telecommunications

Traditional swarm robots mainly rely on a single GPS for positioning.Complex environment or the failure of the GPS receiver may cause some robots cannot be located because their GPS signals lose,so co

关键词： swarm robots UWB ranging Centroid matrix Iterative estimation Distributed algorithm

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Bioinspired Centimeter-scale Sensor Free Obstacle-passing robots with a Wireless Control System

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Journal of Bionic Engineering 2022年第4期19卷 953-964页

作者： Longxin Kan Zhenhua Wu Bo Song Bin Su Yusheng Shi State Key Laboratory of Material Processing and Die&Mould Technology School of Materials Science and EngineeringHuazhong University of Science and TechnologyWuhan 430074HubeiChina

Obstacle avoidance is of great importance for mobile robots since it provides protection for the robots’safety and ensures their routine operations.Sensors are proven to play an important role in robots obstacle avoidance,and they are useful as well.However,more sensors indicating additional space,larger weight load and more energy consumption.Reducing unnecessary sensors is conducive to the development of mobile robots and remains promising.Here we demonstrate Sensor Free Obstacle-Passing robots(SFOPRs)inspired by flies using the Obstacle-passing strategy instead of Obstacle avoidance.The ability to autonomously adjust its direction after hitting obstacles and the ability to continuously hit obstacles are 2 key problems that need to be solved to build this robot.Owing to arc-shaped head design and undulating motion behaviors,the robots can autonomously adjust their direction to the outline of obstacles,such as a 90°corner,dispersive irregular obstacles,and even an"S"type channel without the assistance of any sensor.Besides,the caterpillar-like movement enables robots to continuously hit obstacles.Furthermore,collaborative awareness and mutual aid can be realized among two or more prototype robots,indicating simple yet functional units for future swarm robots.This study could provide a new strategy to pursue sensor-free obstacle-passing robots for future swarm robot applications.

关键词： Bioinspired Sensor Obstacle swarm robots Untethered

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swarm robotics platform for intelligent interaction

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Virtual Reality & Intelligent Hardware 2019年第3期1卷 316-329页

作者： Yu PENG Nan WANG Yuting DIAO Haipeng MI Academe Arts and Design Tsinghua UniversityBeijing 100084China

Background This paper introduces a versatile edutainment platform based on a swarm robotics system that can support multiple interaction methods.We aim to create a re-usable open-ended tangible tool for a variety of educational and entertainment scenarios by utilizing the unique advantages of swarm robots such as flexible mobility,mutual perception,and free control of robot number.Methods Compared with the tangible user interface,the swarm user interface(SUI)possesses more flexible locomotion and more controllable widgets.However,research on SUI is still limited to system construction,and the upper interaction modes along with vivid applications have not been sufficiently studied.Results This study illustrates possible interaction modes for swarm robotics and feasible application scenarios based on these fundamental interaction modes.We also discuss the implementation of swarm robotics(including software and hardware),then design several simple experiments to verify the location accuracy of the swarm robotics system.

关键词： swarm robots Interactive design Storytelling Physical games

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A Novel Analytical Model of Brain Tumor Based on swarm Robotics

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Proceedings of Anticancer Research 2022年第4期6卷 11-20页

作者： Mohamed Abbas Computers and Communications Department College of EngineeringDelta University for Science and TechnologyGamasa 35712Egypt

A tumor is referred to as“intracranial hard neoplasm”if it grows near the brain or central spinal vessel(neoplasm).In certain cases,it is possible that the responsible cells are neurons situated deep inside the brain’s structure.This article discusses a strategy for halting the progression of brain tumor.A precise and accurate analytical model of brain tumors is the foundation of this strategy.It is based on an algorithm known as kill chain interior point(KCIP),which is the result of a merger of kill chain and interior point algorithms,as well as a precise and accurate analytical model of brain tumors.The inability to obtain a clear picture of tumor cell activity is the biggest challenge in this endeavor.Based on the motion of swarm robots,which are considered a subset of artificial intelligence,this article proposes a new notion of this kind of behavior,which may be used in various situations.The KCIP algorithm that follows is used in the analytical model to limit the development of certain cell types.According to the findings,it seems that different KCIP speed ratios are beneficial in preventing the development of brain tumors.It is hoped that this study will help researchers better understand the behavior of brain tumors,so as to develop a new drug that is effective in eliminating the tumor cells.

关键词： swarm robots Brain tumor Analytical computation Kill chain Interior point algorithm

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