• 文献检索
  • 文档翻译
  • 深度研究
  • 学术资讯
  • Suppr Zotero 插件Zotero 插件
  • 邀请有礼
  • 套餐&价格
  • 历史记录
应用&插件
Suppr Zotero 插件Zotero 插件浏览器插件Mac 客户端Windows 客户端微信小程序
定价
高级版会员购买积分包购买API积分包
服务
文献检索文档翻译深度研究API 文档MCP 服务
关于我们
关于 Suppr公司介绍联系我们用户协议隐私条款
关注我们

Suppr 超能文献

核心技术专利:CN118964589B侵权必究
粤ICP备2023148730 号-1Suppr @ 2026

文献检索

告别复杂PubMed语法,用中文像聊天一样搜索,搜遍4000万医学文献。AI智能推荐,让科研检索更轻松。

立即免费搜索

文件翻译

保留排版,准确专业,支持PDF/Word/PPT等文件格式,支持 12+语言互译。

免费翻译文档

深度研究

AI帮你快速写综述,25分钟生成高质量综述,智能提取关键信息,辅助科研写作。

立即免费体验

表型可塑性为最小场群体机器人技术提供了一个生物启发框架。

Phenotypic Plasticity Provides a Bioinspiration Framework for Minimal Field Swarm Robotics.

作者信息

Hunt Edmund R

机构信息

Department of Engineering Mathematics, University of Bristol, Bristol, United Kingdom.

Bristol Robotics Laboratory, University of the West of England, Bristol, United Kingdom.

出版信息

Front Robot AI. 2020 Mar 16;7:23. doi: 10.3389/frobt.2020.00023. eCollection 2020.

DOI:10.3389/frobt.2020.00023
PMID:33501192
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC7805735/
Abstract

The real world is highly variable and unpredictable, and so fine-tuned robot controllers that successfully result in group-level "emergence" of swarm capabilities indoors may quickly become inadequate outside. One response to unpredictability could be greater robot complexity and cost, but this seems counter to the "swarm philosophy" of deploying (very) large numbers of simple agents. Instead, here I argue that bioinspiration in swarm robotics has considerable untapped potential in relation to the phenomenon of phenotypic plasticity: when a genotype can produce a range of distinctive changes in organismal behavior, physiology and morphology in response to different environments. This commonly arises following a natural history of variable conditions; implying the need for more diverse and hazardous simulated environments in offline, pre-deployment optimization of swarms. This will generate-indicate the need for-plasticity. Biological plasticity is sometimes irreversible; yet this characteristic remains relevant in the context of minimal swarms, where robots may become mass-producible. Plasticity can be introduced through the greater use of adaptive threshold-based behaviors; more fundamentally, it can link to emerging technologies such as smart materials, which can adapt form and function to environmental conditions. Moreover, in social animals, individual heterogeneity is increasingly recognized as functional for the group. Phenotypic plasticity can provide meaningful diversity "for free" based on early, local sensory experience, contributing toward better collective decision-making and resistance against adversarial agents, for example. Nature has already solved the challenge of resilient self-organisation in the physical realm through phenotypic plasticity: swarm engineers can follow this lead.

摘要

现实世界高度多变且不可预测,因此在室内能成功实现群体层面“涌现”出群体能力的精细调整的机器人控制器,在室外可能很快就会变得不足。应对不可预测性的一种方法可能是增加机器人的复杂性和成本,但这似乎与部署大量简单智能体的“群体理念”背道而驰。相反,我认为群体机器人技术中的生物启发在表型可塑性现象方面具有相当大的未开发潜力:当一个基因型能够根据不同环境在生物体行为、生理和形态上产生一系列独特变化时。这通常是在经历了各种不同条件的自然历史之后出现的;这意味着在群体的离线、部署前优化中需要更多样化和危险的模拟环境。这将产生——表明需要——可塑性。生物可塑性有时是不可逆的;然而,在最小化群体的背景下,这一特性仍然具有相关性,因为机器人可能会变得可大规模生产。可塑性可以通过更多地使用基于自适应阈值的行为来引入;更根本的是,它可以与智能材料等新兴技术相联系,智能材料能够使形式和功能适应环境条件。此外,在群居动物中,个体异质性越来越被认为对群体具有功能性。表型可塑性可以基于早期的局部感官体验“免费”提供有意义的多样性,例如有助于更好的集体决策和抵御对抗性智能体。自然界已经通过表型可塑性解决了物理领域中弹性自组织的挑战:群体工程师可以效仿这一做法。

相似文献

1
Phenotypic Plasticity Provides a Bioinspiration Framework for Minimal Field Swarm Robotics.表型可塑性为最小场群体机器人技术提供了一个生物启发框架。
Front Robot AI. 2020 Mar 16;7:23. doi: 10.3389/frobt.2020.00023. eCollection 2020.
2
Evolution of Collective Behaviors for a Real Swarm of Aquatic Surface Robots.真实水面机器人集群的集体行为演变
PLoS One. 2016 Mar 21;11(3):e0151834. doi: 10.1371/journal.pone.0151834. eCollection 2016.
3
Reconfigurable Particle Swarm Robotics Powered by Acoustic Vibration Tweezer.由声振动镊子驱动的可重构粒子群机器人
Soft Robot. 2021 Dec;8(6):735-743. doi: 10.1089/soro.2020.0050. Epub 2020 Nov 20.
4
Language Evolution in Swarm Robotics: A Perspective.群体机器人技术中的语言进化:一种视角
Front Robot AI. 2020 Feb 11;7:12. doi: 10.3389/frobt.2020.00012. eCollection 2020.
5
Blockchain Technology Secures Robot Swarms: A Comparison of Consensus Protocols and Their Resilience to Byzantine Robots.区块链技术保障机器人集群安全:共识协议及其对拜占庭机器人的弹性比较
Front Robot AI. 2020 May 12;7:54. doi: 10.3389/frobt.2020.00054. eCollection 2020.
6
Sparse Robot Swarms: Moving Swarms to Real-World Applications.稀疏机器人群体:将群体应用于现实世界
Front Robot AI. 2020 Jul 2;7:83. doi: 10.3389/frobt.2020.00083. eCollection 2020.
7
Recent trends in robot learning and evolution for swarm robotics.群体机器人技术中机器人学习与进化的最新趋势。
Front Robot AI. 2023 Apr 24;10:1134841. doi: 10.3389/frobt.2023.1134841. eCollection 2023.
8
Swarm Robotic Behaviors and Current Applications.群体机器人行为与当前应用
Front Robot AI. 2020 Apr 2;7:36. doi: 10.3389/frobt.2020.00036. eCollection 2020.
9
Mutual Shaping in Swarm Robotics: User Studies in Fire and Rescue, Storage Organization, and Bridge Inspection.群体机器人技术中的相互塑造:消防与救援、存储组织和桥梁检测中的用户研究
Front Robot AI. 2020 Apr 21;7:53. doi: 10.3389/frobt.2020.00053. eCollection 2020.
10
When less is more: Robot swarms adapt better to changes with constrained communication.少即是多:机器人集群在通信受限的情况下能更好地适应变化。
Sci Robot. 2021 Jul 28;6(56). doi: 10.1126/scirobotics.abf1416.

引用本文的文献

1
Adaptivity: a path towards general swarm intelligence?适应性:通向通用群体智能之路?
Front Robot AI. 2023 May 9;10:1163185. doi: 10.3389/frobt.2023.1163185. eCollection 2023.
2
Open-source computational simulation of moth-inspired navigation algorithm: A benchmark framework.受蛾类启发的导航算法的开源计算模拟:一个基准框架。
MethodsX. 2021 Sep 27;8:101529. doi: 10.1016/j.mex.2021.101529. eCollection 2021.

本文引用的文献

1
Automatic Off-Line Design of Robot Swarms: A Manifesto.机器人集群的自动离线设计:宣言
Front Robot AI. 2019 Jul 19;6:59. doi: 10.3389/frobt.2019.00059. eCollection 2019.
2
Autonomous task sequencing in a robot swarm.机器人群自主任务排序。
Sci Robot. 2018 Jul 18;3(20). doi: 10.1126/scirobotics.aat0430.
3
Morphogenesis in robot swarms.机器人群体中的形态发生
Sci Robot. 2018 Dec 19;3(25). doi: 10.1126/scirobotics.aau9178.
4
Minimal navigation solution for a swarm of tiny flying robots to explore an unknown environment.一群微型飞行机器人探索未知环境的最小导航解决方案。
Sci Robot. 2019 Oct 23;4(35). doi: 10.1126/scirobotics.aaw9710.
5
Resting networks and personality predict attack speed in social spiders.静息网络与个性可预测群居蜘蛛的攻击速度。
Behav Ecol Sociobiol. 2019 Jul;73(7). doi: 10.1007/s00265-019-2715-7. Epub 2019 Jun 26.
6
Testing the limits of pheromone stigmergy in high-density robot swarms.测试高密度机器人群体中信息素遗迹定向的极限。
R Soc Open Sci. 2019 Nov 6;6(11):190225. doi: 10.1098/rsos.190225. eCollection 2019 Nov.
7
Photomorphogenesis for robot self-assembly: adaptivity, collective decision-making, and self-repair.光形态发生用于机器人自组装:适应性、集体决策和自修复。
Bioinspir Biomim. 2019 Jul 12;14(5):056006. doi: 10.1088/1748-3190/ab2958.
8
Programmable Collective Behavior in Dynamically Self-Assembled Mobile Microrobotic Swarms.动态自组装移动微型机器人集群中的可编程集体行为
Adv Sci (Weinh). 2019 Jan 23;6(6):1801837. doi: 10.1002/advs.201801837. eCollection 2019 Mar 20.
9
Particle robotics based on statistical mechanics of loosely coupled components.基于松耦合组件统计力学的粒子机器人。
Nature. 2019 Mar;567(7748):361-365. doi: 10.1038/s41586-019-1022-9. Epub 2019 Mar 20.
10
Naturally clonal vertebrates are an untapped resource in ecology and evolution research.自然无性系脊椎动物是生态学和进化研究中尚未开发的资源。
Nat Ecol Evol. 2019 Feb;3(2):161-169. doi: 10.1038/s41559-018-0775-0. Epub 2019 Jan 28.