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I2Bot:一种用于昆虫导航多模态与具身模拟的开源工具。

I2Bot: an open-source tool for multi-modal and embodied simulation of insect navigation.

作者信息

Sun Xuelong, Mangan Michael, Peng Jigen, Yue Shigang

机构信息

Machine Life and Intelligence Research Center, Guangzhou University, Guangzhou, People's Republic of China.

School of Mathematics and Information Science, Guangzhou University, Guangzhou, People's Republic of China.

出版信息

J R Soc Interface. 2025 Jan;22(222):20240586. doi: 10.1098/rsif.2024.0586. Epub 2025 Jan 22.

DOI:10.1098/rsif.2024.0586
PMID:39837486
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC11750368/
Abstract

Achieving a comprehensive understanding of animal intelligence demands an integrative approach that acknowledges the interplay between an organism's brain, body and environment. Insects, despite their limited computational resources, demonstrate remarkable abilities in navigation. Existing computational models often fall short in faithfully replicating the morphology of real insects and their interactions with the environment, hindering validation and practical application in robotics. To address these gaps, we present I2Bot, a novel simulation tool based on the morphological characteristics of real insects. This tool empowers robotic models with dynamic sensory capabilities, realistic modelling of insect morphology, physical dynamics and sensory capacity. By integrating gait controllers and computational models into I2Bot, we have implemented classical embodied navigation behaviours and revealed some fundamental navigation principles. By open-sourcing I2Bot, we aim to accelerate the understanding of insect intelligence and foster advances in the development of autonomous robotic systems.

摘要

要全面理解动物智能,需要一种综合方法,该方法要认识到生物体的大脑、身体和环境之间的相互作用。昆虫尽管计算资源有限,但在导航方面展现出非凡能力。现有的计算模型往往难以如实地复制真实昆虫的形态及其与环境的相互作用,这阻碍了在机器人技术中的验证和实际应用。为了弥补这些差距,我们提出了I2Bot,这是一种基于真实昆虫形态特征的新型模拟工具。该工具赋予机器人模型动态感官能力、对昆虫形态、物理动力学和感官能力的逼真建模。通过将步态控制器和计算模型集成到I2Bot中,我们实现了经典的具身导航行为,并揭示了一些基本的导航原理。通过开源I2Bot,我们旨在加速对昆虫智能的理解,并推动自主机器人系统开发的进展。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/375f/11750368/7c18e15afc02/rsif.2024.0586.f006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/375f/11750368/e07cbfa4d503/rsif.2024.0586.f001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/375f/11750368/aa0e1af93c12/rsif.2024.0586.f002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/375f/11750368/e4698dc9715c/rsif.2024.0586.f003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/375f/11750368/bfe157ad9c9d/rsif.2024.0586.f004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/375f/11750368/1f0da0773dd0/rsif.2024.0586.f005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/375f/11750368/7c18e15afc02/rsif.2024.0586.f006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/375f/11750368/e07cbfa4d503/rsif.2024.0586.f001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/375f/11750368/aa0e1af93c12/rsif.2024.0586.f002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/375f/11750368/e4698dc9715c/rsif.2024.0586.f003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/375f/11750368/bfe157ad9c9d/rsif.2024.0586.f004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/375f/11750368/1f0da0773dd0/rsif.2024.0586.f005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/375f/11750368/7c18e15afc02/rsif.2024.0586.f006.jpg

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2
Reinforcement learning as a robotics-inspired framework for insect navigation: from spatial representations to neural implementation.强化学习作为一种受机器人启发的昆虫导航框架:从空间表征到神经实现。
Front Comput Neurosci. 2024 Sep 9;18:1460006. doi: 10.3389/fncom.2024.1460006. eCollection 2024.
3
Emergent behaviour and neural dynamics in artificial agents tracking odour plumes.
追踪气味羽流的人工主体中的涌现行为与神经动力学
Nat Mach Intell. 2023 Jan;5(1):58-70. doi: 10.1038/s42256-022-00599-w. Epub 2023 Jan 25.
4
Taking inspiration from nature is a no-brainer.从大自然中汲取灵感是显而易见的。
Sci Robot. 2023 May 31;8(78):eadi2720. doi: 10.1126/scirobotics.adi2720.
5
Active Sensing in Bees Through Antennal Movements Is Independent of Odor Molecule.蜜蜂通过触角运动进行主动感知与气味分子无关。
Integr Comp Biol. 2023 Aug 23;63(2):315-331. doi: 10.1093/icb/icad010.
6
neuroWalknet, a controller for hexapod walking allowing for context dependent behavior.神经行走网络,一种用于六足行走的控制器,允许基于上下文的行为。
PLoS Comput Biol. 2023 Jan 24;19(1):e1010136. doi: 10.1371/journal.pcbi.1010136. eCollection 2023 Jan.
7
Olfactory navigation in arthropods.节肢动物的嗅觉导航。
J Comp Physiol A Neuroethol Sens Neural Behav Physiol. 2023 Jul;209(4):467-488. doi: 10.1007/s00359-022-01611-9. Epub 2023 Jan 20.
8
Varieties of visual navigation in insects.昆虫的视觉导航多样性。
Anim Cogn. 2023 Jan;26(1):319-342. doi: 10.1007/s10071-022-01720-7. Epub 2022 Nov 28.
9
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Elife. 2022 Oct 13;11:e73893. doi: 10.7554/eLife.73893.
10
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Neural Comput. 2022 Oct 7;34(11):2205-2231. doi: 10.1162/neco_a_01540.