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基于折纸的机器人集成,实现感知、决策和响应。

Origami-based integration of robots that sense, decide, and respond.

机构信息

Mechanical and Aerospace Engineering Department, UCLA, Los Angeles, CA, USA.

Computer Science and Artificial Intelligence Laboratory, MIT, Cambridge, USA.

出版信息

Nat Commun. 2023 Apr 3;14(1):1553. doi: 10.1038/s41467-023-37158-9.


DOI:10.1038/s41467-023-37158-9
PMID:37012246
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC10070436/
Abstract

Origami-inspired engineering has enabled intelligent materials and structures to process and react to environmental stimuli. However, it is challenging to achieve complete sense-decide-act loops in origami materials for autonomous interaction with environments, mainly due to the lack of information processing units that can interface with sensing and actuation. Here, we introduce an integrated origami-based process to create autonomous robots by embedding sensing, computing, and actuating in compliant, conductive materials. By combining flexible bistable mechanisms and conductive thermal artificial muscles, we realize origami multiplexed switches and configure them to generate digital logic gates, memory bits, and thus integrated autonomous origami robots. We demonstrate with a flytrap-inspired robot that captures 'living prey', an untethered crawler that avoids obstacles, and a wheeled vehicle that locomotes with reprogrammable trajectories. Our method provides routes to achieve autonomy for origami robots through tight functional integration in compliant, conductive materials.

摘要

折纸启发的工程已经使智能材料和结构能够处理和响应环境刺激。然而,在折纸材料中实现完全的感知-决策-执行循环以实现与环境的自主交互是具有挑战性的,主要是因为缺乏能够与传感和致动接口的信息处理单元。在这里,我们通过在柔顺、导电材料中嵌入传感、计算和致动,引入了一种集成的基于折纸的方法来创建自主机器人。通过结合柔性双稳态机构和导电热人工肌肉,我们实现了折纸复用开关,并将其配置为生成数字逻辑门、存储位,从而集成了自主折纸机器人。我们通过一个受捕蝇草启发的机器人演示了它能够捕捉“活体猎物”,一个无需系绳的爬虫可以避开障碍物,以及一个带有可编程轨迹的轮式车辆可以移动。我们的方法通过在柔顺、导电材料中进行紧密的功能集成,为折纸机器人实现自主性提供了途径。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8203/10070436/34da407a5aa1/41467_2023_37158_Fig7_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8203/10070436/4adb86f6ef7e/41467_2023_37158_Fig1_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8203/10070436/1b9763597fb6/41467_2023_37158_Fig2_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8203/10070436/a178f39739a5/41467_2023_37158_Fig3_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8203/10070436/950a198c2317/41467_2023_37158_Fig4_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8203/10070436/1f79454fedb0/41467_2023_37158_Fig5_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8203/10070436/2b44a620695f/41467_2023_37158_Fig6_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8203/10070436/34da407a5aa1/41467_2023_37158_Fig7_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8203/10070436/4adb86f6ef7e/41467_2023_37158_Fig1_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8203/10070436/1b9763597fb6/41467_2023_37158_Fig2_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8203/10070436/a178f39739a5/41467_2023_37158_Fig3_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8203/10070436/950a198c2317/41467_2023_37158_Fig4_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8203/10070436/1f79454fedb0/41467_2023_37158_Fig5_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8203/10070436/2b44a620695f/41467_2023_37158_Fig6_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8203/10070436/34da407a5aa1/41467_2023_37158_Fig7_HTML.jpg

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Soft Robot. 2022-10

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