All-printed soft human-machine interface for robotic physicochemical sensing.
All-printed soft human-machine interface for robotic physicochemical sensing.
复制标题
用于机器人理化传感的全印刷软人机界面。
DOI：
10.1126/scirobotics.abn0495
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发表时间：
2022-06
期刊：
影响因子：
25
通讯作者：
中科院分区：
文献类型：
--
作者：
用于自主机器人决策的超灵敏多模态物理化学传感在农业、安全、环境保护和公共卫生中有许多应用。以前报道的机器人传感技术主要集中在监测物理参数，如压力和温度。在机器人平台上集成用于自主干相分析物检测的化学传感器相当具有挑战性并且基本上不发达。在这里，我们介绍了一种人工智能驱动的多模态机器人传感系统（M-Bot），该系统具有全印刷的可批量生产的基于软电子皮肤的人机界面。使用定制开发的纳米材料墨水的可扩展喷墨打印技术用于制造灵活的物理化学传感器阵列，用于电生理记录，触觉感知和机器人感测各种危险材料，包括硝基芳香族炸药，农药，神经毒剂以及传染性病原体，如SARS-CoV-2。M-Bot通过机器学习算法解码从人体收集的表面肌电图信号，用于远程机器人控制，并可以在极端或污染环境中进行现场威胁化合物检测，并提供用户交互式触觉和威胁警报反馈。基于印刷电子皮肤的机器人传感技术可以进一步推广应用到其他遥感平台。这种多样性在智能多模式机器人船平台上得到了验证，该平台可以通过自主和智能决策算法有效地跟踪痕量危险化合物的来源。这种完全打印的人机交互多模态传感技术可以在设计未来的智能机器人系统中发挥关键作用，并且可以轻松地重新配置为许多新的实际可穿戴和机器人应用。用纳米材料墨水打印的电子皮肤实现了机器学习驱动的自主机器人物理化学传感。
Ultrasensitive multimodal physicochemical sensing for autonomous robotic decision-making has numerous applications in agriculture, security, environmental protection, and public health. Previously reported robotic sensing technologies have primarily focused on monitoring physical parameters such as pressure and temperature. Integrating chemical sensors for autonomous dry-phase analyte detection on a robotic platform is rather extremely challenging and substantially underdeveloped. Here, we introduce an artificial intelligence-powered multimodal robotic sensing system (M-Bot) with an all-printed mass-producible soft electronic skin–based human-machine interface. A scalable inkjet printing technology with custom-developed nanomaterial inks was used to manufacture flexible physicochemical sensor arrays for electrophysiology recording, tactile perception, and robotic sensing of a wide range of hazardous materials including nitroaromatic explosives, pesticides, nerve agents, as well as infectious pathogens such as SARS-CoV-2. The M-Bot decodes the surface electromyography signals collected from the human body through machine learning algorithms for remote robotic control and can perform in-situ threat compound detection in extreme or contaminated environments with user-interactive tactile and threat alarm feedback. The printed electronic-skin-based robotic sensing technology can be further generalized and applied to other remote sensing platforms. Such diversity was validated on an intelligent multimodal robotic boat platform that can efficiently track the source of trace amounts of hazardous compounds through autonomous and intelligent decision-making algorithms. This fully-printed human-machine interactive multimodal sensing technology could play a crucial role in designing future intelligent robotic systems and can be easily reconfigured toward numerous new practical wearable and robotic applications. Electronic skin printed with nanomaterial inks enables machine learning–driven autonomous robotic physicochemical sensing.
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