Multifunctional materials with distributed sensing and programmed mechanical properties are required for myriad emerging technologies. However, current fabrication techniques constrain these materials’ design and sensing capabilities. We address these needs with a method for sensorizing architected materials through fluidic innervation, where distributed networks of empty, air-filled channels are directly embedded within an architected material’s sparse geometry. By measuring pressure changes within these channels, we receive feedback regarding material deformation. Thus, this technique allows for three-dimensional printing of sensorized structures from a single material. With this strategy, we fabricate sensorized soft robotic actuators on the basis of handed shearing auxetics and accurately predict their kinematics from the sensors’ proprioceptive feedback using supervised learning. Our strategy for facilitating structural, sensing, and actuation capabilities through control of form alone simplifies sensorized material design for applications spanning wearables, smart structures, and robotics.

中文翻译：

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流体神经支配从单一构建材料感知结构

无数新兴技术需要具有分布式传感和程序化机械性能的多功能材料。然而，当前的制造技术限制了这些材料的设计和传感能力。我们通过一种通过流体神经支配来感知建筑材料的方法来满足这些需求，其中空的、充气通道的分布式网络直接嵌入到建筑材料的稀疏几何结构中。通过测量这些通道内的压力变化，我们会收到有关材料变形的反馈。因此，该技术允许使用单一材料对传感结构进行 3D 打印。有了这个策略，我们基于手动剪切拉胀学制造传感软机器人执行器，并使用监督学习从传感器的本体感受反馈准确预测其运动学。我们通过仅控制形式来促进结构、传感和驱动能力的策略简化了跨可穿戴设备、智能结构和机器人技术的应用的传感材料设计。