NRI: FND: Scalable, Customizable Sensory Solutions for Dexterous Robotic Hands

该项目旨在增强机械手的触觉。主要目标是开发具有触觉的假手。触摸传感器的主要应用是上肢截肢者。研究团队计划进行基础研究及其应用。这种传感器的应用类型包括：用于辅助工作和老年护理的类人机器人、外科机器人、水下机器人机械手和宇航服。此外，还通过约翰·霍普金斯青年才华中心规划了教育举措，包括实习、对代表不足的少数群体的培训，以及为高中生提供的研究经验和暑期模块。该项目的技术目标是建立一个高度可扩展的传感器设计，模拟人类皮肤中不同的触觉受体，并以类似于触觉受体的神经活动的方式对来自传感器的信息进行编码。该传感器将在多个尺度上对触觉信息进行编码，首先基于不同的感受器属性，然后基于传感器信号的类神经元编码。这种对神经活动进行编码的技术，称为神经形态编码，将传感器活动转换为事件流，并从该数据中获得更精细的特征。基于感受器的感知和各种神经网络算法将首次提供一种纹理和形状识别的方法，因此也可以用于灵巧机器人手的智能触诊和触觉感知。该奖项反映了NSF的法定使命，并通过使用基金会的智力优势和更广泛的影响审查标准进行评估，被认为值得支持。

This project aims to enhance the sense of touch for robotic hands. The main goal is to develop prosthetic hands with a sense of touch. The touch sensor's primary application is for upper limb amputees. The research team plans both fundamental research and its application. The types of applications of this kind of sensor include: humanoid robots for assistive work and elder-care, surgical robotics, underwater robotic manipulators and spacesuits. Additionally, educational initiatives including internships, training of under-represented minority, and research experiences and summer modules for high school students are planned through the Johns Hopkins Center for Talented Youth. The technical goal of the project is to build a highly scalable sensor design mimicking different tactile receptors in human skins and encode information from the sensors in a manner analogous to the neural activity of the tactile receptors. The sensor will encode the tactile information at multiple scales, firstly based on different receptor properties, and secondly based on neuron-like encoding of the sensor signals. This technique of encoding the neural activity, known as neuromorphic encoding, converts the sensor activity as an event stream, and from that data obtains finer features. The receptor based sensing along with the various neural network algorithms, for the first time, will provide an approach to texture and shape recognition and, as such, can also be useful for intelligent palpation and tactile perception by dexterous robotic hands.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.