Zhao Huiqi, Zhang Yizheng, Han Lei, Qian Weiqi, Wang Jiabin, Wu Heting, Li Jingchen, Dai Yuan, Zhang Zhengyou, Bowen Chris R, Yang Ya
CAS Center for Excellence in Nanoscience, Beijing Key Laboratory of Micro-Nano Energy and Sensor, Beijing Institute of Nanoenergy and Nanosystems, Chinese Academy of Sciences, Beijing, 101400, People's Republic of China.
School of Nanoscience and Technology, University of Chinese Academy of Sciences, Beijing, 100049, People's Republic of China.
Nanomicro Lett. 2023 Nov 9;16(1):11. doi: 10.1007/s40820-023-01216-0.
Humans can perceive our complex world through multi-sensory fusion. Under limited visual conditions, people can sense a variety of tactile signals to identify objects accurately and rapidly. However, replicating this unique capability in robots remains a significant challenge. Here, we present a new form of ultralight multifunctional tactile nano-layered carbon aerogel sensor that provides pressure, temperature, material recognition and 3D location capabilities, which is combined with multimodal supervised learning algorithms for object recognition. The sensor exhibits human-like pressure (0.04-100 kPa) and temperature (21.5-66.2 °C) detection, millisecond response times (11 ms), a pressure sensitivity of 92.22 kPa and triboelectric durability of over 6000 cycles. The devised algorithm has universality and can accommodate a range of application scenarios. The tactile system can identify common foods in a kitchen scene with 94.63% accuracy and explore the topographic and geomorphic features of a Mars scene with 100% accuracy. This sensing approach empowers robots with versatile tactile perception to advance future society toward heightened sensing, recognition and intelligence.
人类可以通过多感官融合来感知我们这个复杂的世界。在有限的视觉条件下，人们能够感知各种触觉信号，从而准确、快速地识别物体。然而，在机器人中复制这种独特能力仍然是一项重大挑战。在此，我们展示了一种新型的超轻型多功能触觉纳米层状碳气凝胶传感器，它具备压力、温度、材料识别和三维定位能力，并与用于物体识别的多模态监督学习算法相结合。该传感器具有类似人类的压力（0.04 - 100千帕）和温度（21.5 - 66.2摄氏度）检测能力、毫秒级响应时间（11毫秒）、92.22千帕的压力灵敏度以及超过6000次循环的摩擦电耐久性。所设计的算法具有通用性，可适应一系列应用场景。该触觉系统在厨房场景中识别常见食物的准确率为94.63%，在火星场景中探索地形地貌特征的准确率为100%。这种传感方法赋予机器人通用的触觉感知能力，推动未来社会向更高的传感、识别和智能水平发展。
