Wang Pinkun, Zhang Changchao, Li Bo, Meng Xiancun, Ding Yuechun, Zhang Junqiu, Niu Shichao, Han Zhiwu, Lin Liwei, Ren Luquan
Key Laboratory of Bionic Engineering (Ministry of Education), Jilin University, Changchun, Jilin, 130022, China.
Department of Mechanical Engineering and Berkeley Sensor and Actuator Center, University of California at Berkeley, Berkeley, CA 94720-1740, USA.
Sci Adv. 2025 Aug 22;11(34):eady5008. doi: 10.1126/sciadv.ady5008. Epub 2025 Aug 20.
Sensitivity enhancement for pressure sensors over a broad linear range can improve sensing performance for a wide range of applications such as health monitoring and artificial intelligence. Here, inspired by the high-precision mechanosensory mechanism of the scorpion, a bioinspired piezoresistive pressure sensor (BPPS) is reported for the synergistic enhancement of sensitivity and linearity at 65.56 millivolts per volt per kilopascal and 0.99934, respectively, in a pressure range from 0 to 500 kilopascals. The BPPS can distinguish laminar, transitional, and turbulent flows as well as identify approaching objects of different shapes with an accuracy exceeding 85.42% by integrating a wavelet transform algorithm and the ResNet18 deep learning network. As a proof of concept, BPPS has been engineered in a hexapod robot to enable near-body flow field sensing for active collision avoidance. This work underscores the potential to leverage key design concepts inspired by living insects for improved sensing performance and offers structural insights for other high-precision sensors.
在宽线性范围内提高压力传感器的灵敏度，可以改善其在诸如健康监测和人工智能等广泛应用中的传感性能。在此，受蝎子高精度机械传感机制的启发，报道了一种仿生压阻式压力传感器（BPPS），在0至500千帕的压力范围内，其灵敏度和线性度分别协同提高至每千帕每伏65.56毫伏和0.99934。通过集成小波变换算法和ResNet18深度学习网络，BPPS能够区分层流、过渡流和湍流，还能识别不同形状的接近物体，准确率超过85.42%。作为概念验证，BPPS已被应用于六足机器人中，以实现近体流场传感，用于主动避撞。这项工作强调了利用受活昆虫启发的关键设计概念来提高传感性能的潜力，并为其他高精度传感器提供了结构见解。
