Peng Yulian, Wang Zhengyan, Wu Houping, Luo Junchen, Chang Xinxin, Wang Yufeng, Zhang Shiwu, Feng Zhihua, Jeong Unyong, Wang Hongbo
Department of Precision Machinery and Precision Instrumentation, University of Science and Technology of China, Hefei, China.
Department of Materials Science and Engineering, Pohang University of Science and Technology, Pohang, Republic of Korea.
Nat Commun. 2025 Jul 10;16(1):6370. doi: 10.1038/s41467-025-61784-0.
Soft mechanical sensors with high performance, mechanical robustness, and manufacturing reproducibility are crucial for robotics perception, but simultaneously satisfying these criteria is rarely achieved. Here, we suggest a magnetic crack-based piezoinductive sensor (MC-PIS) which exploits the strain modulation of magnetic flux in cracked ferrite films. The MC-PIS is insensitive to fatigue-induced crack propagation and environmental changes, showing same performance even when scratched in half or run over by a car. It can detect bidirectional bending with a precision of 0.01° from -200° to 327°, allowing for real-time reconstruction of dynamic shape changes of a flexible ribbon. We demonstrate an artificial finger recognizing surface topology and musical notes via vibrations, a crawling robot responding appropriately to external stimuli, a tree-planting gripper performing consecutive tasks from digging soil, removing stones, to placing trees. The MC-PIS opens a new paradigm to develop ultrasensitive yet highly robust sensors in real-world robotics applications.
具有高性能、机械鲁棒性和制造可重复性的柔性机械传感器对于机器人感知至关重要，但同时满足这些标准却很少能够实现。在此，我们提出了一种基于磁致裂纹的压电感测器（MC-PIS），它利用裂纹铁氧体薄膜中磁通量的应变调制。MC-PIS对疲劳引起的裂纹扩展和环境变化不敏感，即使被划破一半或被汽车碾压也能表现出相同的性能。它能够在-200°至327°范围内以0.01°的精度检测双向弯曲，从而实现对柔性带动态形状变化的实时重建。我们展示了一个通过振动识别表面拓扑结构和音符的人造手指、一个对外部刺激做出适当反应的爬行机器人、一个从挖土、清除石块到植树执行连续任务的植树夹具。MC-PIS为在实际机器人应用中开发超灵敏且高度鲁棒的传感器开辟了新的范例。
