School of Precision Instrument and Optoelectronics Engineering, Tianjin University, 92 Weijin Road, Tianjin 300072, China; State Key Laboratory of Precision Measuring Technology and Instruments, Tianjin University, 92 Weijin Road, Tianjin 300072, China.
School of Precision Instrument and Optoelectronics Engineering, Tianjin University, 92 Weijin Road, Tianjin 300072, China; State Key Laboratory of Precision Measuring Technology and Instruments, Tianjin University, 92 Weijin Road, Tianjin 300072, China.
Biosens Bioelectron. 2025 Jan 1;267:116828. doi: 10.1016/j.bios.2024.116828. Epub 2024 Oct 1.
Mechanoreceptors in animals and plants play a crucial role in sensing mechanical stimuli such as touch, motion, stretch, and vibration. Learning from the mechanisms of mechanoreceptors may facilitate the development of bionic tactile sensors, leading to higher sensitivity, spatial resolution, and dynamic ranges. However, very little literature has comprehensively discussed the relevance of biological tactile sensing systems and machine-learning-based bionic tactile sensors. This review first introduces the structural features, signal acquisition and transmission mechanisms, and feedback processes of both plant and animal mechanoreceptors, and then summarizes the efforts to develop bionic tactile sensors by mimicking the morphologies and structures of mechanoreceptors in plants and animals. Additionally, the integration of artificial intelligence approaches with these sensors for data processing and analysis are demonstrated, followed by the perspectives on current challenges and future trends in bionic tactile sensors. This review addresses the challenges in developing high-performance tactile sensors by focusing on surface microstructures and biological mechanoreceptors, serving as a valuable reference for developing bionic tactile sensors with enhanced sensitivity and multimodal sensing capabilities. Furthermore, it may benefit the future development of smart sensing systems integrated with artificial intelligence for more precise object and texture recognition.
动植物中的机械感受器在感知触觉、运动、拉伸和振动等机械刺激方面起着至关重要的作用。从机械感受器的机制中学习,可以促进仿生触觉传感器的发展,从而提高灵敏度、空间分辨率和动态范围。然而,很少有文献全面讨论生物触觉传感系统和基于机器学习的仿生触觉传感器的相关性。本综述首先介绍了植物和动物机械感受器的结构特征、信号采集和传输机制以及反馈过程,然后总结了通过模仿植物和动物机械感受器的形态和结构来开发仿生触觉传感器的努力。此外,还展示了将人工智能方法与这些传感器集成用于数据处理和分析的情况,接着探讨了仿生触觉传感器当前面临的挑战和未来的发展趋势。本综述通过关注表面微观结构和生物机械感受器,解决了开发高性能触觉传感器的挑战,为开发具有更高灵敏度和多模态感知能力的仿生触觉传感器提供了有价值的参考。此外,它可能有益于未来开发与人工智能集成的智能传感系统,以实现更精确的物体和纹理识别。