Shi Hongkai, Tang Ruiqi, Wang Qingmeng, Song Tao
Beijing Key Laboratory of Bioelectromagnetism, Institute of Electrical Engineering, Chinese Academy of Sciences, Haidian District, Beijing 100190, China.
University of Chinese Academy of Sciences, Shijingshan District, Beijing 100049, China.
Sensors (Basel). 2024 Oct 8;24(19):6477. doi: 10.3390/s24196477.
For geomagnetic navigation technology, taking inspiration from nature and leveraging the principle of animals' utilization of the geomagnetic field for long-distance navigation, and employing biomimetic technology to develop higher-precision geomagnetic sensors and more advanced navigation strategies, has emerged as a new trend. Based on the two widely acknowledged biological magnetic induction mechanisms, we have designed a bioinspired weak magnetic vector (BWMV) sensor and integrated it with neural networks to achieve geomagnetic matching navigation. In this paper, we assess the performance of the BWMV sensor through finite element model simulation. The result validates its high measurement accuracy and outstanding adaptability to installation errors with the assistance of specially trained neural networks. Furthermore, we have enhanced the bioinspired geomagnetic navigation algorithm and proposed a more advanced search strategy to adapt to navigation under the condition of no prior geomagnetic map. A simulated geomagnetic navigation platform was constructed based on the finite element model to simulate the navigation of the BWMV sensor in geomagnetic environments. The simulated navigation experiment verified that the proposed search strategy applied to the BWMV sensor can achieve high-precision navigation. This study proposes a novel approach for the research of bioinspired geomagnetic navigation technology, which holds great development prospects.
对于地磁导航技术而言，从自然中获取灵感，利用动物利用地磁场进行长距离导航的原理，并采用仿生技术开发更高精度的地磁传感器和更先进的导航策略，已成为一种新趋势。基于两种广泛认可的生物磁感应机制，我们设计了一种仿生弱磁矢量（BWMV）传感器，并将其与神经网络集成以实现地磁匹配导航。在本文中，我们通过有限元模型仿真评估了BWMV传感器的性能。结果验证了在经过专门训练的神经网络的辅助下，其具有高测量精度和对安装误差的出色适应性。此外，我们改进了仿生地磁导航算法，并提出了一种更先进的搜索策略，以适应在没有先验地磁图的条件下进行导航。基于有限元模型构建了一个模拟地磁导航平台，以模拟BWMV传感器在地磁环境中的导航。模拟导航实验验证了应用于BWMV传感器的所提出的搜索策略能够实现高精度导航。本研究提出了一种用于仿生地磁导航技术研究的新方法，具有广阔的发展前景。
