The inertial navigation system (INS) has been widely used to provide self-contained and continuous motion estimation in intelligent transportation systems. Recently, the emergence of chip-level inertial sensors has expanded the relevant applications from positioning, navigation, and mobile mapping to location-based services, unmanned systems, and transportation big data. Meanwhile, benefit from the emergence of big data and the improvement of algorithms and computing power, artificial intelligence (AI) has become a consensus tool that has been successfully applied in various fields. This article reviews the research on using AI technology to enhance inertial sensing from various aspects, including sensor design and selection, calibration and error modeling, navigation and motion-sensing algorithms, multi-sensor information fusion, system evaluation, and practical application. Based on the over 30 representative articles selected from the nearly 300 related publications, this article summarizes the state of the art, advantages, and challenges on each aspect. Finally, it summarizes nine advantages and nine challenges of AI-enhanced inertial sensing and then points out future research directions.

中文翻译：

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惯性传感遇上人工智能：机遇还是挑战？

惯性导航系统（INS）已被广泛用于在智能交通系统中提供独立和连续的运动估计。近来，芯片级惯性传感器的出现，将相关应用从定位、导航、移动地图扩展到位置服务、无人系统、交通大数据等领域。同时，受益于大数据的出现以及算法和计算能力的提升，人工智能（AI）已成为一种共识工具，并已成功应用于各个领域。本文从传感器设计与选择、标定与误差建模、导航与运动传感算法、多传感器信息融合、系统评价和实际应用。本文基于从近 300 篇相关出版物中选出的 30 多篇代表性文章，总结了各个方面的技术现状、优势和挑战。最后总结了人工智能增强惯性感知的九大优势和九大挑战，并指出了未来的研究方向。