Mobile Robots (MRs) and their applications are undergoing massive development, requiring a diversity of autonomous or self-directed robots to fulfill numerous objectives and responsibilities. Integrating MRs with the Intelligent Internet of Things (IIoT) not only makes robots innovative, trackable, and powerful but also generates numerous threats and challenges in multiple applications. The IIoT combines intelligent techniques, including artificial intelligence and machine learning, with the Internet of Things (IoT). The location information (localization) of the MRs triggers innumerable domains. To fully accomplish the potential of localization, Mobile Robot Localization (MRL) algorithms need to be integrated with complementary technologies, such as MR classification, indoor localization mapping solutions, three-dimensional localization, etc. Thus, this paper endeavors to comprehensively review different methodologies and technologies for MRL, emphasizing intelligent architecture, indoor and outdoor methodologies, concepts, and security-related issues. Additionally, we highlight the diverse MRL applications where information about localization is challenging and present the various computing platforms. Finally, discussions on several challenges regarding navigation path planning, localization, obstacle avoidance, security, localization problem categories, etc., and potential future perspectives on MRL techniques and applications are highlighted.

中文翻译：

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移动机器人定位：当前挑战与未来展望


移动机器人 (MR) 及其应用正在经历大规模发展，需要各种自主或自我引导的机器人来完成众多目标和职责。将 MR 与智能物联网 (IIoT) 集成，不仅使机器人具有创新性、可追踪性和强大功能，而且还会在多种应用中产生众多威胁和挑战。 IIoT 将人工智能和机器学习等智能技术与物联网 (IoT) 相结合。 MR的位置信息（定位）触发无数领域。为了充分发挥定位的潜力，移动机器人定位（MRL）算法需要与互补技术相结合，例如MR分类、室内定位地图解决方案、三维定位等。因此，本文致力于全面回顾不同的方法MRL 和技术，强调智能建筑、室内和室外方法、概念和安全相关问题。此外，我们还重点介绍了各种 MRL 应用，其中有关本地化的信息具有挑战性，并介绍了各种计算平台。最后，重点讨论了有关导航路径规划、定位、避障、安全、定位问题类别等的几个挑战，以及 MRL 技术和应用的潜在未来前景。