A Survey on the Main Techniques Adopted in Indoor and Outdoor Localization

Abstract

In modern engineering applications, localization and orientation play an increasingly crucial role in ensuring the successful execution of assigned tasks. Industrial robots, smart home systems, healthcare environments, nuclear facilities, agriculture, and autonomous vehicles are just a few examples of fields where localization technologies are applied. Over the years, these technologies have evolved significantly, with numerous methods being developed, proposed, and refined. This paper aims to provide a comprehensive review of the primary localization and orientation technologies available in the literature, detailing the fundamental principles on which they are based and the key algorithms used to implement them. To achieve accurate and reliable localization, fusion-based approaches are often necessary, integrating data from multiple sensors and systems or estimating hidden states. For this purpose, algorithms such as Kalman Filters, Particle Filters, or Neural Networks are usually adopted. The first part of this article presents an extensive review of localization technologies, including radio frequency, RFID, laser-based systems, vision-based techniques, light-based positioning, IMU-based methods, odometry, and ultrasound-based solutions. The second part focuses on the most widely used algorithms for localization. Finally, summary tables provide an overview of the best and most consistent accuracies reported in the literature for the investigated technologies and systems.