Mobile robot localization in geometrically symmetric environments

Abstract

With the rapid development of mobile robots in recent years, the demand for localization and positioning algorithms is getting higher and higher. Although there are already localization algorithms that can successfully localize the mobile robots in certain environments, mobile robots localization is still a challenging task in geometrically repetitive and symmetrical environments. At present, the most used global localization method is based on the Global Navigation Satellite System (GNSS). However, when it comes to semi-indoor or indoor situations, the GNSS signal will become unstable, resulting in localization failures. Other commonly used localization methods are based on camera or Light Detection and Ranging (LiDAR) onboard the mobile robots. However, extremely similar and ambiguous environments make these methods difficult to accomplish the localization tasks. In recent years, the ambient magnetic field-based localization has proven to be a feasible solution due to its pervasiveness and ease of implementation, where meter-level accuracy has been achieved in semi-indoor or indoor environments. Therefore, this project aims to propose a magnetic field-based localization system to solve the problem of mobile robots localization issues in highly symmetric environments. At present, the magnetic field-based localization method still faces many problems, such as dependence on the rotation-sensitive magnetic field components, low accuracy in relatively large-scale environments, etc. In addition, the similar magnetic field single fingerprint information can easily cause mismatches in the magnetic field map, then lead to localization failures. This project will explore and propose novel magnetic field-based localization algorithms for mobile robots to achieve highly robust and precise localization in geometrically symmetric environment.