Methods of Autonomous Indoor 3D Navigation

Abstract

The development and implementation of indoor orientation methods are strongly callable in the market of navigation services. Currently, there are different approaches to solve the problem of navigation. They are based on the use of various data networks, the Earth magnetic field, RFID tags and QR codes. However, these approaches have significant limitations in terms of implementation complexity, accuracy, reliability, and cost. In this paper, we consider autonomous indoor navigation systems that are independent from a special infrastructure in the building. As a rule, in such systems, the process of tracking the progress along the route is implemented in accordance with the readings of micromechanical inertial sensors (accelerometers and angular rate sensors). However, due to accumulated measurement errors, such sensors are not reliable in determining the user’s location. The paper presents various methods and approaches that improve the positioning accuracy in the process of autonomous navigation. The use of the floor plans and methods of machine vision in navigation can compensate accumulation of errors of the micromechanical inertial sensors. The 3D visualization greatly facilitates the user’s analysis of the information about their current location. This feature allows the user to control the whole navigation process and to adjust their position if necessary. Besides, use of the 3D visualization allows one to navigate under low (limited) visibility. By combining different approaches, it is possible to compensate for the limitations of individual methods and to obtain more reliable results.