Abstract
Due to the growth of productivity and the development of min-sensors, relevant localization and navigation algorithms are better suited today. However, indoor localization still faces many new problems, and with the popularity of usage scenarios, the variable and complex environmental information brings many new challenges to indoor localization and navigation. Currently, the widely used sensors on the market are vision sensors, ToF sensors and wireless sensors. These three types of sensors are used under different conditions and also have different accuracies and measurement ranges. Through sensors fusion algorithms can complement the strengths and weaknesses of different sensors to achieve better performance in complex using situations. The paper presents a survey on indoor positioning and navigation technologies based on sensor fusion from different sensors and relevant applications. We demonstrate the benefits of sensor fusion algorithms in practical applications by performing sensor fusion based on and single type of sensors and different types of sensors.
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