An Outline of Multi-Sensor Fusion Methods for Mobile Agents Indoor Navigation

Indoor autonomous navigation refers to the perception and exploration abilities of mobile agents in unknown indoor environments with the help of various sensors. It is the basic and one of the most important functions of mobile agents. In spite of the high performance of the single-sensor navigation method, multi-sensor fusion methods still potentially improve the perception and navigation abilities of mobile agents. This work summarizes the multi-sensor fusion methods for mobile agents' navigation by: (1) analyzing and comparing the advantages and disadvantages of a single sensor in the task of navigation; (2) introducing the mainstream technologies of multi-sensor fusion methods, including various combinations of sensors and several widely recognized multi-modal sensor datasets. Finally, we discuss the possible technique trends of multi-sensor fusion methods, especially its technique challenges in practical navigation environments.

Automated summary

Indoor autonomous navigation is a fundamental function of mobile agents, which refers to their perception and exploration abilities in unknown indoor environments with the help of various sensors. Multi-sensor fusion methods have the potential to enhance the perception and navigation abilities of mobile agents, and involve analyzing single sensor advantages and disadvantages, introducing mainstream technologies, and discussing possible technique trends and challenges.