Abstract
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.
Highlights
As early as the 1960s, there were science fiction films and TV works depicting the autonomous navigation of mobile agents: intelligent robots that are able to travel freely in indoors such as in offices, factories, shopping malls, and hospitals and help people in work, production, play, and study
Various sensors have been adopted for mobile agent navigation, such as cameras [2], light detection and ranging (LiDAR) [3], inertial measurement units (IMU) [4], ultra-wide band (UWB) [5], Wi-Fi [6], Bluetooth [7], ZigBee [8], infrared [9], ultrasonic [10], etc
In spite of several mature evaluation methods, such as the Monte Carlo strategy, real-time simulation, and individual calculation in the specific applications, and some simultaneous localization and mapping (SLAM) evaluation methods, for instance relative pose error (RPE) [146], absolute trajectory error (ATE) [146], etc., they are not suitable to evaluate the performance of each sensor in the whole fusion system
Summary
As early as the 1960s, there were science fiction films and TV works depicting the autonomous navigation of mobile agents: intelligent robots that are able to travel freely in indoors such as in offices, factories, shopping malls, and hospitals and help people in work, production, play, and study. In these scenarios, autonomous navigation ability is the basic and one of the most important functions of mobile agents. Autonomous indoor navigation of mobile agents refers to the abilities of autonomous localization and map construction in dynamic scenes [1]. According to the different principles and usages of these sensors, some scholars divided autonomous navigation into two categories: single-sensor navigation methods and multi-sensor fusion navigation methods [11]
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