Autonomous Fast Localization Method Combining Artificial Beacons and Visual SLAM

doi:10.3901/JME.2022.14.137

Abstract

Abstract: Aiming at the problem of low accuracy and poor adaptability of autonomous localization in complex industrial field environment, a dual-camera localization system combining artificial beacons and visual SLAM (simultaneous localization and mapping) is proposed. Artificial beacons need not cover the whole space layout, don't need to have ID information. The two cameras complete the full space positioning by photographing the beacons and running the visual SLAM algorithm respectively. The scale uncertainty of monocular SLAM is recovered by using beacon localization algorithm and the relationship between the coordinate systems of the two localization algorithms is established. Therefore, when the camera moves out of the control field consisting of beacons and back into its coverage again, system initial pose can be obtained by SLAM algorithm. Then the fast matching of beacons and image points can be realized so as to locate accurately again. By installing the dual camera positioning system on the wearable helmet, the surveyors can achieve high precision positioning when wearing the helmet. The working principle of dual-camera helmet positioning system is analyzed and verified by experiments. Experimental results show that this method has high accuracy and strong adaptability, which can meet the requirements of autonomous positioning in the complex industrial environment where the beacons cannot cover the whole space.

Key words: multi-camera system, visual position measurement, artificial beacon, simultaneous localization and mapping

CLC Number:

TP23

SHEN Wenjie, REN Yongjie, ZHU Boyuan, LIN Jiarui. Autonomous Fast Localization Method Combining Artificial Beacons and Visual SLAM[J]. Journal of Mechanical Engineering, 2022, 58(14): 137-145.

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