High-precision map-based visual loopback detection method and device

Abstract

The embodiments of the present invention provide a high-precision map-based visual loopback detection method and device. According to the method and device, element information in a high-precision mapis matched with information extracted from a real-time image, and whether the element information in the high-precision map and the information extracted from the real-time image are information of the same location is judged; when it is detected that the element information in the high-precision map and the information extracted from the real-time image are the information of the same location,an error function is constructed through position coordinates in the high-precision map and positions in a real-time visual odometer; and a real-time pose is optimized by minimizing the error function, and therefore, the real-time pose in the visual odometer can be optimized, more accurate motion trajectories can be obtained, and the accuracy of the precise position calculation of the visual odometer can be improved. With the high-precision map-based visual loopback detection system adopted, more loopback detection constraints can be brought about; and since the information of the high-precision map is abundant, the accuracy of the high-precision map is higher than that of road sign points in a traditional visual odometer, and therefore, the accuracy of the real-time visual odometer can beimproved.

Description

technical field [0001] Embodiments of the present invention relate to the technical field of visual positioning, and more specifically, to a high-precision map-based visual loop detection method and device. Background technique [0002] Simultaneous Localization And Mapping (SLAM) is widely used on small mobile platforms. In recent years, with the development of SLAM technology and the enhancement of computing power of small platforms, mobile phones, drones, robots and other small motion platforms have more and more demands for SLAM applications. Small platform application scenarios pose a series of challenges to related algorithms in SLAM. The limitations of computing power, sensor types, complex scenes and other aspects put forward higher requirements for the implementation of SLAM algorithms. At this stage, SLAM is developing rapidly towards high-speed computing, data fusion and stronger scene adaptability. Visual SLAM is favored by many small mobile platform applicati...

AI Technical Summary

Problems solved by technology

Whether the cumulative error of positioning can be eliminated in the loop detection depends on whether the camera passes the same place twice or even multiple times, and in some scenes it may not have the conditions to pass the same plac

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