Visual and inertial navigation fusion SLAM-based external parameter and time sequence calibration method on mobile platform

Abstract

The invention discloses a visual and inertial navigation fusion SLAM-based external parameter and time sequence calibration method on a mobile platform. The method comprises an initialization stage, wherein the relative rotation parameters between two frames estimated by a camera and an IMU are aligned through a loosely-coupled method, and the relative rotation parameters of the camera and the IMUare estimated and obtained; a front-end stage, wherein the front end completes the function of a visual odometer, namely, the pose of the current frame of the camera in the world coordinate system isgenerally estimated according to the pose of the camera in the world coordinate system estimated in the former several frames, and the estimated value serves as an initial value of back-end optimization; a back-end stage, wherein some key frames are selected from all the frames, variables to be optimized are set, a uniform objective function is established, and optimization is carried out according to the corresponding constraint conditions, and therefore, accurate external parameters are obtained. By adoption of the method disclosed by the invention, the error of the estimated external parameters is relatively low, and the precision of the time sequence calibration track is high.

Description

technical field [0001] The present invention relates to a method for merging camera and IMU (Inertial Measurement Unit, IMU) information for positioning and map construction, in particular to a method for calibrating external parameters and timing based on visual and inertial navigation fusion SLAM on a mobile platform. Background technique [0002] With the increasing demands of people and the rapid development of robot technology, related fields such as unmanned aerial vehicles, unmanned driving, and augmented reality are also making rapid progress. These fields involve a wide range of technologies, including machine control, parallel computing, sensor technology, signal processing, and more. In terms of perception, highly intelligent devices are inseparable from their own positioning and perception of the environment. SLAM (Simultaneous Location and Mapping, SLAM) technology is the key technology to solve this problem, which can realize positioning and mapping in unknown ...

AI Technical Summary

Problems solved by technology

[0008] 3. In addition, due to hardware limitations, the camera and IMU have different clocks. How to fuse the camera and IMU under asynchronous conditions is also one of the difficulties in solving this problem.

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