Random trihedron-based radar-camera system external parameter calibration method

Abstract

The invention discloses a random trihedron-based radar-camera system external parameter calibration method. According to the method, an external parameter of a system can be solved with only two frames of data by using a trihedron scene a natural environment. The method comprises the following steps of: stipulating a world coordinate system by using a trihedron; performing planar fitting on the trihedron observed in a radar system to obtain a parameter of each plane and solving conversion relation of the world coordinate system and the radar coordinate system and relative motion between the two frames of data under the radar coordinate system; and in a camera system, solving an essential matrix by using matching characteristic points extracted by front and rear frames, then solving relation motion under the camera coordinate system, solving the plane parameter under the camera coordinate system by using the parameter under the radar coordinate system, finally solving an external parameter of a radar-camera, and performing final optimization by using coplanarity of points on corresponding planes under the two coordinate systems. A scene required by the method is simpler; and the method has the characteristics of high anti-interference performance, simple experimental equipment and high flexibility.

Description

technical field [0001] The invention relates to a method for calibrating external parameters of a radar-camera system, in particular to a calibrating method for external parameters of a radar-camera system based on an arbitrary trihedron. Background technique [0002] The real-time construction of the terrain environment is a basic problem in the field of mobile robotics. To achieve this goal, a binocular camera system or a radar sensor is usually used to provide three-dimensional information. However, because the binocular camera system requires dense stereo matching for 3D reconstruction, it takes a long time and is easily affected by the external environment, so it cannot meet the requirements of real-time and accuracy; although radar sensors can provide real-time 3D information, the accuracy is relatively low. High, but lacks color information for the environment. Therefore, more and more researchers combine radar and monocular cameras to form a radar-camera system to p...

AI Technical Summary

Problems solved by technology

However, because the binocular camera system requires dense stereo matching for 3D reconstruction, it takes a long time and is easily affected by the external environment, so it cannot meet the requirements of real-time and accuracy; although radar sensors can provide real-time 3D information, the accuracy is relatively low. High, but lacks ambient color information

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