Research on the key techniques of 3D computer vision four-wheel aligner

Four-wheel alignment parameters have important effects on the vehicle handling capacity, safety performance and fuel consumption. The main alignment parameters, such as toe angle, camber angle, kingpin inclination and caster angles are explained. The structure and measurement principle of 3D computer vision four-wheel aligner are described. The key technologies of 3D four-wheel aligner based on machine vision were developed, including the sub-pixel positioning technique for extracting the x-corners of chessboard using partial grey-level model of the image features, the calibration technique for camera interior parameters using plane target, the calibration technique for camera exterior parameters using two plane targets with invariable pose and position relation, and the optimization method of least squares for detecting the rotation centers and axis vectors of 4 wheels based on certain geometric motion relations in target rotation and translation. A commercial 3D four-wheel aligner was developed, employing USB3.0 industrial cameras of 1 600×1 200 pixels with the pixel dimension of 3.0 μm×3.0 μm, LED lighting sources with the wavelength of 940 nm, 8 mm focus low-distortion industrial camera lens, and a 6×6 chessboard target. The designed four-wheel aligner and a certain international brand four-wheel aligner in the same hardware rank were tested and compared. The test results show that the developed product has reached the design accuracy, and the products have launched to the market with excellent consumer responses.