A ball-target-based extrinsic calibration technique for high-accuracy 3-D metrology using off-the-shelf laser-stripe sensors

This paper presents a ball-target-based method for the extrinsic calibration of a three-dimensional (3-D), multiple-axis, structured-light (laser-stripe) scanning system. The calibration involves the scanning of a physical artifact (a ball-target) in the working volume of the measurement system whenever a change of sensor occurs or during initial system setup. Based on the fact that there are only eight independent parameters in the transformation from the skewed sensor frame to an orthogonal reference frame, a constrained optimization calibration algorithm is developed. A slice-interpolation algorithm is used to identify the conjugate pairs. Through calibration, the usually nonorthogonal skewed sensor frame can be related to a Cartesian world frame. Experimental studies using a tetra-ball target demonstrate the effectiveness of the proposed calibration technique. As reflected by the radii of the ball target, the shape distortion of the image was reduced from an average of 1.44 to 0.04 mm over an 18.93-mm range. As reflected by the distances between the centers of the balls, the dimensional distortion was reduced from an average of 4.28 to 0.07 mm over a 90-mm range.