Precise angle estimation using geometry features for bin picking

In the recent automation process, the manufacturing automation innovation is being done by using vision technology that can make instant judgement. In this paper, a method of vision based angle estimation is presented. The central moment is calculated and the rotation angle is estimated by the angle with the principal axis. There is also a method of estimating the precision rotation angle using the angle between matching points of SIFT descriptors. We propose a rotation angle estimation method that is invariant to object posture. We used affine transformation for the preprocessing of the image for the invariance to object posture. To estimate the accuracy of the rotation angle, we used blobs which are features in the object area. We conducted the angle estimation accuracy and repeatability tests under the experimental environment which has been constructed in our lab. We obtain less than 0.154 angle estimation accuracy.