Precise pose estimation using landmark feature extraction and blob analysis for bin picking

Abstract

This paper proposes a method of vision based pose estimation of randomly piled objects. It is necessary to estimate precise rotation angle of picking objects. However, it is non-trivial task because an object placed in every position makes distorted image far from right position image. We propose a precise pose estimation method of bin picking objects. The landmark feature of a picking object is extracted and is used to estimate coarse rotation angle of object. The pose of the object can be precisely estimated by analyzing feature blobs in the landmark. We have experimented to evaluate proposed method in the pilot system, which is constructed like a real manufacturing environment. The experiments have been conducted using 1,000 images. As a result, the pose estimation accuracy of less than 0.154 degree has obtained.