An Object Detection and Pose Estimation Approach for Position Based Visual Servoing

Abstract

Abstract In this paper, an object recognition method and a pose estimation approach using stereo vision is presented. The proposed approach was used for position based visual servoing of a 6 DoF manipulator. The object detection and recognition method was designed with the purpose of increasing robustness. A RGB color-based object descriptor and an online correction method is proposed for object detection and recognition. Pose was estimated by using the depth information derived from stereo vision camera and an SVD based method. Transformation between the desired pose and object pose was calculated and later used for position based visual servoing. Experiments were carried out to verify the proposed approach for object recognition. The stereo camera was also tested to see whether the depth accuracy is adequate. The proposed object recognition method is invariant to scale, orientation and lighting condition which increases the level of robustness. The accuracy of stereo vision camera can reach 1 mm. The accuracy is adequate for tasks such as grasping and manipulation.