The study aims to integrate the image sensor for a three-axial pneumatic parallel manipulator which can pick and place objects automatically by the feature information of the image processed through the SURF algorithm. The SURF algorithm is adopted for defining and matching the features of a target object and an object database. In order to accurately mark the center of target and strengthen the feature matching results, the random sample and consensus method (RANSAC) is utilized. The ASUS Xtion Pro Live depth camera which can directly estimate the 3-D location of the target point is used in this study. A set of coordinate estimation calibrations is developed for enhancing the accuracy of target location estimation. This study also presents hand gesture recognition exploiting skin detection and noise elimination to determine the active finger count for input signals of the parallel manipulator. The end-effector of the parallel manipulator can be manipulated to the desired poses according to the measured finger count. Finally, the proposed methods are successfully to achieve the feature recognition and pick and place of the target object.
Keywords: hand gesture recognition; image recognition; parallel manipulator; pneumatic servo system; random sample and consensus algorithm; speed up robust feature algorithm.