Combining stereo vision and fuzzy image based visual servoing for autonomous object grasping using a 6-DOF manipulator

This research presents a new grasping method in which a 6-DOF industrial robot can autonomously grasp a stationary, randomly positioned rectangular object using a combination of stereo vision and image-based visual servoing with a fuzzy controller (IBVSFC). First, openCV software and a color filter algorithm are used to extract the specific color features of the object. Then, the 3D coordinates of the object to be grasped are derived by the stereo vision algorithm, and the coordinates are used to guide the robotic arm to the approximate location of the object using inverse kinematics. Finally, IBVSFC precisely adjusts the pose of the end-effector to coincide with that of the object to make a successful grasp. The accuracy and robustness of the system and the algorithm were tested and proven to be effective in real scenarios involving a 6-DOF industrial robot. Although the application of this research is limited in grasping a simple cubic object, the same methodology can be easily applied to objects with other geometric shapes.