Guiding a robotic gripper by visual feedback for object manipulation tasks

This paper presents a novel object manipulation technique that could be adopted by any advanced mechatronic platform in order to perform demanding pick and place tasks. The ultimate goal of a robotics researcher is to provide an applicable manipulation solution that minimizes user´s involvement. It has been shown that the best solution to this problem is provided by the introduction of sensors that allow an automatic or, at least, semi-automatic grasping of the targets. The proposed method relies on a vision-based framework that is responsible for several vital tasks that affect directly the manipulation process. The contribution of the paper incorporates a shape retrieval technique accompanied with classification and clustering algorithms that are utilized during the objects´ pose estimation process. The experimental results obtained confirm the validity of the presented approach.