Visional grasping control of robot based on QR code

Positioning and grasping objects are a necessary skill for service robots. This research proposes a monocular visual location method based on QR code for service robots in an indoor environment by service robots. This method utilizes the unique geometric features of QR codes and can fast realize the spatial location of an object with high accuracy. Furthermore, the NAO robot's arm is kinematical modelled by the DH parameters, and then find the inverse kinematic solution to accomplish the grasping task according to the location of an object. Due to the buffer of robot very limit and the real time required, some in-depth mathematical connotations with complicated calculation and deep learning are impossible, so the QR code algorithm for the visional grasping is useful in order to let robot to response quickly. We also made a comparison with another research method, these experimental results show that the proposed method can more stably and accurately complete the identification, positioning and grasping of target objects.