Calculation of 6-DOF Pose of Arbitrary Inclined Nuts for a Grasping Task by Dual-Arm Robot
Ruhizan Liza Ahmad Shauri and Kenzo Nonami
Department of Mechanical Engineering, Division of Artificial Systems Science, Graduate School of Engineering, Chiba University, 1-33 Yayoi-cho, Inage-ku, Chiba 263-8522, Japan
The capability to manipulate small objects is one of the important requirements for producing assembly work robots. Moreover, a robot that exhibits humanlike skills could be used to reduce the high labor cost for complex tasks. Therefore, we propose a seven-link dual-arm robot with three-fingered hands for cooperative tasks to manipulate small parts such as nuts and bolts in an unstructured environment. As an initial experiment, we need to obtain the six degrees of freedom (DOF) posture of a hexagonal M10 nut (diameter, 19.6 mm), which is small and possesses an indistinguishable color. These constraints have made it difficult to recognize such a target by current available methods where a higher order of posture data is necessary for robot operation. Hence, we propose a technique that we have labeled as Confirm-Estimate-Rotate (CER), which employs integration between the image and robot algorithms in consecutive iteration loops via a visual servoing structure. Real-time experimental results indicate the capability of our method to change the seven-link arm robot posture safely to match the posture of a target in an inclined position. Furthermore, a statistical grasping result by this method has shown a moderate performance for nuts in arbitrary poses. Thus, this shows that the method could be applied to solve the problem of aligning nuts and bolts from the previous screwing task performed by the dual-arm robot in the next future work.
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