Abstract
In automated assembly tasks, ellipse detection is usually applied in the vision-based pose estimation of circular workpieces. However, the existing ellipse detection methods cannot effectively solve severe visual occlusion in cluttered environments. To address this problem, this paper proposes a Generative Adversarial Networks (GAN)-supported ellipse detection method against the occlusion condition. The trained GAN network can restore the occluded image of workpieces, so that the elliptical features can be detected robustly. In the experiments with different degrees of occlusion, the ellipse detection rate is above 90%, which shows better performance than other existing methods.
Published Version
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a call