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http://dx.doi.org/10.7746/jkros.2021.16.4.299

Pose Estimation and Image Matching for Tidy-up Task using a Robot Arm  

Piao, Jinglan (Mechanical Engineering, Korea University)
Jo, HyunJun (Mechanical Engineering, Korea University)
Song, Jae-Bok (Mechanical Engineering, Korea University)
Publication Information
The Journal of Korea Robotics Society / v.16, no.4, 2021 , pp. 299-305 More about this Journal
Abstract
In this study, the task of robotic tidy-up is to clean the current environment up exactly like a target image. To perform a tidy-up task using a robot, it is necessary to estimate the pose of various objects and to classify the objects. Pose estimation requires the CAD model of an object, but these models of most objects in daily life are not available. Therefore, this study proposes an algorithm that uses point cloud and PCA to estimate the pose of objects without the help of CAD models in cluttered environments. In addition, objects are usually detected using a deep learning-based object detection. However, this method has a limitation in that only the learned objects can be recognized, and it may take a long time to learn. This study proposes an image matching based on few-shot learning and Siamese network. It was shown from experiments that the proposed method can be effectively applied to the robotic tidy-up system, which showed a success rate of 85% in the tidy-up task.
Keywords
Robotic; Tidy-up Task; Pose Estimation; Image Matching; Grasping; Object Manipulation;
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