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Verification of recognition performance of cloth handling robot with photo-model-based matching

机译:通过基于照片模型的匹配来验证衣物处理机器人的识别性能

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Recently, vision-based robots have been used in the garment factories. However, deformable objects such as cloths, strings have been difficult to be recognized and handled automatically by robots. Moreover, robots have been facing with two main problems in 3D cloth recognition and handling performance. These problems are to judge that the cloth placed in front of the robot is rightly the intended one to be handled and to pick and place (handle) at a designated position automatically. In this paper, model generation method from cloth photograph and model-based matching method (recognition method) utilizing Genetic Algorithm (GA) are presented. The proposed system recognizes the target cloth and estimates the pose of that cloth for handling even though the target cloth is occluded partially and there are another cloth in the field of view of robot's camera. In this paper, 3D recognition accuracy has been confirmed experimentally by using 12 different samples cloths.
机译:最近,基于视觉的机器人已在服装工厂中使用。但是,诸如布料,细绳之类的可变形物体很难被机器人自动识别和处理。此外,机器人在3D布识别和处理性能方面面临两个主要问题。这些问题是为了判断放在机器人前面的布料正确地是要处理的布料,并自动将其放在指定的位置。本文提出了一种基于布料照片的模型生成方法以及利用遗传算法(GA)的基于模型的匹配方法(识别方法)。所提出的系统识别目标布料并估计该布料的姿势以进行处理,即使目标布料被部分遮挡并且在机器人摄像机的视野中还有另一块布料也是如此。在本文中,通过使用12种不同的样品布在实验上证实了3D识别的准确性。

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