Manipulation of deformable linear objects using knot invariants to classify the object condition based on image sensor information
Manipulation of deformable linear objects using knot invariants to classify the object condition based on image sensor information
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DOI：
10.1109/tmech.2006.878557
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发表时间：
2006-08
期刊：
影响因子：
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通讯作者：
Takayuki Matsuno;Daichi Tamaki;F. Arai;Toshio Fukuda
中科院分区：
文献类型：
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作者：
Takayuki Matsuno;Daichi Tamaki;F. Arai;Toshio Fukuda
使用拓扑模型和结理论，我们提出了一种描述绳索状况的方法。我们还提出了一种基于从电荷耦合器件相机获得的图像信息的识别方法，以获取机器人操纵时绳索的结构。该方法为可变形物体操纵提供错误恢复的理论框架，有助于解决机器人操纵可变形物体的困难。我们通过实验证实了方法的有效性
Using a topological model and knot theory, we propose a method for describing the condition of a rope. We also propose a recognition method based on the image information obtained from the charge-coupled device cameras to obtain the structure of the rope when manipulated by a robot. This method will help solve the difficulties of robots manipulating deformable objects by providing a theoretical framework of error recovery for deformable object manipulation. We confirm the effectiveness of the methods through experiments