Manipulating Highly Deformable Materials Using a Visual Feedback Dictionary
2018 IEEE INTERNATIONAL CONFERENCE ON ROBOTICS AND AUTOMATION (ICRA)(2018)
摘要
The complex physical properties of highly deformable materials such as clothes pose significant challenges for autonomous robotic manipulation systems. We present a novel visual feedback dictionary-based method for manipulating deformable objects towards a desired configuration. Our approach is based on visual servoing and we use an efficient technique to extract key features from the RGB sensor stream in the form of a histogram of deformable model features. These histogram features serve as high-level representations of the state of the deformable material. Next, we collect manipulation data and use a visual feedback dictionary that maps the velocity in the high-dimensional feature space to the velocity of the robotic end-effectors for manipulation. We have evaluated our approach on a set of complex manipulation tasks and human-robot manipulation tasks on different cloth pieces with varying material characteristics.
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关键词
complex physical properties,autonomous robotic manipulation systems,visual feedback dictionary-based method,deformable objects,visual servoing,RGB sensor stream,deformable model features,histogram features,high-level representations,deformable material,manipulation data,robotic end-effectors,complex manipulation tasks,human-robot manipulation tasks,material characteristics,deformable materials
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