Classification of Clothing using Interactive Perception
We present a system for automatically extracting and classifying items in a pile of laundry. Using only visual sensors, the robot identifies and extracts items sequentially from the pile. When an item has been removed and isolated, a model is captured of the shape and appearance of the object, which is then compared against a database of known items. The classification procedure relies upon silhouettes, edges, and other low-level image measurements of the articles of clothing. The contributions of this paper are a novel method for extracting articles of clothing from a pile of laundry and a novel method of classifying clothing using interactive perception. Experiments demonstrate the ability of the system to efficiently classify and label into one of six categories (pants, shorts, short-sleeve shirt, long-sleeve shirt, socks, or underwear). These results show that, on average, classification rates using robot interaction are 59％ higher than those that do not use interaction.
Bryan Willimon Stan Birchfield Ian Walker
Department of Electrical and Computer Engineering Clemson University,Clemson,SC 29634
国际会议
2011 IEEE International Conference on Robotics and Automation(2011年IEEE世界机器人与自动化大会 ICRA 2011)
上海
英文
1862-1868
2011-05-09（万方平台首次上网日期，不代表论文的发表时间）