Abstract
Compared with more rigid objects, clothing items are inherently difficult for robots to recognize and manipulate. We propose a method for detecting how cloth is folded, to facilitate choosing a manipulative action that corresponds to a garment’s shape and position. The proposed method involves classifying the edges and corners of a garment by distinguishing between edges formed by folds and the hem or ragged edge of the cloth. Identifying the type of edges in a corner helps to determinate how the object is folded. This bottom-up approach, together with an active perception system, allows us to select strategies for robotic manipulation. We corroborate the method using a two-armed robot to manipulate towels of different shapes, textures, and sizes.
Highlights
In recent years, robots have contributed to a significant increase in the automation of industrial tasks
The demand for robots capable of assisting with household tasks is likely to increase in parallel with aging global populations, a demographic phenomenon caused by improved life expectancies and dropping birth rates
One operation that is central to many household tasks, including laundry, assisted dressing, and bed making, is the manipulation of cloth items
Summary
Robots have contributed to a significant increase in the automation of industrial tasks. One operation that is central to many household tasks, including laundry, assisted dressing, and bed making, is the manipulation of cloth items. This skill, which is simple for most humans, is very difficult for robots to perform. The difficulty of cloth manipulation lies in the deformability, nonlinearity, and low predictability of the behavior of the materials Because of their deformable nature, compared with rigid objects, cloth objects are inherently difficult for robots to recognize. This is why it is often necessary to completely unfold cloth items prior to starting a task.
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