Abstract
AbstractCompared 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.
Funder
Japan Society for the Promotion of Science
Publisher
Springer Science and Business Media LLC
Subject
Artificial Intelligence,Control and Optimization,Mechanical Engineering,Instrumentation,Modeling and Simulation
Cited by
4 articles.
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1. Visual-Tactile Learning of Garment Unfolding for Robot-Assisted Dressing;IEEE Robotics and Automation Letters;2023-09
2. UnfoldIR: Tactile Robotic Unfolding of Cloth;IEEE Robotics and Automation Letters;2023-08
3. Clothing gripping and sorting based on a dual-arm collaborative robot;2023 International Conference on Robotics and Automation in Industry (ICRAI);2023-03-03
4. Development and Control of Robot Hand with Finger Camera for Garment Handling Tasks;2022 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS);2022-10-23