Dynamic Manipulation of Flexible Objects with Torque Sequence Using a Deep Neural Network
January 29, 2019 Β· Declared Dead Β· π IEEE International Conference on Robotics and Automation
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Authors
Kento Kawaharazuka, Toru Ogawa, Juntaro Tamura, Cota Nabeshima
arXiv ID
1901.10142
Category
cs.RO: Robotics
Citations
19
Venue
IEEE International Conference on Robotics and Automation
Last Checked
4 months ago
Abstract
For dynamic manipulation of flexible objects, we propose an acquisition method of a flexible object motion equation model using a deep neural network and a control method to realize a target state by calculating an optimized time-series joint torque command. By using the proposed method, any physics model of a target object is not needed, and the object can be controlled as intended. We applied this method to manipulations of a rigid object, a flexible object with and without environmental contact, and a cloth, and verified its effectiveness.
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