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arXiv · 2205.00225

Recognising Known Configurations of Garments For Dual-Arm Robotic Flattening

Li Duan·Gerardo Argon-Camarasa
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Abstract

Robotic deformable-object manipulation is a challenge in the robotic industry because deformable objects have complicated and various object states. Predicting those object states and updating manipulation planning is time-consuming and computationally expensive. In this paper, we propose learning known configurations of garments to allow a robot to recognise garment states and choose a pre-designed manipulation plan for garment flattening.

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Li Duan, Gerardo Argon-Camarasa. 2022-04-30. Recognising Known Configurations of Garments For Dual-Arm Robotic Flattening. https://arxiv.org/abs/2205.00225

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