Web: http://arxiv.org/abs/2205.00225

June 20, 2022, 1:13 a.m. | Li Duan, Gerardo Argon-Camarasa

cs.CV updates on arXiv.org arxiv.org

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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