オプティカルフローの学習に基づく着衣作業中の布製品のオンライン状態推定

抄録

In this paper, we present a learning-based method for estimating the state of a cloth product on basis of its optical flow during a dressing process. Using this method, we realize the following capabilities: (1) handling of many different kinds of fabric products, (2) detection of fabric manipulation failures (e.g. cloth snagging), (3) fabric manipulation with complex procedures, and (4) online state estimation. We evaluate state estimation accuracy in two dressing experiments: pulling a plain cylindrical cloth onto an L-shaped stand, and pulling a long-sleeved dress onto the arm of a doll. The experimental results confirm that our method can estimate the state of the fabric during the dressing process more accurately than conventional methods.