ペアワイズ損失による制御ポリシーのシミュレーションから実機への転移
Adapting control policies from simulation to reality using a pairwise loss
ペアワイズ損失関数を用いて、シミュレーションで学習した制御ポリシーを実機ロボットへ転移する手法を提案し、新規物体の嵌合タスクで有効性を示した。
著者: Ulrich Viereck, Xingchao Peng, Kate Saenko, Robert Platt
分類: cs.RO, cs.AI, cs.CV
原文アブストラクト
This paper proposes an approach to domain transfer based on a pairwise loss function that helps transfer control policies learned in simulation onto a real robot. We explore the idea in the context of a 'category level' manipulation task where a control policy is learned that enables a robot to perform a mating task involving novel objects. We explore the case where depth images are used as the main form of sensor input. Our experimental results demonstrate that proposed method consistently outperforms baseline methods that train only in simulation or that combine real and simulated data in a naive way.
