ロボットドラミングのためのマルチセンサリ学習フレームワーク
Multisensory Learning Framework for Robot Drumming
音声・映像・固有感覚を時系列同期して収集するオープンソース基盤を構築し、ヒューマノイドドラムロボットが音声から新規動作を生成する非線形センサモータマッピングを学習した。
著者: A. Barsky, C. Zito, H. Mori, T. Ogata, J. L. Wyatt
分類: cs.RO, cs.CV, cs.SD
原文アブストラクト
The hype about sensorimotor learning is currently reaching high fever, thanks to the latest advancement in deep learning. In this paper, we present an open-source framework for collecting large-scale, time-synchronised synthetic data from highly disparate sensory modalities, such as audio, video, and proprioception, for learning robot manipulation tasks. We demonstrate the learning of non-linear sensorimotor mappings for a humanoid drumming robot that generates novel motion sequences from desired audio data using cross-modal correspondences. We evaluate our system through the quality of its cross-modal retrieval, for generating suitable motion sequences to match desired unseen audio or video sequences.