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Multisensory Learning Framework for Robot Drumming
- Source :
- Workshop on Crossmodal Learning for Intelligent Robotics 2nd Edition. IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), 2018
- Publication Year :
- 2019
-
Abstract
- 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.<br />Comment: Extended abstract
Details
- Database :
- arXiv
- Journal :
- Workshop on Crossmodal Learning for Intelligent Robotics 2nd Edition. IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), 2018
- Publication Type :
- Report
- Accession number :
- edsarx.1907.09775
- Document Type :
- Working Paper