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.
| Original language | English |
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| Publication status | Published - 2018 |
| Event | 2nd Workshop on Crossmodal Learning for Intelligent Robotics 2018 - Madrid, Spain Duration: 5 Oct 2018 → … |
Workshop
| Workshop | 2nd Workshop on Crossmodal Learning for Intelligent Robotics 2018 |
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| Abbreviated title | CLIR'18 |
| Country/Territory | Spain |
| City | Madrid |
| Period | 5/10/18 → … |