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Towards a learning framework for dancing robots
How can we make robots learn how to dance? How do humans learn to dance? An emerging culture of dancing robots is becoming more prominent in the research community with more emphasis on how we can show of our own creativity rather than allowing the robots to develop their own cognitive and psycholog...
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| Main Authors: | , , |
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| Format: | Default Conference proceeding |
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2009
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| Online Access: | https://hdl.handle.net/2134/10114 |
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| _version_ | 1818174638209892352 |
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| author | Ibrahim S. Tholley Qinggang Meng Paul Chung |
| author_facet | Ibrahim S. Tholley Qinggang Meng Paul Chung |
| author_sort | Ibrahim S. Tholley (7168124) |
| collection | Figshare |
| description | How can we make robots learn how to dance? How do humans learn to dance? An emerging culture of dancing robots is becoming more prominent in the research community with more emphasis on how we can show of our own creativity rather than allowing the robots to develop their own cognitive and psychological behaviours to the music being played. There are many different types of music and indeed, many different robots and many ways, in which they can dance to music however, much of the work carried out in this field concern limiting robots to dance in particular ways to a specific music and no adaptive behaviour implemented in them to be able to respond intuitively to music in general. We propose in this paper, a way in which such a problem can begin to be looked into, by introducing fundamental things that should be learnt that are necessary for dancing. We programmed a virtual robot to learn to dance to the beat as well as recognise the downbeat of any time-signature and tailor its movements to the loudness of music, using the Sarsa and the Sarsa(lambda) algorithms from reinforcement learning as the learning framework. Experimental results show that it is possible to make robots learn to dance to these fundamental rhythmic features of music. |
| format | Default Conference proceeding |
| id | rr-article-9404777 |
| institution | Loughborough University |
| publishDate | 2009 |
| record_format | Figshare |
| spelling | rr-article-94047772009-01-01T00:00:00Z Towards a learning framework for dancing robots Ibrahim S. Tholley (7168124) Qinggang Meng (1257072) Paul Chung (1250973) Other information and computing sciences not elsewhere classified untagged Information and Computing Sciences not elsewhere classified How can we make robots learn how to dance? How do humans learn to dance? An emerging culture of dancing robots is becoming more prominent in the research community with more emphasis on how we can show of our own creativity rather than allowing the robots to develop their own cognitive and psychological behaviours to the music being played. There are many different types of music and indeed, many different robots and many ways, in which they can dance to music however, much of the work carried out in this field concern limiting robots to dance in particular ways to a specific music and no adaptive behaviour implemented in them to be able to respond intuitively to music in general. We propose in this paper, a way in which such a problem can begin to be looked into, by introducing fundamental things that should be learnt that are necessary for dancing. We programmed a virtual robot to learn to dance to the beat as well as recognise the downbeat of any time-signature and tailor its movements to the loudness of music, using the Sarsa and the Sarsa(lambda) algorithms from reinforcement learning as the learning framework. Experimental results show that it is possible to make robots learn to dance to these fundamental rhythmic features of music. 2009-01-01T00:00:00Z Text Conference contribution 2134/10114 https://figshare.com/articles/conference_contribution/Towards_a_learning_framework_for_dancing_robots/9404777 CC BY-NC-ND 4.0 |
| spellingShingle | Other information and computing sciences not elsewhere classified untagged Information and Computing Sciences not elsewhere classified Ibrahim S. Tholley Qinggang Meng Paul Chung Towards a learning framework for dancing robots |
| title | Towards a learning framework for dancing robots |
| title_full | Towards a learning framework for dancing robots |
| title_fullStr | Towards a learning framework for dancing robots |
| title_full_unstemmed | Towards a learning framework for dancing robots |
| title_short | Towards a learning framework for dancing robots |
| title_sort | towards a learning framework for dancing robots |
| topic | Other information and computing sciences not elsewhere classified untagged Information and Computing Sciences not elsewhere classified |
| url | https://hdl.handle.net/2134/10114 |