Robots Learn Writing
This paper proposes a general method for robots to learn motions and corresponding semantic knowledge simultaneously. A modified ISOMAP algorithm is used to convert the sampled 6D vectors of joint angles into 2D trajectories, and the required movements for writing numbers are learned from this modif...
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| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
| Published: |
Wiley
2012-01-01
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| Series: | Journal of Robotics |
| Online Access: | http://dx.doi.org/10.1155/2012/505191 |
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| _version_ | 1849406281721315328 |
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| author | Huan Tan Qian Du Na Wu |
| author_facet | Huan Tan Qian Du Na Wu |
| author_sort | Huan Tan |
| collection | DOAJ |
| description | This paper proposes a general method for robots to learn motions and corresponding semantic knowledge simultaneously. A modified ISOMAP algorithm is used to convert the sampled 6D vectors of joint angles into 2D trajectories, and the required movements for writing numbers are learned from this modified ISOMAP-based model. Using this algorithm, the knowledge models are established. Learned motion and knowledge models are stored in a 2D latent space. Gaussian Process (GP) method is used to model and represent these models. Practical experiments are carried out on a humanoid robot, named ISAC, to learn the semantic representations of numbers and the movements of writing numbers through imitation and to verify the effectiveness of this framework. This framework is applied into training a humanoid robot, named ISAC. At the learning stage, ISAC not only learns the dynamics of the movement required to write the numbers, but also learns the semantic meaning of the numbers which are related to the writing movements from the same data set. Given speech commands, ISAC recognizes the words and generated corresponding motion trajectories to write the numbers. This imitation learning method is implemented on a cognitive architecture to provide robust cognitive information processing. |
| format | Article |
| id | doaj-art-4b79ea2ed87c4ecc8bb110c952f48a86 |
| institution | Kabale University |
| issn | 1687-9600 1687-9619 |
| language | English |
| publishDate | 2012-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | Journal of Robotics |
| spelling | doaj-art-4b79ea2ed87c4ecc8bb110c952f48a862025-08-20T03:36:26ZengWileyJournal of Robotics1687-96001687-96192012-01-01201210.1155/2012/505191505191Robots Learn WritingHuan Tan0Qian Du1Na Wu2Department of Electrical Engineering and Computer Science, Vanderbilt University, Nashville, TN 37240, USAInstitute of Robotics and Automatic Information System, Nankai University, Tianjin 300071, ChinaGraduate School of Decision and Technology, Tokyo Institute of Technology, Tokyo 152-8552, JapanThis paper proposes a general method for robots to learn motions and corresponding semantic knowledge simultaneously. A modified ISOMAP algorithm is used to convert the sampled 6D vectors of joint angles into 2D trajectories, and the required movements for writing numbers are learned from this modified ISOMAP-based model. Using this algorithm, the knowledge models are established. Learned motion and knowledge models are stored in a 2D latent space. Gaussian Process (GP) method is used to model and represent these models. Practical experiments are carried out on a humanoid robot, named ISAC, to learn the semantic representations of numbers and the movements of writing numbers through imitation and to verify the effectiveness of this framework. This framework is applied into training a humanoid robot, named ISAC. At the learning stage, ISAC not only learns the dynamics of the movement required to write the numbers, but also learns the semantic meaning of the numbers which are related to the writing movements from the same data set. Given speech commands, ISAC recognizes the words and generated corresponding motion trajectories to write the numbers. This imitation learning method is implemented on a cognitive architecture to provide robust cognitive information processing.http://dx.doi.org/10.1155/2012/505191 |
| spellingShingle | Huan Tan Qian Du Na Wu Robots Learn Writing Journal of Robotics |
| title | Robots Learn Writing |
| title_full | Robots Learn Writing |
| title_fullStr | Robots Learn Writing |
| title_full_unstemmed | Robots Learn Writing |
| title_short | Robots Learn Writing |
| title_sort | robots learn writing |
| url | http://dx.doi.org/10.1155/2012/505191 |
| work_keys_str_mv | AT huantan robotslearnwriting AT qiandu robotslearnwriting AT nawu robotslearnwriting |