Automatic Grouping of Redundant Sensors and Actuators Using Functional and Spatial Connections: Application to Muscle Grouping for Musculoskeletal Humanoids
| Autor: | Kento Kawaharazuka, Yuki Asano, Yasunori Toshimitsu, Yuya Koga, Manabu Nishiura, Masayuki Inaba, Yusuke Omura, Kei Okada, Koji Kawasaki |
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| Rok vydání: | 2021 |
| Předmět: |
0209 industrial biotechnology
Control and Optimization Artificial neural network Computer science business.industry Mechanical Engineering Biomedical Engineering 02 engineering and technology Construct (python library) Computer Science Applications Human-Computer Interaction 020901 industrial engineering & automation Artificial Intelligence Control and Systems Engineering Control theory Robot Graph (abstract data type) Computer vision Computer Vision and Pattern Recognition Artificial intelligence Actuator Geometric modeling business Humanoid robot |
| Zdroj: | IEEE Robotics and Automation Letters. 6:1981-1988 |
| ISSN: | 2377-3774 |
| DOI: | 10.1109/lra.2021.3060715 |
| Popis: | For a robot with redundant sensors and actuators distributed throughout its body, it is difficult to construct a controller or a neural network using all of them due to computational cost and complexity. Therefore, it is effective to extract functionally related sensors and actuators, group them, and construct a controller or a network for each of these groups. In this study, the functional and spatial connections among sensors and actuators are embedded into a graph structure and a method for automatic grouping is developed. Taking a musculoskeletal humanoid with a large number of redundant muscles as an example, this method automatically divides all the muscles into regions such as the forearm, upper arm, scapula, neck, etc., which has been done by humans based on a geometric model. The functional relationship among the muscles and the spatial relationship of the neural connections are calculated without a geometric model. This study is applied to muscle grouping of musculoskeletal humanoids Musashi and Kengoro, and its effectiveness is verified. |
| Databáze: | OpenAIRE |
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