Automatic Grouping of Redundant Sensors and Actuators Using Functional and Spatial Connections: Application to Muscle Grouping for Musculoskeletal Humanoids
Fuente:
arXiv
Gespeichert in:
| Hauptverfasser: | , , , , , , , , |
|---|---|
| Format: | Preprint |
| Veröffentlicht: |
2024
|
| Schlagworte: | |
| Online-Zugang: | |
| Tags: |
Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
|
| _version_ | 1866913488308273152 |
|---|---|
| author | Kawaharazuka, Kento Nishiura, Manabu Koga, Yuya Omura, Yusuke Toshimitsu, Yasunori Asano, Yuki Okada, Kei Kawasaki, Koji Inaba, Masayuki |
| author_facet | Kawaharazuka, Kento Nishiura, Manabu Koga, Yuya Omura, Yusuke Toshimitsu, Yasunori Asano, Yuki Okada, Kei Kawasaki, Koji Inaba, Masayuki |
| contents | 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. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2409_00678 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | Automatic Grouping of Redundant Sensors and Actuators Using Functional and Spatial Connections: Application to Muscle Grouping for Musculoskeletal Humanoids Kawaharazuka, Kento Nishiura, Manabu Koga, Yuya Omura, Yusuke Toshimitsu, Yasunori Asano, Yuki Okada, Kei Kawasaki, Koji Inaba, Masayuki Robotics 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. |
| title | Automatic Grouping of Redundant Sensors and Actuators Using Functional and Spatial Connections: Application to Muscle Grouping for Musculoskeletal Humanoids |
| topic | Robotics |
| url | https://arxiv.org/abs/2409.00678 |