arXiv Open Access 2024

Task-specific Self-body Controller Acquisition by Musculoskeletal Humanoids: Application to Pedal Control in Autonomous Driving

Kento Kawaharazuka Kei Tsuzuki Shogo Makino Moritaka Onitsuka Koki Shinjo +4 lainnya

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Abstrak

The musculoskeletal humanoid has many benefits that human beings have, but the modeling of its complex flexible body is difficult. Although we have developed an online acquisition method of the nonlinear relationship between joints and muscles, we could not completely match the actual robot and its self-body image. When realizing a certain task, the direct relationship between the control input and task state needs to be learned. So, we construct a neural network representing the time-series relationship between the control input and task state, and realize the intended task state by applying the network to a real-time control. In this research, we conduct accelerator pedal control experiments as one application, and verify the effectiveness of this study.

Topik & Kata Kunci

cs.RO

Penulis (9)

Kento Kawaharazuka

Kei Tsuzuki

Shogo Makino

Moritaka Onitsuka

Koki Shinjo

Yuki Asano

Kei Okada

Koji Kawasaki

Masayuki Inaba

Format Sitasi

APA MLA BibTeX

Kawaharazuka, K., Tsuzuki, K., Makino, S., Onitsuka, M., Shinjo, K., Asano, Y. et al. (2024). Task-specific Self-body Controller Acquisition by Musculoskeletal Humanoids: Application to Pedal Control in Autonomous Driving. https://arxiv.org/abs/2412.08270

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Informasi Jurnal

Tahun Terbit: 2024
Bahasa: en
Sumber Database: arXiv
Akses: Open Access ✓