Using deep reinforcement learning, flexible skills and behaviours emerge in humanoid robots, as demonstrated in two recent reports.
This is a preview of subscription content, access via your institution
Access options
Access Nature and 54 other Nature Portfolio journals
Get Nature+, our best-value online-access subscription
$29.99 / 30 days
cancel any time
Subscribe to this journal
Receive 12 digital issues and online access to articles
$119.00 per year
only $9.92 per issue
Buy this article
- Purchase on SpringerLink
- Instant access to full article PDF
Prices may be subject to local taxes which are calculated during checkout
References
Pfeifer, R., Lungarella, M. & Iida, F. Science 318, 1088–1093 (2007).
Varela, F. J., Thompson, E. & Rosch, E. The Embodied Mind (MIT Press, 1991).
Haarnoja, T. et al. Sci. Robot. 9, eadi8022 (2024).
Radosavovic, I. et al. Sci. Robot. 9, eadi9579 (2024).
Wurman, P. R., Stone, P. & Spranger, M. Science 381, 147–148 (2023).
Li, G., Gomez, R., Nakamura, K. & He, B. IEEE Trans. Hum. Mach. Syst. 49, 337–349 (2019).
Kwon, M., Xie, S. M., Bullard, K. & Sadigh, D. In Proc. International Conference on Learning Representation https://go.nature.com/3XnHupe (ICLR, 2023).
Author information
Authors and Affiliations
Corresponding author
Ethics declarations
Competing interests
The authors declare no competing interests.
Rights and permissions
About this article
Cite this article
Li, G., Gomez, R. Realizing full-body control of humanoid robots. Nat Mach Intell 6, 990–991 (2024). https://doi.org/10.1038/s42256-024-00891-x
Published:
Issue Date:
DOI: https://doi.org/10.1038/s42256-024-00891-x