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Robotics: Science and Systems (RSS)
Open accessAbstract
The conference Robotics: Science and Systems was held at the University of Washington in Seattle, from June 28 to July 1, 2009. More than 300 international researchers attended this single‐track conference to learn about the most exciting robotics research and most advanced robotic systems. The program committee selected 39 papers out of 154 submissions. The program also included invited talks. The plenary presentations were complemented by workshops.
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Cited by
VoxelNet: End-to-End Learning for Point Cloud Based 3D Object Detection
Zhou, Y., & Tuzel, O. (2018) · 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition · doi:10.1109/cvpr.2018.00472 · Cited by 4,813
Simultaneous localization and mapping: part I
Durrant-Whyte, H., & Bailey, T. (2006) · IEEE Robotics & Automation Magazine · doi:10.1109/mra.2006.1638022 · Cited by 4,199
A survey of deep learning techniques for autonomous driving
Grigorescu, S., Trasnea, B., Cocias, T., & Macesanu, G. (2020) · Journal of Field Robotics · doi:10.1002/rob.21918 · Cited by 1,809
How to train your robot with deep reinforcement learning: Lessons we have learned
Ibarz, J., Tan, J., Finn, C., Kalakrishnan, M., Pastor, P., & Levine, S. (2021) · The International Journal of Robotics Research · doi:10.1177/0278364920987859 · Cited by 570
Rational quantitative attribution of beliefs, desires and percepts in human mentalizing
Baker, C. L., Jara-Ettinger, J., Saxe, R., & Tenenbaum, J. B. (2017) · Nature Human Behaviour · doi:10.1038/s41562-017-0064 · Cited by 515
Metadata
- Authors
- Trinkle, J., & Matsuoka, Y.
- Venue
- AI Magazine
- Publisher
- Wiley
- Published
- 2010-03
- Volume
- 31
- Issue
- 1
- Pages
- 99-100
- ISSN
- 0738-4602 (ISSN-L)
- 2371-9621
- OpenAlex
- W4242073862
- Cited by
- 1,081
- References
- 0
- FWCI
- 36.64
- Type
- journal article
- Language
- en
- Open access
- bronze
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Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
