The DOI matches its Crossref record; 38 of the 38 references it cites were found in a registry or an index.
Information-Theoretic Model Predictive Control: Theory and Applications to Autonomous Driving
Open accessAbstract
We present an information-theoretic approach to stochastic optimal control problems that can be used to derive general sampling-based optimization schemes. This new mathematical method is used to develop a sampling-based model predictive control algorithm. We apply this information-theoretic model predictive control scheme to the task of aggressive autonomous driving around a dirt test track, and compare its performance with a model predictive control version of the cross-entropy method.
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Cites
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Stanley: The robot that won the DARPA Grand Challenge
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Cited by
Deep learning, reinforcement learning, and world models
Matsuo, Y., LeCun, Y., Sahani, M., Precup, D., Silver, D., Sugiyama, M., Uchibe, E., & Morimoto, J. (2022) · Neural Networks · doi:10.1016/j.neunet.2022.03.037 · Cited by 543
Outracing champion Gran Turismo drivers with deep reinforcement learning
Wurman, P. R., Barrett, S., Kawamoto, K., MacGlashan, J., Subramanian, K., Walsh, T. J., Capobianco, R., Devlic, A., Eckert, F., Fuchs, F., et al. (2022) · Nature · doi:10.1038/s41586-021-04357-7 · Cited by 369
Autonomous Vehicles on the Edge: A Survey on Autonomous Vehicle Racing
Betz, J., Zheng, H., Liniger, A., Rosolia, U., Karle, P., Behl, M., Krovi, V., & Mangharam, R. (2022) · IEEE Open Journal of Intelligent Transportation Systems · doi:10.1109/ojits.2022.3181510 · Cited by 322
Interoception as modeling, allostasis as control
Sennesh, E., Theriault, J., Brooks, D., van de Meent, J.-W., Barrett, L. F., & Quigley, K. S. (2022) · Biological Psychology · doi:10.1016/j.biopsycho.2021.108242 · Cited by 107
Metadata
- Authors
- Williams, G., Drews, P., Goldfain, B., Rehg, J. M., & Theodorou, E. A.
- Venue
- IEEE Transactions on Robotics
- Published
- 2018-12
- Volume
- 34
- Issue
- 6
- Pages
- 1603-1622
- ISSN
- 1552-3098 (ISSN-L)
- 1941-0468
- OpenAlex
- W2734458532
- Cited by
- 334
- References
- 38
- FWCI
- 9.62
- Type
- journal article
- Language
- en
- Open access
- green
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- Williams, G., Drews, P., Goldfain, B., Rehg, J. M., & Theodorou, E. A. (2018). Information-Theoretic Model Predictive Control: Theory and Applications to Autonomous Driving. IEEE Transactions on Robotics. https://doi.org/10.1109/tro.2018.2865891
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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.
