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Predictive control for agile semi-autonomous ground vehicles using motion primitives
Abstract
This paper presents a hierarchical control framework for the obstacle avoidance of autonomous and semi-autonomous ground vehicles. The high-level planner is based on motion primitives created from a four-wheel nonlinear dynamic model. Parameterized clothoids and drifting maneuvers are used to improve vehicle agility. The low-level tracks the planned trajectory with a nonlinear Model Predictive Controller. The first part of the paper describes the proposed control architecture and methodology. The second part presents simulative and experimental results with an autonomous and semi-autonomous ground vehicle traveling at high speed on an icy surface.
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Citations
Cited by
Optimization‐based autonomous racing of 1:43 scale RC cars
Liniger, A., Domahidi, A., & Morari, M. (2015) · Optimal Control Applications and Methods · doi:10.1002/oca.2123 · Cited by 537
Lane Change Maneuvers for Automated Vehicles
Nilsson, J., Brannstrom, M., Coelingh, E., & Fredriksson, J. (2017) · IEEE Transactions on Intelligent Transportation Systems · doi:10.1109/tits.2016.2597966 · Cited by 227
Ahn, H., Rizzi, A., Colombo, A., & Del Vecchio, D. (2015) · 2015 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) · doi:10.1109/iros.2015.7354056 · Cited by 25
Metadata
- Authors
- Gray, A., Gao, Y., Lin, T., Hedrick, J. K., Tseng, H. E., & Borrelli, F.
- Venue
- 2012 American Control Conference (ACC)
- Publisher
- IEEE
- Published
- 2012-06
- Pages
- 4239-4244
- ISSN
- 0743-1619 (ISSN-L)
- OpenAlex
- W2166446174
- Cited by
- 194
- References
- 0
- FWCI
- 15.53
- Type
- conference paper
- Language
- en
- Open access
- closed
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- CoChat. (2026). Citation check: Predictive control for agile semi-autonomous ground vehicles using motion primitives. https://app.cochat.ai/papers/10.1109/acc.2012.6315303
- The paper
- Gray, A., Gao, Y., Lin, T., Hedrick, J. K., Tseng, H. E., & Borrelli, F. (2012). Predictive control for agile semi-autonomous ground vehicles using motion primitives. 2012 American Control Conference (ACC). https://doi.org/10.1109/acc.2012.6315303
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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.
