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On Low Complexity Predictive Approaches to Control of Autonomous Vehicles
| Content Provider | Semantic Scholar |
|---|---|
| Author | Falcone, Paolo Borrelli, Francesco Tseng, H. Eric Hrovat, Davor |
| Copyright Year | 2009 |
| Abstract | In this paper we present low complexity predictive approach es to the control of autonomous vehicles. A general hierarchical arc hite ture for fully autonomous vehicle guidance systems is presented together wi th a review of two control design paradigms. Our review emphasizes the trade off b etween performance and computational complexity at different control levels o f the architecture. In particular, experimental results are presented, showing that if the controller at the lower level is properly designed, then it can handle system nonlin earities and model uncertainties even if those are not taken into account at the hi gher level. |
| File Format | PDF HTM / HTML |
| Alternate Webpage(s) | http://www.me.berkeley.edu/~frborrel/pdfpub/pub-1034.pdf |
| Language | English |
| Access Restriction | Open |
| Subject Keyword | Autonomous robot Computational complexity theory Controllers Drug vehicle Guidance system Trajectory optimization |
| Content Type | Text |
| Resource Type | Article |
