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This paper considers the design of open loop control laws for nonlinear systems that are subject to nonconvex state space constraints. The focus is on finding feasible trajectories for two challenging sets of nonlinear systems: 1) the determination of automobile trajectories through obstacle courses; 2) the design of re-entry trajectories for a reusable launch vehicle model based on the NASA X33 prototype. Our algorithms are based on rapidly-exploring random trees (RRTs) that incrementally explore the state space while satisfying both the global constraints imposed by obstacles and velocity bounds and differential constraints imposed by the equations of motion. The method is particularly suited for high-dimensional problems in which classical numerical approaches such as dynamic programming cannot be applied in practice. Our algorithms for trajectory design have been implemented and evaluated on several challenging examples, which are presented in the paper.
Słowa kluczowe
Czasopismo
Rocznik
Tom
Strony
167--194
Opis fizyczny
Bibliogr. 51 poz., rys., wzory
Twórcy
autor
- Dept. of Computer Science, 1304 W. Springfield Ave., University of Illinois, Urbana, IL, 61801, USA
autor
- Dept. of Aerospace Engineering and Engineering Mechanics, 2271 Howe Hall, Iowa State University, Ames, IA 50011, USA
autor
- Dept. of Computer Science, 1304 W. Springfield Ave., University of Illinois, Urbana, IL, 61801, USA
Bibliografia
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Bibliografia
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bwmeta1.element.baztech-article-BSW9-0009-1702