### Abstract

This paper describes a finite-horizon receding horizon trajectory optimization scheme which uses an approximation of the value function to provide cost-to-go (CTG) and associated state information. The value function approximation is computed using a finite-state, motion primitive automaton approximation of the vehicle dynamics. Using an actual value function approximation instead of heuristic CTG allows a tighter integration between the planning and control layers needed for vehicles operating in challenging spatial environments. It also enables a more rigorous use of the receding horizon control framework for autonomous control applications. The paper describes the finite-state value function approximation and its integration into the receding horizon scheme. Simulation examples illustrate the scheme's capabilities and highlight interesting open issues that will need to be addressed to take full advantage of the approach.

Original language | English (US) |
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Title of host publication | 2008 American Control Conference, ACC |

Pages | 3810-3816 |

Number of pages | 7 |

DOIs | |

State | Published - Sep 30 2008 |

Event | 2008 American Control Conference, ACC - Seattle, WA, United States Duration: Jun 11 2008 → Jun 13 2008 |

### Publication series

Name | Proceedings of the American Control Conference |
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ISSN (Print) | 0743-1619 |

### Other

Other | 2008 American Control Conference, ACC |
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Country | United States |

City | Seattle, WA |

Period | 6/11/08 → 6/13/08 |

### Fingerprint

### Cite this

*2008 American Control Conference, ACC*(pp. 3810-3816). [4587087] (Proceedings of the American Control Conference). https://doi.org/10.1109/ACC.2008.4587087

**Receding horizon trajectory optimization with a finite-state value function approximation.** / Mettler May, Berenice F; Kong, Zhaodan.

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

*2008 American Control Conference, ACC.*, 4587087, Proceedings of the American Control Conference, pp. 3810-3816, 2008 American Control Conference, ACC, Seattle, WA, United States, 6/11/08. https://doi.org/10.1109/ACC.2008.4587087

}

TY - GEN

T1 - Receding horizon trajectory optimization with a finite-state value function approximation

AU - Mettler May, Berenice F

AU - Kong, Zhaodan

PY - 2008/9/30

Y1 - 2008/9/30

N2 - This paper describes a finite-horizon receding horizon trajectory optimization scheme which uses an approximation of the value function to provide cost-to-go (CTG) and associated state information. The value function approximation is computed using a finite-state, motion primitive automaton approximation of the vehicle dynamics. Using an actual value function approximation instead of heuristic CTG allows a tighter integration between the planning and control layers needed for vehicles operating in challenging spatial environments. It also enables a more rigorous use of the receding horizon control framework for autonomous control applications. The paper describes the finite-state value function approximation and its integration into the receding horizon scheme. Simulation examples illustrate the scheme's capabilities and highlight interesting open issues that will need to be addressed to take full advantage of the approach.

AB - This paper describes a finite-horizon receding horizon trajectory optimization scheme which uses an approximation of the value function to provide cost-to-go (CTG) and associated state information. The value function approximation is computed using a finite-state, motion primitive automaton approximation of the vehicle dynamics. Using an actual value function approximation instead of heuristic CTG allows a tighter integration between the planning and control layers needed for vehicles operating in challenging spatial environments. It also enables a more rigorous use of the receding horizon control framework for autonomous control applications. The paper describes the finite-state value function approximation and its integration into the receding horizon scheme. Simulation examples illustrate the scheme's capabilities and highlight interesting open issues that will need to be addressed to take full advantage of the approach.

UR - http://www.scopus.com/inward/record.url?scp=52449129557&partnerID=8YFLogxK

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U2 - 10.1109/ACC.2008.4587087

DO - 10.1109/ACC.2008.4587087

M3 - Conference contribution

AN - SCOPUS:52449129557

SN - 9781424420797

T3 - Proceedings of the American Control Conference

SP - 3810

EP - 3816

BT - 2008 American Control Conference, ACC

ER -