Learning optimal guidance behavior in unknown environments within receding horizon planning

Abhishek Verma, Berenice F Mettler May

Research output: Chapter in Book/Report/Conference proceedingConference contribution

1 Citation (Scopus)

Abstract

Aerospace Engineering and Mechanics, University of Minnesota Minneapolis, Minnesota, USA This paper describes a guidance algorithm for autonomous operation in partially known environments. The emphasis of the paper is enabling learning within a receding horizon trajectory optimization framework. The information acquired from an exteroceptive sensor is assimilated into a spatial value function. This setup has the advantage that the system learns information directly relevant to optimal guidance and control behavior and enables efficient trajectory-planning in unknown or partially known environments. The system's performance is demonstrated using successive runs in high-fidelity indoor simulations.

Original languageEnglish (US)
Title of host publication70th American Helicopter Society International Annual Forum 2014
PublisherAmerican Helicopter Society
Pages2158-2168
Number of pages11
ISBN (Print)9781632666918
StatePublished - Jan 1 2014
Event70th American Helicopter Society International Annual Forum 2014 - Montreal, QC, Canada
Duration: May 20 2014May 22 2014

Publication series

NameAnnual Forum Proceedings - AHS International
Volume3
ISSN (Print)1552-2938

Other

Other70th American Helicopter Society International Annual Forum 2014
CountryCanada
CityMontreal, QC
Period5/20/145/22/14

Fingerprint

Trajectories
Planning
Aerospace engineering
Mechanics
Information systems
Sensors

Cite this

Verma, A., & Mettler May, B. F. (2014). Learning optimal guidance behavior in unknown environments within receding horizon planning. In 70th American Helicopter Society International Annual Forum 2014 (pp. 2158-2168). (Annual Forum Proceedings - AHS International; Vol. 3). American Helicopter Society.

Learning optimal guidance behavior in unknown environments within receding horizon planning. / Verma, Abhishek; Mettler May, Berenice F.

70th American Helicopter Society International Annual Forum 2014. American Helicopter Society, 2014. p. 2158-2168 (Annual Forum Proceedings - AHS International; Vol. 3).

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Verma, A & Mettler May, BF 2014, Learning optimal guidance behavior in unknown environments within receding horizon planning. in 70th American Helicopter Society International Annual Forum 2014. Annual Forum Proceedings - AHS International, vol. 3, American Helicopter Society, pp. 2158-2168, 70th American Helicopter Society International Annual Forum 2014, Montreal, QC, Canada, 5/20/14.
Verma A, Mettler May BF. Learning optimal guidance behavior in unknown environments within receding horizon planning. In 70th American Helicopter Society International Annual Forum 2014. American Helicopter Society. 2014. p. 2158-2168. (Annual Forum Proceedings - AHS International).
Verma, Abhishek ; Mettler May, Berenice F. / Learning optimal guidance behavior in unknown environments within receding horizon planning. 70th American Helicopter Society International Annual Forum 2014. American Helicopter Society, 2014. pp. 2158-2168 (Annual Forum Proceedings - AHS International).
@inproceedings{ab283fe10bcd44e5bfcdde60615d4f8e,
title = "Learning optimal guidance behavior in unknown environments within receding horizon planning",
abstract = "Aerospace Engineering and Mechanics, University of Minnesota Minneapolis, Minnesota, USA This paper describes a guidance algorithm for autonomous operation in partially known environments. The emphasis of the paper is enabling learning within a receding horizon trajectory optimization framework. The information acquired from an exteroceptive sensor is assimilated into a spatial value function. This setup has the advantage that the system learns information directly relevant to optimal guidance and control behavior and enables efficient trajectory-planning in unknown or partially known environments. The system's performance is demonstrated using successive runs in high-fidelity indoor simulations.",
author = "Abhishek Verma and {Mettler May}, {Berenice F}",
year = "2014",
month = "1",
day = "1",
language = "English (US)",
isbn = "9781632666918",
series = "Annual Forum Proceedings - AHS International",
publisher = "American Helicopter Society",
pages = "2158--2168",
booktitle = "70th American Helicopter Society International Annual Forum 2014",
address = "United States",

}

TY - GEN

T1 - Learning optimal guidance behavior in unknown environments within receding horizon planning

AU - Verma, Abhishek

AU - Mettler May, Berenice F

PY - 2014/1/1

Y1 - 2014/1/1

N2 - Aerospace Engineering and Mechanics, University of Minnesota Minneapolis, Minnesota, USA This paper describes a guidance algorithm for autonomous operation in partially known environments. The emphasis of the paper is enabling learning within a receding horizon trajectory optimization framework. The information acquired from an exteroceptive sensor is assimilated into a spatial value function. This setup has the advantage that the system learns information directly relevant to optimal guidance and control behavior and enables efficient trajectory-planning in unknown or partially known environments. The system's performance is demonstrated using successive runs in high-fidelity indoor simulations.

AB - Aerospace Engineering and Mechanics, University of Minnesota Minneapolis, Minnesota, USA This paper describes a guidance algorithm for autonomous operation in partially known environments. The emphasis of the paper is enabling learning within a receding horizon trajectory optimization framework. The information acquired from an exteroceptive sensor is assimilated into a spatial value function. This setup has the advantage that the system learns information directly relevant to optimal guidance and control behavior and enables efficient trajectory-planning in unknown or partially known environments. The system's performance is demonstrated using successive runs in high-fidelity indoor simulations.

UR - http://www.scopus.com/inward/record.url?scp=84906673974&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=84906673974&partnerID=8YFLogxK

M3 - Conference contribution

AN - SCOPUS:84906673974

SN - 9781632666918

T3 - Annual Forum Proceedings - AHS International

SP - 2158

EP - 2168

BT - 70th American Helicopter Society International Annual Forum 2014

PB - American Helicopter Society

ER -