Temporal logic planning in uncertain environments with probabilistic roadmaps and belief spaces

S. Haesaert; R. Thakker; P. Nilsson; A. Agha-Mohammadi; R.M. Murray

doi:10.1109/CDC40024.2019.9029240

Temporal logic planning in uncertain environments with probabilistic roadmaps and belief spaces

S. Haesaert, R. Thakker, P. Nilsson, A. Agha-Mohammadi, R.M. Murray

Control Systems

Onderzoeksoutput: Hoofdstuk in Boek/Rapport/Congresprocedure › Conferentiebijdrage › Academic › peer review

4 Citaten (Scopus)

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Navigation problems expressed via temporal logics show promise for autonomous robot applications due to their versatility. In this paper, we introduce a method for planning with these specifications in uncertain environments that yields guaranteed satisfaction probabilities. We show that point-based value iteration can be combined with probabilistic roadmaps to solve this planning problem over the belief space of the uncertain environment.

Originele taal-2	Engels
Titel	2019 IEEE 58th Conference on Decision and Control, CDC 2019
Uitgeverij	Institute of Electrical and Electronics Engineers
Pagina's	6282-6287
Aantal pagina's	6
ISBN van elektronische versie	978-1-7281-1398-2
DOI's	https://doi.org/10.1109/CDC40024.2019.9029240
Status	Gepubliceerd - dec. 2019
Evenement	2019 IEEE 58th Conference on Decision and Control (CDC) - Nice, France, Nice, Frankrijk Duur: 11 dec. 2019 → 13 dec. 2019 Congresnummer: 58 https://cdc2019.ieeecss.org/

Congres

Congres	2019 IEEE 58th Conference on Decision and Control (CDC)
Verkorte titel	CDC 2019
Land/Regio	Frankrijk
Stad	Nice
Periode	11/12/19 → 13/12/19
Internet adres	https://cdc2019.ieeecss.org/

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Haesaert, S., Thakker, R., Nilsson, P., Agha-Mohammadi, A., & Murray, R. M. (2019). Temporal logic planning in uncertain environments with probabilistic roadmaps and belief spaces. In 2019 IEEE 58th Conference on Decision and Control, CDC 2019 (blz. 6282-6287). Artikel 9029240 Institute of Electrical and Electronics Engineers. https://doi.org/10.1109/CDC40024.2019.9029240

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title = "Temporal logic planning in uncertain environments with probabilistic roadmaps and belief spaces",

abstract = "Navigation problems expressed via temporal logics show promise for autonomous robot applications due to their versatility. In this paper, we introduce a method for planning with these specifications in uncertain environments that yields guaranteed satisfaction probabilities. We show that point-based value iteration can be combined with probabilistic roadmaps to solve this planning problem over the belief space of the uncertain environment.",

author = "S. Haesaert and R. Thakker and P. Nilsson and A. Agha-Mohammadi and R.M. Murray",

year = "2019",

month = dec,

doi = "10.1109/CDC40024.2019.9029240",

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pages = "6282--6287",

booktitle = "2019 IEEE 58th Conference on Decision and Control, CDC 2019",

publisher = "Institute of Electrical and Electronics Engineers",

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note = "58th IEEE Conference on Decision and Control, CDC 2019, CDC 2019 ; Conference date: 11-12-2019 Through 13-12-2019",

url = "https://cdc2019.ieeecss.org/",

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Haesaert, S, Thakker, R, Nilsson, P, Agha-Mohammadi, A & Murray, RM 2019, Temporal logic planning in uncertain environments with probabilistic roadmaps and belief spaces. in 2019 IEEE 58th Conference on Decision and Control, CDC 2019., 9029240, Institute of Electrical and Electronics Engineers, blz. 6282-6287, 2019 IEEE 58th Conference on Decision and Control (CDC), Nice, Frankrijk, 11/12/19. https://doi.org/10.1109/CDC40024.2019.9029240

Temporal logic planning in uncertain environments with probabilistic roadmaps and belief spaces. / Haesaert, S.; Thakker, R.; Nilsson, P. et al.
2019 IEEE 58th Conference on Decision and Control, CDC 2019. Institute of Electrical and Electronics Engineers, 2019. blz. 6282-6287 9029240.

Onderzoeksoutput: Hoofdstuk in Boek/Rapport/Congresprocedure › Conferentiebijdrage › Academic › peer review

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AU - Agha-Mohammadi, A.

AU - Murray, R.M.

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AB - Navigation problems expressed via temporal logics show promise for autonomous robot applications due to their versatility. In this paper, we introduce a method for planning with these specifications in uncertain environments that yields guaranteed satisfaction probabilities. We show that point-based value iteration can be combined with probabilistic roadmaps to solve this planning problem over the belief space of the uncertain environment.

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Temporal logic planning in uncertain environments with probabilistic roadmaps and belief spaces

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