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  A Pilot Intent Estimator for Haptic Support Systems in Helicopter Maneuvering Tasks

D'Intino, G., Olivari, M., Geluardi, S., Fabbroni, D., Bülthoff, H., & Pollini, L. (2018). A Pilot Intent Estimator for Haptic Support Systems in Helicopter Maneuvering Tasks. In 2018 AIAA Modeling and Simulation Technologies Conference (pp. 132-140). Red Hook, NY, USA: Curran.

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Item Permalink: http://hdl.handle.net/21.11116/0000-0001-7D60-7 Version Permalink: http://hdl.handle.net/21.11116/0000-0001-8119-1
Genre: Conference Paper

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D'Intino, G1, 2, 3, Author              
Olivari, M1, 2, 3, 4, Author              
Geluardi, S1, 2, 3, Author              
Fabbroni, D1, 3, Author              
Bülthoff, HH1, 2, 3, Author              
Pollini, L, Author
Affiliations:
1Department Human Perception, Cognition and Action, Max Planck Institute for Biological Cybernetics, Max Planck Society, ou_1497797              
2Project group: Cybernetics Approach to Perception & Action, Max Planck Institute for Biological Cybernetics, Max Planck Society, ou_2528701              
3Max Planck Institute for Biological Cybernetics, Max Planck Society, ou_1497794              
4Project group: Motion Perception & Simulation, Max Planck Institute for Biological Cybernetics, Max Planck Society, ou_2528705              

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 Abstract: Haptic support systems are commonly designed as feedback systems that track a known trajectory. However, when a pilot performs a maneuver in a free airspace, the desired trajectory is not known a priori. Thus, an estimation of the pilot intended trajectory is needed. This paper investigates the estimation of the pilot desired trajectory for designing a haptic support system that helps pilots perform helicopter maneuvers in a free airspace. A probabilistic algorithm is implemented to estimate the pilot intended trajectory according to the actions made on the control devices. The haptic aid is developed as a feedback controller able to follow the estimated intended trajectory. Two simulations were conducted to test the effectiveness of the proposed algorithm. First, filtered step-wise pilot control inputs were considered. Then, real pilot inputs were employed, which were recorded in a lateral reposition maneuver performed on a motion simulator. The developed algorithm was able to recognize the intended path according to the given pilot inputs in both scenarios.

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 Dates: 2018-01
 Publication Status: Published in print
 Pages: -
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 Rev. Method: -
 Identifiers: DOI: 10.2514/6.2018-0116
BibTex Citekey: D039IntinoOGFBP2018
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Title: AIAA Modeling and Simulation Technologies Conference: Held at the AIAA SciTech Forum 2018
Place of Event: Kissimmee, FL, USA
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Title: 2018 AIAA Modeling and Simulation Technologies Conference
Source Genre: Proceedings
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Publ. Info: Red Hook, NY, USA : Curran
Pages: - Volume / Issue: - Sequence Number: - Start / End Page: 132 - 140 Identifier: ISBN: 978-1-5108-5710-0