Package Delivery Experiments with a Camera Drone

Publikation: KonferenzbeitragPaperForschungBegutachtung

Abstract

The undergoing efforts for the integration of robotics into logistics systems is affecting the production workflow at all stages, from the transportation and the handling of parts inside storage and production facilities to the final product distribution. In this paper we address the problem of delivering a package by means of a multirotor drone. We describe a fully autonomous package delivery flight demonstration prepared in collaboration with an industrial partner. All computations are performed in real-time on-board the drone. A gimbal camera is utilized to realize the vision-based localization, by means of fiducial markers, of the delivery position and the landing platform on a pickup truck. The demonstration consists of the fully autonomous execution of the following tasks: the drone takes-off from the truck, looks for the delivery position, proceeds to land and drop the package, flies back to the distribution truck and follows it, and the flight is finished by performing the landing on the static vehicle. The experiments focus on the performance of the vision-based truck following.
Originalspracheenglisch
PublikationsstatusVeröffentlicht - 12 Mai 2017
VeranstaltungAustrian Robotics Workshop 2017 - Palais Eschenbach, 1010 , Vienna, Österreich
Dauer: 10 Mai 201712 Mai 2017
http://roboticsworkshop.at/

Konferenz

KonferenzAustrian Robotics Workshop 2017
KurztitelARW2017
LandÖsterreich
OrtVienna
Zeitraum10/05/1712/05/17
Internetadresse

Fingerprint

Trucks
Cameras
Landing
Demonstrations
Experiments
Pickups
Takeoff
Logistics
Robotics
Drones

Schlagwörter

    Fields of Expertise

    • Information, Communication & Computing

    Dies zitieren

    Pestana Puerta, J., Maurer, M., Muschick, D., Adlakha, D., Bischof, H., & Fraundorfer, F. (2017). Package Delivery Experiments with a Camera Drone. Beitrag in Austrian Robotics Workshop 2017, Vienna, Österreich.

    Package Delivery Experiments with a Camera Drone. / Pestana Puerta, Jesus; Maurer, Michael; Muschick, Daniel; Adlakha, Devesh; Bischof, Horst; Fraundorfer, Friedrich.

    2017. Beitrag in Austrian Robotics Workshop 2017, Vienna, Österreich.

    Publikation: KonferenzbeitragPaperForschungBegutachtung

    Pestana Puerta, J, Maurer, M, Muschick, D, Adlakha, D, Bischof, H & Fraundorfer, F 2017, 'Package Delivery Experiments with a Camera Drone' Beitrag in, Vienna, Österreich, 10/05/17 - 12/05/17, .
    Pestana Puerta J, Maurer M, Muschick D, Adlakha D, Bischof H, Fraundorfer F. Package Delivery Experiments with a Camera Drone. 2017. Beitrag in Austrian Robotics Workshop 2017, Vienna, Österreich.
    Pestana Puerta, Jesus ; Maurer, Michael ; Muschick, Daniel ; Adlakha, Devesh ; Bischof, Horst ; Fraundorfer, Friedrich. / Package Delivery Experiments with a Camera Drone. Beitrag in Austrian Robotics Workshop 2017, Vienna, Österreich.
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    AU - Adlakha, Devesh

    AU - Bischof, Horst

    AU - Fraundorfer, Friedrich

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    AB - The undergoing efforts for the integration of robotics into logistics systems is affecting the production workflow at all stages, from the transportation and the handling of parts inside storage and production facilities to the final product distribution. In this paper we address the problem of delivering a package by means of a multirotor drone. We describe a fully autonomous package delivery flight demonstration prepared in collaboration with an industrial partner. All computations are performed in real-time on-board the drone. A gimbal camera is utilized to realize the vision-based localization, by means of fiducial markers, of the delivery position and the landing platform on a pickup truck. The demonstration consists of the fully autonomous execution of the following tasks: the drone takes-off from the truck, looks for the delivery position, proceeds to land and drop the package, flies back to the distribution truck and follows it, and the flight is finished by performing the landing on the static vehicle. The experiments focus on the performance of the vision-based truck following.

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