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Data Collection Planning with Non-zero Sensing Distance for a Budget and Curvature Constrained Unmanned Aerial Vehicle

The result's identifiers

  • Result code in IS VaVaI

    <a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21230%2F19%3A00328623" target="_blank" >RIV/68407700:21230/19:00328623 - isvavai.cz</a>

  • Result on the web

    <a href="https://doi.org/10.1007/s10514-019-09844-5" target="_blank" >https://doi.org/10.1007/s10514-019-09844-5</a>

  • DOI - Digital Object Identifier

    <a href="http://dx.doi.org/10.1007/s10514-019-09844-5" target="_blank" >10.1007/s10514-019-09844-5</a>

Alternative languages

  • Result language

    angličtina

  • Original language name

    Data Collection Planning with Non-zero Sensing Distance for a Budget and Curvature Constrained Unmanned Aerial Vehicle

  • Original language description

    Data collection missions are one of the many effective use cases of Unmanned Aerial Vehicles (UAVs), where the UAV is required to visit a predefined set of target locations to retrieve data. However, the flight time of a real UAV is time constrained, and therefore only a limited number of target locations can typically be visited within the mission. In this paper, we address the data collection planning problem called the Dubins Orienteering Problem with Neighborhoods (DOPN), which sets out to determine the sequence of visits to the most rewarding subset of target locations, each with an associated reward, within a given travel budget. The objective of the DOPN is thus to maximize the sum of the rewards collected from the visited target locations using a budget constrained path between predefined starting and ending locations. The variant of the Orienteering Problem (OP) addressed here uses curvature-constrained Dubins vehicle model for planning the data collection missions for UAV. Moreover, in the DOPN, it is also assumed that the data, and thus the reward, may be collected from a close neighborhood sensing distance around the target locations, e.g., taking a snapshot by an onboard camera with a wide field of view, or using a sensor with a long range. We propose a novel approach based on the Variable Neighborhood Search (VNS) metaheuristic for the DOPN, in which combinatorial optimization of the sequence for visiting the target locations is simultaneously addressed with continuous optimization for finding Dubins vehicle waypoints inside the neighborhoods of the visited targets. The proposed VNS-based DOPN algorithm is evaluated in numerous benchmark instances, and the results show that it significantly outperforms the existing methods in both solution quality and computational time. The practical deployability of the proposed approach is experimentally verified in a data collection scenario with a real hexarotor UAV.

  • Czech name

  • Czech description

Classification

  • Type

    J<sub>imp</sub> - Article in a specialist periodical, which is included in the Web of Science database

  • CEP classification

  • OECD FORD branch

    20204 - Robotics and automatic control

Result continuities

  • Project

    Result was created during the realization of more than one project. More information in the Projects tab.

  • Continuities

    P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Others

  • Publication year

    2019

  • Confidentiality

    S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Data specific for result type

  • Name of the periodical

    Autonomous Robots

  • ISSN

    0929-5593

  • e-ISSN

    1573-7527

  • Volume of the periodical

    43

  • Issue of the periodical within the volume

    8

  • Country of publishing house

    US - UNITED STATES

  • Number of pages

    20

  • Pages from-to

    1937-1956

  • UT code for WoS article

    000487951900002

  • EID of the result in the Scopus database

    2-s2.0-85062029285