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
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Czech description
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Classification
Type
J<sub>imp</sub> - Article in a specialist periodical, which is included in the Web of Science database
CEP classification
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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