Proceedings of the 2017 2nd International Conference on Electrical, Control and Automation Engineering (ECAE 2017)

A Precision Spraying Mission Assignment and Path Planning Performed by Multi-Quadcopters

Authors
Baihui Du
Corresponding Author
Baihui Du
Available Online December 2017.
DOI
10.2991/ecae-17.2018.49How to use a DOI?
Keywords
precision spraying; mission assignment; path planning; multi-quadcopters; Travelling Salesman Problem (TSP)
Abstract

This paper proposes a hierarchal approach to solving a spraying mission assignment and path planning problem by using multi-quadcopters in an upland area. A mathematical model of the mission assignment and path-planning problem has been established. An inner-and-outer loop structure is employed in the hierarchal approach, in which the inner loop utilizes a genetic algorithm-based Travelling Salesman Problem (TSP) method while the outer loop uses a nonlinear programming method based on the optimal results given by the inner loop. In the end, simulation comparisons to a multi-TSP-based conventional approach have been carried out to illustrate the performance of the proposed approach.

Copyright
© 2018, the Authors. Published by Atlantis Press.
Open Access
This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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Volume Title
Proceedings of the 2017 2nd International Conference on Electrical, Control and Automation Engineering (ECAE 2017)
Series
Advances in Engineering Research
Publication Date
December 2017
ISBN
10.2991/ecae-17.2018.49
ISSN
2352-5401
DOI
10.2991/ecae-17.2018.49How to use a DOI?
Copyright
© 2018, the Authors. Published by Atlantis Press.
Open Access
This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

Cite this article

TY  - CONF
AU  - Baihui Du
PY  - 2017/12
DA  - 2017/12
TI  - A Precision Spraying Mission Assignment and Path Planning Performed by Multi-Quadcopters
BT  - Proceedings of the 2017 2nd International Conference on Electrical, Control and Automation Engineering (ECAE 2017)
PB  - Atlantis Press
SP  - 233
EP  - 237
SN  - 2352-5401
UR  - https://doi.org/10.2991/ecae-17.2018.49
DO  - 10.2991/ecae-17.2018.49
ID  - Du2017/12
ER  -