Remote Sensing for Agricultural Crops Based on a Low Cost Quadcopter

Authors

  • Liseth Viviana Campo Arcos Universidad del Cauca, Popayán
  • Juan Carlos Corrales Muñoz Universidad del Cauca, Popayán
  • Agapito Ledezma Espino Universidad del Cauca, Popayán

DOI:

https://doi.org/10.18046/syt.v13i34.2092

Keywords:

AR Drone, altitude control, path planner, precision agriculture, quadcopter, remote sensing.

Abstract

This paper presents a proposal for information gathering from crops by means of a low-cost quadcopter known as the AR Drone 2.0. To achieve this, we designed a system for remote sensing that addresses challenges identified in the present research, such as acquisition of aerial photographs of an entire crop and AR Drone navigation on non-planar areas arises. The project is currently at an early stage of development. The first stage describes platform and hardware/software tools used to build the proposed prototype. Second stage characterizes performance experiments of sensors stability and altitude in AR Drone, in order to design an altitude strategy control over non-flat crops. In addition, path planning algorithms based on shortest route by graphs (Dijkstra, A* and wavefront propagation) are evaluated with simulated quadcopter. The implementation of the shortest path algorithms is the beginning to full coverage of a crop. Observations of quadcopter behavior in Gazebo simulator and real tests demonstrate viability to execute the project by using AR Drone like platform of a remote sensing system to precision agriculture.

Author Biographies

  • Liseth Viviana Campo Arcos, Universidad del Cauca, Popayán

    Received an Engineering degree in engineering physics from Universidad del Cauca, Colombia, in 2012, and presently is working towards a master’s degree in telematics engineering from Universidad del Cauca, Colombia. Her current research interest is the application of quadcopters for precision agriculture.

  • Juan Carlos Corrales Muñoz, Universidad del Cauca, Popayán

    Received his Dipl-Ing and master’s degrees in telematics engineering  from the Universidad del Cauca, Colombia, in 1999 and 2004 respectively, and a Ph.D. degree in sciences, specialty computer science, from the University of Versailles Saint-Quentin-en-Yve- lines, France, in 2008. Presently, he is a full Professor and leads the Telematics Engineering Group at the Universidad del Cauca. His research interests focus on service composition and data analysis.

  • Agapito Ledezma Espino, Universidad del Cauca, Popayán

    Received an engineering degree in informatics from the Latin American University of Science and Technology (ULACIT), Panamá, in 1997, and a Ph.D. degree in sciences, specialty informatics engineering, from the University Carlos III of Madrid, Spain, in 2004. Presently, he is a full Professor and member of Control, Learning and Systems Optimization Group at the Universidad Carlos III de Madrid. His research interests focus on artificial intelligence and computational intelligence.

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Published

2015-09-30

Issue

Section

Original Research