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3D Scenery Construction of Agricultural Environments for Robotics Awareness

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Information and Communication Technologies for Agriculture—Theme III: Decision

Part of the book series: Springer Optimization and Its Applications ((SOIA,volume 184))

Abstract

Depth cameras started to gain popularity in agricultural applications during the last years. This type of cameras has been implemented mainly for three-dimensional (3D) reconstruction of objects in indoor or outdoor sceneries. The use of such cameras in the construction of 3D models for simulation purposes of complex structures that are usually met in nature, such as trees and other plants, is a great challenge. Remarkably, agricultural environments are extremely complex. Thus, the proper setup and implementation of such technologies is particularly important in order to attain useable data. So far, the depth information collected using these cameras varies among different objects’ structure and sensing conditions due to the uncertainty of the outdoor environment. The use of a specific methodology using color and depth images gives the opportunity to extract geometrical characteristics information about point clouds of the targeted objects. This chapter explores the different technologies used by depth cameras and presents several applications concerning indoor and outdoor environments by presenting indicative scenarios for agricultural applications. Towards that direction, a 3D reconstruction of trees was established producing point clouds from Red Green Blue Depth (RGB-D) images acquired in real field conditions. The point cloud samples of trees were collected using an unmanned ground vehicle (UGV) and imported in Gazebo in order to visualize a simulation of the environment. This simulation technique can be used for testing and evaluating the navigation of robotic systems. By further analyzing the resulted 3D point clouds, various geometrical measurements of the simulated samples, such as the volume or the height of tree canopies, can be calculated. Possible weaknesses of this procedure are mainly attributed to the camera’s limitations and the sampling parameters. However, results show that it is possible to establish a suitable simulation environment to implement it in several agricultural applications by utilizing automated unmanned robotic platforms.

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Authors and Affiliations

  1. Institute for Bio-Economy and Agri-Technology (IBO), Centre for Research and Technology Hellas (CERTH), Thessaloniki, Greece

    Aristotelis Christos Tagarakis, Damianos Kalaitzidis, Evangelia Filippou, Lefteris Benos & Dionysis Bochtis

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  1. Aristotelis Christos Tagarakis
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  2. Damianos Kalaitzidis
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Correspondence to Aristotelis Christos Tagarakis .

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Editors and Affiliations

  1. Institute for Bio-Economy and Agri-Technology (iBO), Centre for Research and Technology Hellas (CERTH), Thessaloniki, Greece

    Dionysis D. Bochtis

  2. Department of Electrical and Computer Engineering, University of Aarhus, Aarhus N, Denmark

    Claus Grøn Sørensen

  3. Department of Resources Management and Agricultural Engineering, Agricultural University of Athens, Athens, Greece

    Spyros Fountas

  4. Institute for Bio-Economy and Agri-Technology (iBO), Centre for Research and Technology Hellas (CERTH), Thessaloniki, Greece

    Vasileios Moysiadis

  5. Department of Industrial and Systems Engineering, University of Florida, Gainesville, FL, USA

    Panos M. Pardalos

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Tagarakis, A.C., Kalaitzidis, D., Filippou, E., Benos, L., Bochtis, D. (2022). 3D Scenery Construction of Agricultural Environments for Robotics Awareness. In: Bochtis, D.D., Sørensen, C.G., Fountas, S., Moysiadis, V., Pardalos, P.M. (eds) Information and Communication Technologies for Agriculture—Theme III: Decision. Springer Optimization and Its Applications, vol 184. Springer, Cham. https://doi.org/10.1007/978-3-030-84152-2_6

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