Trajectory planning for robotic maintenance of pasture based on approximation algorithms

Cariou, Christophe; Gobor, Zoltan

doi:10.1016/j.biosystemseng.2018.07.009

Cited by 5 publications

(2 citation statements)

References 13 publications

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“…From an initial population, new generations are successively created with some mutations. The principle of the algorithm proposed in this paper is depicted in Figure 11 and inspired from [ 38 ]. The algorithm starts with the creation of a population of one hundred routes of the UAV, randomly chosen and passing above all the buried sensor nodes (waypoints).…”

Section: Materials and Methodsmentioning

confidence: 99%

Data Collection from Buried Sensor Nodes by Means of an Unmanned Aerial Vehicle

Cariou

Moiroux-Arvis

Pinet

et al. 2022

Sensors

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The development of Wireless Underground Sensor Networks (WUSNs) is a recent research axis based on sensor nodes buried a few dozen centimeters deep. The communication ranges are, however, highly reduced due to the high attenuation of electromagnetic waves in soil, leading to issues of data collection. This paper proposes to embed a data collector on an Unmanned Aerial Vehicle (UAV) coming close to each buried sensor node. The whole system was developed (sensor nodes, data collector, gateway) and experimentations were carried out in real conditions. In hovering mode, the measurements on the RSSI levels with respect to the position of the UAV highlight the interest in maintaining a high altitude when the UAV is far from the node. In dynamic mode, the experimental results demonstrate the feasibility of carrying out the data collection task while the UAV is moving. The speed of the UAV has, however, to be adapted to the required time to collect the data. In the case of numerous buried sensor nodes, evolutionary algorithms are implemented to plan the trajectory of the UAV optimally. To the best of our knowledge, this paper is the first one that reports experiment results combining WUSN and UAV technologies.

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Section: Materials and Methodsmentioning

confidence: 99%

Data Collection from Buried Sensor Nodes by Means of an Unmanned Aerial Vehicle

Cariou

Moiroux-Arvis

Pinet

et al. 2022

Sensors

Self Cite

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“…Except for using dedicated robotic platforms, several studies elaborated path planning software tools, integrated into simulation and emulation modelling efforts, that could provide guidance to real-world vehicles [39,40,48]. Finally, several studies utilized 2D simulation methods for path planning of autonomous vehicles in field operations [24,25,29,50,56,63].…”

Section: Cyber Space: Simulation and Emulation Modellingmentioning

confidence: 99%

AgROS: A Robot Operating System Based Emulation Tool for Agricultural Robotics

2019

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This research aims to develop a farm management emulation tool that enables agrifood producers to effectively introduce advanced digital technologies, like intelligent and autonomous unmanned ground vehicles (UGVs), in real-world field operations. To that end, we first provide a critical taxonomy of studies investigating agricultural robotic systems with regard to: (i) the analysis approach, i.e., simulation, emulation, real-world implementation; (ii) farming operations; and (iii) the farming type. Our analysis demonstrates that simulation and emulation modelling have been extensively applied to study advanced agricultural machinery while the majority of the extant research efforts focuses on harvesting/picking/mowing and fertilizing/spraying activities; most studies consider a generic agricultural layout. Thereafter, we developed AgROS, an emulation tool based on the Robot Operating System, which could be used for assessing the efficiency of real-world robot systems in customized fields. The AgROS allows farmers to select their actual field from a map layout, import the landscape of the field, add characteristics of the actual agricultural layout (e.g., trees, static objects), select an agricultural robot from a predefined list of commercial systems, import the selected UGV into the emulation environment, and test the robot’s performance in a quasi-real-world environment. AgROS supports farmers in the ex-ante analysis and performance evaluation of robotized precision farming operations while lays the foundations for realizing “digital twins” in agriculture.

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