Autonomous field navigation, data acquisition and node location in wireless sensor networks

Autonomous field navigation, data acquisition and node location in wireless sensor networks To overcome the limited transmission range of spatially separated nodes of a wireless sensor network (WSN), a small 4-wheel autonomous robot assembled the data from nodes distributed in a vineyard. First, the robot followed a predefined way-point route between the grapevine rows, in order to evaluate the sensor node locations by their received signal strength indication (RSSI). Then, the recorded and geo-referenced RSSI data were analysed and mapped. By using the evaluated node positions, an optimised second route was generated. While navigating, a laser scanner was used for obstacle detection and avoidance. Path planning with known positions of the nodes reduced the driving time by 15 times compared with the first run, because the hybrid control system used was capable of navigating within the plantation even perpendicular to the row structures. For locating the nodes, results based on trilateration were compared with the values of an attached differential global navigation satellite system (DGNSS). The results showed that it is possible to locate and geo-reference the sensor nodes with a robot, even without any prior knowledge about their absolute position. The best achieved location showed a deviation with DGNSS of 1.2 m and with RSSI trilateration of 0.6 m compared to the actual position. Precision Agriculture Springer Journals

Autonomous field navigation, data acquisition and node location in wireless sensor networks

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Springer US
Copyright © 2016 by Springer Science+Business Media New York
Life Sciences; Agriculture; Soil Science & Conservation; Remote Sensing/Photogrammetry; Statistics for Engineering, Physics, Computer Science, Chemistry and Earth Sciences; Atmospheric Sciences
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