Precision RTK GNSS for low-cost robotic systems

Castles, Simon (2021) Precision RTK GNSS for low-cost robotic systems. [USQ Project]

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CASTLES Simon dissertation_redacted.pdf

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The agriculture industry has been under increasing pressure to do more with less; increase efficiency and productivity while minimising cost and environmental impacts. Advanced technology has become an essential part of farming and with improvements in GNSS, robotics and geospatial software, so has the potential for improving accuracy and control of farming practices.

Real-time kinematic (RTK) GNSS offers centimetre level accuracy using a base station situated at a known location providing correction data to one or more rover stations within a 10 km range. In agronomy, RTK GNSS enables more sustainable and profitable management practices, such as tractor guidance, and more recently precision application of herbicides. However, the capital investment in establishing an RTK network to gain precise localisation benefits often erode the profitability of the system when compared to a less accurate, cheaper system with reduced benefits. The aim of this project is to design a low cost RTK GNSS sub-system for an autonomous robotic system and evaluate the accuracy of the system in an agricultural setting.

A system was designed and built using ArduSimple RTK receiver boards (based on the Ublox ZED-F9P receiver module), Xbee radio modules and an STM32 microcontroller to provide both position and heading data. To verify the accuracy of the designed system, a testing procedure based on ISO 12188-1 was developed, which involved the design and production of a drive system on a non-metallic track so that the actual path traversed could be accurately recorded. The data from the RTK receiver was then analysed to calculate cross-track error and therefore the accuracy of the system, finding that centimetre level accuracy is achievable with low-cost receivers, with the system estimated to have a relative cross-track accuracy of 12.13 mm and a heading accuracy of 0.45°.

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Item Type: USQ Project
Item Status: Live Archive
Faculty/School / Institute/Centre: Historic - Faculty of Health, Engineering and Sciences - School of Mechanical and Electrical Engineering (1 Jul 2013 - 31 Dec 2021)
Supervisors: Lobsey, Craig
Qualification: Bachelor of Engineering (Mechatronics)
Date Deposited: 02 Jan 2023 23:50
Last Modified: 26 Jun 2023 00:10
Uncontrolled Keywords: Precision agriculture, robotics, localisation, GNSS, RTK, accuracy

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