GPS-guided mobile robot platform featuring modular design elements for agricultural applications : a thesis presented in partial fulfilment of the requirements for the degree of Masters of Engineering in Mechatronics at Massey University Turitea Campus, Palmerston North, New Zealand

The agricultural industry has not seen significant innovation in development of low-cost automated farming solutions, with current systems costing several thousands of dollars to implement. Currently these automated solutions are primarily implemented around crop planting and harvesting, and the large implementation cost of these systems makes them unfeasible for small-scale operations. Within many agricultural industries, workers expend a considerable amount of time undertaking simple tasks that are labour intensive. Many of these tasks could instead be completed using a self-driving robotic platform outfitted with the appropriate devices required for the tasks. This thesis covers the research work aiming to produce a solution that could turn an existing farming vehicle into a multipurpose low-cost agricultural platform, to act as the platform for an autonomous vehicle capable of performing pre-programmed tasks within an agricultural environment. A quad bike was selected as the vehicle platform for this research in which the control modules would control the speed and direction of this farm bike. Four modules were developed to control the vehicle components that would normally be operated by a human operator. These modules are comprised of mechanical actuators coupled with a microcontroller control system and includes some specific designs to maintain the user's ability to manually control the pre-existing systems. A gear-changing module controls the vehicles manual gearbox, providing a method to detect and control the vehicles current gear. A speed control module was developed to control the vehicles throttle and braking system and detects the vehicles speed. A steering module controls the vehicles steering system, allowing for accurate control of the vehicles direction. Finally, a vehicle controller module provides a central command interface that ties the previous three modules together and controls the vehicles electrical components and engine. Development of a low-cost differential GPS (DGPS) system was also undertaken to reduce the implementation cost of the system. Due to inconclusive results in relation to the positional accuracy of this system is was decided that a standard GPS system would be used for the vehicle prototype with further development on the DGPS system would be undertaken in future development of the research. The successful development of a farm automated vehicle platform was achieved through this research. With further improvement on software, intelligent control and the development of a low-cost differential global positioning satellite (GPS) system, a fully autonomous farm platform that can be outfitted with different tools or devices for the required farm tasks is feasible and practical

Image processing mini manual

The intent is to provide an introduction to the image processing capabilities available at the Langley Research Center (LaRC) Central Scientific Computing Complex (CSCC). Various image processing software components are described. Information is given concerning the use of these components in the Data Visualization and Animation Laboratory at LaRC

Wireless Technology for Monitoring Site-specific Landslide in Vietnam

Climate change has caused an increasing number of landslides, especially in the mountainous provinces of Vietnam, resulting in the destruction of vital transport and other infrastructure. Current monitoring and forecasting systems of the meteorology department cannot deliver accurate and reliable forecasts for weather events and issue timely warnings. This paper describes the development of a simple, low cost, and efficient system for monitoring and warning landslide in real-time. The authors focus on the use of wireless and related technologies in the implementation of a technical solution and some of the problems of the wireless sensor network (WSN) related to power consumption. Promising compressed sensing (CS) based solution for landslide monitoring is discussed and evaluated in the paper

NASA scientific and technical publications: A catalog of special publications, reference publications, conference publications, and technical papers, 1989

This catalog lists 190 citations of all NASA Special Publications, NASA Reference Publications, NASA Conference Publications, and NASA Technical Papers that were entered into the NASA scientific and technical information database during accession year 1989. The entries are grouped by subject category. Indexes of subject terms, personal authors, and NASA report numbers are provided

Multidisciplinary design and flight testing of a remote gas/particle airborne sensor system

The main objective of this paper is to describe the development of a remote sensing airborne air sampling system for Unmanned Aerial Systems (UAS) and provide the capability for the detection of particle and gas concentrations in real time over remote locations. The design of the air sampling methodology started by defining system architecture, and then by selecting and integrating each subsystem. A multifunctional air sampling instrument, with capability for simultaneous measurement of particle and gas concentrations was modified and integrated with ARCAA’s Flamingo UAS platform and communications protocols. As result of the integration process, a system capable of both real time geo-location monitoring and indexed-link sampling was obtained. Wind tunnel tests were conducted in order to evaluate the performance of the air sampling instrument in controlled nonstationary conditions at the typical operational velocities of the UAS platform. Once the remote fully operative air sampling system was obtained, the problem of mission design was analyzed through the simulation of different scenarios. Furthermore, flight tests of the complete air sampling system were then conducted to check the dynamic characteristics of the UAS with the air sampling system and to prove its capability to perform an air sampling mission following a specific flight path

AOIPS water resources data management system

A geocoded data management system applicable for hydrological applications was designed to demonstrate the utility of the Atmospheric and Oceanographic Information Processing System (AOIPS) for hydrological applications. Within that context, the geocoded hydrology data management system was designed to take advantage of the interactive capability of the AOIPS hardware. Portions of the Water Resource Data Management System which best demonstrate the interactive nature of the hydrology data management system were implemented on the AOIPS. A hydrological case study was prepared using all data supplied for the Bear River watershed located in northwest Utah, southeast Idaho, and western Wyoming

The 90 GHz radiometric imaging

A 90-GHz (3 mm wavelength) radiometer with a noise output fluctuation of 0.22 K (RMS), with a scanning antenna beam mirror, and the data processing system are described. Real-time radiometric imaging of terrain and man-made objects are shown. Flying at an altitude of 1500 ft a radiometer antenna with a 2 degrees halfpower beamwidth can distinguish landforms, waterways, roads, runways, bridges, ships at sea and their wakes, aircraft on runways, and athletic fields. A flight taken at an altitude of 3000 ft with approximately 2000 ft of clouds below the radiometer demonstrates the ability to distinguish bridges, rivers, marshland and other landforms even though the clouds are optically opaque. The radiometric images of a few representative scenes along with photographs of the corresponding scenes are presented to demonstrate the resolution of the imager system

Machine Learning with Kay

Computational power is very important when training Deep Learning (DL) models with large amounts of data (Wooldridge, 2021). Hence, High-Performance Computing (HPC) can be leveraged to reduce computational cost, and the Irish Centre for High-End Computing (ICHEC) provides significant infrastructure and services for research and development to both academia and industry. A portion of ICHEC\u27s HPC system has been allocated for institutional access, and this paper presents a case study of how to use Kay (Ireland\u27s national supercomputer) in the remote sensing domain. Specifically, this study uses clusters of Kay Graphics Processing Units (GPUs) for training DL models to extract buildings from satellite imagery using a large number of input data samples