A Kalman Filter Implementation for Precision Improvement in Low-Cost GPS Positioning of Tractors

Low-cost GPS receivers provide geodetic positioning information using the NMEA protocol, usually with eight digits for latitude and nine digits for longitude. When these geodetic coordinates are converted into Cartesian coordinates, the positions fit in a quantization grid of some decimeters in size, the dimensions of which vary depending on the point of the terrestrial surface. The aim of this study is to reduce the quantization errors of some low-cost GPS receivers by using a Kalman filter. Kinematic tractor model equations were employed to particularize the filter, which was tuned by applying Monte Carlo techniques to eighteen straight trajectories, to select the covariance matrices that produced the lowest Root Mean Square Error in these trajectories. Filter performance was tested by using straight tractor paths, which were either simulated or real trajectories acquired by a GPS receiver. The results show that the filter can reduce the quantization error in distance by around 43%. Moreover, it reduces the standard deviation of the heading by 75%. Data suggest that the proposed filter can satisfactorily preprocess the low-cost GPS receiver data when used in an assistance guidance GPS system for tractors. It could also be useful to smooth tractor GPS trajectories that are sharpened when the tractor moves over rough terrain

Trolls: a novel low-cost controlling system platform for walk-behind tractor

A novel low-cost controlling system platform for walk-behind hand tractors (Quick G3000 and G1000) was designed and developed to solve the fatigue problem faced by farmers when ploughing the rice field. This platform is dedicated to designing and manufacturing mechanical, electrical, and software components. The tractor was modified and added with an embedded control system that functioned as the slave, while the direction of the tractor movement was controlled remotely by humans through Bluetooth communication with the smartphone application as the master. Several servos and direct currents (DCs) were used as the actuator to move some levers and clutches instead of the tractor to make it remotely controllable. This system has been directly tested in the paddy farming land through two tractors: Quick G3000 and G1000. The testing results showed that this system could be used within more or less six hours; there is a cost-efficiency of 21.74% and 84.62% battery usage efficiency. More efficient mechanics caused this cost efficiency, and the reduction in electronic devices affects battery efficiency. A low-cost platform for controlling walk-behind tractors has been successfully developed; this platform assists farmers in ploughing their fields

Design of a Low-cost GPS/magnetometer System for Land-based Navigation: Integration and Autocalibration Algorithms

The land-based navigation, paying attention to precision farming, is the research topic: the final purpose is the design and development of a guidance-aided system focusing on a low-cost GPS receiver able to provide a pseudorange-based solution only. Specific tests have been carried out to reproduce the trajectories followed by the vehicle in agricultural applications, whose accuracy target is typically 1 m. Results show that the investigated low-cost receiver is affected by a drift in time which is mainly detected while turning and causing a deviation from the optimal reference solution. Thus, the goal is to correct this behavior because the deviation accumulates during time and causes a not optimal treatment of the field (waste of material and money). Paying attention to the cost of the system, a new idea is proposed: the integration between the low-cost GPS with a magnetometer/digital compass. A dedicated algorithm has been also implemented, taking the heading provided by th e magnetometer and using it to correct the deviation in turns. Unluckily a magnetometer is deeply influenced by ferrous materials and the sensor is supposed to be installed on the vehicle, which is mainly made by metal. As a consequence, the sensed measurements are affected by a deviation from the actual magnetic field. Those disturbances need to be properly reduced by an autocalibration procedure. A new approach for the autocalibration problem has been developed and implemented; then the comparison with respect to the traditional method has been also performed in order to test and validate the new idea. A comprehensive and detailed description of all the algorithms will be produced concerning both the sensors integration (GPS and magnetometer) along with the magnetometer autocalibration. Particular attention will be focused on results and performances of the autocalibration procedure, which appears to provide very interesting results. The new approach, which is simply based on the covariance matrix, appears to be more successful than the traditional one. Several tests have been analyzed: the stand-alone low-cost GPS provides solutions which are not acceptable for precision farming applications, while the integration with a magnetometer slightly increases the accuracy. Furthermore, the innovation of the research is connected to the autocalibration algorithm itself. The final goal was the design of a low-cost system for supporting the guidance in land-based navigation; improvements are still required but the goal is close to be achieved

Where Am I? SLAM for Mobile Machines on a Smart Working Site

The current optimization approaches of construction machinery are mainly based on internal sensors. However, the decision of a reasonable strategy is not only determined by its intrinsic signals, but also very strongly by environmental information, especially the terrain. Due to the dynamic changing of the construction site and the consequent absence of a high definition map, the Simultaneous Localization and Mapping (SLAM) offering the terrain information for construction machines is still challenging. Current SLAM technologies proposed for mobile machines are strongly dependent on costly or computationally expensive sensors, such as RTK GPS and cameras, so that commercial use is rare. In this study, we proposed an affordable SLAM method to create a multi-layer grid map for the construction site so that the machine can have the environmental information and be optimized accordingly. Concretely, after the machine passes by the grid, we can obtain the local information and record it. Combining with positioning technology, we then create a map of the interesting places of the construction site. As a result of our research gathered from Gazebo, we showed that a suitable layout is the combination of one IMU and two differential GPS antennas using the unscented Kalman filter, which keeps the average distance error lower than 2m and the mapping error lower than 1.3% in the harsh environment. As an outlook, our SLAM technology provides the cornerstone to activate many efficiency improvement approaches. View Full-Tex

Signal processing techniques for agro-industrial machinery monitoring

En los últimos tiempos, las técnicas de procesado de señal han ido ganando importancia dentro de numerosas aplicaciones industriales. Estos enfoques orientados al procesado de señal están abriendo nuevas perspectivas en muchas áreas del ámbito agro-industrial, destacando entre ellas la monitorización de maquinaria. El principal objetivo de esta tesis es el diseño, implementación y evaluación de esquemas de procesado de señal específicos que permitan la monitorización de equipamiento agro-industrial en tres sentidos: mantenimiento predictivo, seguimiento de vehículos y equipos de medida. Las técnicas propuestas en esta tesis contribuyen al estado del arte, expandiendo o extendiendo técnicas existentes, e incluso proponiendo esquemas completamente novedosos. La metodología seguida a lo largo de esta tesis, con objeto de alcanzar los objetivos marcados, se puede dividir en cinco etapas: revisión del estado del arte, formulación de hipótesis, desarrollo y evaluación, análisis de resultados y publicación de resultados. En esta tesis se han abordado tres problemas agro-industriales diferentes: mantenimiento predictivo de una cosechadora agrícola, seguimiento cinemático de un vehículo y monitorización del flujo a través de cada una de las boquillas en un pulverizador agrícola. Tres características principales de los métodos propuestos destacan sobre el resto. La primera es que todos los métodos satisfacen los objetivos con una precisión suficiente. La segunda característica es que todos los métodos propuestos conducen a sistemas que son asequibles y baratos. La última característica es la optimización de los métodos, que conduce a menores necesidades computacionales en comparación con otros enfoques existentes. Esta última propiedad hace que estos métodos puedan emplearse en aplicaciones con requisitos de tiempo real. Los resultados obtenidos en esta tesis ofrecen muestras de la capacidad de monitorizar maquinaria agro-industrial ofrecida por los métodos de procesado de señal. Hay dos conclusiones principales que se puede extraer de estos resultados. La primera es que las técnicas de procesado de señal pueden obtener información útil relativa a los problemas agro-industriales abordados. La segunda conclusión es que las soluciones propuestas tienden a proporcionar mayor precisión, mejor relación efectividad-coste y son más fáciles de desplegar, en comparación con otras alternativas existentes.Departamento de Teoría de la Señal y Comunicaciones e Ingeniería TelemáticaDoctorado en Tecnologías de la Información y las Telecomunicacione

Development of Soil Compaction Analysis Software (SCAN) Integrating a Low Cost GPS Receiver and Compactometer

A software for soil compaction analysis (SCAN) has been developed for evaluating the compaction states using the data from the GPS as well as a compactometer attached on the roller. The SCAN is distinguished from other previous software for intelligent compaction (IC) in that it can use the results from various types of GPS positioning methods, and it also has an optimal structure for remotely managing the large amounts of data gathered from numerous rollers. For this, several methods were developed: (1) improving the accuracy of low cost GPS receiver’s positioning results; (2) modeling the trajectory of a moving roller using a GPS receiver’s results and linking it with the data from the compactometer; and (3) extracting the information regarding the compaction states of the ground from the modeled trajectory, using spatial analysis methods. The SCAN was verified throughout various field compaction tests, and it has been confirmed that it can be a very effective tool in evaluating field compaction states

Contribuciones en el área del guiado autónomo de tractores agrícolas basado en la utilización de receptores GPS de bajo coste: mejora de la estabilidad y de la precisión de estos sistemas mediante el desarrollo de leyes de control asintóticamente estables y métodos geométricos

En esta tesis se realiza el estudio guiado de vehículos agrícolas con receptores GPS de bajo coste (receptores GPS L 1 de código) y se desarrollan diversas leyes de control y metodologías para mejorar su adaptación. En primer lugar, se analiza la validez de estos receptores para el guiado agrícola, obteniendo que es posible realizar el guiado autónomo a velocidades de hasta 9 km/h. En segundo lugar, se desarrolla una ley de control para el guiado en línea recta y en circunferencia, asintóticamente estable y convergente desde cualquier orientación del vehículo. Finalmente, se estudia el posicionamiento de la antena del receptor sobre el tractor y su influencia sobre el guiado y se desarrolla un método geométrico que obtiene el estado del vehículo a partir de los datos del receptor, con la antena en una posición adelantada del vehículo, incrementando la estabilidad, respuesta y tolerancia a ruido de los sistemas de guiado con receptores de bajo coste. Los métodos desarrollados se validan tanto de forma teórica como experimental.Departamento de Teoría de la Señal, Comunicaciones e Ingeniería Telemátic

A dynamic two-dimensional (D2D) weight-based map-matching algorithm

Existing map-Matching (MM) algorithms primarily localize positioning fixes along the centerline of a road and have largely ignored road width as an input. Consequently, vehicle lane-level localization, which is essential for stringent Intelligent Transport System (ITS) applications, seems difficult to accomplish, especially with the positioning data from low-cost GPS sensors. This paper aims to address this limitation by developing a new dynamic two-dimensional (D2D) weight-based MM algorithm incorporating dynamic weight coefficients and road width. To enable vehicle lane-level localization, a road segment is virtually expressed as a matrix of homogeneous grids with reference to a road centerline. These grids are then used to map-match positioning fixes as opposed to matching on a road centerline as carried out in traditional MM algorithms. In this developed algorithm, vehicle location identification on a road segment is based on the total weight score which is a function of four different weights: (i) proximity, (ii) kinematic, (iii) turn-intent prediction, and (iv) connectivity. Different parameters representing network complexity and positioning quality are used to assign the relative importance to different weight scores by employing an adaptive regression method. To demonstrate the transferability of the developed algorithm, it was tested by using 5,830 GPS positioning points collected in Nottingham, UK and 7,414 GPS positioning points collected in Mumbai and Pune, India. The developed algorithm, using stand-alone GPS position fixes, identifies the correct links 96.1% (for the Nottingham data) and 98.4% (for the Mumbai-Pune data) of the time. In terms of the correct lane identification, the algorithm was found to provide the accurate matching for 84% (Nottingham) and 79% (Mumbai-Pune) of the fixes obtained by stand-alone GPS. Using the same methodology adopted in this study, the accuracy of the lane identification could further be enhanced if the localization data from additional sensors (e.g. gyroscope) are utilized. ITS industry and vehicle manufacturers can implement this D2D map-matching algorithm for liability critical and in-vehicle information systems and services such as advanced driver assistant systems (ADAS)