Real-time Kinematic Global Positioning System Research Articles

Enhancing survey field data with artificial intelligence: a real-time kinematic GPS study

Enhancing survey field data with artificial intelligence: a real-time kinematic GPS study

Delayed Kalman filter for vision-based autonomous flight in ocean environments

This paper presents the developments of flight hardware and software for a multirotor unmanned aerial vehicle, performing autonomous take-off and landing on a moving vessel in ocean environments. The proposed flight hardware is composed of a general-purpose computing module connected to a low-cost inertial measurement, an real-time kinematics GPS, motor speed controller, and a camera, through a custom-made printed circuit board. The flight software is developed in C++ with multi-threading such that the multiple tasks of control, estimation, and communication are executed simultaneously. The proposed flight system is verified with autonomous flight experiments on a United States Naval Academy research vessel operating in Chesapeake Bay. Two types of flight experiments are performed: autonomous flight utilizing real-time kinematics GPS for relative positioning, and vision-based autonomous flight, both for shipboard launch and landing.

Roles of Exposure Time and Geochemical Factors in the Characteristics of the Surface Sediments of the Hwangdo Tidal Flat, Taean, Cheonsu Bay, West Coast of Korea

The Hwangdo tidal flat is an intertidal landform located in Cheonsu Bay, Taean-gun, Chungcheongnam-do, on the west coast of Korea. The topographical characteristics of the semi-enclosed bay on the eastern side of the study area include waterways, sandbars, small islands, and tidal flats. In this study, data were acquired from tide gauges installed on the Hwangdo Bridge, and the height of the ellipsoid was measured using a real-time kinematics global positioning system (RTK-GPS). Digital elevation model (DEM) using Matrice 300 drone data were also acquired after processing. The geochemical sediment characteristics in the study area were analyzed, together with tidal-flat exposure-time characteristics based on environmental factors. Sediment data (n = 107) collected from October 25 to 28, 2022 (Korean local time) were used to classify sediment particles according to Folk and Ward (1957). Sedimentary facies ranged from coarse sand (sand:mud ratio = 9:1) to sandy silt (sZ) followed by muddy sand (mS) and slightly gravelly sandy mud ((g)sM). Total organic carbon (TOC) in the surface sediments was also characterized based on a particle-size analysis. The mean change in tidal height measured at Hwangdo Bridge during the sampling period was ~7.53 m (minimum: −3.86 m, maximum: +3.67 m). Based on the Boryeong’s sea level measurement tide data in 2022, the tidal area in the drone images ranged from 6.362 m2 (0.006 km2) at DEM +4.0 to 4,841,078 m2 (4.841 km2) at DEM −4.0 m, indicating an increase in the tidal-flat area according to the tidal level of up to ~800-fold. The daily average exposure time was 9.0 h (minimum: 1.5 h, maximum: 17.9 h). Based on the results of multivariate analysis using exposure times and a geochemical dataset, four groups were identified: upper, middle, and lower intertidal zones and regions with a relatively high organic-matter concentration. A determination of the main characteristics of the Hwangdo tidal flat according to their spatial distribution showed that, among various environmental factors, changes in the sand or clay sediment composition were determined by community factors. The results of this study demonstrate the four statistically processed groups of marine environmental characteristics in the Hwangdo tidal flats. Changes in sedimentary patterns, rather than in the exposure time, accounted for the differences in the sediment compositions of the upper, middle, and lower stations, a response that is expected to continue.

Utilizing Drone-Based Ground-Penetrating Radar for Crime Investigations in Localizing and Identifying Clandestine Graves.

The decomposition of a body is influenced by burial conditions, making it crucial to understand the impact of different conditions for accurate grave detection. Geophysical techniques using drones have gained popularity in locating clandestine graves, offering non-invasive methods for detecting surface and subsurface irregularities. Ground-penetrating radar (GPR) is an effective technology for identifying potential grave locations without disturbance. This research aimed to prototype a drone system integrating GPR to assist in grave localization and to develop software for data management. Initial experiments compared GPR with other technologies, demonstrating its valuable applicability. It is suitable for various decomposition stages and soil types, although certain soil compositions have limitations. The research used the DJI M600 Pro drone and a drone-based GPR system enhanced by the real-time kinematic (RTK) global positioning system (GPS) for precision and autonomy. Tests with simulated graves and cadavers validated the system's performance, evaluating optimal altitude, speed, and obstacle avoidance techniques. Furthermore, global and local planning algorithms ensured efficient and obstacle-free flight paths. The results highlighted the potential of the drone-based GPR system in locating clandestine graves while minimizing disturbance, contributing to the development of effective tools for forensic investigations and crime scene analysis.

Accurate and Robust Rotation-Invariant Estimation for High-Precision Outdoor AR Geo-Registration

Geographic registration (geo-registration) is a crucial foundation for augmented reality (AR) map applications. However, existing methods encounter difficulties in aligning spatial data with the ground surface in complex outdoor scenarios. These challenges make it difficult to accurately estimate the geographic north orientation. Consequently, the accuracy and robustness of these methods are limited. To overcome these challenges, this paper proposes a rotation-invariant estimation method for high-precision geo-registration in AR maps. The method introduces several innovations. Firstly, it improves the accuracy of generating heading data from low-cost hardware by utilizing Real-Time Kinematic GPS and visual-inertial fusion. This improvement contributes to the increased stability and precise alignment of virtual objects in complex environments. Secondly, a fusion method combines the true-north direction vector and the gravity vector to eliminate alignment errors between geospatial data and the ground surface. Lastly, the proposed method dynamically combines the initial attitude relative to the geographic north direction with the motion-estimated attitude using visual-inertial fusion. This approach significantly reduces the requirements on sensor hardware quality and calibration accuracy, making it applicable to various AR precision systems such as smartphones and augmented reality glasses. The experimental results show that this method achieves AR geo-registration accuracy at the 0.1-degree level, which is about twice as high as traditional AR geo-registration methods. Additionally, it exhibits better robustness for AR applications in complex scenarios.

GPS + Galileo + BDS-3 medium to long-range single-baseline RTK: an alternative for network-based RTK?

AbstractThanks to the development of the real-time kinematic (RTK) algorithm and the emerging Global Navigation Satellite System (GNSS), especially for Galileo and BeiDou-3, reliable positioning accuracy for medium and long-baseline RTK became possible globally. Moreover, with the development of the GNSS receiver hardware, baseline length limitations due to radio-based communications are removed thanks to internet-based communication. In this work, single-baseline RTK, incorporated partial ambiguity resolution with troposphere and ionosphere weighting, using GPS (G), Galileo (E), BeiDou-3 (C3) and multi-GNSS (GE and GEC3), is conducted with real GNSS data of EUREF Permanent GNSS network under three different cutoff angles (10°, 20°, and 30°) for six different lengths of baselines (~50, ~150, ~250, ~350, ~450, and ~550 km). The results show that the multi-GNSS RTK solution significantly contributed to the positioning accuracy and convergence time of the single-system RTK solutions. Based on the results, non-available epoch-wise solutions for the high-degree cutoff angles are more obvious for the single-system RTK, whereas multi-GNSS solutions provide 100% solutions for each cutoff angle and baseline. The results indicate that instantaneous and a few epochs single-epoch ambiguity resolution is feasible for 50, 150, 250 and 350 km baseline lengths for multi-GNSS RTK. Based on the positioning results, horizontal–vertical positioning improvements of multi-GNSS RTK (GEC3) compared with the single-system GPS RTK are found as 50%–37%, 40%–35%, 55%–47%, 53%–54%, 57%–49% and 57%–49% for 50, 150, 250, 350, 450 and 550 km, respectively, under a 10° cutoff angle. For 20° and 30° cutoff angles, the accuracy improvements are much higher. The convergence time improvements (n/e/u) of multi-GNSS RTK (GEC3) compared with the single-system GPS RTK are found as 86/92/75%, 77/67/72%, 75/77/83%, 53/56/52%, 69/49/62%, and 52/45/39% for 50, 150, 250, 350, 450 and 550 km, respectively, under a 10° cutoff angle.

Stochastic modeling with robust Kalman filter for real-time kinematic GPS single-frequency positioning

The centimeter-level positioning accuracy of real-time kinematic (RTK) depends on correctly resolving integer carrier-phase ambiguities. To improve the success rate of ambiguity resolution and obtain reliable positioning results, an enhanced Kalman filtering procedure has been developed. Based on a posteriori residuals of measurements and state predictions, the measurement noise variance–covariance matrix for double-differenced measurements is adaptively estimated, rather than approximated by an empirical function which uses satellite elevation angle as input. Since, in real-world situations, unexpected outliers and carrier-phase outages can degrade the filter performance, a stochastic model based on robust Kalman filtering is proposed, for which the double-differenced measurement noise variance–covariance matrix is computed empirically with a modified version of the IGG (Institute of Geodesy and Geophysics) III method in order to detect and identify outliers. The performance of the proposed method is assessed by two tests, one with simulated data and one with real data. In addition, the performance of F-ratio and W-ratio tests as proxies for the success of ambiguity fixing is investigated. Experimental results reveal that the proposed method can improve the reliability and robustness of relative kinematic positioning for simulation scenarios as well as in a real urban test.

Exploring distinct types of intertidal bars on either side of a small estuary using a multifaceted approach

Multiple intertidal bars are common sedimentary landforms found on low-gradient sandy coasts exposed to low to moderate wave energy with a significant tidal range. However, studying the factors that influence their morphology can be challenging due to limited high-resolution field data and tools for bedform analysis. To address this, a multifaceted approach was used to investigate the morphology of intertidal bars at two adjacent tidal beaches on the north and south coasts of a small estuary on the Lianyungang coast of China. This approach included repeated real-time kinematic-global positioning system (RTK-GPS) leveling, unmanned aerial vehicle (UAV) surveys, surface sediment sampling, satellite remote sensing analysis, and automated bedform analysis. The study revealed two distinct types of intertidal bars on either side of the estuary with similar hydrodynamic settings. The north coast presented low-amplitude ridges (also called ridges and runnels), while the south coast had sand waves. The north coast displayed 2–5 oblique, asymmetrical, and dynamic bars that appeared at the seaward end of the intertidal zone and migrated landward to eventually attach to the steep beach on the landward end of the intertidal zone, representing a life cycle. The south coast had 6–9 parallel, continuous, symmetrical, and stable sand bars occupying the lower part of the intertidal zone. Due to the nearly identical hydrodynamic background, the alongshore variability in sediment supply is suggested as a key factor driving the formation of distinct types of bars.

Real Time Kinematic (RTK) heave as a replacement of Motion Reference Unit (MRU) heave in hydrographic surveying works

Heave is one of the major contributors to errors in water depth measurements. Motion Reference Unit (MRU) measures the heave signal with high-level accuracy as well as other ship motions. Unfortunately, MRU has been reported to have some of drawbacks such as; heave drift error, influence of ship motion dynamic, In addition to its very expensive price Real-Time Kinematic (RTK) GPS uses dual frequency receiver and carrier phase differential technique under kinematic solution and provides very accurate position in all three components in real time. In addition, RTK GPS also calculates the low frequency changes in water level such as tidal oscillation. This research is an attempt to investigate the possibility of using the RTK GPS data to deduce the heave signal from the GPS height (tides - heave) instead of heave from MRU to correct the water depth. Moreover, to examine to what extent, RTK heave can be used as a backup to satisfy the International Hydrographic Organization (IHO) survey order standards. A comparison between the extracted RTK heave and MRU heave signals revealed a good agreement with a strong direct correlation of 0.96. As shown in figure 1 RTK heave as a replacement for MRU heave in hydrographic surveying was statistically validated with the use of a lot of methods of analysis such as Test of the Normality, Paired Samples T Test, Wilcoxon Signed Ranks Test, Heave Signals Frequency Adjustment , Descriptive Statistics for the Two Heave Signals , Descriptive Statistics for Each Signal Individually , Correlation and Trend, Analysis Between the Two Signals, Scatter Diagram and Trend, Standard Deviation and Uncertainty for Soundings, Characteristics of the Difference between Two Signals , Comparing the Surfaces by TIN Model. The results of this analysis provided the possibility of using RTK heave as a replacement for MRU heave in hydrographic surveying. Therefore, RTK GPS is not only used to provide precise position or tidal oscillations but also based on this study, can be used to measure heave accurately to correct the depth satisfying IHO survey standards. Received: 28 January 2023 Accepted: 26 April 2023 Published: 22 May 2023

Mapping subsurface defects and surface deformation along the artificial levee of the Lower Tisza River, Hungary

Artificial levees along alluvial rivers are major components of flood-risk mitigation. This is especially true in the case of Hungary, where more than one-third of the country is threatened by floods and protected by an over 4200-km-long levee system. Most of such levees were built in the nineteenth century. Since then, several natural and anthropogenic processes, such as compaction and erosion, might have contributed to these earth structures' slow but steady deformation. Meanwhile, as relevant construction works were scarcely documented, the structure and composition of artificial levees are not well known. Therefore, the present analysis mapped structural differences, possible compositional deficiencies, and sections where elevation decrease is significant along a 40-km section of the Lower Tisza River. Investigations were conducted using real-time kinematic GPS and ground-penetrating radar (GPR). Onsite data acquisition was complemented with an analysis using a Persistent Scatterer Synthetic Aperture Radar to assess general surface deformation. GPR profiles showed several anomalies, including structural and compositional discontinuities and local features. The GPR penetration depth varied between 3 and 4 m. According to height measurements, the mean elevation of the levee crown decreased by 8 cm in 40 years. However, the elevation decrease reached up to 30 cm at some locations. Sections affected by structural anomalies, compositional changes, and increased surface subsidence are especially sensitive to floods when measurement results are compared with flood phenomena archives.

Structure and topology of a brittle-ductile fault swarm at Crawford Knob, Franz Josef, New Zealand

ABSTRACT We present surface and structural models of a swarm of dm-scale subparallel faults exposed in a ∼2000 m2 glaciated outcrop near Franz Josef Glacier, in the Southern Alps of New Zealand. These structures are inferred to have slipped at ∼20 km depth in the hanging-wall Alpine Schist of the Alpine Fault under conditions that were variably brittle to ductile as the Pacific Plate was tilted and uplifted. Using field mapping, real-time kinematic GPS and digital images from a remotely piloted aircraft system, we have created a digital surface model of the outcrop and orthophotographs at a ground resolution of ∼1 cm to map compositional layering in the metasediments and the array of brittle-ductile faults displacing them. In order of decreasing relative age (and average thickness), displaced markers in the schist include primary psammite and pelite beds, quartz veins, and a deformational foliation. The surface models have been used to create 2-D transects and a 3-D model where faults are projected down-dip, to determine the connectivity, topology and intersection types of the fault swarm. Lithological variations, particularly the interface between pelitic and psammitic schist, were a primary control on the topology of the fault network and the spacing between faults.

Potential of Precise Fertilization through Adoption of Management Zones Strategy to Enhance Wheat Production

The variability in soil properties and crop yield can be overcome by adoption of smart farming practices through interpolation and mapping of spatial variability patterns. Geospatial technologies can be utilized to determine the cause of spatial variability in fields for site-specific application of fertilizer. This study was designed to quantify and identify the spatial variation in soil properties and wheat (Triticum aestivum L.) yield and to delineate prescription maps for precise application of fertilizer in a semi-arid subtropical region of Pakistan. To examine the variability in soil properties on the production of the considered crop, this study comprised two different fields and each field was divided into (20 × 20 m) grids. The samples of soil were collected at 15 cm and 30 cm soil depths before the fertilization to analyze the different soil characteristics i.e., nitrogen (N), electrical conductivity (EC), potassium (K), soil organic matter (SOM), phosphorus (P), and pH. The boundaries of selected fields and grid points were established with a real-time kinematics-global positioning system (RTK-GPS). The soil data were acquired with a soil proximal sensor at a depth of 7 cm after fertilization. The statistical analysis coefficient of variation (CV), geostatistical-analysis-nugget-to-sill ratio (N:S), and the interpolated maps (ArcGIS pro 2.3) were used to characterize the least to moderate variability of soil parameters and yield, demanding site-specific management of fertilizer application. Cluster analysis was conducted using Minitab 21, which classified soil and yield characteristics into five categories: “very good”, “very low”, “good”, “poor”, and “medium”, with an external heterogeneity and internal homogeneity both more than 60%. Significant relationships (p < 0.05) between soil and crop properties were used to develop the management zones (MZs) for the precise application of fertilizer in wheat fields. Significant differences (p < 0.05) in soil nutrients were found in the very high and very low productivity zones at both sampling times, which suggest delineating the MZs for precise application of fertilizer according to the need of crop and soil properties. The results revealed that the optimum number of MZs for the wheat fields was five and there was heterogeneity in the soil nutrients in five MZs. The findings of this study also highlight the necessity of predicting the crop and soil factors by using precision technologies to develop the prescription maps, because sampling and analysis of soil are expensive and time-consuming. Based on the demand of the soil and crops, site-specific fertilization can increase economic and environmental efficiency.

Coarse-to-fine visual autonomous unmanned aerial vehicle landing on a moving platform

Autonomous unmanned aerial vehicle (UAV) landing is a challenging task, especially on a moving platform in an unstructured environment. Under such a scenario, successful UAV landing is mainly affected by poor UAV localization performance. To solve this problem, we propose a coarse-to-fine visual autonomous UAV landing system based on an enhanced visual positioning approach. The landing platform is marked with a specially designed QR code marker, which is developed to improve the landing accuracy when the UAV approaches the landing site. Besides, we employ the you only look once framework to enhance the visual positioning accuracy, thereby promoting the landing platform detection when the UAV is flying far away. The framework recognizes the QR code and decodes the position of a UAV by the corner points of the QR code. Further, we use the Kalman filter to fuse the position data decoded from the QR code with those from the inertia measurement unit sensor. Then, the position data are used for UAV landing with a developed hierarchical landing strategy. To verify the effectiveness of the proposed system, we performed experiments in different environments under various light conditions. The experimental results demonstrate that the proposed system can achieve UAV landing with high accuracy, strong adaptability, and robustness. In addition, it can achieve accurate landing in different operating environments without external real-time kinematic global positioning system (RTK-GPS) signals, and the average landing error is 11.5 cm, which is similar to the landing error when using RTK-GPS signals as the ground truth.

Short-term dynamics of a high energy embayed beach: Stanwell Park, NSW, Australia

The three-dimensional variability of the subaerial beach is examined for Stanwell Park Beach, New South Wales (NSW), Australia. This embayed environment has previously been studied over long time scales (decades), but not over shorter time scales (days, weeks). Embayed beaches experience rotation events during which opposite accretion and erosion patterns are observed at the extremities of the beach. To analyse this phenomenon, the beach is mapped with 10 Real-Time Kinematic Global Positioning System (RTK-GPS) surveys collected from 10th February 2016 to 14th May 2016. This study aims to examine short-term changes (days, weeks) to the morphology of the subaerial beach of Stanwell Park Beach and any factors that may influence its behaviours. We show that a short-time beach rotation event occurs over one month, caused by a large eastern swell. However, swell with a southern direction generates rip current channels on the subaerial beach face. During this particular event, the amount of sediment transported is lower than during beach rotation events. Furthermore, Stanwell Park Beach has two lagoons that can open to discharge water accumulated in these lagoons. We show that during heavy rainfall, the lagoons open, transporting sediment in surf zone and thus causing erosion. This study provides a clear demonstration of the sensitivity of embayed beaches to short-term variability in wave climate.

Morphodynamics of Rip Current Systems at Haeundae Beach, Korea

Lee, J. and Hong, S., 2023. Morphodynamics of rip current systems at Haeundae Beach, Korea. Journal of Coastal Research, 39(1), 199–206. Charlotte (North Carolina), ISSN 0749-0208. Rip current generation and beach morphodynamics were measured for about 60 days at Haeundae Beach, Busan, Korea, using various instruments comprising co-located velocity and pressure sensors, ADCPs, and kinematic GPS surveys. Rip currents are narrow currents initiated close to the shoreline that flow strongly in a seaward direction through the surf zone and beyond. It is generally accepted that rip currents arise mostly from the variation of wave height alongshore attritutable to wave refraction over inhomogeneous bathymetry. Field measurement was performed to clarify the generation mechanism of rip currents at Haeundae Beach, Korea. The creation and destruction of sandbars could be identified clearly using data from a photogrammetric survey taken from the roof of a high building during the summer season. In this study, a surf-zone depth survey was performed periodically using Network Real-Time Kinematic GPS, a device that can provide a detailed topographic survey of the surf-zone region. Using these data, we perform a correlation analysis between rip current generation and surf-zone morphological variation.

İnsansız Hava Araçlarının Orman Yolu Projelerinde Kullanımı

Road networks are accepted as a criterion showing the level of development of countries. Undoubtedly, the role of highways in facilitating human life is quite important. However, road routes involve high cost land surveying studies that can pass through areas with various land use types and cover.For forest road routes to be built in forest areas, points representing the land surface can be obtained by various measurement methods (remote sensing, photogrammetry and terrestrial measurement techniques). Depending on the land structure and cover, difficulties are encountered in the determination of spatial points with terrestrial measurement techniques. In this study, as an alternative to the terrestrial measurement technique, 341 m long forest road excavation and filling calculations were carried out with the help of Unmanned Aerial Vehicle (UAV) photogrammetry. Photo pairs taken from different heights (50 m, 75 m and 100 m) with real-time kinematics (RTK) GPS UAV were processed with Agisoft to produce a point cloud. The point cloud data obtained by digital photogrammetry and land measurement methods were carried out in NetCAD environment for the excavation and filling calculations for the same road route. Between the two methods, in the 50 m, 75 m and 100 m measurements of the UAV obtained by ground measurement; In the calculation of the UAV 50m measurement amount, 0.27% in the total excavation amount and 1.08% difference in the total filling amount, 2.51% in the total excavation amount and 5.22% in the total filling amount in the calculation of the UAV 75 m measurement amount, and the total difference in the UAV 100m measurement amount in the calculation of the UAV 50m measurement amount. A difference of 3.13% in the amount of excavation and 2.53% in the total amount of filling was determined. These results show that UAV photogrammetry is very effective in forest road projects and in calculating the amount of earthwork volume in mountainous terrain.

Clothoid-Based Lane-Level High-Definition Maps: Unifying Sensing and Control Models

Autonomous vehicles rely on lane-level high-definition (HD) maps for self-localization and trajectory planning. Current mapping, however, relies on simple line models, while clothoid curves have unexplored potential. Clothoids, well known in road design, are often chosen to model the vehicle trajectory in planning and control systems as they describe the road with higher fidelity. For this reason, we propose two vision-based pipelines for generating lane-level HD maps using clothoid models. The first pipeline performs mapping with known poses, requiring precise real-time kinematics GPS (RTK GPS) measurements; the second copes with noisy localizations, solving the simultaneous localization and mapping (SLAM) problem. Both pipelines rely on a line detection algorithm to identify each line marking and perform a graph-based optimization to estimate the map.

Impact of Field Topography and Soil Characteristics on the Productivity of Alfalfa and Rhodes Grass: RTK-GPS Survey and GIS Approach

Understanding the spatial pattern of soil chemical properties along with the topologic indicators is essential for site-specific agriculture management. A study was conducted on a 50 ha field to investigate the effect of selected topographic indicators, including elevation (DEM), slope (SL), flow accumulation (FA) and Topographic Wetness Index (TWI) on forage crop production. The soil samples and yield data were obtained from the field inventory. Topographical parameters of elevation and slope were estimated with the use of a real-time kinematic global positioning system (RTK-GPS), and then the DEM was generated. The collected soil samples were analyzed for pH, EC, nitrogen and soil organic carbon. Sentinel-2 images were for the creation of yield maps of alfalfa and Rhodes grass. Subsequently, on the basis of DEM, the generated elevation, slope and FA model were then compared with the yield and soil chemical properties. Statistical analysis revealed that the SL, FA and TWI, which are associated with water distribution, were significantly related to crop yields. The FA showed a medium-to-non-significant correlation with the productivity of both alfalfa (R2 = 0.586; p = 0.015) and Rhodes grass (R2 = 0.578; p = 0.01). A significant inverse correlation was recorded between the SL and the yield of both crops (R2 = −0.591 to −0.617; p = 0.01). The yield map revealed that the majority of the area (37.56%) of the experimental field was occupied by the medium-yield class, followed by the high-yield class (33.03%).

Deep semantic segmentation for the quantification of grape foliar diseases in the vineyard.

Plant disease evaluation is crucial to pathogen management and plant breeding. Human field scouting has been widely used to monitor disease progress and provide qualitative and quantitative evaluation, which is costly, laborious, subjective, and often imprecise. To improve disease evaluation accuracy, throughput, and objectiveness, an image-based approach with a deep learning-based analysis pipeline was developed to calculate infection severity of grape foliar diseases. The image-based approach used a ground imaging system for field data acquisition, consisting of a custom stereo camera with strobe light for consistent illumination and real time kinematic (RTK) GPS for accurate localization. The deep learning-based pipeline used the hierarchical multiscale attention semantic segmentation (HMASS) model for disease infection segmentation, color filtering for grapevine canopy segmentation, and depth and location information for effective region masking. The resultant infection, canopy, and effective region masks were used to calculate the severity rate of disease infections in an image sequence collected in a given unit (e.g., grapevine panel). Fungicide trials for grape downy mildew (DM) and powdery mildew (PM) were used as case studies to evaluate the developed approach and pipeline. Experimental results showed that the HMASS model achieved acceptable to good segmentation accuracy of DM (mIoU > 0.84) and PM (mIoU > 0.74) infections in testing images, demonstrating the model capability for symptomatic disease segmentation. With the consistent image quality and multimodal metadata provided by the imaging system, the color filter and overlapping region removal could accurately and reliably segment grapevine canopies and identify repeatedly imaged regions between consecutive image frames, leading to critical information for infection severity calculation. Image-derived severity rates were highly correlated (r > 0.95) with human-assessed values, and had comparable statistical power in differentiating fungicide treatment efficacy in both case studies. Therefore, the developed approach and pipeline can be used as an effective and efficient tool to quantify the severity of foliar disease infections, enabling objective, high-throughput disease evaluation for fungicide trial evaluation, genetic mapping, and breeding programs.

3D LiDAR Based SLAM System Evaluation with Low-Cost Real-Time Kinematics GPS Solution

Positioning mobile systems with high accuracy is a prerequisite for intelligent autonomous behavior, both in industrial environments and in field robotics. This paper describes the setup of a robotic platform and its use for the evaluation of simultaneous localization and mapping (SLAM) algorithms. A configuration using a mobile robot Husky A200, and a LiDAR (light detection and ranging) sensor was used to implement the setup. For verification of the proposed setup, different scan matching methods for odometry determination in indoor and outdoor environments are tested. An assessment of the accuracy of the baseline 3D-SLAM system and the selected evaluation system is presented by comparing different scenarios and test situations. It was shown that the hdl_graph_slam in combination with the LiDAR OS1 and the scan matching algorithms FAST_GICP and FAST_VGICP achieves good mapping results with accuracies up to 2 cm.