Real-time Kinematic Research Articles

Mapping Gaps in Sugarcane Fields Using UAV-RTK Platform

Unmanned aerial vehicles (UAVs) equipped with a global real-time kinematic navigation satellite system (GNSS RTK) could be a state-of-the-art solution to measuring gaps in sugarcane fields and enable site-specific management. Recent studies recommend the use of UAVs to map these gaps. However, low-accuracy GNSS provides incomplete or inaccurate photogrammetric reconstructions, which could easily generate an error in the gap measurement and constrain the applicability of these techniques. Therefore, in this study, we evaluated the potential of UAV RTK imagery for mapping gaps in sugarcane. To compare this solution with conventional UAV approaches, the precision and accuracy of RTK and non-RTK flights were evaluated. To increase the robustness of the research, flights were performed to map gaps found naturally in the field and with plants at different stages of development. Our results showed that the lengths of gaps identified by both RTK and non-RTK UAV imagery were similar, with differences in precision and accuracy of about 1% for both systems. In contrast, RTK was much more efficient and provides stakeholders with guidelines for accurate and precise mapping gaps, allowing them to make confident decisions on site-specific management.

Understanding microtopography changes in agricultural landscapes through precision assessments of digital surface models by the UAV-RTK-PPK method without ground control points

Soil erosion on agricultural land causes severe environmental problems and damages crop plants. Structure-from-motion with multiview stereo (SfM-MVS) together with data obtained via unmanned aerial vehicles (UAVs) helps understand spatiotemporal changes in the ground surface if there is enough precise data. However, installing ground control points in the field is labor intensive and disturbs field conditions. Here, images georeferenced using the Real-Time Kinematic (RTK) method were further improved using Post-Processing Kinematic (PPK) analysis. This study aims to verify whether the UAV-RTK-PPK method can create precise digital surface models to evaluate topographic changes owing to erosion without ground control points. The effects of the camera's interior orientation parameters settings and the addition of oblique images to nadiral images on the precision were also examined to reduce the positional error by the doming and bowling phenomena. Field observations were conducted in a 150 m × 25 m potato field with 156 poles to consider the three-dimensional object shapes in the verification. The doming or bowling phenomena occurred using only the nadiral images. The precision of the digital surface model was approximately 0.40 and 0.20 m (in the Z-direction) using the estimated and fixed camera's interior orientation parameters, respectively. In contrast, the digital surface models produced by adding oblique images to the nadiral images had a precision of approximately 0.04 m, regardless of the camera's interior orientation parameters. Thus, a high-precision digital surface model was obtained from images acquired using the UAV-RTK-PPK and SfM-MVS methods without ground control points. The digital surface model positional precision was improved by adding oblique images to the nadiral images without having to consider the camera's interior orientation parameters. Topographic changes >0.05 m after erosion by heavy rainfall were evaluated without ground control points using the UAV-RTK-PPK method with oblique and nadiral images. Therefore, our method can monitor the erosion of agricultural fields that may cause crop damage, such as the greening of potatoes.

High-Accuracy Positioning in GNSS-Blocked Areas by Using the MSCKF-Based SF-RTK/IMU/Camera Tight Integration

The integration of global navigation satellite system (GNSS) single-frequency (SF) real-time kinematics (RTKs) and inertial navigation system (INS) has the advantages of low-cost and low-power consumption compared to the multiple-frequency GNSS RTK/INS integration system. However, due to the vulnerability of GNSS signal reception, the application of the GNSS SF-RTK/INS integration is limited in complex environments. To improve the positioning accuracy of SF-RTK/INS integration in GNSS-blocked environments, we present a low-cost tight integration system based on BDS/GPS SF-RTK, a low-cost inertial measurement unit (IMU), and a monocular camera. In such a system, a multi-state constraint Kalman filter (MSCKF) is adopted to integrate the single-frequency pseudo-range, phase-carrier, inertial measurements, and visual data tightly. A wheel robot dataset collected under satellite signal-blocked conditions is used to evaluate its performance in terms of position, attitude, and run time, respectively. Results illustrated that the presented model can provide higher position accuracy compared to those provided by the RTK/INS tight integration system and visual-inertial tight integration system. Moreover, the average running time presents the potential of the presented method in real-time applications.

Spatio-Temporal Analysis of Ground Movement Using Unmanned Aerial Vehicle Photogrammetry in Gampong Lamkleng, Aceh Besar

Ground movement is one of the most frequent disasters causing major damages in Indonesia. Unmanned Aerial Vehicle (UAV) has been widely used as a rapid observation method to obtain detailed characterization of ground movement. Often, active landslide area is difficult to access. This hinders close monitoring and observations of the ground movement. This study aims to demonstrate the use of UAV as tools for monitoring and observations on active ground movement area and to validate the results. For this purpose, the study was conducted at Gampong Lamkleng, Aceh Besar-Indonesia using spatio-temporal analysis by UAV photogrammetry. The UAV was chosen because it is easy to use, practical, and safe for landslide area that are relatively small and difficult to reach. Aerial photographs were processed using the Agisoft Metashape software in modeling and analyzed using Quantum GIS (QGIS) and ArcGis. The observation results show that the largest ground movement occurred in January 20 to 23, 2021 which was related to precipitation rates measured at a nearby rainfall station. The movement volume was 1,411.063 m3 and a rate of ground movement reaching 0.69 m/day due to heavy rain. The estimated value of losses is IDR 1,055,854,000. The UAV images analysis were compared to actual ground elevation measured using Real-Time Kinematic (RTK). The validation show that the accuracy based on comparison between photogrammetric and RTK measurement was at agreeable rate (99%). Otherwise, the accuracy performed on 19 check point using Root Mean Square Error analysis found that the accuracy was still very low. The low RMSE value is due to the georeferencing process using the Ground Control Point not being carried out.

METHODOLOGY TO IMPROVE THE ACCURACY OF DETERMINING THE POSITION OF UAVS EQUIPPED WITH SINGLE-FREQUENCY RECEIVERS FOR THE PURPOSES OF GATHERING DATA ON AVIATION OBSTACLES

Low-altitude photogrammetric studies are often applied in detection of aviation obstacles. The low altitude of the Unmanned Aerial Vehicle (UAV) flight guarantees high spatial resolution (X, Y) of the obtained data. At the same time, due to high temporal resolution, UAVs have become an appropriate tool for gathering data about such obstacles. In order to ensure the required accuracy of orientation of the photogrammetric block, Ground Control Points (GCPs) are measured. The recently introduced UAV positioning solutions that are based on Post-Processing Kinematic (PPK) and Real Time Kinematic (RTK) are known to effectively reduce, or, according to other sources, even completely eliminate the necessity to conduct GCP measurements. However, the RTK method involves multiple limitations that result from the need to ensure continuous communication between the reference station and the rover receiver. The main challenge lies in achieving accurate orientation of the block without the need to conduct time-consuming ground measurements that are connected to signalling and measuring the GCPs. Such solution is required if the SPP code method is applied to designation the position of the UAV. The paper presents a research experiment aimed at improving the accuracy of the determination of the coordinates of UAV for the SPP method, in real time. The algorithm of the SPP method was improved with the use of IGS products.

Sequential Generation of Multi-GNSS Multi-Frequency PPP-RTK Products and Their Performance Using the EUREF Permanent GNSS Network

In the classic Precise Point Positioning (PPP) approach, observations of Global Navigation Satellite Systems (GNSS) are processed at the network level to generate satellite clocks and positions. This information can be used to enable accurate point positioning for a single GNSS receiver. In the PPP Real-Time Kinematic (PPP-RTK) approach, satellite phase biases are considered as well, enabling ambiguity resolution at the network and user levels. In this research, 30 s multi-frequency raw GPS, Galileo, and BDS-2/3 observations are processed at the network and user levels in a sequential Kalman filter. PPP-RTK enabling products are generated for up to five frequencies, and ambiguity resolution is performed at the network and user levels using a flexible ambiguity reparameterization approach, comparable to wide- and narrow-laning, which has shown to yield a significantly improved single epoch coordinate solution when multi-frequency observations are available. Different assumptions regarding the time stability of receiver and satellite phase biases have been made and compared. The availability of a precise user coordinate solution when multi-frequency and dual-frequency observations are processed is assessed and compared. A precise ambiguity-fixed solution is available in three epochs or fewer in 77% of all cases with an average of 24 visible satellites for static and kinematic receivers when multi-frequency observations are processed. When only dual-frequency observations are considered, a fixed solution is available in seven epochs or fewer in 71% of all cases. The fastest fixed solution was found in two epochs with multi-frequency observations and in six epochs with dual-frequency observations. Estimating a reference phase clock did not lead to an improvement in the coordinate solution. The findings indicate that a fixed solution can potentially be found faster than often suggested, with potential for further improvement when more satellites or regional atmospheric corrections are considered.

A PPP-RTK APPROACH TO MASS-MARKET APPLICATIONS

Abstract. PPP-RTK has been widely investigated to take the advantages of both real-time kinematic (RTK) and precise point positioning (PPP) techniques. Prior to PPP-RTK, the conventional RTK based on the use of a single base station, on the one hand, has been extended to work within a regional network of multiple base stations, known as network RTK (NRTK). The RTK and NRTK enable fast ambiguity resolution over a short baseline or a local region. PPP, on the other hand, eliminates the need to establish any local network like NRTK, which is able to work in a single receiver mode but it suffers long convergence time in ambiguity resolution. PPP-RTK therefore can provide fast ambiguity resolution capability like RTK and NRTK. Current PPP-RTK techniques however still face challenges in supporting mass-market applications such as mobile devices and autonomous vehicles. Although PPP-RTK system (a combination of RTK and PPP technologies) can help expand the coverage of RTK and speed up the ambiguity resolution in PPP, the deployment and maintenance of a dense network of permanent base stations and a central data processing infrastructure for generation of SSR corrections increases not only the system cost but also the system complexity. This is particularly an obstacle for mass-market applications. In this paper, a new RTK approach is described. First it is based on a single base station state-space-representation (SSR) correction generation strategy to support fast ambiguity resolved PPP. Further it presents a new peer-to-peer propagation strategy to form a real-time dynamically generated network of base stations to support mass-market application users with unbounded coverage. As a result, the new approach eliminates the need to deploy and maintain a dense network of permanent base stations and central data processing infrastructure as required in a conventional PP-RTK system.

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

Improving the Spatial Accuracy of UAV Platforms Using Direct Georeferencing Methods: An Application for Steep Slopes

The spatial accuracy of unmanned aerial vehicles (UAVs) and the images they capture play a crucial role in the mapping process. Researchers are exploring solutions that use image-based techniques such as structure from motion (SfM) to produce topographic maps using UAVs while accessing locations with extremely high accuracy and minimal surface measurements. Advancements in technology have enabled real-time kinematic (RTK) to increase positional accuracy to 1–3 times the ground sampling distance (GSD). This paper focuses on post-processing kinematic (PPK) of positional accuracy to achieve a GSD or better. To achieve this, precise satellite orbits, clock information, and UAV global navigation satellite system observation files are utilized to calculate the camera positions with the highest positional accuracy. RTK/PPK analysis is conducted to improve the positional accuracies obtained from different flight patterns and altitudes. Data are collected at altitudes of 80 and 120 meters, resulting in GSD values of 1.87 cm/px and 3.12 cm/px, respectively. The evaluation of ground checkpoints using the proposed PPK methodology with one ground control point demonstrated root mean square error values of 2.3 cm (horizontal, nadiral) and 2.4 cm (vertical, nadiral) at an altitude of 80 m, and 1.4 cm (horizontal, oblique) and 3.2 cm (vertical, terrain-following) at an altitude of 120 m. These results suggest that the proposed methodology can achieve high positional accuracy for UAV image georeferencing. The main contribution of this paper is to evaluate the PPK approach to achieve high positional accuracy with unmanned aerial vehicles and assess the effect of different flight patterns and altitudes on the accuracy of the resulting topographic maps.

Real-time high-precision landslide displacement monitoring based on a GNSS CORS network

GNSS technology is an effective all-weather, continuous and real-time method of detecting three-dimensional landslide displacement. However, current positioning methods such as the network real-time kinematic (RTK) technique based on virtual reference station (VRS) technology have some limitations, particularly a sensitivity to atmospheric modeling error. In this study, taking advantage of existing GNSS continuously operating reference stations (CORS), we propose a network RTK algorithm (virtual atmosphere constraint (VAC)) for high-precision landslide monitoring. Network modeling atmosphere delays were used as virtual observations for the terminal position solution, by which their accuracy information can be considered. Additionally, a noise reduction method that combines complementary ensemble empirical mode decomposition and median filtering was proposed to reduce GNSS signal residual errors in the original RTK coordinate time series. To validate the effectiveness of the algorithm, we processed one week of data from two monitoring receivers on the Heifangtai landslide and four surrounding CORS using the VAC and VRS methods. Results show that the original displacement time series processed with VRS was prone to jitter, whereas the VAC method exhibited better accuracy, stability, and ambiguity fixing rates. Horizontal and vertical RMS errors at a stable monitoring point were 1.7 cm and 3.9 cm for VRS-RTK and 0.9 cm and 2.3 cm for VAC-RTK; thus, VAC reduced the error by 40.1% and 20.5%, respectively. After noise reduction, the RMS values of the VAC method at the stable and the other collapsed monitoring point were both reduced to an mm-level accuracy.

Precision spraying using variable time delays and vision-based velocity estimation

Traditionally, precision farm equipment often relies on real-time kinematics and global positioning systems (RTK-GPS) for accurate position and velocity estimates. This approach proved effective and widely adopted in developed regions where RTK-GPS satellite and base station availability and visibility are not limited. However, RTK-GPS signal can be limited in farm areas due to topographic and economic constraints. Thus, this study developed a precision sprayer that estimated the travel velocity locally by tracking the relative motion of plants using a deep-learning-based machine vision system. Sprayer valves were then controlled by variable time delay (VTD) queuing and dynamic filtering. The proposed velocity estimation approach was tested at different velocities and tracking thresholds. The results showed that the velocity estimates agreed with actual measurements with a mean absolute error of 0.036 m/s. Further, testing the targeting algorithm on rows of artificial crops and weeds at different levels of spraying duration and filter size factor (FSF) showed that short spraying duration and small FSF increase overall spraying accuracy. Finally, testing the sprayer using the optimum settings at 0.87 m/s and 1.03 m/s successfully sprayed all targets. Further, only 2% to 7% of non-targets were sprayed at the low and high test velocities, respectively. With these results, this study suggests that vision-based velocity estimation combined with VTD queuing and dynamic filtering can be an accurate and low-cost solution for targeted spraying without using auxiliary velocity measurement systems.

Low-cost multi-GNSS, single-frequency RTK averaging for marine applications: accurate stationary positioning and vertical tide measurements

The use of Real Time Kinematic (RTK) Global Navigation Satellite System (GNSS) for accurate horizontal and vertical measurements in the marine environment has been considered since the late-1980’s and tested from the 1990’s when GPS and GLONASS were the only operational constellations available and high-cost multi-frequency receiver equipment was required. This paper modernizes the conversation using multi-constellation, low-cost, single-frequency RTK GNSS measurements and proves their value with accurate positioning and tide measurements. Our tests show average stationary horizontal positioning measurements using this equipment are suitable (95% CI) for the most stringent International Hydrographic Organization (IHO) Standard S-44 ‘Exclusive Order’ at base station ranges of up to 27 km. Vertical observations on a moving platform, smoothed using a baseline distance-dependent moving average filter show the equipment and method are comparable with traditional electronic tide gauge observations over the same base station range. All of our measurement results show the potential to improve total uncertainty calculations undertaken by hydrographers, engineers and scientists in the marine realm, while the low-cost equipment raises the possibility that more measurements can be taken, leading to improvements in monitoring, modelling and understanding the marine environment.

A Dynamic Continuous Constrained Phase Factor Graph Optimization Method for GNSS Kinematic Precise Point Positioning

Carrier phase measurements play a more critical role in achieving precise positioning for lower noise and insensitivity to multipath error over code (pseudorange) measurements. Real-time kinematic (RTK) is the most used precise positioning technique. However, the application costs are increased due to the demands for differential base stations. The undifferenced precise point positioning (PPP) does not require differential station assistance but is typically for static use. This paper proposes a dynamic continuous constrained phase (DCCP) method based on factor graph optimization for kinematic positioning without differential stations, even in the presence of cycle slips. The precise velocity estimated via integral doppler and the time correlation of phase ambiguity are regarded as the probability constraints in the factor graph. A real-world experiment was carried out to verify the feasibility of the DCCP method. Experimental results show that the proposed method had a better performance than the kinematic PPP method and window carrier phase (WCP) optimization method with 0.034m standard deviation and 1.338m mean error. It is our hope that this approach provides new insight into the study of other time-correlated state estimation problems.

UAV Photogrammetry for Soil Surface Deformation Detection in a Timber Harvesting Area, South Korea

During forest operations, canopy removal results in the soil surface being vulnerable to deformation, negatively impacting soil fertility and water quality. This study utilized unmanned aerial vehicle (UAV) photogrammetry to accurately detect soil surface deformation (SSD). Two-dimensional images were safely collected on a steep slope without real-time kinematics by conducting vertically parallel flights (VPFs). A high-resolution digital surface model (DSM) with a <3 cm resolution was acquired for precise SSD detection. Using DSM of difference (DoD), SSDs were calculated from DSMs acquired in June, July, September, and October 2022. By checking spatial distances at ground control points, errors of DSM alignments were confirmed as only 3 cm, 11.1 cm, and 4 cm from July to June, September to June, and October to June, respectively. From the first month of monitoring, erosion and deposition of approximately 7 cm and 9 cm, respectively, were detected at validation points (VPs). However, from total monitoring, cumulative SSD was assessed as having deposition tendencies at all VPs, even compared to ground truths. Although UAV photogrammetry can detect SSDs, spatial distortion may occur during UAV surveys. For vegetation growth issues, UAV photogrammetry may be unable to capture data on the soil surface itself.

Performance analysis of BDS-3 vehicle-/ship-/air-borne kinematic SPP/PPP/RTK

This paper comprehensively analyzes the kinematic positioning performance of the third-generation BeiDou Navigation Satellite System (BDS-3) in car-borne, ship-borne, and air-borne scenes. Specifically, this work collects three types kinematic data, i.e., car-borne, ship-borne, and air-borne in three scenes including a real experimental scene, a simulated urban canyon or forest-covered scene, and a simulated regional interference or covered scene. Based on these datasets, the kinematic positioning performance of the BDS-3 interoperable signals of B1C and B2a is systematically analyzed and compared with GPS. The results demonstrate that the BDS-3 has slightly more visible satellites than GPS in the Asia-Pacific test area, and the positioning performance indexes for the B1C and B2a new signals are comparable to GPS in terms of the single point positioning (SPP), precise point positioning (PPP), and real-time kinematic (RTK) positioning.

Development of a 3D Printed New Metering Mechanism for a Multi-Crop Seed Broadcasting System Using an Autonomous Small-Scale Vehicle

Developing countries in Asia widely use manual seed broadcasting methods due to a lack of appropriate seeding machinery. The agricultural sector is currently facing labor shortages and high labor costs, especially seasonal labor shortages for broadcasting and transplanting operations. However, the primary constraint in adopting existing broadcasting seeders for small-scale farmers in developing countries is the high initial purchase costs. Therefore, developing locally commercial accessible technology for small-scale farmers is an urgent requirement. In this regard, attempt was taken to develop a new low-cost 3D printed seeder that can be used for multi-crop seed broadcasting operations when integrated with an autonomous terrain vehicle. A new seed metering mechanism was proposed for seed broadcasting that can be controlled electronically from the autonomous terrain vehicle. Positional sensors based on the real time kinematics—global navigation satellite system (RTK-GNSS) were used to record positional information. The best observation was noted at a vehicle operational speed of 0.351 ms−1 and had a coefficient of variation (CV) referring to the distribution uniformity of seeds of 19% for green peas, 22% for cowpeas, and 25% for chickpeas. The developed seeder could spread multi-crop seeds and adjust the seed rates electronically at the different ranges of rotational speeds. Therefore, the use of 3D printed fabricated prototype seed broadcasting units with small-scale autonomous vehicles can be implemented to help in labor supplements and perform the broadcasting of different seeds.

Using Radio Technical Commission for Maritime Services Corrections in a Consumer-Grade Lane-Level Positioning System for Connected Vehicles

<div>Connected vehicle (CV) technology has the potential to greatly improve the safety, mobility, and environmental sustainability of traffic. Many CV applications require the vehicle position as input, which is primarily provided by global navigation satellite systems (GNSS). Although a large number of those applications (e.g., Intersection Movement Assist) require vehicle positioning to have lane-level accuracy, it has been shown that the type of positioning system typically used by CVs currently cannot provide consistent lane-level accuracy, even under open-sky conditions. In order to address this gap, we have evaluated an enhanced positioning system that adds little, if any, to the cost of the CV. It consists of a single-frequency real-time kinematic (RTK)-capable GNSS receiver onboard the vehicle, which utilizes Radio Technical Commission for Maritime Services (RTCM) differential corrections transmitted over dedicated short-range communications (DSRC) by the roadside infrastructure. Tests on a moving vehicle show that this system could provide lane-level accuracy over 95% of the time in open-sky conditions. These tests also show the DSRC to be an effective means of disseminating RTCM corrections, given the intersection spacings and communication ranges in the test. However, neither RTCM nor the more commonly used space-based augmentation system (SBAS) differential corrections appeared to improve the positioning accuracy of GNSS in urban canyons.</div>

Permafrost degradation at two monitored palsa mires in north-west Finland

Abstract. Palsas and peat plateaus are expected to disappear from many regions, including Finnish Lapland. However, detailed long-term monitoring data of the degradation process on palsas are scarce. Here, we present the results of the aerial photography time series analysis (1959–2021), annual real-time kinematic (RTK) GNSS and active layer monitoring (2007–2021), and annual unoccupied aerial system surveys (2016–2021) at two palsa sites (Peera and Laassaniemi, 68∘ N) located in north-west Finland. We analysed temporal trends of palsa degradation and their relation to climate using linear regression. At both sites, the decrease in palsa area by −77 % to −90 % since 1959 and height by −16 % to −49 % since 2007 indicate substantial permafrost degradation throughout the study periods. The area loss rates are mainly connected to winter air temperature changes at Peera and winter precipitation changes at Laassaniemi. The active layer thickness (ALT) has varied annually between 2007 and 2021 with no significant trend and is related mainly to the number of very warm days during summer, autumn rainfall of previous year, and snow depths at Peera. At Laassaniemi, the ALT is weakly related to climate and has been decreasing in the middle part of the palsa during the past 8 years despite the continuous decrease in palsa volume. Our findings imply that the ALT in the inner parts of palsas do not necessarily reflect the overall permafrost conditions and underline the importance of surface position monitoring alongside the active layer measurements. The results also showed a negative relationship between the ALT and snow cover onset, indicating the complexity of climate–permafrost feedbacks in palsa mires.

Robot positioning and navigation technology is based on Integration of the Global Navigation Satellite System and real-time kinematics

This paper provides a new robot positioning and navigation technique that combines GNSS-RTK and visual SLAM to address the shortcomings of existing single robot positioning and navigation techniques, such as limited adaptation to scenarios and susceptibility to environmental influences. Real-time kinematics (RTK) is a real-time dynamic observation technique based on carrier phase observations, which can provide real-time 3D positioning results of the measurement site in a specified coordinate system, and can be positioned with centimetre-level accuracy, which is suitable for It is suitable for outdoor positioning of mobile robots. In this paper, a dataset is studied to compare and analyse the advantages and disadvantages of different SLAMs in order to determine the most suitable robot positioning and navigation technique for autonomous indoor and outdoor mobility. These sensors were well calibrated and the composition was applied to the RK3588. The results show good performance in indoor-outdoor switching scenarios, obtaining a mapping technique that cannot be achieved with a single visual SLAM, effectively improving the ability to adapt to multiple scenarios and enhancing the operational range of the transportable robot.

A Cost-Effective GNSS Solution for Continuous Monitoring of Landslides

The development of low-cost dual-frequency global navigation satellite system (GNSS) receivers in recent years has enabled the use of these devices in numerous applications. In the monitoring of natural hazards, such as landslides, these devices can be considered suitable sensors. In this work, dual-frequency GNSS receivers and antennas were used for setting up near-real-time continuous low-cost GNSS monitoring systems (LGMSs) under field conditions. The SimpleRTK2B board, which integrates the u-blox ZED-F9P dual-frequency GNSS chip and the survey-calibrated GNSS antenna are the main components of the GNSS system. The LGMS was installed and tested for six months in the Laze landslide located in the northwestern part of Slovenia. A total of four GNSS systems were deployed, three of which were located in pillars in the landslide itself and one in a stable area. Open-source software was used to postprocess the acquired data, providing daily coordinates in static relative and precise point positioning (PPP) positioning modes. The results of six months of near-real-time monitoring showed that the Laze landslide was stable during this period, with only minor changes in the vertical component. The trend of decreasing ellipsoid height was evident at all stations, although it was in the range of a few millimeters. To validate the results in static relative positioning mode, the coordinate differences between low-cost and high-end geodetic GNSS instruments were estimated and found to be in the range of 5 mm or less, while the difference between horizontal and spatial positions was less than 7 mm for all stations. The same data were processed in PPP, vertical displacements were not detected as in the static relative positioning mode due to the lower accuracy of the method itself. Considering the six-month performance of a low-cost GNSS system under field conditions, it can be emphasized that these devices are capable of performing near real-time continuous monitoring of slow movements with high accuracy and decreased costs. In addition, an experimental test was performed to identify the size of detected displacements in real-time kinematic (RTK). Based on the achieved results, it was concluded that 20 mm spatial displacements are detectable with LGMSs in RTK considering only 15 s of observations.