New Methodology of Designation the Precise Aircraft Position Based on the RTK GPS Solution

The paper presents the results of research on improving the accuracy of aircraft positioning using RTK-OTF (Real Time Kinematic–On The Fly) technique in air navigation. The paper shows a new solution of aircraft positioning for the application of the differential RTK-OTF technique in air navigation. In particular, a new mathematical model is presented which makes it possible to determine the resultant position of an aircraft based on the solution for the method of least squares in a stochastic process. The developed method combines in the process of alignment of GPS (Global Positioning System) observations, three independent solutions of the aircraft position in OTF mode for geocentric coordinates XYZ of the aircraft. Measurement weights as a function of the vector length and the mean vector length error, respectively, were used in the calculations. The applied calculation method makes it possible to determine the resultant position of the aircraft with high accuracy: better than 0.039 m with using the measurement weight as a function of the vector length and better than 0.009 m with the measurement weight as a function of the mean error of the vector length, respectively. In relation to the classical RTK-OTF solution as a model of the arithmetic mean, the proposed method makes it possible to increase the accuracy of determination of the aircraft position by 45–46% using the measurement weight as a function of the vector length, and 86–88% using the measurement weight as a function of the mean error of the vector length, respectively. The obtained test results show that the developed method improves to significantly improve the accuracy of the RTK-OTF solution as a method for determining the reference position in air navigation.

Integrating Vehicle Positioning and Path Tracking Practices for an Autonomous Vehicle Prototype in Campus Environment

This paper presents the implementation of an autonomous electric vehicle (EV) project in the National Taiwan University of Science and Technology (NTUST) campus in Taiwan. The aim of this work was to integrate two important practices of realizing an autonomous vehicle in a campus environment, including vehicle positioning and path tracking. Such a project is helpful to the students to learn and practice key technologies of autonomous vehicles conveniently. Therefore, a laboratory-made EV was equipped with real-time kinematic GPS (RTK-GPS) to provide centimeter position accuracy. Furthermore, the model predictive control (MPC) was proposed to perform the path tracking capability. Nevertheless, the RTK-GPS exhibited some robust positioning concerns in practical application, such as a low update rate, signal obstruction, signal drift, and network instability. To solve this problem, a multisensory fusion approach using an unscented Kalman filter (UKF) was utilized to improve the vehicle positioning performance by further considering an inertial measurement unit (IMU) and wheel odometry. On the other hand, the model predictive control (MPC) is usually used to control autonomous EVs. However, the determination of MPC parameters is a challenging task. Hence, reinforcement learning (RL) was utilized to generalize the pre-trained datum value for the determination of MPC parameters in practice. To evaluate the performance of the RL-based MPC, software simulations using MATLAB and a laboratory-made, full-scale electric vehicle were arranged for experiments and validation. In a 199.27 m campus loop path, the estimated travel distance error was 0.82% in terms of UKF. The MPC parameters generated by RL also achieved a better tracking performance with 0.227 m RMSE in path tracking experiments, and they also achieved a better tracking performance when compared to that of human-tuned MPC parameters.

A bathymetric mapping and SLAM dataset with high-precision ground truth for marine robotics

In recent years, sonar systems for surface and underwater vehicles have increased in resolution and become significantly less expensive. As such, these systems are viable at a wide range of price points and are appropriate for a broad set of applications on surface and underwater vehicles. However, to take full advantage of these high-resolution sensors for seafloor mapping tasks an adequate navigation solution is also required. In GPS-denied environments this usually necessitates a simultaneous localization and mapping (SLAM) technique to maintain good accuracy with minimal error accumulation. Acoustic positioning systems such as ultra short baseline (USBL) and long baseline (LBL) are sometimes deployed to provide additional bounds on the navigation solution, but the positional uncertainty of these systems is often much greater than the resolution of modern multibeam or interferometric side scan sonars. As such, subsurface vehicles often lack the means to adequately ground-truth navigation solutions and the resulting bathymetic maps. In this article, we present a dataset with four separate surveys designed to test bathymetric SLAM algorithms using two modern sonars, typical underwater vehicle navigation sensors, and high-precision (2 cm horizontal, 10 cm vertical) real-time kinematic (RTK) GPS ground truth. In addition, these data can be used to refine and improve other aspects of multibeam sonar mapping such as ray-tracing, gridding techniques, and time-varying attitude corrections.

Applying a Hand-Held Laser Scanner to Monitoring Gully Erosion: Workflow and Evaluation

Detailed understanding of gully erosion processes is essential for monitoring gully remediation and requires fine-scale monitoring. Hand-held laser scanning systems (HLS) enable rapid ground-based data acquisition at centimeter precision and ranges of 10–100 m. This study quantified errors in measuring gully morphology and erosion over a four year period using two models of HLS. Reference datasets were provided by Real-Time-Kinematic (RTK) GPS and a RIEGL Terrestrial Laser Scanner (TLS). The study site was representative of linear gullies that occur extensively on hillslopes throughout Great Barrier Reef catchments, where gully erosion is the dominant source of fine sediment. The RMSE error against RTK survey points varied 0.058–0.097 m over five annual scans. HLS was found to measure annual gully headcut extension within 0.035 m of RTK. HLS was, on average, within 6% of TLS for morphological metrics of depth, area and volume. Volumetric change over a 60 m length of the gully and four years was estimated to within 23% of TLS. Errors could potentially be improved by scanning at times of year with lower ground vegetation cover. HLS provided similar levels of error and was relatively more rapid than TLS and RTK for monitoring gully morphology and change.

Subaerial beach morphology change from multiple storms during the 2020 hurricane season

Frequent or consecutive storms impacting coastal areas can result in unexpected or variable impacts. This study evaluates spatiotemporal variability and cumulative impacts on the subaerial beach from four major tropical storms of varying intensity and proximity impacting the study area of Palm Beach County, Florida, during the 2020 Atlantic Basin Hurricane season. Impacts from Hurricanes Isaias, Laura, Sally, and Teddy were measured using Real-Time Kinematic Global Positioning System (RTK GPS) at 14 transects throughout the northern and southern portion of the county. Alongshore morphologic variability resulted from each storm, with some expected patterns of erosion and accretion with a few unexpected impacts. The first three storms caused swash or collision regime impacts on the Sallenger scale. Hurricane Teddy was the fourth storm to impact the study area, causing overwash at numerous locations. Whereas the first two storms of the season caused mostly erosion of the subaerial beach, the southeasterly approach of Hurricane Sally reversed the cumulative volume loss trend in the northern portion of the study area with accretion. Hurricane Teddy was the most distant storm but occurred at the highest tide and produced the largest waves and highest winds. The most variable patterns in erosion and accretion resulted from Hurricane Teddy, which also dominated the overall (or cumulative) volume and contour change. Further study is recommended for a multi-storm season that includes the subaqueous portion of the beach profile to elucidate trends of cross-shore and alongshore drivers of storm-induced morphology change.

The techniques and challenges of GPS surveying for vertical alignments in high-rise buildings

PurposeVertical alignment in high-rise building is a very important aspect. The architects are nowadays interested in improvising untypical complicated morphology in building designs which increase the difficulty in surveying for vertical alignments. Although the GNSS survey techniques are widely applied in constructions, there is a lack of data sources to explicitly expose their applicability in high-rise buildings and the challenges to be considered. This study has been oriented to find out the best suitable GPS survey technique for the vertical alignment in high-rise buildings and the practical challenges to be considered.Design/methodology/approachThe findings have been attained by analyzing the reliable data gained through experts' comments through structured questionnaire survey, case studies and experiments on different GPS survey techniques.FindingsThe findings express that the GPS techniques can be used for vertical alignments in high-rise buildings except for direct setting out for which only RTK GPS can be used. There are some practical challenges to be considered in such GPS applications.Research limitations/implicationsThe findings encourage the research community to further focus on the GNSS survey applications in the constructions of high-rise buildings.Practical implicationsThe research expresses applicability of easier and less time-consumed modern GNSS survey techniques instead of traditional survey methods for expediting building constructions.Social implicationsThe knowledge on such modern rapid survey techniques with accuracy, efficiency and reliability highly affects the process of infrastructure development.Originality/valueThe research presents a useful new knowledge on applying GNSS survey techniques for precise survey requirements in the construction industry and exposes the gateways for further researches and development.

Monitoring Re-Growth of Invasive Plants Using an Autonomous Surface Vessel

Invasive aquatic plant species, and in particular Eurasian Water-Milfoil (EWM), pose a major threat to domestic flora and fauna and can in turn negatively impact local economies. Numerous strategies have been developed to harvest and remove these plant species from the environment. However it is still an open question as to which method is best suited to removing a particular invasive species and the impact of different lake conditions on the choice. One problem common to all harvesting methods is the need to assess the location and degree of infestation on an ongoing manner. This is a difficult and error prone problem given that the plants grow underwater and significant infestation at depth may not be visible at the surface. Here we detail efforts to monitor EWM infestation and evaluate harvesting methods using an autonomous surface vessel (ASV). This novel ASV is based around a mono-hull design with two outriggers. Powered by a differential pair of underwater thrusters, the ASV is outfitted with RTK GPS for position estimation and a set of submerged environmental sensors that are used to capture imagery and depth information including the presence of material suspended in the water column. The ASV is capable of both autonomous and tele-operation.