Search Results (4)

Location is critical for the safe and effective completion of Unmanned Aerial Vehicle (UAV) missions. Since positioning errors tend to accumulate over time, uncorrected measurements from Inertial Navigation Systems (INSs) are unreliable. Aiming for UAV self-positioning under the challenges of a Global Navigation Satellite System (GNSS), this article integrates Digital Terrestrial Multimedia Broadcast (DTMB) signals and assisted INS components as external radiation sources for system design. The trigonometric geometry algorithm is proposed to estimate the pseudo-measurement, and the impact factors of the positioning error are analyzed. After filtering the pseudo-measurement by multi-point initiation, we designed a model for cross-regional positioning scenarios using the nearest-neighbor navigation association and scalar weighted distributed fusion. The simulation results demonstrate that the model can effectively track the target. Finally, the effectiveness of the positioning at a constant altitude is evaluated through different vehicle-mounted scenarios with a speed of 60 km/h. The experimental results show that the minimum positioning error can reach 18.95 m over a 525 m trajectory, thus meeting actual UAV requirements and having practical value. Full article

Food security is threatened by climate change and associated abiotic stresses that affect the flowering stage and the biochemistry of flowers and fruits. In tomato, managed insect pollination and grafting elite tomato varieties onto robust rootstocks are widely practiced commercially to enhance tomato crop profitability, particularly under suboptimal conditions. However, little is known about rootstock–pollinator interactions and their impact on the chemical composition of fruit. In this study, a commercial tomato F1 hybrid (Solanum lycopersicum L.) was self-grafted and grafted onto a set of experimental rootstocks and cultivated under optimal and saline (75 mM NaCl) conditions in the presence of managed bumblebee pollinators (Bombus terrestris). The number of visits (VN) and total visiting time (TVT) by pollinators to different grafted plants were monitored through an RFID (radio-frequency identification) tracking system, while targeted metabolites (hormones, sugars, and organic and amino acids) and mineral composition were analyzed in the fruit juice by UHPLC-MS and ICP-OES, respectively. Pollinator foraging decisions were influenced by the rootstocks genotype and salinity treatment. Experimental rootstocks predominantly increased pollinator attraction compared to the self-grafted variety. Interestingly, the pollinator parameters were positively associated with the concentration of abscisic acid, salicylic acid, malate and fumarate, and tyrosine in salinized fruits. Moreover, a high accumulation of sodium was detected in the fruits of the plants most visited by pollinators, while rootstock genotype-specific responses were found for nitrogen and potassium concentrations. In addition to the known effect on yield, these findings underscore the synergic interactions between rootstocks, pollinators, and environmental stressors on tomato fruit composition. Full article

This paper describes in detail the applicability of the developed ground-penetrating radar (GPR) model with a kinematic GPR and self-tracking (robotic) terrestrial positioning system (TPS) surveying setup (GPR-TPS model) for the acquisition, processing and visualisation of underground utility infrastructure (UUI) in a real urban environment. The integration of GPR with TPS can significantly improve the accuracy of UUI positioning in a real urban environment by means of efficient control of GPR trajectories. Two areas in the urban part of Celje in Slovenia were chosen. The accuracy of the kinematic GPR-TPS model was analysed by comparing the three-dimensional (3D) position of UUI given as reference values (true 3D position) from the officially consolidated cadastre of utility infrastructure in the Republic of Slovenia and those obtained by the GPR-TPS method. To determine the reference 3D position of the GPR antenna and UUI, the same positional and height geodetic network was used. Small unmanned aerial vehicles (UAV) were used for recording to provide a better spatial display of the results of UUI obtained with the GPR-TPS method. As demonstrated by the results, the kinematic GPR-TPS model for data acquisition can achieve an accuracy of fewer than 15 centimetres in a real urban environment. Full article

This paper describes in detail the development of a ground-penetrating radar (GPR) model for the acquisition, processing and visualisation of underground utility infrastructure (UUI) in a controlled environment. The initiative was to simulate a subsurface urban environment through the construction of regional road, local road and pedestrian pavement in real urban field/testing pools (RUTPs). The RUTPs represented a controlled environment in which the most commonly used utilities were installed. The accuracy of the proposed kinematic GPR-TPS (terrestrial positioning system) model was analysed using all the available data about the materials, whilst taking into account the thickness of the pavement as well as the materials, dimensions and 3D position of the UUI as given reference values. To determine the reference 3D position of the UUI, a terrestrial geodetic surveying method based on the established positional and height geodetic network was used. In the first phase of the model, the geodetic network was used as a starting point for determining the 3D position of the GPR antenna with the efficient kinematic GPR surveying setup using a GPR and self-tracking (robotic) TPS. In the second phase, GPR-TPS system latency was quantified by matching radargram pairs with a set of fidelity measures based on a correlation coefficient and mean squared error. This was followed by the most important phase, where, by combining sets of “standard” processing routines of GPR signals with the support of advanced algorithms for signal processing, UUI were interpreted and visualised semi-automatically. As demonstrated by the results, the proposed GPR model with a kinematic GPR-TPS surveying setup for data acquisition is capable of achieving an accuracy of less than ten centimetres. Full article