Search Results (49)

Most visual simultaneous localization and mapping (SLAM) systems are based on the assumption of a static environment in autonomous vehicles. However, when dynamic objects, particularly vehicles, occupy a large portion of the image, the localization accuracy of the system decreases significantly. To mitigate this challenge, this paper unveils DOT-SLAM, a novel stereo visual SLAM system that integrates dynamic object tracking through graph optimization. By integrating dynamic object pose estimation into the SLAM system, the system can effectively utilize both foreground and background points for ego vehicle localization and obtain a static feature points map. To rectify the inaccuracies in depth estimation from stereo disparity directly on the foreground points of dynamic objects due to their self-similarity characteristics, a coarse-to-fine depth estimation method based on camera–road plane geometry is presented. This method uses rough depth to guide fine stereo matching, thereby obtaining the 3 dimensions (3D)spatial positions of feature points on dynamic objects. Subsequently, by establishing constraints on the dynamic object’s pose using the road plane and non-holonomic constraints (NHCs) of the vehicle, reducing the initial pose uncertainty of dynamic objects leads to more accurate dynamic object initialization. Finally, by considering foreground points, background points, the local road plane, the ego vehicle pose, and dynamic object poses as optimization nodes, through the establishment and joint optimization of a nonlinear model based on graph optimization, accurate six degrees of freedom (DoFs) pose estimations are obtained for both the ego vehicle and dynamic objects. Experimental validation on the KITTI-360 dataset demonstrates that DOT-SLAM effectively utilizes features from the background and dynamic objects in the environment, resulting in more accurate vehicle trajectory estimation and a static environment map. Results obtained from a real-world dataset test reinforce the effectiveness. Full article

The performance of 5G/6G cellular systems operating in millimeter wave (mmWave, 30–100 GHz) and sub-terahertz (sub-THz, 100–300 GHz) bands is conventionally assessed by utilizing the static distributions of user locations. The rationale is that the use of the beam tracking procedure allows for keeping the beams of a base station (BS) and user equipment (UE) aligned at all times. However, by introducing 3GPP Reduced Capability (RedCap) UEs utilizing the Radio Resource Management (RRM) Relaxation procedure, this may no longer be the case, as UEs are allowed to skip synchronization signal blocks (SSB) to improve energy efficiency. Thus, to characterize the performance of such UEs, methods explicitly accounting for UE mobility are needed. In this paper, we will utilize the tools of the stochastic geometry and random walk theory to derive signal-to-noise ratio (SNR), spectral efficiency, and rate as an explicit function of time by accounting for mmWave/sub-THZ specifics, including realistic directional antenna radiation patterns and micro- and macro-mobilities causing dynamic antenna misalignment. Different from other studies in the field that consider time-averaged performance measures, these metrics are obtained as an explicit function of time. Our numerical results illustrate that the macro-mobility specifies the overall trend of the time-dependent spectral efficiency, while local dynamics at 1–3 s scales are mainly governed by micro-mobility. The difference between spectral efficiency corresponding to perfectly synchronized UE and BS antennas and time-dependent spectral efficiency in a completely desynchronized system is rather negligible for realistic cell coverages and stays within approximately 5–10% for a wide range of system parameters. These conclusions are not affected by the utilized antenna array at the BS side. However, accounting for realistic radiation patterns is critical for a time-dependent performance analysis of 5G/6G mmWave/sub-THz systems. Full article

Motorcycle motion is largely influenced by the road geometry, which alters the allowable accelerations in longitudinal and lateral directions and influences the vertical wheel loads. Recently, a method for three-dimensional road reconstruction and its incorporation into transient and quasi-steady-state (QSS) minimum lap time simulations (MLTSs) has been proposed. The main purpose of this work is to demonstrate how significantly different results from a minimum lap time optimal control problem can be obtained when using inappropriate elevation data sources in the track reconstruction problem, and how the road model reconstructed using poor input data can lead to misleading conclusions when analyzing real vehicle and driver performances. Two road models derived from high- and low-resolution digital elevation models (DEMs) are compared and their impact on the optimal maneuver of a racing motorcycle is examined. The essentials of track identification are presented, as well as vehicle positioning on the 3D road and the generalized QSS motorcycle model. Obtained 3D and 2D road models are analyzed in detail, on a case example of the Road Atlanta racetrack, and used in minimum lap time simulations, which are validated by the experimental data recorded on the Supersport motorcycle. The comparative analysis showed that great care should be taken when selecting the elevation dataset in the track reconstruction process, and that the 1 m resolution local DEMs seem to be sufficient to obtain MLTS results close to the measured ones. The example of using the 3D free-trajectory QSS minimum lap time problem to localize the track segments where real driver actions can be improved is also presented. The differences between simulation results on different road models of the same racetrack can be large and influence the interpretation of optimal maneuver. Full article

Switches are an essential, safety-critical part of the railway infrastructure. Compared to open tracks, their complex geometry leads to increased dynamic loading on the track superstructure from passing trains, resulting in high maintenance costs. To increase efficiency, condition monitoring methods specific to railway switches are required. A common approach to track superstructure monitoring is to measure the acceleration caused by vehicle track interaction. Local interruptions in the wheel–rail contact, caused for example by local defects or track discontinuities, appear in the data as transient impact events. In this paper, such transient events are investigated in an experimental setup of a railway switch with track-side acceleration sensors, using frequency and waveform analysis. The aim is to understand if and how the origins of these impact events can be distinguished in the data of this experiment, and what the implications for condition monitoring of local track discontinuities and defects with wayside acceleration sensors are in practice. For the same experimental configuration, individual impact events are shown to be reproducible in waveform and frequency content. Nevertheless, with this track-side sensor setup, the different types of track discontinuities and defects (squats, joints, crossing) could not be clearly distinguished using characteristic frequencies or waveforms. Other factors, such as the location of impact event origin relative to the sensor, are shown to have a much stronger influence. The experimental data suggest that filtering the data to narrow frequency bands around certain natural track frequencies could be beneficial for impact event detection in practice, but differentiating between individual impact event origins requires broadband signals. A multi-sensor setup with time-synchronized acceleration sensors distributed over the switch is recommended. Full article

Although numerous effective Simultaneous Localization and Mapping (SLAM) systems have been developed, complex dynamic environments continue to present challenges, such as managing moving objects and enabling robots to comprehend environments. This paper focuses on a visual SLAM method specifically designed for complex dynamic environments. Our approach proposes a dynamic feature removal module based on the tight coupling of instance segmentation and multi-view geometric constraints (TSG). This method seamlessly integrates semantic information with geometric constraint data, using the fundamental matrix as a connecting element. In particular, instance segmentation is performed on frames to eliminate all dynamic and potentially dynamic features, retaining only reliable static features for sequential feature matching and acquiring a dependable fundamental matrix. Subsequently, based on this matrix, true dynamic features are identified and removed by capitalizing on multi-view geometry constraints while preserving reliable static features for further tracking and mapping. An instance-level semantic map of the global scenario is constructed to enhance the perception and understanding of complex dynamic environments. The proposed method is assessed on TUM datasets and in real-world scenarios, demonstrating that TSG-SLAM exhibits superior performance in detecting and eliminating dynamic feature points and obtains good localization accuracy in dynamic environments. Full article

A simplified analytical method useful for ductile ground support design in underground mine workings is presented. This approach allows for maintaining the stability of sidewalls in rectangular openings extracted in competent and homogeneous rocks, especially in high-pressure conditions, favoring rockburst event occurrence. The proposed design procedure involves the typical assumptions governing the limit equilibrium method (LEM) with respect to a triangular rock block expelled from a sidewall of a long mine excavation subjected to normal stresses of the values determined based on the Maugis’s analytical solution concerned with stress distribution around the elliptical opening extracted within the homogeneous infinite elastic space. This stage of the local assessment of rock susceptibility to ejection from the walls of the excavation allowed for determining the geometry of the block whose ejection is most likely in a given geological and mining situation. Having extensive information about the geometry of the excavations and the properties of the surrounding rocks, it was possible to make an exemplary map of the risk from rockburst hazard, developed as the 2D contours of safety indexes’ values, for special-purpose excavations such as heavy machinery chambers, main excavations, etc. in conditions of selected mining panel of the deep copper mine at Legnica-Głogów Copper Basin, Poland. Another important element of the obtained results is the calculated values of the horizontal forces potentially pushing out the predetermined rock blocks. These forces are the surplus over the potential of frictional resistance and cohesion on the surfaces of previously identified discontinuities or on new cracks appearing as a result of overloading of the sidewalls. Finally, the presented algorithm allows us to perform quantitative tracking of rockburst phenomena as a function of time by determination of acceleration, velocity, and displacement of expelled rocks. Such information may be useful at the stage of designing the support for underground workings. Full article

The use of high-precision positioning systems in modern navigation applications is crucial since location data is one of the most important pieces of information in Industry 4.0, especially for robots operating outdoors. In the modernization process of global navigation satellite system (GNSS) positioning, precise point positioning (PPP) has demonstrated its effectiveness in comparison to traditional differential positioning methods over the past thirty years. However, various challenges hinder the integration of PPP techniques into Internet of Things (IoT) systems for robot localization, with accuracy being a primary concern. This accuracy is impacted by factors such as satellite availability and signal disruptions in outdoor environments, resulting in less precise determination of satellite observations. Effectively addressing various GNSS errors is crucial when collecting PPP observations. The paper investigates the trade-off between kinematic PPP accuracy and cost effectiveness, through the examination of various influencing factors, including the choice of GNSS system (single or mixed), observation type (single or dual frequency), and satellite geometry. This research investigates kinematic PPP accuracy variation on a 10.4 km observed track based on different factors, using the GNSS system (single or mixed), and observation type (single or dual frequency). It can be concluded that mixed (GPS/GLONASS) dual frequency offers a 3D position accuracy of 9 cm, while mixed single frequency offers a 3D position accuracy of 13 cm. In industry, the results enable manufacturers to select suitable robot localization solutions according to the outdoor working environment (number of available satellites), economical constraint (single or dual frequency), and 3D position accuracy. Full article

On behalf of MÁV Hungarian State Railways Ltd., the authors carried out a research and development (R&D) project on behalf of the Budapest University of Technology and Economics, Department of Highway and Railway Engineering, on the subject of “Research and investigation of the causes of gauge narrowing by finite-element modeling in running track and turnout, and under operational and laboratory conditions”. The main objective of the research was to investigate the causes of localized defects of gauge narrowing in railway tracks based on machine and manual track measurements, laboratory measurements, and theoretical considerations. The measures proposed as a consequence of identifying the causes could significantly contribute to reducing the number and extent of local defects in the future. Furthermore, the research aims to develop new theories in less scientifically mature areas and provide procedures and instructions that professional engineers and practitioners can easily apply. The main areas of research, which are not exhaustive, are as follows: (i) the evaluation of the measurement results provided by track geometry measuring and recording cars; (ii) on-site investigations in the railway track in terms of gauge and rail profile measurements; and, based on these, (iii) the selection of concrete sleepers, which were removed from the track and subjected to more detailed geometrical investigations in the laboratory, together with the components of the rail reinforcement; (iv) the track–vehicle connection, tight running in straight and curved track sections under track confinement; (v) modeling of the stability and deflection of the rail when the rail fastenings lose part of their supporting function; and (vi) finite element modeling of the concrete sleepers under operating conditions such as slow deformation of the concrete, temperature variation effects, and lateral support on the ballast. In the already-narrowed track section, the tight vehicle running is not the cause of the track gauge narrowing but a consequence, so it is not investigated in this paper. Full article

This paper proposes a model-less feedback system driven by tourist tracking data that are automatically collected through mobile applications to visualize the gap between geomedia recommendations and the actual routes selected by tourists. High-frequency GPS data essentially make it difficult to interpret the semantic importance of hot spots and the presence of street-level features on a density map. Our mobile collaborative framework reorganizes tourist trajectories. This processing comprises (1) extracting the location of the user-generated content (UGC) recording, (2) abstracting the locations where tourists stay, (3) discarding locations where users remain stationary, and (4) simplifying the remaining points of location. Then, our heatmapping system visualizes heatmaps for hot streets, UGC-oriented hot spots, and indoor-oriented hot spots. According to our experimental study, this method can generate a trajectory that is more adaptable for hot street visualization than the raw trajectory and a simplified trajectory according to its geometry. This paper extends our previous work at the 2022 IEEE International Conference on Big Data, providing deeper discussions on application for local tourism. The framework allows us to derive insights for the development of guide content from mobile sensor data. Full article

On February 6, 2023 (local time), two earthquakes (Mw7.8 and Mw7.7) struck central and southern Turkey, causing extensive damage to several cities and claiming a toll of 40,000 lives. In this study, we propose a method for seismic building damage assessment and analysis by combining SAR amplitude and phase coherence change detection. We determined building damage in five severely impacted urban areas and calculated the damage ratio by measuring the urban area and the damaged area. The largest damage ratio of 18.93% is observed in Nurdagi, and the smallest ratio of 7.59% is found in Islahiye. We verified the results by comparing them with high-resolution optical images and AI recognition results from the Microsoft team. We also used pixel offset tracking (POT) technology and D-InSAR technology to obtain surface deformation using Sentinel-1A images and analyzed the relationship between surface deformation and post-earthquake urban building damage. The results show that Nurdagi has the largest urban average surface deformation of 0.48 m and Antakya has the smallest deformation of 0.09 m. We found that buildings in the areas with steeper slopes or closer to earthquake faults have higher risk of collapse. We also discussed the influence of SAR image parameters on building change recognition. Image resolution and observation geometry have a great influence on the change detection results, and the resolution can be improved by various means to raise the recognition accuracy. Our research findings can guide earthquake disaster assessment and analysis and identify influential factors of earthquake damage. Full article

The Polarization CrossFire (PCF) suite onboard the Chinese GaoFen-5(02) satellite has been sophisticatedly composed by the Particulate Observing Scanning Polarimeter (POSP) and the Directional Polarimetric Camera (DPC). Among them, DPC is a multi-angle sequential measurement polarization imager, while POSP is a cross-track scanning simultaneous polarimeter with corresponding radiometric and polarimetric calibrators, which can theoretically be used for cross comparison and calibration with DPC. After the data preprocessing of these two sensors, we first select local homogeneous cluster scenes by calculating the local variance-to-mean ratio in DPC’s Level 1 product projection grids to reduce the influence of scale differences and geometry misalignment between DPC and POSP. Then, taking the observation results after POSP data quality assurance as the abscissa and taking the DPC observation results under the same wavelength band and geometric conditions as the same ordinate, a two-dimensional radiation/polarization feature space is established. Results show that the normalized top of the atmosphere (TOA) radiances of DPC and POSP processed data at the nadir are linearly correlated. The normalized TOA radiance root mean square errors (RMSEs) look reasonable in all common bands. The DPC and POSP normalized radiance ratios in different viewing zenith angle ranges at different times reveal the temporal drift of the DPC relative radiation response. The RMSEs, mean absolute errors (MAEs), relative errors (REs), and scatter percentage of DPC degree of linear polarization (DoLP) falling within the expected error (EE = ±0.02) of POSP measured DoLP are better than 0.012, 0.009, 0.066, and 91%, respectively. Full article

Additive manufacturing methods, such as the laser powder bed fusion, do not need any special tool or casting mold. This enables the fast realization of complex and individual geometries with integrated functions. However, the local heat input during the manufacturing process often leads to residual stresses and distortion. This in turn causes poor quality, scrap parts or can even terminate a job prematurely if the powder recoating mechanism collides with a distorted part during the process. This study investigates the generation mechanisms of residual stresses and distortion during laser powder bed fusion (LPBF) of stainless steel 316L in order to reduce these effects and thus contribute to improved process safety and efficiency. Therefore, numerical investigations with a finite element model on the scale of a few melt tracks and layers serve to develop a detailed understanding of the mechanisms during production. The work includes an investigation of the build plate temperature, the laser power and speed and the layer thickness. The results show a strong dependency on the build plate preheating and energy per unit length. A higher build plate temperature and a reduction of the energy per unit length both lead to lower residual stresses. Full article

Today’s railway transport is built upon high-performance infrastructure. Cost-effective yet sustainable infrastructure presumes tracks with a precise and durable geometry. At ballasted tracks, the geometry is created and restored through tamping machines, which position the track panel and compact the ballast beneath the sleepers. It is commonly agreed that the ballast compaction plays an important role in the long-term stability of the track. Yet, there is no method available which allows a direct correlation between the compactness of the ballast and the stability of the track geometry. Available studies either model track behaviour without considering the bedding, or analyse ballast compactness locally while disregarding its influence on the track geometry. This paper presents a new methodology which establishes a relation between these two topics—ballast compaction during tamping and subsequent track behaviour. A state-of-the-art tamping machine has been equipped with an experimental measurement setup, constantly recording relevant data during every tamping process. These data can be used to derive an indication for the achieved compaction under every sleeper. Utilising the tamping machine’s internal measuring system for track geometry documentation, every tamping process (every sleeper) is assigned to the precise position along the track. The data set is merged and synchronised with regular track geometry measurements of the infrastructure manager. The result is a comprehensive data set which allows precise analyses between tamping machine measurements and track behaviour. This data set provides the foundation for future research, aiming towards a better understanding of the tamping process and its influence on the quality and durability of the established track geometry. Full article

LiDAR sensors provide rich 3D information about their surroundings and are becoming increasingly important for autonomous vehicles tasks such as localization, semantic segmentation, object detection, and tracking. Simulation accelerates the testing, validation, and deployment of autonomous vehicles while also reducing cost and eliminating the risks of testing in real-world scenarios. We address the problem of high-fidelity LiDAR simulation and present a pipeline that leverages real-world point clouds acquired by mobile mapping systems. Point-based geometry representations, more specifically splats (2D oriented disks with normals), have proven their ability to accurately model the underlying surface in large point clouds, mainly with uniform density. We introduce an adaptive splat generation method that accurately models the underlying 3D geometry to handle real-world point clouds with variable densities, especially for thin structures. Moreover, we introduce a fast LiDAR sensor simulator, working in the splatted model, that leverages the GPU parallel architecture with an acceleration structure while focusing on efficiently handling large point clouds. We test our LiDAR simulation in real-world conditions, showing qualitative and quantitative results compared to basic splatting and meshing techniques, demonstrating the interest of our modeling technique. Full article

Localization of emitting sources is a fundamental task in sonar applications. One of the most important factors that affect the localization performance is the sensor–target geometry. The sensor formation problem is usually addressed in related work assuming that the target is static and the location is known to a certain degree, but this is not the case for many underwater surveillance problems. In this paper, we deal with the target–receiver formation problem from a different perspective, and propose to investigate the effect of target–receiver geometry on localization performance by exploiting the spatial spectrum of the direct position determination (DPD) methods. For a given multi-array system, the transformation of geometrical patterns can be explicitly demonstrated as the target moves along the track. Meaningful characteristics of the DPD methods are obtained from the experimental results, where coherent and non-coherent bearing information is used and compared. The feasibility of the DPD approaches in the ocean environments is also investigated by comparing with a matched filter processing (MFP)-based multi-array processor in order to validate the credibility of the results in this paper. Full article