Real Terrain Research Articles

Wind Farm Layout Optimization (WindFLO) : An advanced framework for fast wind farm analysis and optimization

A new framework for Wind Farm Layout Optimization (WindFLO) is developed to accelerate the design of wind farms. The framework provides a large set of analytical wake models and wake superposition schemes. It is able to take into account terrain elevation and the ambient wind velocity profile. The schemes in the WindFLO model were validated against experimental data from a wind tunnel to within 1% relative error. A turbine rotor diameter and height dependent cost model was also developed using data from 250 different wind turbines. A land usage model was also developed using the convex hull approach. The framework was used to optimize a wind farm layout for maximum annual energy production using real wind farm terrain and conditions. The nonlinear optimization problem was solved using a robust Single-Objective Hybrid Optimizer. The wind farm layout and wind turbine (rotor diameter and tower height) were optimized and resulted in increased annual energy production, reduced cost and reduced land usage. The WindFLO framework is made publicly available to accelerate and advance the techniques for wind farm optimization.11WindFLO can be downloaded from https://github.com/sohailrreddy/WindFLO.

Real-Time Pose Estimation of a Mobile Rover Using Kinect Sensor

The critical challenge of vision-based control of the mobile robot is to accurately estimate the position and orientation (pose) in the exploration of unknown terrains. In this paper, first a new approach of determining random er-rors in a pose measurement of Kinect scanner's 3D datasets by frame propagat-ing transformation approach is presented. Next, 3D visual information provided by Kinect scanner is used to track the optimum (minimum error) pose path of the rover through Kalman filter. The experimental results have been performed on real terrains which demonstrate the proposed approach efficiently tracks the poses from noisy 3D datasets.

Generation algorithm of grid model for complex terrain based on geodetic coordinate data transformation

Grid model construction is one of the preconditions for computational fluid dynamics (CFD) simulation. As many environmental accidents or unfavorable incidents occur in complex real terrain circumstances, corresponding grid model generation algorithm for scenario simulation has become a hot research field. The digital elevation model (DEM) is common for three-dimensional terrain modeling. DEM data usually consist of a certain number of geodetic coordinates, however, CFD preprocessing platform can't identify geodetic coordinates directly. In this paper, firstly an algorithm of coordinate transformation was proposed, which could convert geodetic coordinates to Cartesian coordinates in the form of length (x), width (y) and height (z). Secondly, another algorithm that generates a complex real terrain grid model was recommended based on the algorithm mentioned previously, which could import converted terrain data into a gridding platform for constructing the CFD terrain grid model. Experiments’ results showed that the terrain grid algorithm obtained through the combination of the two algorithms is highly geometrically consistent with real terrain. The algorithm provided by this study could give a more reliable and convenient basis for the application of CFD fine simulation in real complex terrain.

Two-Phase Object-Based Deep Learning for Multi-Temporal SAR Image Change Detection

Change detection is one of the fundamental applications of synthetic aperture radar (SAR) images. However, speckle noise presented in SAR images has a negative effect on change detection, leading to frequent false alarms in the mapping products. In this research, a novel two-phase object-based deep learning approach is proposed for multi-temporal SAR image change detection. Compared with traditional methods, the proposed approach brings two main innovations. One is to classify all pixels into three categories rather than two categories: unchanged pixels, changed pixels caused by strong speckle (false changes), and changed pixels formed by real terrain variation (real changes). The other is to group neighbouring pixels into superpixel objects such as to exploit local spatial context. Two phases are designed in the methodology: (1) Generate objects based on the simple linear iterative clustering (SLIC) algorithm, and discriminate these objects into changed and unchanged classes using fuzzy c-means (FCM) clustering and a deep PCANet. The prediction of this Phase is the set of changed and unchanged superpixels. (2) Deep learning on the pixel sets over the changed superpixels only, obtained in the first phase, to discriminate real changes from false changes. SLIC is employed again to achieve new superpixels in the second phase. Low rank and sparse decomposition are applied to these new superpixels to suppress speckle noise significantly. A further clustering step is applied to these new superpixels via FCM. A new PCANet is then trained to classify two kinds of changed superpixels to achieve the final change maps. Numerical experiments demonstrate that, compared with benchmark methods, the proposed approach can distinguish real changes from false changes effectively with significantly reduced false alarm rates, and achieve up to 99.71% change detection accuracy using multi-temporal SAR imagery.

Cutting Path Planning Technology of Shearer Based on Virtual Reality

With regards to the low degree of digitization, lack of real geological terrain, and low degree of automation in the cutting process of the traditional virtual fully mechanized mining face, we studied the key technologies of virtual operation and cutting path planning of the shearer on the three-dimensional (3D) roof and floor based on the virtual reality engine (Unity3D). Firstly, the virtual 3D coal seam was constructed through the 3D geological coordinate data of the mine. On this basis, the shape function of the scraper conveyor with the adaptive configuration on the floor was constructed to obtain the combined operation of the virtual shearer and the scraper conveyor. The movement of the shearer’s walking and height-adjustment was then, analyzed. A strategy for automatic height-adjustment based on the adjustment of the direction of the drum movement is hence, proposed to control the cutting path of the shearer. Finally, different experimental schemes were simulated in the developed prototype system after which each of the schemes was evaluated using the fuzzy comprehensive evaluation method. The results show that the proposed strategy for trajectory control can improve the accuracy and stability of the shearer’s motion trajectory. In Unity3D, the pre-selected schemes and digital and visual planning of coal production are previewed ahead of time, the whole production process can be mapped synchronously in the production process. It is also obtained that the virtual preview and evaluation of the production process can provide some guidance for actual production.

ZERO - ÚLTIMA IMAGEM

O presente trabalho analisa os contextos da Realidade Virtual, Imersão, Ilusão e Suspensão da Descrença no contexto da arte cénica. Para isso se tem como objecto o espetáculo ZERO que é definido como uma Realidade Virtual Artesanal. O conceito de presença/telepresença vai ser fundamental, visto que sua definição clarifica que: o que se pode chamar de Realidade Virtual é antes uma relação que se estabelece com a imagem ou com o médium, independentemente de como a imagem é produzida. O objectivo é estender conceitos, geralmente estão ligados à tecnologia ao mundo artesanal do objecto em causa – ZERO. Pretende-se descrever de que forma estes conceitos podem ser transferidos de uma esfera digital para um terreno de produção de imagem em tempo real. Outro objectivo é definir o conceito de Última Imagem. Um conceito processual que se descreve resumidamente como momento de suspensão do dispositivo da imagem e a suspensão da estrutura do espectador.

Constrained Hopping Traversability Analysis on Non-Uniform Polygonal Chains

We analyze the existence of constrained ballistic hopping paths on a nonuniform polygonal chain. This analysis has practical significance in constrained path planning applications for jumping robots where robot dynamic constraints, uneven surface structure, and non-uniform surface properties are considered. We derive closed-form conditions to satisfy i) damage-free robot landing ii) non-sliding of the robot iii) actuator saturation, and iv) intermediate terrain avoidance constraints. Using the closed-form conditions, we propose a traversability algorithm to determine the path existence between two given points on the polygonal chain. Correspondingly, a path generation approach is discussed to generate an optimal constrained hopping path with minimum number of intermediate hops and least take-off speed per hop. Applicability and viability of the proposed algorithms are demonstrated through computer simulations in a realistic terrain scenario with robot jumping motion uncertainties and disturbances.

Tailings dam safety monitoring and early warning based on spatial evolution process of mud-sand flow

Analyze the spatial evolution process of the mud-sand flow and reasonably judge and estimate the mud-sand flow disaster after tailings dam-break are the premise for the construction and safety management of tailings ponds. In this paper, mainly focus on tailings dam safety monitoring and early warning by establishing three dimensional according to real terrain and the present situation of backfilling stockpiling. Take Qinglong tailing dam as example, the mud-sand flow hazard scope, extent, and spatial state after dam-broken of expanded were simulated and analyzed through a flood and debris flow numerical simulation approach, and it is concluded that the disaster area downstream village of sand flow velocity, flow depth, the influence of the impact, demonstrates the expansion of heightening the feasibility of tailings dam project, and the hazard risk grade of different spatial locations of downstream village was obtained from the simulation. The spatial simulation and analysis have provided the basis to make more reasonable engineering decision, protection measure design, downstream disaster management, emergency evacuation, emergency rescue and response for villages after the expansion of the tailing dam, and also provided the technical support for tailing dam-break accident prevention, the safety management of tailing dam and the mine production safety.

PSD – probabilistic algorithm for mobile robot 6D localization without natural and artificial landmarks based on 2.5D map and a new type of laser scanner in GPS-denied scenarios

This paper presents an approach to mobile robot 6D localization based on a 3D laser scanner in GPS-denied scenarios. Commonly, 6D localization using laser scanners is performed with the use of extraction and association of the features or by comparison of the whole scans (very often off-line) using the ICP algorithm or its modifications. However, in some unstructured non-urbanized rough terrain environments, feature extraction does not seem to be reliable enough. For such kind of environment, we present a new method to mobile robot localization in GPS-denied applications, called PSD (Point-to-Surfel Distance). Unlike state of the art localization methods using laser scanners, we consider every single laser scanner measurement as an observation and use Point-to-Surfel Distance for correction of position and orientation of the robot. Mobile robot localization is based on a specific representation of the terrain in the 2.5D surfel map (terrain height and inclination). The simulation tests compared our method using extended Kalman filter (EKF) and single laser scanner measurements with an up-to-date method using particle filter (PF) and comparing the scan lines with the reference map and with another method using Gaussian mixture maps. The tests confirmed that the proposed method provides satisfying results for GPS-denied scenarios in rough terrain without extractable landmarks and our method is thirty times faster than the PF method (serial implementation). KITTI benchmark tests and real terrain experiments confirmed its usefulness and advantages as well.

Modeling the Seismic Response of Unstable Rock Mass With Deep Compliant Fractures

AbstractAn experimental quantification of the strength and volume of real, heterogeneous, fractured rock masses is crucial when assessing rock slope stability. In order to quantitatively characterize the internal structure of fractured rock slopes, we present three‐dimensional numerical simulations of seismic wave propagation and compare with observations. We introduce a simple, effective model for fractured rock mass, which can easily be applied to simulate weak‐motion seismic wave propagation. The macroscopic compliant fractures cutting the rock mass are modeled as finite‐width zones of reduced elastic parameters characterized by shear and normal stiffness. The widths of such zones are not fixed and can be adjusted to fit the grid step in the numerical method. The proposed rock mass model is applied and tested for the Walkerschmatt site in southwest Switzerland. Synthetic ambient vibrations are generated using a finite‐difference method for the fractured rock mass, shaped by the real terrain geometry, and compared with the measurements. The observed seismic response is satisfactorily reproduced in a broad frequency range (0.5–10 Hz). The synthetized response is primarily controlled by the stiffness, depth, number of fractures, and inertial mass of the fractured rock. The simulated amplification and ground‐motion directionality correspond with the observed levels, unless (1) the simplified cracks reach depths of 200–300 m; and (2) the fracture network is larger with respect to the mapped network. This illustrates the potential of ambient vibration methods in combination with numerical simulations to infer depth, volume, and mechanical characteristics of slope instability.

Construction and optimization method of the open-pit mine DEM based on the oblique photogrammetry generated DSM

The digital surface model (DSM) of open-pit mines generated by oblique photogrammetry has a large amount of data and much interference information. Therefore, it is necessary to construct a 3D model with a small amount of data that can reflect the real terrain of open-pit mines. The model should adapt to the existing 3D mining software and provide a guarantee for the subsequent production planning and open-pit mine design. Taking three different complexity scenes in two open-pit mines with 1:500 mapping scale as experimental objects, we realized the DEM construction of the DSM in different scenarios in open-pit mines. The extraction completeness of mining equipment in the DSM using this method is 94.7%. The data can be compressed to approximately 0.02% of the original data. The accuracy of 210 check points in the model is consistent with the industry standard. The DEM model can be quickly imported into 3D mining software.

Ground effects on sonic boom reflection

Impact of a real terrain on the sonic boom signature at the ground has been little studied in the literature. In the current prediction schemes, a flat and perfectly reflecting ground is usually assumed and the reflected boom is obtained by multiplying the incident boom by a constant factor. In this paper, the effects of a non-flat and absorbing ground are investigated. For this, a numerical study is conducted. The 2-D Euler equations are solved in curvilinear coordinates using high-order finite difference schemes. Signatures of the incident boom typical of a classical N-wave and of a low boom are considered. The variability on the waveform at the ground induced by the terrain irregularities is studied for different characteristic length scales of the terrain.Impact of a real terrain on the sonic boom signature at the ground has been little studied in the literature. In the current prediction schemes, a flat and perfectly reflecting ground is usually assumed and the reflected boom is obtained by multiplying the incident boom by a constant factor. In this paper, the effects of a non-flat and absorbing ground are investigated. For this, a numerical study is conducted. The 2-D Euler equations are solved in curvilinear coordinates using high-order finite difference schemes. Signatures of the incident boom typical of a classical N-wave and of a low boom are considered. The variability on the waveform at the ground induced by the terrain irregularities is studied for different characteristic length scales of the terrain.

A comprehensive methodology to evaluate the performance of a cooperative wireless network

Performance evaluation of a cooperative wireless communication network depends on several parameters. Many of the studies, in fact, take a limited number of performance metrics individually to reach a conclusion about the performance of a network. Besides, in general, some performance metrics might be in conflict. Thus, ignoring the combined effect of all performance criteria in the network may lead to an incorrect conception of the overall communication performance of the network. Therefore, in this study, a comprehensive evaluation methodology in terms of various metrics is proposed to calculate the performance of a cooperative wireless communication network deployment using a real terrain map. The proposed methodology, based on desirability functions, is discussed in terms of signal quality, signal quality with hopping, average number of hopping, hopping duty, and deployment altitude. In addition to individual scores for each performance criterion, an overall performance score is also obtained. Furthermore, the effects of the desirability function's ambition factor, terrain characteristics, and connectivity requirement rate on the score are also presented. The simulation results show that the desirability function-based performance evaluation approach could support a flexible evaluation as well as provide an agreement on the conflicting performance metrics.

Flood-Risk Analysis on Terrains under the Multiflow-Direction Model

An important problem in terrain analysis is modeling how water flows across a terrain and creates floods by filling up depressions. In this article, we study a number of flood-risk related problems: Given a terrain Σ, represented as a triangulated xy -monotone surface with n vertices, a rain distribution R , and a volume of rain ψ, determine which portions of Σ are flooded. We develop efficient algorithms for flood-risk analysis under the multiflow-directions (MFD) model, in which water at a point can flow along multiple downslope edges and which more accurately represent flooding events. We present three main results: First, we present an O ( n log n )-time algorithm to answer a terrain-flood query: if it rains a volume ψ according to a rain distribution R , determine what regions of Σ will be flooded. Second, we present a O ( n log n + nm )-time algorithm for preprocessing Σ containing m sinks into a data structure of size O ( nm ) for answering point-flood queries: Given a rain distribution R , a volume of rain ψ falling according to R , and point q ∈ Σ, determine whether q will be flooded. A point-flood query can be answered in O (| R | k + k 2 ) time, where k is the number of maximal depressions in Σ containing the query point q and | R | is the number of vertices in R with positive rainfall. Finally, we present algorithms for answering a flood-time query : given a rain distribution R and a point q ∈ Σ, determine the volume of rain that must fall before q is flooded. Assuming that the product of two k × k matrices can be computed in O ( k ω ) time, we show that a flood-time query can be answered in O ( nk + k ω ) time. We also give an α-approximation algorithm, for α > 1, which runs in O ( n log n log α ρ)-time, where ρ is a variable on the terrain that depends on the ratio between depression volumes. We implemented our algorithms for computing terrain and point-flood queries as well as approximate flood-time queries. We tested the efficacy and efficiency of these algorithms on three real terrains of different types (urban, suburban, and mountainous.)

The application of artificial immune algorithm to earthquake relief route planning

After an extreme earthquake attacks an urban area with many mountains, the main objective of a search and rescue operation is to minimize the number of fatalities. Therefore the task of transportation rescue resources to operational areas is of great importance to disaster managers. This paper presents a quick path planning method based on Artificial Immune Algorithm (AIA) and helicopter operation performance in order to design an optimal path for an operational area. First, a simulation of an earthquake is implemented in environment only including terrain threat. Second, a more complex model contains terrain, weather, building and communication threats simulation is executed and the resulting performance measures are evaluated by considering the survival time and total value for taken out entrapped occupants in the disaster area. Additionally, the best parameters of planning path for dual helicopters to an operational area are determined. Further work will be dedicated to adding real 3D terrain model into the current threat model.

Support vector machine based real-time terrain estimation for tracked robots

This paper describes the use of support vector machine (SVM) classifier for real-time terrain estimation to improve autonomous navigation of tracked mobile robots. Real-time terrain identification and terrain property estimation has been explored previously for application on a wide range of systems from planetary exploration rovers to commercial vehicles like cars and trucks. A majority of the existing methods rely on the use of dedicated sensors including vibration sensors, accelerometers, cameras, LIDAR, etc., which makes them susceptible to the failure modes of each of these sensors. This work proposes a method for real-time classification of different terrain types based on the state evolution of a ground robot, specifically the measured change in the pose of the robot for a known control input. By using a trained SVM to perform terrain estimation based on the collected state evolution data, the proposed method does not require dedicated sensing modalities solely for the terrain estimation. In addition, this method is generally applicable in all conditions where the robot can traverse. The training data was obtained from four different terrain conditions including vinyl flooring, asphalt, artificial turf, and grass–gravel, to train the SVM to perform terrain estimation. The proposed technique is validated using a skid-steer tracked robot over multiple simulated and real terrain transitions cases, where the response to control inputs is significantly affected by terrain characteristics. The results show that the proposed method provides greater than 80% accuracy in all cases, with fast detection of terrain transitions. The paper concludes with a detailed description on the application of real-time terrain estimation in improving autonomous navigation.

Pathfinding in hierarchical representation of large realistic virtual terrains for simulation systems

A prominent pathfinding challenge is the fast computation of path plans in large virtual terrain environments used in simulation systems. Based on a hierarchical approach for pathfinding and terrain representation, this work details the design, the implementation and the test of a quadtree-based structure in the irregular grid navigation map representation of large realistic virtual terrain environments. To achieve this goal, it is described how a hierarchical global A* pathfinding algorithm searches for a path in a coarse initial irregular grid structure then proceeding with the search in refined regions of interest where obstacles are found. Thus, the proposed solution presents as major contribution the enhanced quadtree-based map representation for pathfinding in large virtual terrains. The pathfinding response time of this solution is statistically compared with different hierarchical/non-hierarchical and regular/irregular terrain representation structures instantiated in the modeling of “small” realistic terrain scenarios. After these experiments, similar ones are developed in a massive (large) virtual terrain inserted into a real-life simulation system for the development of military tactical training exercises. The results show that the response time required to generate pathfinding results can be reduced when the proposed global pathfinding technique over the quadtree-based hierarchical and irregular navigation map representation of the large virtual terrain is explored in the development of simulation systems.

Contour Lines Generation in Karstic Plateaus for Topographic Maps

Abstract. Contour lines are a key features of topographic maps as they make the comprehension of terrain more easy. But they are no longer drawn by cartographers, they are mostly automatically derived from digital terrain models. Despite real progress in this automated derivation, some specific terrain landscapes remain incorrectly depicted with such techniques, and this is the case for karstic plateaus full of sinkholes. This paper proposes a specific automated method to derive better contour lines in plateaus, particularly around sinkholes. The process first detects karstic plateaus with many sinkholes, as well as the individual sinkholes. Then, the DTM is smoothed to better reflect the terrain in the plateau and in its surroundings. As a third step, the contour lines around sinkholes are enhanced to draw legible round features that better reflect the real terrain. The process was implemented in a QGIS plugin and tested on a small area with a karstic plateau in the Jura mountain in France, and the cartographers of IGN, the French national mapping agency assessed the results as a great improvement compared to the generic automated process to derive contour lines.

Phase unwrapping method based on improved quadratic pseudo-Boolean optimization.

Maximum a posteriori estimation of Markov random fields (MRFs) is a popular research area in computer vision, and many algorithms have been proposed to deal with these types of problems. The phase-unwrapping problem is modeled as the optimization of MRFs in this research, and the binary algorithm, improved quadratic pseudo-Boolean optimization, is utilized to solve the phase-unwrapping problem. Both the interferometric phases generated from the commonly used computer simulated surfaces and also real terrains are researched in the experimental section, and the unwrapping results are compared. The proposed algorithm achieves unwrapping results comparable to the state-of-the-art unwrapping method but costs less time for large-scale phase images.

Numerical study of wind turbine wakes over escarpments by a modified delayed detached eddy simulation

The wake of wind turbine in a complex terrain site is investigated by a modified delayed detached eddy simulation (MDDES) and a hybrid framework to predict the wind turbine wake effects in a real wind farm are presented. The wind field and turbine wake flows over the real terrain are simulated for different directions and validated by comparing with those measured by a LiDAR in the wind farm. Subsequently, the wake characteristics over the escarpment are systematically investigated by numerical simulations and the terrain effects on the turbine wake flow are clarified. A hybrid framework is then utilized for a wind farm over complex terrain. In this framework, the effects of local terrain and surface roughness on the wind speed, wind direction and turbulence intensity are taken into account by the numerical simulation, while the wind turbine wakes are represented by a new Gaussian-based analytical wake model. Finally, the applicability of the proposed framework is verified by comparison with the numerical simulation results of wake over the escarpment.