3D Routing Research Articles

Geological Heritage in the “Arribes del Duero” Natural Park (Western, Spain): A Case Study of Introducing Educational Information via Augmented Reality and 3D Virtual Itineraries

The concept of geological heritage has been introduced into the protected area of the Arribes del Duero Natural Park, which is west of the Salamanca and Zamora Provinces, Spain for the purpose of developing a guide to places of geological and geomorphological interest, through which geoenvironmental itineraries were developed in order to demonstrate to both the students and tourists, the geological context of the events in the geological history of this natural park. Twelve of the most geologically representative geosites were assessed using 18 quantitative parameters dealing with the scientific, didactic and cultural-tourist interest of each site. The objective of this paper is to describe and analyze the points of interest that are of geoheritage significance and to develop of an inventory that will ultimately facilitate geoconservation and the dissemination of information through educational virtual itineraries that reveal the known geological history of an area. A 3D virtual geological route was created in Google Earth for educational use with superimposed georeferenced cartographies, together with a field guide and an app. The virtual route allows the participants to follow the geological events and the natural history of the park using digital devices in real time with the possibility of observing the relief, the geology and having access to the informative files describing each geosite. Using a field guide, each geosite is complemented with activities, and the participants have the option to evaluate what has been learned. An app makes the itinerary more interactive. These georesources allow a teaching–learning process where the student is an active part of the development and creation of the contents using technologies that provide an entertaining and didactic learning experience, and this involves working as a team and interacting with social networks, thus, potentially influencing the attitudes and skills development that are involved in geoconservation as an element for its sustainable development. The identification of geological heritage currently constitutes a great resource to promote the sustainable development of it and employment in very depopulated rural areas.

Research on the Symbolic 3D Route Scene Expression Method Based on the Importance of Objects

In the study of 3D route scene construction, the expression of key targets needs to be highlighted. This is because compared with the 3D model, the abstract 3D symbols can reflect the number and spatial distribution characteristics of entities more intuitively. Therefore, this research proposes a symbolic 3D route scene representation method based on the importance of the object. The method takes the object importance evaluation model as the theoretical basis, calculates the spatial importance of the same type of objects according to the spatial characteristics of the geographical objects in the 3D route scene, and constructs the object importance evaluation model by combining semantic factors. The 3D symbols are then designed in a hierarchical manner on the basis of the results of the object importance evaluation and the CityGML standard. Finally, the LOD0-LOD4 symbolic 3D railway scene was constructed on the basis of a railroad data to realise the multi-scale expression of symbolic 3D route scene. Compared with the conventional loading method, the real-time frame rate of the scene was improved by 20 fps and was more stable. The scene loading speed was also improved by 5–10 s. The results show that the method can effectively improve the efficiency of the 3D route scene construction and the prominent expression effect of the key objects in the 3D route scene.

Wireless power transfer based on 2D routing

In this paper, a dual-frequency wireless power transfer method is proposed, capable of achieving controllable routing and providing power through magnetic coupling resonance to various positions on a two-dimensional plane. The plane is composed of multiple power supply units with a uniform structure. Every unit has two different resonant states to switch, an activated state to power the receiver and a low-power inactive state adopted to maintain power required for state-switching. By switching and combining units in different states through wireless control circuits, directional wireless transfer of power on the plane can be realized. The circuit of power transfer through coupling is modelled and analysed. Electromagnetic simulations are conducted, followed by implementation and test of an experimental system. Both single-receiver and multiple-receiver situations are applicable in this method. The highest transmission efficiency can reach 93.3% under single receiver situation after coupling 5 units, which reveals satisfactory ability in flexibility and efficiency. Embedded in multiple application scenes, we envision further possibilities of this method such as indoor-device wireless charging and free-moving robot charging systems in factories.

UAV safe route planning based on PSO-BAS algorithm

In order to solve the current situation that unmanned aerial vehicles (UAVs) ignore safety indicators and cannot guarantee safe operation when operating in low-altitude airspace, a UAV route planning method that considers regional risk assessment is proposed. Firstly, the low-altitude airspace is discretized based on rasterization, and then the UAV operating characteristics and environmental characteristics are combined to quantify the risk value in the low-altitude airspace to obtain a 3D risk map. The path risk value is taken as the cost, the particle swarm optimization-beetle antennae search (PSO-BAS) algorithm is used to plan the spatial 3D route, and it effectively reduces the generated path redun dancy. Finally, cubic B-spline curve is used to smooth the plan ned discrete path. A flyable path with continuous curvature and pitch angle is generated. The simulation results show that the generated path can exchange for a path with a lower risk value at a lower path cost. At the same time, the path redundancy is low, and the curvature and pitch angle continuously change. It is a flyable path that meets the UAV performance constraints.

Microstructural Development of Ti-6Al-4V Alloy via Powder Metallurgy and Laser Powder Bed Fusion

A detailed study was carried out to gain a better understanding of the microstructural differences between Ti-6Al-4V parts fabricated via the conventional powder metallurgy (PM) and the laser powder bed fusion (L-PBF) 3D printing routes. The parts were compared in terms of the constituent phases in the microstructure and their effects on the micro- and nano-hardness. In L-PBF parts, the microstructure has a single phase of martensitic α′ with hcp crystal structure and acicular laths morphology, transformed from prior parent phase β formed upon solidification of the melt pool. However, for the sintered parts via powder metallurgy, two phases of α and β are noticeable and the microstructure is composed of α grains and α + β Lamellae. The microhardness of L-PBF processed Ti-6Al-4V samples is remarkably higher than that of the PM samples but, surprisingly, the nano-hardness of the bulk martensitic phase α′ (6.3 GPa) is almost the same as α (i.e., 6.2 GPa) in PM samples. This confirms the rapid cooling of the β phase does not have any effect on the hardening of the bulk martensitic hcp α′. The high microhardness of L-PBF parts is due to the fine lath morphology of α′, with a large concentration of low angle boundaries of α′. Furthermore, it is revealed that for the α phase in PM samples, a higher level of vanadium concentration lowers the nano-hardness of the α phase. In addition, as expected, the compacting pressure and sintering temperature during the PM process led to variations in the porosity level as well as the microstructural morphology of the fabricated specimens, which will in turn have a significant effect on the mechanical properties.

Determination of Point-to-Point 3D Routing Algorithm Using LiDAR Data for Noise Prediction

Urban planning, noise propagation modelling, viewshed analysis, etc., require determination of routes or supply lines for propagation. A point-to-point routing algorithm is required to determine the best routes for the propagation of noise levels from source to destination. Various optimization algorithms are present in the literature to determine the shortest route, e.g., Dijkstra, Ant-Colony algorithms, etc. However, these algorithms primarily work over 2D maps and multiple routes. The shortest route determination in 3D from unlabeled data (e.g., precise LiDAR terrain point cloud) is very challenging. The prediction of noise data for a place necessitates extraction of all possible principal routes between every source of noise and its destination, e.g., direct route, the route over the top of the building (or obstruction), routes around the sides of the building, and the reflected routes. It is thus required to develop an algorithm that will determine all the possible routes for propagation, using LiDAR data. The algorithm uses the novel cutting plane technique customized to work with LiDAR data to extract all the principal routes between every pair of noise source and destination. Terrain parameters are determined from routes for modeling. The terrain parameters, and noise data when integrated with a sophisticated noise model give an accurate prediction of noise for a place. The novel point-to-point routing algorithm is developed using LiDAR data of the RGIPT campus. All the shortest routes were tested for their spatial accuracy and efficacy to predict the noise levels accurately. Various routes are found to be accurate within ±9 cm, while predicted noise levels are found to be accurate within ±6 dBA at an instantaneous scale. The novel accurate 3D routing algorithm can improve the other urban applications too.

Physical Security Roadmap for Heterogeneous Integration Technology

Abstract Interposers play an important role in 2.5D and 3D packages, routing power and communication signals between dies while maintaining electrical contact with I/O pins. This role and their relatively simple construction makes interposers a target for malicious attacks. In this article, the authors assess the vulnerabilities inherent in the fabrication of interposers and describe various types of optical attacks along with practical countermeasures.

Adaptive 3D routing protocol for flying ad hoc networks based on prediction-driven Q-learning

The routing protocols are paramount to guarantee the Quality of Service (QoS) for Flying Ad Hoc Networks (FANETs). However, they still face several challenges owing to high mobility and dynamic topology. This paper mainly focuses on the adaptive routing protocol and proposes a Three Dimensional Q-Learning (3DQ) based routing protocol to guarantee the packet delivery ratio and improve the QoS. In 3DQ routing, we propose a Q-Learning based routing decision scheme, which contains a link-state prediction module and routing decision module. The link-state prediction module allows each Unmanned Aerial Vehicle (UAV) to predict the link-state of Neighboring UAVs (NUs), considering their Three Dimensional mobility and packet arrival. Then, UAV can produce routing decisions with the help of the routing decision module considering the link-state. We evaluate the various performance of 3DQ routing, and simulation results demonstrate that 3DQ can improve packet delivery ratio, goodput and delay of baseline protocol at most 71.36%, 89.32% and 83.54% in FANETs over a variety of communication scenarios.

Research and Application of Intelligent Layout Design Algorithm for 3D Pipeline of Nuclear Power Plant

The pipeline layout design of nuclear power plant is to find the optimal route to meet the objectives and constraints in the 3D routing space. However, due to the intensive equipment and complex structure of the nuclear power plant, various types of pipeline systems, complex layout constraints, and a large number of pipelines, even for experienced designers, pipeline layout is a difficult and time-consuming task. In order to solve the problem of the automatic layout of pipeline in 3D routing space of nuclear power plant, a pipeline automatic routing method combining Dijkstra algorithm in large space and improved A∗algorithm in local space is proposed in this paper. Firstly, the method identifies the key vertices of each room in the nuclear power plant, constructs the topological routing map, and determines the preliminary passage area of the pipeline through the traditional Dijkstra algorithm. Secondly, the space of the layout area is divided into 3D grids, and then the items in the area are identified and preprocessed. Finally, the 3D pipeline routing environment is established through AABB-OBB hybrid collision detection technology. On this basis, the improved method of A∗evaluation function is given to satisfy the pipeline layout constraints and improve the search efficiency. Through experiments, the effectiveness of this method is proved. This method can quickly and automatically route the nuclear power pipelines that meet the requirements of the engineering, which greatly improves the efficiency of 3D pipeline layout design for the nuclear power plant.

An Anti-Disturbance Resilience Enhanced Algorithm for UAV 3D Route Planning.

Considering that the actual operating environment of UAV is complex and easily disturbed by the space environment of urban buildings, the RoutE Planning Algorithm of Resilience Enhancement (REPARE) for UAV 3D route planning based on the A* algorithm and artificial potential fields algorithm is carried out in a targeted manner. First of all, in order to ensure the safety of the UAV design, we focus on the capabilities of the UAV body and build a risk identification, assessment, and modeling method such that the mission control parameters of the UAV can be determined. Then, the three-dimensional route planning algorithm based on the artificial potential fields algorithm is used to ensure the safe operation of the UAV online and in real time. At the same time, by adjusting the discriminant coefficient of potential risks in real time to deal with time-varying random disturbance encountered by the UAV, the resilience of the UAV 3D flight route planning can be improved. Finally, the effectiveness of the algorithm is verified by the simulation. The simulation results show that the REPARE algorithm can effectively solve the traditional route planning algorithm’s insufficiency in anti-disturbance. It is safer than a traditional A* route planning algorithm, and its running time is shorter than that of the traditional artificial potential field route planning algorithm. It solves the problems of local optimization, enhances the UAV’s ability to tolerate general uncertain disturbances, and eventually improves resilience of the system.

Asymmetric Crosstalk Harnessed Signaling for Large 3D Routing Integration

This paper presents a high level of integration for parallel source-synchronous interfaces using Asymmetric Crosstalk Harnessed Signaling (ACHS) on 3D routing environments. ACHS is shown to successfully overcome the high noise susceptibility related to the common encoding eigenmode present in the original Crosstalk Harnessed Signaling (CHS) scheme, with a small routing overhead. In this study, a bus design case is presented where multiple channels are wired together in a 3D routing environment by a multi-stripline stackup. CHS and ACHS performances are compared using the same routing realestate availability; ACHS shows a far superior performance due to the absence of the common encoding mode. The best performing eigenmodes are applied to the strobe encoding to achieve very good integrity for this critical signal.

Inductor Design for Nonisolated Critical Soft Switching Converters Using Solid and Litz PCB and Wire Windings Leveraging Neural Network Model

High frequency and high efficiency inductor design method is proposed for the application of critical soft switching with large current ripple to improve the power density and efficiency of electrified energy conversion systems. Firstly for the theoretical design section, the core/coil size, number of turns, airgap, inductance are optimized to minimize the inductor losses. Secondly for the structural design section of coil, a 3D routing method of litz PCB winding is developed to reduce the AC copper losses. The strand number, trace width, thickness and layout of litz PCB are analyzed in detail. Different types of coil, including solid/litz types of PCB/wire windings, are compared and analyzed based on the high frequency copper loss reduction and space utilization. For the structural design section of core, E and I cores are optimized to reduce the volume and core losses. Specifically, E-E, E-I, I-I and E-Air types of core structures are designed and compared considering the core loss, volume reduction and airgap limitation for the stack of turns. Ten derived prototypes are built to benchmark with the commercial inductors. Power losses, temperature rise and cost are reduced by a factor of 10, 2.5 and 3 with the proposed core and coil structures.

A Brief Review of Recent Developments in the Integration of Deep Learning with GIS

The interaction of Deep Learning (DL) methods with Geographical Information System (GIS) provides the opportunity to obtain new insights into environmental processes through the spatial, temporal and spectral resolutions as well as data integration. The two technologies may be connected to form a dynamic system that is incredibly well adapted to the evaluation of environmental conditions through the interrelationships of texture, size, pattern, and process. This perspective has acquired popularity in multiple disciplines. GIS is significantly dependant on processors, particularly for 3D calculations, map rendering, and route calculation whereas DL can process huge amounts of data. DL has received a lot of attention recently as a technology with a plethora of promising results. Furthermore, the growing use of DL methods in a variety of disciplines, including GIS, is evident. This study tries to provide a brief overview of the use of DL methods in GIS. This paper introduces the essential DL concepts relevant to GIS, the majority of which have been published in recent years. This research explores remote sensing applications and technologies in areas such as mapping, hydrological modelling, disaster management, and transportation route planning. Finally, conclusions on contemporary framework methodologies and suggestions for further studies are provided.

Disentangled Capsule Routing for Fast Part-Object Relational Saliency.

Recently, the Part-Object Relational (POR) saliency underpinned by the Capsule Network (CapsNet) has been demonstrated to be an effective modeling mechanism to improve the saliency detection accuracy. However, it is widely known that the current capsule routing operations have huge computational complexity, which seriously limited the usability of the POR saliency models in real-time applications. To this end, this paper takes an early step towards a fast POR saliency inference by proposing a novel disentangled part-object relational network. Concretely, we disentangle horizontal routing and vertical routing from the original omnidirectional capsule routing, thus generating Disentangled Capsule Routing (DCR). This mechanism enjoys two advantages. On one hand, DCR that disentangles orthogonal 1D (i.e., vertical and horizontal) routing greatly reduces parameters and routing complexity, resulting in much faster inference than omnidirectional 2D routing adopted by existing CapsNets. On the other hand, thanks to the light POR cues explored by DCR, we could conveniently integrate the part-object routing process to different feature layers in CNN, rather than just applying it to the small-scaled one as in previous works. This helps to increase saliency inference accuracy. Compared to previous POR saliency detectors, DPORTNet infers visual saliency (5 ∼9 ) × faster, and is more accurate. DPORTNet is available under the open-source license at https://github.com/liuyi1989/DCR.

Hyperspectral image classification with deep 3D capsule network and Markov random field

To address the existing problems of capsule networks in deep feature extraction and spatial-spectral feature fusion of hyperspectral images, this paper proposes a hyperspectral image classification method that combines a deep residual 3D capsule network and Markov random field. Based on this method, the deep spatial-spectral features of hyperspectral images are extracted using the deep residual 3D convolutional structure, the vector capsules of the features are obtained by the initial capsule layer and mapped into probability capsules via the 3D dynamic routing mechanism to construct the classification probability map, and the spatial structure of the classification results is regularised by the Markov random field to further improve the classification accuracy and performance of the images. Two sets of benchmark hyperspectral images, namely Indian Pines and Pavia University data sets, were used to conduct comparative experiments and ablation study. The experimental results showed that, compared with the conventional convolutional neural network and existing capsule network models, the proposed method not only improves the classification accuracy of the images but also partly eliminates the category noise and affords a more regular classification probability map.

3D Aerial Highway: The Key Enabler of the Retail Industry Transformation

The retail industry is facing an inevitable transformation worldwide, which is accelerating with the current pandemic situation. Indeed, consumer habits are shifting from brick-and-mortar stores to online shopping. The bottleneck in the online shopping experience remains efficient and fast delivery to consumers. In this context, unmanned aerial vehicle (UAV) technology is seen as a potential solution to address cargo delivery issues. Hence, the number of cargo UAVs is expected to increase in the next few decades and the airspace to become crowded. To successfully deploy UAVs for mass cargo delivery, seamless and reliable cellular connectivity for cargo UAVs is required. Thus, organized and “connected” routes in the sky are needed. Like highways for vehicles, 3D routes in the airspace should be designed to fulfill cargo UAV operations safely and efficiently. We refer to these routes as “3D aerial highways.” In this article, we investigate the feasibility of the aerial highways paradigm. First, we discuss the related motivations and concerns. Then we present our aerial highways paradigm design. Finally, we present linked connectivity issues and potential solutions.

From Multi-Agent Pathfinding to 3D Pipe Routing

The 2D Multi-Agent Path Finding (MAPF) problem aims at finding collision-free paths for a number of agents, from a set of start locations to a set of goal positions in a known 2D environment. MAPF has been studied in theoretical computer science, robotics, and artificial intelligence over several decades, due to its importance for robot navigation. It is currently experiencing significant scientific progress due to its relevance in automated warehousing (such as those operated by Amazon) and in other contemporary application areas. In this paper, we demonstrate that some recently developed MAPF algorithms apply more broadly than currently believed in the MAPF research community. In particular, we describe the 3D Pipe Routing (PR) problem, which aims at placing collision-free pipes from given start locations to given goal locations in a known 3D environment. The MAPF and PR problems are similar: a solution to a MAPF instance is a set of blocked cells in x-y-t space, while a solution to the corresponding PR instance is a set of blocked cells in x-y-z space. We show how to use this similarity to apply several recently developed MAPF algorithms to the PR problem, and discuss their performance on real-world PR instances. This opens up a new direction of industrial relevance for the MAPF research community.

A 3D printing route to fabrication of ZrCuSi alloy target for ZrCuSiN nanocomposite thin films

The present study demonstrates a simple and robust strategy for fabricating nanocomposite thin films with high quality using a multi-component ZrCuSi single target. The ZrCuSi target was produced by using computer numerical control (CNC) based direct energy deposition (i.e., 3D printing). The influence of the energy density on morphological features and porosity of the ZrCuSi target surface was closely examined at a certain range of the energy density (75–225 J/mm3). X-ray diffractometer (XRD) and scanning electron microscopy (SEM) were applied for confirming the presence of the preferable crystallographic orientation and elucidating the morphological features of the nanocomposite target. In addition, functional nanocomposite thin films deposited from the ZrCuSi target presented in the current study were characterized. A scratch test and field-emission SEM (FE-SEM) revealed the adhesion properties and the morphological features of the nanocomposite coatings. Therefore, this work is highly expected to provide a facile and robust way to fabrication of e multi-component functional targets based ZrN, thereby envisioning usefulness of the nanocomposite coatings for automotive engine parts and various other wear protection applications.

Landing route planning method for micro drones based on hybrid optimization algorithm

Aiming at the obstacle avoidance trajectory planning problem in the landing process of the micro drone, this paper proposes a swarm optimization algorithm that combines the dragonfly optimization method and the differential evolution method. The orthogonal learning mechanism is adopted to realize the adaptive switch between the two algorithms. In the process of landing route planning, the planning plane is first obtained by making the gliding plane tangent to the obstacle. In the planning plane, the projection of obstacle is transformed into multiple unreachable line segments. By designing an optimization model, the 3D landing route planning problem is transformed into a 2D obstacle avoidance route optimization problem. Taking the shortest route as the optimization objective, the penalty factor is introduced into the cost function to avoid the intersection of the landing route and obstacle. During the optimization process, through the orthogonal learning of the intermediate iterative results, the hybrid algorithm can adaptively select the next iterative algorithm, so it can give full play to the respective advantages of the two algorithms. The optimization results show that, compared with the single optimization algorithm, the hybrid optimization algorithm proposed in this paper can better solve the problem of landing route planning for micro-small UAVs.

Self-sensing impact damage in and non-destructive evaluation of carbon fiber-reinforced polymers using electrical resistance and the corresponding electrical route models

Carbon fiber-reinforced plastics (CFRPs) made of uni-directional carbon fibers (UDCFs) are used in various applications such as construction, aerospace, and automobiles. Therefore, their structural health monitoring (SHM) and non-destructive evaluation (NDE) are important to ensure safety during operation. While there is literature on self-sensing of CFRPs to realize various properties, there is no information on their impact self-sensing properties. Therefore, in this study, CFRPs in several orientations were investigated in terms of their mechanical fracture and electromechanical behavior. Changes in their electrical resistance due to impact damage can be utilized for SHM using the corresponding electrically equivalent circuit models. The circuit models constructed consisted of electrical resistors that described the UDCFs. In addition to converting CFRPs into 2D circuits, 3D electrical routes between electrodes were proposed for NDE. Calculating the detour length of the electrical routes using the proposed models helps in assessing the severity of the impact damage. Therefore, the models for CFRPs developed in this study not only provide support for SHM but also for NDE using electrical resistance.