A Novel Real-Time Autonomous Crack Inspection System Based on Unmanned Aerial Vehicles.

Traditional methods on crack inspection for large infrastructures require a number of structural health inspection devices and instruments. They usually use the signal changes caused by physical deformations from cracks to detect the cracks, which is time-consuming and cost-ineffective. In this work, we propose a novel real-time crack inspection system based on unmanned aerial vehicles for real-world applications. The proposed system successfully detects and classifies various types of cracks. It can accurately find the crack positions in the world coordinate system. Our detector is based on an improved YOLOv4 with an attention module, which produces 90.02% mean average precision (mAP) and outperforms the YOLOv4-original by 5.23% in terms of mAP. The proposed system is low-cost and lightweight. Moreover, it is not restricted by navigation trajectories. The experimental results demonstrate the robustness and effectiveness of our system in real-world crack inspection tasks.

Transmission mitigation of COVID-19: Exhaled contaminants removal and energy saving in densely occupied space by impinging jet ventilation.

The pandemic of COVID-19 and its transmission ability raise much attention to ventilation design as indoor-transmission outstrips outdoor-transmission. Impinging jet ventilation (IJV) systems might be promising to ventilate densely occupied large spaces due to their high jet momentum. However, their performances in densely occupied spaces have rarely been explored. This study proposes a modified IJV system and evaluates its performance numerically in a densely occupied classroom mockup. A new assessment formula is also proposed to evaluate the nonuniformity of target species CO2. The infector is assumed as the manikin with the lowest tracer gas concentration in the head region. The main results include: a) Indoor air quality (IAQ) in the classroom is improved significantly compared with a mixing ventilation system, i.e., averaged CO2 in the occupied zone (OZ) is reduced from 1287 ppm to 1078 ppm, the OZ-averaged mean age of air is reduced from 439 s to 177 s; b) The mean infection probability is reduced from 0.047% to 0.027% with an infector, and from 0.035% to 0.024% with another infector; c) Cooling coil load is reduced by around 21.0%; d) Overall evaluation indices meet the requirements for comfortable environments, i.e., the temperature difference between head and ankle is within 3 °C and the OZ-averaged predictive mean vote is in the range of -0.5 - 0.5; e) Thermal comfort level and uniformity are decreased, e.g., overcooling near diffuser at ankle level. Summarily, the target system effectively improves IAQ, reduces exhaled-contaminant concentration in head regions, and saves energy as well.

Autonomous Exploration of Unknown Indoor Environments for High-Quality Mapping Using Feature-Based RGB-D SLAM.

Simultaneous localization and mapping (SLAM) system-based indoor mapping using autonomous mobile robots in unknown environments is crucial for many applications, such as rescue scenarios, utility tunnel monitoring, and indoor 3D modeling. Researchers have proposed various strategies to obtain full coverage while minimizing exploration time; however, mapping quality factors have not been considered. In fact, mapping quality plays a pivotal role in 3D modeling, especially when using low-cost sensors in challenging indoor scenarios. This study proposes a novel exploration algorithm to simultaneously optimize exploration time and mapping quality using a low-cost RGB-D camera. Feature-based RGB-D SLAM is utilized due to its various advantages, such as low computational cost and dense real-time reconstruction ability. Subsequently, our novel exploration strategies consider the mapping quality factors of the RGB-D SLAM system. Exploration time optimization factors are also considered to set a new optimum goal. Furthermore, a Voronoi path planner is adopted for reliable, maximal obstacle clearance and fixed paths. According to the texture level, three exploration strategies are evaluated in three real-world environments. We achieve a significant enhancement in mapping quality and exploration time using our proposed exploration strategies compared to the baseline frontier-based exploration, particularly in a low-texture environment.

Development of Fixed-Wing UAV 3D Coverage Paths for Urban Air Quality Profiling.

Due to the ever-increasing industrial activity, humans and the environment suffer from deteriorating air quality, making the long-term monitoring of air particle indicators essential. The advances in unmanned aerial vehicles (UAVs) offer the potential to utilize UAVs for various forms of monitoring, of which air quality data acquisition is one. Nevertheless, most current UAV-based air monitoring suffers from a low payload, short endurance, and limited range, as they are primarily dependent on rotary aerial vehicles. In contrast, a fixed-wing UAV may be a better alternative. Additionally, one of the most critical modules for 3D profiling of a UAV system is path planning, as it directly impacts the final results of the spatial coverage and temporal efficiency. Therefore, this work focused on developing 3D coverage path planning based upon current commercial ground control software, where the method mainly depends on the Boustrophedon and Dubins paths. Furthermore, a user interface was also designed for easy accessibility, which provides a generalized tool module that links up the proposed algorithm, the ground control software, and the flight controller. Simulations were conducted to assess the proposed methods. The result showed that the proposed methods outperformed the existing coverage paths generated by ground control software, as it showed a better coverage rate with a sampling density of 50 m.

Proactive Guidance for Accurate UAV Landing on a Dynamic Platform: A Visual-Inertial Approach.

This work aimed to develop an autonomous system for unmanned aerial vehicles (UAVs) to land on moving platforms such as an automobile or a marine vessel, providing a promising solution for a long-endurance flight operation, a large mission coverage range, and a convenient recharging ground station. Unlike most state-of-the-art UAV landing frameworks that rely on UAV onboard computers and sensors, the proposed system fully depends on the computation unit situated on the ground vehicle/marine vessel to serve as a landing guidance system. Such a novel configuration can therefore lighten the burden of the UAV, and the computation power of the ground vehicle/marine vessel can be enhanced. In particular, we exploit a sensor fusion-based algorithm for the guidance system to perform UAV localization, whilst a control method based upon trajectory optimization is integrated. Indoor and outdoor experiments are conducted, and the results show that precise autonomous landing on a 43 cm × 43 cm platform can be performed.

Dynamic Object Tracking on Autonomous UAV System for Surveillance Applications.

The ever-burgeoning growth of autonomous unmanned aerial vehicles (UAVs) has demonstrated a promising platform for utilization in real-world applications. In particular, a UAV equipped with a vision system could be leveraged for surveillance applications. This paper proposes a learning-based UAV system for achieving autonomous surveillance, in which the UAV can be of assistance in autonomously detecting, tracking, and following a target object without human intervention. Specifically, we adopted the YOLOv4-Tiny algorithm for semantic object detection and then consolidated it with a 3D object pose estimation method and Kalman filter to enhance the perception performance. In addition, UAV path planning for a surveillance maneuver is integrated to complete the fully autonomous system. The perception module is assessed on a quadrotor UAV, while the whole system is validated through flight experiments. The experiment results verified the robustness, effectiveness, and reliability of the autonomous object tracking UAV system in performing surveillance tasks. The source code is released to the research community for future reference.

Learning-Based Autonomous UAV System for Electrical and Mechanical (E&M) Device Inspection.

The inspection of electrical and mechanical (E&M) devices using unmanned aerial vehicles (UAVs) has become an increasingly popular choice in the last decade due to their flexibility and mobility. UAVs have the potential to reduce human involvement in visual inspection tasks, which could increase efficiency and reduce risks. This paper presents a UAV system for autonomously performing E&M device inspection. The proposed system relies on learning-based detection for perception, multi-sensor fusion for localization, and path planning for fully autonomous inspection. The perception method utilizes semantic and spatial information generated by a 2-D object detector. The information is then fused with depth measurements for object state estimation. No prior knowledge about the location and category of the target device is needed. The system design is validated by flight experiments using a quadrotor platform. The result shows that the proposed UAV system enables the inspection mission autonomously and ensures a stable and collision-free flight.

An Actuator Allocation Method for a Variable-Pitch Propeller System of Quadrotor-based UAVs.

This paper presents a control allocation method for enhancing the attitude following performance and the energy efficiency of a variable-pitch propeller (VPP) system on quadrotor-based unmanned aerial vehicles. The VPP system was modeled according to the blade element momentum (BEM) theory, and an actuator allocation method was developed with the aim of enhancing the attitude control and energy performance. A simulation environment was built to validate the VPP system by creating a thrust and moment database from the experiments. A four-motor variable-pitch quadrotor was built for verifying the proposed method. The control allocation method was firstly verified in a simulation environment, and was then implemented in a flight controller for indoor flight experiments. The simulation results show the proposed control allocation method greatly improves the yaw following performance. The experimental results demonstrate a difference in the energy consumption through various pitch angles, as well as a reduction in energy consumption, by applying this VPP system.

Perception in the Dark-Development of a ToF Visual Inertial Odometry System.

Visual inertial odometry (VIO) is the front-end of visual simultaneous localization and mapping (vSLAM) methods and has been actively studied in recent years. In this context, a time-of-flight (ToF) camera, with its high accuracy of depth measurement and strong resilience to ambient light of variable intensity, draws our interest. Thus, in this paper, we present a realtime visual inertial system based on a low cost ToF camera. The iterative closest point (ICP) methodology is adopted, incorporating salient point-selection criteria and a robustness-weighting function. In addition, an error-state Kalman filter is used and fused with inertial measurement unit (IMU) data. To test its capability, the ToF-VIO system is mounted on an unmanned aerial vehicle (UAV) platform and operated in a variable light environment. The estimated flight trajectory is compared with the ground truth data captured by a motion capture system. Real flight experiments are also conducted in a dark indoor environment, demonstrating good agreement with estimated performance. The current system is thus shown to be accurate and efficient for use in UAV applications in dark and Global Navigation Satellite System (GNSS)-denied environments.

Development of Model Predictive Controller for a Tail-Sitter VTOL UAV in Hover Flight.

This paper presents a model predictive controller (MPC) for position control of a vertical take-off and landing (VTOL) tail-sitter unmanned aerial vehicle (UAV) in hover flight. A 'cross' configuration quad-rotor tail-sitter UAV is designed with the capabilities for both hover and high efficiency level flight. The six-degree-of-freedom (DOF) nonlinear dynamic model of the UAV is built based on aerodynamic data obtained from wind tunnel experiments. The model predictive position controller is then developed with the augmented linearized state-space model. Measured and unmeasured disturbance model are introduced into the modeling and optimization process to improve disturbance rejection ability. The MPC controller is first verified and tuned in the hardware-in-loop (HIL) simulation environment and then implemented in an on-board flight computer for real-time indoor experiments. The simulation and experimental results show that the proposed MPC position controller has good trajectory tracking performance and robust position holding capability under the conditions of prevailing and gusty winds.

A Camera-Based Target Detection and Positioning UAV System for Search and Rescue (SAR) Purposes.

Wilderness search and rescue entails performing a wide-range of work in complex environments and large regions. Given the concerns inherent in large regions due to limited rescue distribution, unmanned aerial vehicle (UAV)-based frameworks are a promising platform for providing aerial imaging. In recent years, technological advances in areas such as micro-technology, sensors and navigation have influenced the various applications of UAVs. In this study, an all-in-one camera-based target detection and positioning system is developed and integrated into a fully autonomous fixed-wing UAV. The system presented in this paper is capable of on-board, real-time target identification, post-target identification and location and aerial image collection for further mapping applications. Its performance is examined using several simulated search and rescue missions, and the test results demonstrate its reliability and efficiency.

Development and Testing of a Two-UAV Communication Relay System.

In the development of beyond-line-of-sight (BLOS) Unmanned Aerial Vehicle (UAV) systems, communication between the UAVs and the ground control station (GCS) is of critical importance. The commonly used economical wireless modules are restricted by the short communication range and are easily blocked by obstacles. The use of a communication relay system provides a practical way to solve these problems, improving the performance of UAV communication in BLOS and cross-obstacle operations. In this study, a communication relay system, in which a quadrotor was used to relay radio communication for another quadrotor was developed and tested. First, the UAVs used as the airborne platform were constructed, and the hardware for the communication relay system was selected and built up. Second, a set of software programs and protocol for autonomous mission control, communication relay control, and ground control were developed. Finally, the system was fully integrated into the airborne platform and tested both indoor and in-flight. The Received Signal Strength Indication (RSSI) and noise value in two typical application scenarios were recorded. The test results demonstrated the ability of this system to extend the communication range and build communication over obstacles. This system also shows the feasibility to coordinate multiple UAVs' communication with the same relay structure.

An innovative numerical approach to resolve the pulse wave velocity in a healthy thoracic aorta model.

Aortic dissection and atherosclerosis are highly fatal diseases. The development of both diseases is closely associated with highly complex haemodynamics. Thus, in predicting the onset of cardiac disease, it is desirable to obtain a detailed understanding of the flowfield characteristics in the human cardiovascular circulatory system. Accordingly, in this study, a numerical model of a normal human thoracic aorta is constructed using the geometry information obtained from a phase-contrast magnetic resonance imaging (PC-MRI) technique. The interaction between the blood flow and the vessel wall dynamics is then investigated using a coupled fluid-structure interaction (FSI) analysis. The simulations focus specifically on the flowfield characteristics and pulse wave velocity (PWV) of the blood flow. Instead of using a conventional PC-MRI method to measure PWV, we present an innovative application of using the FSI approach to numerically resolve PWV for the assessment of wall compliance in a thoracic aorta model. The estimated PWV for a normal thoracic aorta agrees well with the results obtained via PC-MRI measurement. In addition, simulations which consider the FSI effect yield a lower predicted value of the wall shear stress at certain locations in the cardiac cycle than models which assume a rigid vessel wall. Consequently, the model provides a suitable basis for the future development of more sophisticated methods capable of performing the computer-aided analysis of aortic blood flows.

Numerical analysis of a rapid magnetic microfluidic mixer.

This paper presents a detailed numerical investigation of the novel active microfluidic mixer proposed by Wen et al. (Electrophoresis 2009, 30, 4179-4186). This mixer uses an electromagnet driven by DC or AC power to induce transient interactive flows between a water-based ferrofluid and DI water. Experimental results clearly demonstrate the mixing mechanism. In the presence of the electromagnet's magnetic field, the magnetic nanoparticles create a body force vector that acts on the mixed fluid. Numerical simulations show that this magnetic body force causes the ferrofluid to expand significantly and uniformly toward miscible water. The magnetic force also produces many extremely fine finger structures along the direction of local magnetic field lines at the interface in both upstream and downstream regions of the microchannel when the external steady magnetic strength (DC power actuation) exceeds 30 Oe (critical magnetic Peclet number Pe(m),cr = 2870). This study is the first to analyze these pronounced finger patterns numerically, and the results are in good agreement with the experimental visualization of Wen et al. (Electrophoresis 2009, 30, 4179-4186). The large interfacial area that accompanies these fine finger structures and the dominant diffusion effects occurring around the circumferential regions of fingers significantly enhance the mixing performance. The mixing ratio can be as high as 95% within 2.0 s. at a distance of 3.0 mm from the mixing channel inlet when the applied peak magnetic field supplied by the DC power source exceeds 60 Oe. This study also presents a sample implementation of AC power actuation in a numerical simulation, an experimental benchmark, and a simulation of DC power actuation with the same peak magnetic strength. The simulated flow structures of the AC power actuation agree well with the experimental visualization, and are similar to those produced by DC power. The AC and DC power actuated flow fields exhibited no significant differences. This numerical study suggests approaches to maximize the performance of the proposed rapid magnetic microfluidic mixer, and confirms its exciting potential for use in lab-on-a-chip systems.

Investigation of pulsatile flowfield in healthy thoracic aorta models.

Cardiovascular disease is the primary cause of morbidity and mortality in the western world. Complex hemodynamics plays a critical role in the development of aortic dissection and atherosclerosis, as well as many other diseases. Since fundamental fluid mechanics are important for the understanding of the blood flow in the cardiovascular circulatory system of the human body aspects, a joint experimental and numerical study was conducted in this study to determine the distributions of wall shear stress and pressure and oscillatory WSS index, and to examine their correlation with the aortic disorders, especially dissection. Experimentally, the Phase-Contrast Magnetic Resonance Imaging (PC-MRI) method was used to acquire the true geometry of a normal human thoracic aorta, which was readily converted into a transparent thoracic aorta model by the rapid prototyping (RP) technique. The thoracic aorta model was then used in the in vitro experiments and computations. Simulations were performed using the computational fluid dynamic (CFD) code ACE+((R)) to determine flow characteristics of the three-dimensional, pulsatile, incompressible, and Newtonian fluid in the thoracic aorta model. The unsteady boundary conditions at the inlet and the outlet of the aortic flow were specified from the measured flowrate and pressure results during in vitro experiments. For the code validation, the predicted axial velocity reasonably agrees with the PC-MRI experimental data in the oblique sagittal plane of the thoracic aorta model. The thorough analyses of the thoracic aorta flow, WSSs, WSS index (OSI), and wall pressures are presented. The predicted locations of the maxima of WSS and the wall pressure can be then correlated with that of the thoracic aorta dissection, and thereby may lead to a useful biological significance. The numerical results also suggest that the effects of low WSS and high OSI tend to cause wall thickening occurred along the inferior wall of the aortic arch and the anterior wall of the brachiocephalic artery, similar implication reported in a number of previous studies.

Rapid magnetic microfluidic mixer utilizing AC electromagnetic field.

This paper presents a novel simple micromixer based on stable water suspensions of magnetic nanoparticles (i.e. ferrofluids). The micromixer chip is built using standard microfabrication and simple soft lithography, and the design can be incorporated as a subsystem into any chemical microreactor or a miniaturized biological sensor. An electromagnet driven by an AC power source is used to induce transient interactive flows between a ferrofluid and Rhodamine B. The alternative magnetic field causes the ferrofluid to expand significantly and uniformly toward Rhodamine B, associated with a great number of extremely fine fingering structures on the interface in the upstream and downstream regions of the microchannel. These pronounced fingering patterns, which have not been observed by other active mixing methods utilizing only magnetic force, increase the mixing interfacial length dramatically. Along with the dominant diffusion effects occurring around the circumferential regions of the fine finger structures, the mixing efficiency increases significantly. The miscible fingering instabilities are observed and applied in the microfluidics for the first time. This work is carried with a view to developing functionalized ferrofluids that can be used as sensitive pathogen detectors and the present experimental results demonstrate that the proposed micromixer has excellent mixing capabilities. The mixing efficiency can be as high as 95% within 2.0 s and a distance of 3.0 mm from the inlet of the mixing channel, when the applied peak magnetic field is higher than 29.2 Oe and frequency ranges from 45 to 300 Hz.

Electrokinetic instability effects in microchannels with and without nanofilm coatings.

This paper presents a parametric experimental investigation into the electrokinetic instability (EKI) phenomenon within three different types of microfluidic device, namely T-type, cross-shaped, and cross-form with an expansion configuration. The critical electric field strength at which the EKI phenomenon is induced is examined as a function of the conductivity ratio, the microchannel width, the expansion ratio, and the surface treatment of the microchannel walls. It is found that the critical electric field strength associated with the onset of EKI is strongly dependent on the conductivity ratio of the two samples within the microfluidic device and reduces as the channel width increases. The surfaces of the microchannel walls are coated with hydrophilic or hydrophobic organic-based spin-on-glass (SOG) nanofilms for glass-based microchips. The experimental results indicate that no significant difference exists in the critical electric field strengths in the hydrophilic or hydrophobic SOG-coated microchannels, respectively. However, for a given conductivity ratio and microchannel width, the critical strength of the electric field is slightly lower in the SOG-coated microchannels than in the non-coated channels. In general, the results presented in this study demonstrate the potential for designing and controlling on-chip assays requiring the manipulation of samples with high conductivity gradients, and provide a useful general reference for avoiding EKI effects in capillary electrophoresis analysis applications.

Quantification of the pulse wave velocity of the descending aorta using axial velocity profiles from phase-contrast magnetic resonance imaging.

The pulse wave velocity (PWV) of aortic blood flow is considered a surrogate for aortic compliance. A new method using phase-contrast (PC)-MRI is presented whereby the spatial and temporal profiles of axial velocity along the descending aorta can be analyzed. Seventeen young healthy volunteers (the YH group), six older healthy volunteers (the OH group), and six patients with coronary artery disease (the CAD group) were studied. PC-MRI covering the whole descending aorta was acquired, with velocity gradients encoding the in-plane velocity. From the corrected axial flow velocity profiles, PWV was determined from the slope of an intersecting line between the presystolic and early systolic phases. Furthermore, the aortic elastic modulus (Ep) was derived from the ratio of the brachial pulse pressure to the strain of the aortic diameter. The PWV increased from YH to OH to CAD (541 +/- 94, 808 +/- 184, 1121 +/- 218 cm/s, respectively; P = 0.015 between YH and OH; P = 0.023 between OH and CAD). There was a high correlation between PWV and Ep (r = 0.861, P < 0.001). Multivariate analysis showed that age and CAD were independent risk factors for an increase in the PWV. Compared to existing methods, our method requires fewer assumptions and provides a more intuitive and objective way to estimate the PWV.