Journals
2025 EN
Qiu Qingan · Liu Bosen · Pei Cuicui
+2 more
ABSTRACT This study addresses the growing safety challenges associated with data transmission and processing in cloud computing systems, particularly in light of their vulnerability to external shocks such as hacker attacks. We introduce risk control strategies that focus on condition‐based data backup and mission abort decisions. We establish a mission abort threshold based on the number of shocks specific to cloud computing systems engaged in data transmission, aiming to reduce the risk of system failures. Before executing a mission abort decision, we propose a condition‐based backup strategy that triggers data backup once the transmitted data reaches a predefined threshold, thus mitigating the risk of data loss. Within the framework of the integrated backup and mission abort strategies, we evaluate critical system performance metrics, including mission success probability (MSP) and expected total costs, utilizing a recursive method. Optimization of integrated backup and mission abort policies seeks to minimize expected total costs associated with system failures, mission failures, data backups, and data loss. To validate the effectiveness of our proposed strategies, we conduct a comprehensive numerical example, demonstrating that the implementation of condition‐based backup and abort thresholds can significantly reduce expected costs and enhance MSP.
Journals
2025 EN
Rubin Michael · Du Dongping
ABSTRACT Dynamic fault trees (DFTs) have been used successfully to evaluate both the reliability and failure management of complex, redundant systems. Although existing static and DFTs are effective in determining overall failure probabilities and reliability, and even optimizing redundant resources, they do not have the ability to effectively characterize and optimize partially degraded components. This paper presents two new DFT gates, namely the Capacity Gate and the Preference Gate, which utilize dynamically updated capacity degradation profiles, failure probability distribution (PDF) profiles, and remaining useful life (RUL) predictions as inputs to the fault tree model and generate an optimized set of outputs, based on user preferences, that can be fully integrated with existing static and DFT gates. Using reaction wheel (RW) data from the Rosetta space mission, an experiment was conducted in which three fault trees were implemented and analyzed for effectiveness. These include a static fault tree (SFT), a DFT using existing gates, and a DFT using the new Capacity and Preference gates. This experiment validated that the new DFT gates can significantly extend mission lifetime and improve system reliability more than either a DFT or SFT that use existing fault tree gates.
Journals
2025 EN
Gökalp Ali · Değirmenci Nail
Abstract The rapid development of technology in our age has also affected the educational environments, and technology has been widely used in these environments. The importance of the contribution of technology to education and training is undeniable. Social studies, one of the disciplines that come to mind about the correct and appropriate use of technology, is capable of creating awareness in students regarding its purpose and structure. Social studies is a course that has a mission to interpret the effects of scientific and technological developments on social life in terms of change and continuity. Pre‐service teachers' self‐efficacy regarding technology integration is very important to acquire the pedagogical skills required for their age. If the factors affecting pre‐service teachers' self‐efficacy in this regard are known, the obstacles to creating innovative and effective learning environments can be understood. It has been observed that there are minimal studies in the existing literature that broadly address the relationship between pre‐service social studies teachers' technology integration competencies and both individual and environmental factors. The current study aimed to investigate Turkish pre‐service social studies teachers' self‐efficacy perceptions of technology integration in education in the context of variables at both the student and school levels. This study was conducted with 1136 pre‐service teachers enrolled in the social studies teaching departments of 36 universities in Türkiye. Participants were determined by random sampling. The study emphasises that teacher training programmes should be updated and technology‐oriented courses should be enriched. The results reveal that individual efforts and institutional support are important to improve future teachers' technology integration skills. Context and implications Rationale for this study This study examines the factors affecting the self‐efficacy perceptions of pre‐service social studies teachers in Türkiye regarding technology integration in education by considering student and school‐level variables together. Why the new findings matter At the student level, technology use and content knowledge, and at the school level, the ceiling scores of the universities and the development of the province where the universities are located, are essential factors affecting pre‐service social studies teachers' perceptions of technology integration self‐efficacy. Implications for education programmes and researchers This study reveals the necessity of renewing the curricula of education faculties in order to improve the technology integration competencies of pre‐service social studies teachers in teaching and practice. It suggests that technology‐oriented courses should be enriched with theoretical and practical content, in‐class technology experiences should be increased, and institutional technological infrastructure should be strengthened. For researchers, it is recommended to plan longitudinal studies examining the effect of technology integration competencies of pre‐service social studies teachers on their professional development.
Journals
2025 EN
Jin Yufei · Zeng Zheng · Lian Lian
Abstract This paper presents the design, manufacturing and testing of a tail‐sitting vertically takeoff and landing fixed‐wing hybrid aerial underwater vehicle (HAUV) called Nezha‐SeaDart. Nezha‐SeaDart can vertically take off and land from ground and water, cruise in the air with lift generated by the wings, seamlessly cross the water–air interface and operate underwater like an autonomous underwater vehicle. Nezha‐SeaDart underwent a 10‐day field test in China's Thousand Islands Lake of Zhejiang Province, proving its ability to perform full cross‐domain missions. This research has the following contributions to the field of HAUV. (i) A working prototype of vertical takeoff and landing tail‐sitting HAUV with all basic functions verified and full mission cycle capability demonstrated in a field test. (ii) An HAUV that travels fast both in the air and underwater. (iii) An HAUV capable of autonomous and seamless water exit that does not rely on a dedicated propulsion system. (iv) A method of sizing the vehicle's wing and thrust considering aerial cruises, underwater operations, and seamless water exits.
Journals
2025 EN
Du Wenliao · Yu Xinlong · Guo Zhen
+3 more
Abstract Given the demanding and unpredictable operational conditions, autonomous underwater vehicles (AUVs) often encounter different propulsion faults, leading to significant economic losses and mission impairments. To address this challenge, vibratory time‐series features can be extracted for the precise propulsion fault diagnosis of AUVs. A squeeze‐and‐excitation (SE) attention residual network (SEResNet) is therefore put forward to enhance the feature extraction for AUV propulsion fault diagnosis. By leveraging the vibratory time‐series data obtained from the AUV, an SE attention mechanism is embedded into a residual network. This integration facilitates the extraction of pertinent vibratory fault features, subsequently utilized for accurate diagnosis of any propulsion faults. The effectiveness of the proposed SEResNet was validated through its application to an actual experimental AUV, with comparison against the state‐of‐the‐arts. The results reveal that the present SEResNet outperforms all other comparison methods in terms of diagnosis performance for AUV propulsion faults.
Journals
2025 EN
Duan Yu · Guan Xiawei · Liu Yifan
+3 more
ABSTRACT Dynamic docking control technology is crucial for autonomous underwater vehicles (AUV) to perform tasks underwater. To enhance the docking success rate of AUVs during dynamic docking, this paper presents a robust anti‐disturbance control algorithm specifically designed for overactuated AUV dynamic docking scenarios. During a dynamic docking mission, the AUV's depth control is adversely affected by the complex flow field generated by the underwater recovery device. To address this issue, this research proposes an AUV control scheme that combines an extended state observer (ESO) with a combined disturbance rejection method of the elevator‐vertical tunnel controller. First, an ESO is constructed to estimate and compensate for complicated disturbances such as model uncertainty and environmental disturbances. These estimations are then incorporated into the control law to mitigate the effects of the complicated flow field interference experienced during the AUV's dynamic docking process. Second, as turbulence intensifies at the end of the docking stage, the vertical thrust allocation is achieved using a hyperbolic tangent transition function. This ensures the stability of the AUV's attitude and depth, thereby enabling precise docking. Finally, the effectiveness of the proposed control algorithm is verified through lake trials and compared against the classic proportional‐integral‐differential (PID) and active disturbance rejection control (ADRC) methods. The trial results indicate that the proposed control algorithm significantly reduces the pitch and depth errors of the AUV, resulting in a remarkable 91% success rate for dynamic docking (based on 45 tests). The lake trials demonstrate that the proposed control algorithm is highly precise and robust.
Journals
2025 EN
Guo Qing · Guo Zihua · Shi Yujie
+2 more
ABSTRACT The multimodal land‐air aircraft combines the advantages of traditional drones and ground unmanned equipment. It can cross obstacles on the ground, such as lakes and mountains, and fly quickly in the air, reaching a wider range. It can also switch to an energy‐saving mode based on the characteristics of the surrounding environment and mission requirements, reducing energy consumption and noise while increasing endurance. Based on the idea of reusing the same structure, we have designed a multi‐mode agile land‐air aircraft, abbreviated as ALAA. ALAA has eight actuators, and it combines propellers, wheels, and gearboxes in different ways to achieve multiple modes of locomotion on the ground and in the air: flight mode, driving mode, and upright mode. In propeller‐assisted driving mode, it can climb slopes up to 50°. It can also combine driving and upright modes, demonstrating strong obstacle‐crossing capabilities. In addition, ALAA reuses the same components, simplifying the transition between flight and ground movement without the need for deformation, thus enabling fast and rational mode transition suitable for complex environments. Ground modes can extend the endurance time of ALAA, and experimental results show that ALAA can operate 21 times longer than an aerial only system. This paper presents the overall design and mechanical architecture of ALAA, discusses the algorithm and controller design, and verifies the feasibility of the scheme and design through experiments with the physical prototype, showing its performance in different modes.
Journals
2025 EN
Nordström Samuel · Stathoulopoulos Nikolaos · Dahlquist Niklas
+4 more
ABSTRACT This article presents the first ever fully autonomous UAV (Unmanned Aerial Vehicle) mission to perform gas measurements after a real blast in an underground mine. The demonstration mission was deployed around 40 min after the blast took place, and as such realistic gas levels were measured. We also present multiple field robotics experiments in different mines detailing the development process. The presented novel autonomy stack, denoted as the Routine Inspection Autonomy (RIA) framework, combines a risk‐aware 3D path planningD+ *, with 3D LiDAR‐based global relocalization on a known map, and it is integrated on a custom hardware and a sensing stack with an onboard gas sensing device. In the presented framework, the autonomous UAV can be deployed in incredibly harsh conditions (dust, significant deformations of the map) shortly after blasting to perform inspections of lingering gases that present a significant safety risk to workers. We also present a change detection framework that can extract and visualize the areas that were changed in the blasting procedure, a critical parameter for planning the extraction of materials, and for updating existing mine maps. As will be demonstrated, the RIA stack can enable robust autonomy in harsh conditions, and provides reliable and safe navigation behavior for autonomous Routine Inspection missions.
Journals
2025 EN
Claro Rafael Marques · Neves Francisco Soares Pinto · Pinto Andry Maykol Gomes
ABSTRACT The integration of precise landing capabilities into unmanned aerial vehicles (UAVs) is crucial for enabling autonomous operations, particularly in challenging environments such as the offshore scenarios. This work proposes a heterogeneous perception system that incorporates a multimodal fiducial marker, designed to improve the accuracy and robustness of autonomous landing of UAVs in both daytime and nighttime operations. This work presents ViTAL‐TAPE, a visual transformer‐based model, that enhance the detection reliability of the landing target and overcomes the changes in the illumination conditions and viewpoint positions, where traditional methods fail. VITAL‐TAPE is an end‐to‐end model that combines multimodal perceptual information, including photometric and radiometric data, to detect landing targets defined by a fiducial marker with 6 degrees‐of‐freedom. Extensive experiments have proved the ability of VITAL‐TAPE to detect fiducial markers with an error of 0.01 m. Moreover, experiments using the RAVEN UAV, designed to endure the challenging weather conditions of offshore scenarios, demonstrated that the autonomous landing technology proposed in this work achieved an accuracy up to 0.1 m. This research also presents the first successful autonomous operation of a UAV in a commercial offshore wind farm with floating foundations installed in the Atlantic Ocean. These experiments showcased the system's accuracy, resilience and robustness, resulting in a precise landing technology that extends mission capabilities of UAVs, enabling autonomous and Beyond Visual Line of Sight offshore operations.
Journals
2025 EN
Frutuoso Adriano · Silva Felipe O. · Barros Ettore A.
ABSTRACT Autonomous underwater vehicles (AUVs) are specialized robots used to accomplish important field operations such as inspection of oil and gas pipelines, marine wildlife monitoring, imaging of river and sea beds, nondestructive testing of ship hulls, and so on. Before the start of an AUV mission, its navigation system, which is generally comprised of a doppler velocity log (DVL)/pressure sensor (PS)‐aided inertial navigation system (INS) needs to be initialized. After a brief coarse stage of initialization, the AUV attitude is generally refined (as well as some inertial measurement unit (IMU)/aiding sensor systematic error parameters are corrected for) in a Kalman filter (KF)‐based estimation process known as fine alignment, which is usually performed in open sea conditions. When the latter is conducted before the submerged phase of the AUV, a Global Navigation Satellite System (GNSS) receiver may provide additional aiding information to the refinement process. As the excitation of the degrees of freedom of the AUV is known to interfere with the performance of the KF fine alignment, this study exploits Baram and Kailath's concept of estimability to assess what kind of deliberate AUV maneuver is able to deliver the best estimation results. As the main contribution, we show that among the tested AUV motion profiles, the lawn mower is the maneuver that, except for the IMU/DVL misalignment around the AUV longitudinal axis, decreases the estimation uncertainties of all remaining INS/GNSS/DVL/PS fine alignment states. Results from simulated and experimental tests confirm the adequacy of the outlined verifications.