With the rapid growth of internet content, multimodal long document data has become increasingly prominent, drawing significant attention from researchers. However, most existing methods primarily focus on scenarios w...
详细信息
This paper deals with the problem of achieving formation control for underactuated multiple quadrotors without velocity measurements by employing the higher-order sliding mode (HOSM) differentiator. The primary object...
This paper deals with the problem of achieving formation control for underactuated multiple quadrotors without velocity measurements by employing the higher-order sliding mode (HOSM) differentiator. The primary objective of this work is to attain a coordinated formation behavior among the quadrotor group. In this paper, the dynamics of each quadrotor are transformed into a new form, wherein the attitude is described using rotation matrices. Subsequently, an intermediate guide is designed using the HOSM differentiator, taking into account the desired relative positions between the quadrotors and their actual positions. Next, the actual control thrusts and torques for each quadrotor are designed and solved by the intermediate guide. Finally, rigorous theoretical analysis and multiple simulations are performed to ensure that the multiple quadrotors converge asymptotically and accurately to the desired formation shape.
Deception attacks are employed to compromise cyber-physical systems through fake data injection. This paper concentrates on the distributed resilient estimation issue of multi-sensor networked systems under deception ...
详细信息
ISBN:
(数字)9798331518493
ISBN:
(纸本)9798331518509
Deception attacks are employed to compromise cyber-physical systems through fake data injection. This paper concentrates on the distributed resilient estimation issue of multi-sensor networked systems under deception attacks. In order to detect deception attacks, we utilize Kullback-Leibler(K-L) divergence as a criterion to distinguish the discrepancy between the deceived information and the estimated information. When the attack does not exist, the transmitted information can be restored to ensure the resilient estimation performance. Based on the extended Kalman filter design method, a distributed resilient estimation with a dual-gain mechanism is developed. This advanced approach dynamically adjusts the weighting balance between the predictive model and sensor data inputs, achieving the optimal estimation during the shutdown and activation of spoofing attacks. Finally, numerical simulations are provided to further illustrate the results.
Nuclear energy is widely recognized as an important source to meet the increasing energy demand in the future. However, since the occurrence of the Fukushima accident, its potential safety hazards have been strongly c...
详细信息
Egocentric gesture recognition is a pivotal technology for enhancing natural human-computer interaction, yet traditional RGB-based solutions suffer from motion blur and illumination variations in dynamic scenarios. Wh...
详细信息
visual localization is considered an essential capability in robotics and has attracted increasing interest for the past few years. However, most proposed visual localization systems assume that the surrounding enviro...
详细信息
visual localization is considered an essential capability in robotics and has attracted increasing interest for the past few years. However, most proposed visual localization systems assume that the surrounding environment is static, which is difficult to maintain in real-world scenarios due to the presence of moving objects. In this paper, we present DFR-SLAM, a real-time and accurate RGB-D SLAM based on ORB-SLAM2 that achieves satisfactory performance in a variety of challenging dynamic scenarios. At the core of our system lies a motion consensus filtering algorithm estimating the initial camera pose and a graph-cut optimization framework combining long-term observations, prior information, and spatial coherence to jointly distinguish dynamic and static visual features. Other systems for dynamic environments detect dynamic components by using the information from short time-span frames, whereas our system uses observations from a long period of keyframes. We evaluate our system using dynamic sequences from the public TUM dataset, and the evaluation demonstrates that the proposed system outperforms the original ORB-SLAM2 system significantly. In addition, our system provides competitive localization accuracy with satisfactory real-time performance compared to closely related SLAM systems designed to adapt to dynamic environments.
This study proposes an image-based visual servoing(IBVS)method based on a velocity observer for an unmanned aerial vehicle(UAV)for tracking a dynamic target in Global Positioning System(GPS)-denied *** proposed method...
详细信息
This study proposes an image-based visual servoing(IBVS)method based on a velocity observer for an unmanned aerial vehicle(UAV)for tracking a dynamic target in Global Positioning System(GPS)-denied *** proposed method derives the simplified and decoupled image dynamics of underactuated UAVs using a constructed virtual camera and then considers the uncertainties caused by the unpredictable rotations and velocities of the dynamic target.A novel image depth model that extends the IBVS method to track a rotating target with arbitrary orientations is *** depth model ensures image feature accuracy and image trajectory smoothness in rotating target *** relative velocities of the UAV and the dynamic target are estimated using the proposed velocity *** to the velocity observer,translational velocity measurements are not required,and the control chatter caused by noise-containing measurements is *** integral-based filter is proposed to compensate for unpredictable environmental disturbances in order to improve the antidisturbance *** stability of the velocity observer and IBVS controller is analyzed using the Lyapunov *** simulations and multistage experiments are conducted to illustrate the tracking stability,anti-disturbance ability,and tracking robustness of the proposed method with a dynamic rotating target.
Continuous-variable quantum key distribution (CVQKD) is a mature technology that can theoretically provide an unconditional security guarantee. However, a practical CVQKD system may be vulnerable to various quantum ha...
详细信息
Continuous-variable quantum key distribution (CVQKD) is a mature technology that can theoretically provide an unconditional security guarantee. However, a practical CVQKD system may be vulnerable to various quantum hacking attacks due to imperfect devices and insufficient assumptions. In this paper, we propose a universal defense strategy called a machine-learning-based attack detection scheme (MADS). Leveraging the combined advantages of density-based spatial clustering of applications with noise (DBSCAN) and multiclass support vector machines (MCSVMs), MADS demonstrates remarkable effectiveness in detecting quantum hacking attacks. Specifically, we first establish a set of attack-related features to extract feature vectors. These vectors are then utilized as input data for DBSCAN to identify and remove any noise or outliers. Finally, the trained MCSVMs are employed to classify and predict the processed data. The predicted results can immediately determine whether or not to generate a final secret key. Simulation results show that the proposed MADS can efficiently detect most quantum hacking attacks and revise the overestimated secret key rates caused by a CVQKD system without any defense strategy to obtain a tighter security bound.
Surgical navigation based on multimodal image registration has played a significant role in providing intraoperative guidance to surgeons by showing the relative position of the target area to critical anatomical stru...
详细信息
People with visual Impairments (PVI) typically recognize objects through haptic perception. Knowing objects and materials before touching is desired by the target users but under-explored in the field of human-centere...
详细信息
ISBN:
(数字)9798350384574
ISBN:
(纸本)9798350384581
People with visual Impairments (PVI) typically recognize objects through haptic perception. Knowing objects and materials before touching is desired by the target users but under-explored in the field of human-centered robotics. To fill this gap, in this work, a wearable vision-based robotic system, MATErobot, is established for PVI to recognize materials and object categories beforehand. To address the computational constraints of mobile platforms, we propose a lightweight yet accurate model MATEViT to perform pixel-wise semantic segmentation, simultaneously recognizing both objects and materials. Our methods achieve respective 40.2% and 51.1% of mIoU on COCOStuff-10K and DMS datasets, surpassing the previous method with +5.7% and +7.0% gains. Moreover, on the field test with participants, our wearable system reaches a score of 28 in the NASA-Task Load Index, indicating low cognitive demands and ease of use. Our MATErobot demonstrates the feasibility of recognizing material property through visual cues and offers a promising step towards improving the functionality of wearable robots for PVI. The source code has been made publicly available at MATErobot.
暂无评论