In this letter, the problem of head movement prediction for virtual reality videos is studied. In the considered model, a deep learning network is introduced to leverage position data as well as video frame content to...
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Bionic limb prosthetics continue to face significant challenges in terms of artificial limb embodiment, often leading to prosthesis abandonment in patients. Following recent results in literature on digital trainings,...
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A combination of two shared input splitting capacitor banks and varying number of individualized inverter-leg flying-capacitors characterized topological feature of a large group of 5L ANPC inverters configurations. T...
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An investigation area of interest including the use of blockchain technology to address Internet of Things security concerns (IoT). Despite the fact that numerous relevant ideas have been offered, there are few publis...
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Photovoltaic (PV) system fault diagnosis is crucial because it helps PV system operators reduce energy and income losses. It also decreases the risk of fire and electric shock from PV system failures. Thus, the implem...
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Deep neural networks (DNNs)-based battery remaining useful life (RUL) prognostics models suffer from high computational costs, long inference times, and a tendency to overfit, posing significant challenges for deploym...
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The unconditioned reflex (e.g., protective reflex), which is the innate reaction of the organism and usually performed through the spinal cord rather than the brain, can enable organisms to escape harms from environme...
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The unconditioned reflex (e.g., protective reflex), which is the innate reaction of the organism and usually performed through the spinal cord rather than the brain, can enable organisms to escape harms from environments. Accordingly, it is essential to endow robots the highly-dynamic unconditioned reflexes to humans and/or environments, such that it can work collaboratively with humans or serve people in daily life. Although various sampling-based and optimization-based motion planning methods have been developed for robots, their limited computational speed is not suitable for rapid motion planning in highly-dynamic environments. In this paper, we propose an online, highly-dynamic motion planning algorithm to enable highly-dynamic unconditioned reflexes for manipulators. Our method is based on a chained version of Signed Distance Functions (SDFs), which can be pre-computed and stored. Our proposed algorithm is divided into two stages. In the offline stage, we create 3 groups of local SDFs to store the geometric information of the manipulator and its working environment. The SDFs in the first group are to describe the geometric information of the static environment. The SDFs in the second group are to describe the geometric information of each link. While the SDFs in the last group are to describe the reachability of each link’s end of the manipulator. In the online stage, the precomputed local SDFs are chained together according the configuration of the manipulator, to provide global geometric information about the environment. While the point clouds of the dynamic objects serve as query points to look up these local SDFs for quickly generating escape velocity. Then we propose a modified geometric Jacobian matrix and use the Jacobian-pseudo-inverse method to generate real-time reflex behaviors to avoid the static and dynamic obstacles in the environment. The benefits of our method are validated in both static and dynamic scenarios. In the static scenario, our meth
In this study, the performance of existing U-shaped neural network architectures was enhanced for medical image segmentation by adding Transformer. Although Transformer architectures are powerful at extracting global ...
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In 2020 Sala, Sogiorno and Taufer [14] have been able to find the private keys of some Bitcoin addresses, thus being able to spend the cryptocurrency linked to them. This result was unexpected, since the recovery of n...
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Considering the actual multi-agent coverage process, the motion trajectories are seriously affected by disturbances and noise. In this paper, a cooperative control method based on active disturbance rejection controll...
Considering the actual multi-agent coverage process, the motion trajectories are seriously affected by disturbances and noise. In this paper, a cooperative control method based on active disturbance rejection controller (ADRC) for multiple mecanum-wheeled robots (MWMR) is proposed to improve its robustness. In particular, to suppress the total disturbances during the running of each robot and reduce large computation and observation cost of high order ADRC, a reduced-order cascaded ADRC (RC-ADRC) is proposed. Moreover, distributed controller is proposed to track the expected trajectories of multiple mecanum-wheeled robots under disturbances. Compared with the proposed RC-ADRC based cooperative control scheme and PID based cooperative control one, the favorable motion trajectory tracking performance is obtained. Simulation results verify the superiority of the method.
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