Accurate prediction of agent motion trajectories is crucial for ensuring the safety and reliability of autonomous driving systems. Current research predominantly focuses on traditional deep learning methods, including...
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In this study, the problem of measuring noise pollution distribution by the intertial-based integrated navigation system is effectively suppressed. Based on nonlinear inertial navigation error modeling, a nested dual ...
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In this study, the problem of measuring noise pollution distribution by the intertial-based integrated navigation system is effectively suppressed. Based on nonlinear inertial navigation error modeling, a nested dual Kalman filter framework structure is developed. It consists of unscented Kalman filter (UKF)master filter and Kalman filter slave filter. This method uses nonlinear UKF for integrated navigation state estimation. At the same time, the exact noise measurement covariance is estimated by the Kalman filter dependency filter. The algorithm based on dual adaptive UKF (Dual-AUKF) has high accuracy and robustness, especially in the case of measurement information interference. Finally, vehicle-mounted and ship-mounted integrated navigation tests are conducted. Compared with traditional UKF and the Sage-Husa adaptive UKF (SH-AUKF), this method has comparable filtering accuracy and better filtering stability. The effectiveness of the proposed algorithm is verified.
To improve the optimization performance of the standard Aquila Optimizer (AO), an Improved Hybrid Aquila Optimizer and Pigeon-Inspired Optimization (IHAOPIO) algorithm based on stochastic balancing factor and Dimensio...
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Being able to safely land on the surface is one of the primary challenges when a probe exploring an asteroid. In order to ensure landing safety, the landing location planning needs to comprehensively consider the terr...
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With the rapid development of Large Language Model (LLM) technology, it has become an indispensable force in biomedical data analysis research. However, biomedical researchers currently have limited knowledge about LL...
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Traditional visual localization algorithms often assume a static world, making them susceptible to inaccuracies and reduced robustness in real environments with dynamic objects. Additionally, these algorithms struggle...
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Dear editor,Human-object interaction(HOI) detection is an important human-centric visual understanding task with several applications in visual monitoring, intelligent robot, etc. It aims at localizing and inferring i...
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Dear editor,Human-object interaction(HOI) detection is an important human-centric visual understanding task with several applications in visual monitoring, intelligent robot, etc. It aims at localizing and inferring interaction relationships between humans and objects in images. As a result of their success in object detection, many object detectors can be used to localize human and object instances. Therefore, the key to HOI detection mainly lies in the second part, namely interaction recognition.
This paper introduces a fixed-time sliding mode control (FTSMC) scheme that utilizes a fixed-time disturbance observer (FTDOB) for three-level neutral-point-clamped (3L-NPC) converters. Therein, a FTSMC with adaptive ...
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This paper addresses the control synthesis of heterogeneous stochastic linear multi-agent systems with realtime allocation of signal temporal logic (STL) specifications. Based on previous work, we decompose specificat...
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As an application of fine-grained wireless sensing, RF-based material identification follows the paradigm of RF computing that fetches the information during RF signal propagation. Specifically, the RF signal accesses...
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