This paper focuses on the vision-based autonomous landing mission of a quadrotor unmanned aerial vehicle (UAV). A double-layered nested Aruco landing marker is designed which can adapt to the situation that the field ...
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This paper illustrates the application of an autonomous decentralized system introducing edge nodes in a smart factory. The nodes include atomic nodes, the most fundamental autonomic units constituting an autonomous d...
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Euler-Lagrange (EL) systems represent a crucial and large class of dynamical systems, and a precise model of the true system would be beneficial in planning and tracking problems. This work aims to learn an unknown EL...
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ISBN:
(数字)9798350316339
ISBN:
(纸本)9798350316346
Euler-Lagrange (EL) systems represent a crucial and large class of dynamical systems, and a precise model of the true system would be beneficial in planning and tracking problems. This work aims to learn an unknown EL system using noisy measurement data to achieve improved data utilization efficiency. Specifically, for the considered EL system, a linear representation of the system is constructed using the Koopman operator, which is further characterized by sample data using Willems’ fundamental lemma. Moreover, an event-triggered learning mechanism is proposed to improve data utilization efficiency, and it is designed based on the analysis of the learning error bounds. The effectiveness of the proposed event-triggered learning approach is validated through a manipulator example.
Cavitation erosion would reduce the performance of the fluid machinery. In order to improve the reliability and prolong the life span of fluid machinery, it is necessary to study the mechanism of cavitation erosion an...
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As one of the most important parts in the engine,the structure and state of the rotating blade directly affect the normal performance of the *** order to monitor engine crack failure and ensure flight safety,it is nec...
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As one of the most important parts in the engine,the structure and state of the rotating blade directly affect the normal performance of the *** order to monitor engine crack failure and ensure flight safety,it is necessary to carry out research on the dynamic modeling of the cracked blade and breathing crack-induced vibration *** paper summarizes the current research status on the dynamics of cracked blade,and the related topics mainly include four aspects:crack propagation path,mechanical model of open and breathing cracks,dynamic modeling methods of cracked blades such as lumped mass model,semi-analytical model and finite element model,and dynamic characteristics of cracked *** review will provide valuable references for future studies on dynamics and fault diagnosis of cracked blade in aeroengine.
Differential privacy is a widely used framework for evaluating privacy loss in data anonymization. While the continuous noise-adding mechanism has been extensively studied, there is a dearth of research on discrete ra...
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作者:
Jiwei ShanYirui LiQiyu FengDitao LiLijun HanHesheng WangDepartment of Automation
Key Laboratory of System Control and Information Processing of Ministry of Education Key Laboratory of Marine Intelligent Equipment and System of Ministry of Education Shanghai Engineering Research Center of Intelligent Control and Management Shanghai Jiao Tong University Shanghai China School of Mechanical Engineering
Shanghai Jiao Tong University Shanghai China
Building a self-model for robots, enabling them to simulate their physical selves and predict future states without direct interaction with the physical world, is crucial for robot motion planning and control. Existin...
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ISBN:
(数字)9798350377705
ISBN:
(纸本)9798350377712
Building a self-model for robots, enabling them to simulate their physical selves and predict future states without direct interaction with the physical world, is crucial for robot motion planning and control. Existing self-modeling methods primarily focus on rigid robots and typically require significant time, effort, and resources to gather training data. In this study, we introduce SoftNeRF, a self-supervised visual self-model designed for soft robots. We use a hybrid neural shape representation based on the Signed Distance Function (SDF) to capture both the geometry and complex nonlinear motion of soft robots. By leveraging differentiable rendering, our method learns a self-model from readily available RGB images, similar to how humans understand their physical state through reflection. To improve training efficiency and model accuracy, we propose an error-guided adaptive sampling strategy. SoftNeRF can serve as a plug-in for various downstream tasks, even when trained with data unrelated to those tasks. We demonstrate SoftNeRF’s ability to support shape prediction and motion planning for robots in both simulated and real-world environments. Furthermore, SoftNeRF excels in detecting and recovering from damage, thereby enhancing machine resilience. Code is available at: https://***/irmvlab/soft-nerf.
The salvo attack of multi-missile is investigated, where the communication topology is randomly switching and unsustainably connected due to the unreliable links, and the probability of the packet loss is unavailable....
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Estimating camera motion and continuously reconstructing dense scenes in deformable environments presents a complex and open challenge. Many existing approaches tend to rely on assumptions about the scene’s topology ...
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ISBN:
(数字)9798350377705
ISBN:
(纸本)9798350377712
Estimating camera motion and continuously reconstructing dense scenes in deformable environments presents a complex and open challenge. Many existing approaches tend to rely on assumptions about the scene’s topology or the nature of deformable motion. However, these assumptions do not hold true in medical endoscopy applications. To address these challenges, we introduce DDS-SLAM, a novel dense deformable semantic neural SLAM that achieves accurate camera tracking, continuous dense scene reconstruction, and high-quality image rendering in deformable scenes. First, we propose a novel hybrid neural scene representation method capable of capturing both natural and artificial deformations. Additionally, by leveraging the 2D semantic information of the scene, we introduce a semantic loss function based on semantic distance fields. This approach guides network optimization at a higher level, thereby enhancing system performance. Furthermore, we validate our method through a series of experiments conducted on several representative medical datasets, demonstrating its superiority over other state-of-the-art approaches. The code is available at: https://***/IRMVLab/DDS-SLAM.
Nuclear power is one of several significant clean energy and its production capacity is increasing rapidly. This paper proposed a novel PID self-tuning method based on closed-loop identification used in nuclear power ...
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