Angle-of-arrival (AOA) target localization using the unmanned aerial vehicle (UAV) has been widely applied in many practical applications. To localize an invasive target quickly and accurately, both the estimation and...
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ISBN:
(纸本)9781665402460
Angle-of-arrival (AOA) target localization using the unmanned aerial vehicle (UAV) has been widely applied in many practical applications. To localize an invasive target quickly and accurately, both the estimation and UAV path optimization algorithms are required. This paper focuses on developing a path optimization method to improve the target estimation performance. Firstly, the problem formulation of AOA target localization is introduced. Secondly, the classical pseudolinear Kalman filter (PLKF) and the gradient-based path optimization are presented. Thirdly, we analyze the problems that existed in the previous methods and propose an improved gradient-descent path optimization algorithm combined with a simple grid search method. Finally, the simulation examples verify the effectiveness of the proposed methods.
In angle-of-arrival (AOA) target tracking, the target states are estimated using the noisy angular measurements. The non-Gaussian measurement noise is common in practical applications and will decrease the estimation ...
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The short-term hydrothermal scheduling (STHS) is a complex non-linear, non-convex and high-dimensional mathematical optimization problem. Due to the fact that the original chimp optimization algorithm (ChOA) is likely...
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The unique self-healing and self-bending properties of acoustic Airy beams enable promising applications in imaging and therapeutic interventions, particularly in scenarios involving obstacles. In this study, we desig...
The unique self-healing and self-bending properties of acoustic Airy beams enable promising applications in imaging and therapeutic interventions, particularly in scenarios involving obstacles. In this study, we designed and fabricated a 3 MHz focused ultrasound transducer integrated with a binary acoustic metasurface for Airy beam generation using 3D-printing technology. Finite element simulations of the acoustic field distribution demonstrated that the metasurface exhibits broadband frequency adaptability for stable focusing. To address impedance mismatch between the sound source and metasurface, a quartz glass intermediate matching layer was incorporated. Two material systems—red wax epoxy resin and ethylene–vinyl acetate copolymer (EVA)—were selectively 3D-printed to construct the binary metasurface. Experimental validation through acoustic field scanning and focused ablation tests confirmed the transducer’s exceptional focusing capability and obstacle-penetrating self-healing performance. These results highlight its potential for ultrasound-guided interventions, such as tumor ablation and imaging in complex anatomical environments with obstructing structures.
The reinforcement learning (RL) of the autonomous mobile agent is one of the actual research topics. It permits mobile agents to interact constantly with their environment and to avoid obstacles. First, this paper pre...
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This paper focuses on unsupervised low-light enhancement methods for practical applications such as automated driving, surveillance cameras, and so on. This paper proposes an unsupervised method that is independent of...
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ISBN:
(数字)9781728172934
ISBN:
(纸本)9781728172941
This paper focuses on unsupervised low-light enhancement methods for practical applications such as automated driving, surveillance cameras, and so on. This paper proposes an unsupervised method that is independent of paired samples and works well to solve the image darkness problem. Furthermore, to increase the brightness of the image and restore the information hidden in the dark, an auxiliary attention module is incorporated into our model. This proposed module can help generate images with good edges and make the image colors and details richer. The experimental results show that the proposed method works well for both image enhancement and noise control.
Object detection plays an important role in the field of self-driving. Illumination has a great impact on object detection, but most of the current methods do not solve the problem of object detection in poor light en...
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Estimating 6D poses of objects from RGB images is very crucial for robots to interact with the surrounding environment and to cooperate with humans. It is a challenging problem due to the various shapes of objects, th...
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Computational pathology targets the automatic analysis of Whole Slide Images (WSI). WSIs are high-resolution digitized histopathology images, stained with chemical reagents to highlight specific tissue structures and ...
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This paper proposed a method to detect cliff edge by using an RGB-D camera, and then to fuse the cliff information with LiDAR, finally to provide navigation information for robot autonomous exploration and autonomous ...
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ISBN:
(数字)9781728172934
ISBN:
(纸本)9781728172941
This paper proposed a method to detect cliff edge by using an RGB-D camera, and then to fuse the cliff information with LiDAR, finally to provide navigation information for robot autonomous exploration and autonomous movement. Compared with the prior methods which set sonar or infra-red sensor in the bottom of the robot, our method could detect cliff earlier by set the RGB-D camera forward. In cliff detection, we use region growing algorithm and the normal vector of plane to segment out ground plane in point cloud, then extract the boundary points of ground, and we proposed an Edge Point Filter (EPF) to get the edge points of cliff, then use the edge points to simulate LiDAR data and combine with real LiDAR data to mark the untraversable area. We verified the practicability of this method in simulation, and verified the accuracy with real sensors.
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