In order to solve the problem of small obstacles avoidance in ultra-low altitude flying of unmanned aerial vehicles (UAVs), a depth estimation algorithm based on monocular visual for small tower obstacles is proposed ...
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ISBN:
(数字)9781728180250
ISBN:
(纸本)9781728180267
In order to solve the problem of small obstacles avoidance in ultra-low altitude flying of unmanned aerial vehicles (UAVs), a depth estimation algorithm based on monocular visual for small tower obstacles is proposed by combining deep learning and traditional methods. With the advantage of convolutional neural networks to extract the salient features of the images, a lightweight and multi-level residual convolution neural network for obstacle segmentation is proposed. The cross-entropy loss function is optimized by adding the weight of the background and obstacles area. A method based on pairs of coplanar points is introduced to complete the depth estimation of a single frame image. Moreover, the recursive formula of sequence images depth results is derived, and a multi-frame voting optimization algorithm is proposed. Finally, the simulation results show that the proposed algorithm can effectively realize the fast segmentation and accurate depth estimation of the small tower obstacles in the sequence images.
As an effective implement, failure mode and effects analysis (FMEA) is widely applied in the security of system for practical application. Nowadays, many methods determine the order of fault mode by a crisp risk prior...
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This paper presented a p-norm constraint Lorentzian adaptive algorithm to estimate the sparse multi-path channel inα-stable noise environment. We derived the proposed algorithm based on the Lagrange multiplier method...
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ISBN:
(数字)9781728198057
ISBN:
(纸本)9781728198064
This paper presented a p-norm constraint Lorentzian adaptive algorithm to estimate the sparse multi-path channel inα-stable noise environment. We derived the proposed algorithm based on the Lagrange multiplier method and we also evaluated the performance of the developed adaptive algorithm via estimating a sparse multi-path channel. The gotten results on the basis of computer simulations proved that the developed Lorentzian adaptive algorithm is superior to the popular method in the comparisons.
In this paper, an autonomous positioning method based on coarse-to-fine multi-modal image matching is proposed for UAV navigation in GPS denied environment. Coarse image matching refers to roughly determining the appr...
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ISBN:
(数字)9781728190044
ISBN:
(纸本)9781728190051
In this paper, an autonomous positioning method based on coarse-to-fine multi-modal image matching is proposed for UAV navigation in GPS denied environment. Coarse image matching refers to roughly determining the approximate position of the real-time image in the reference image. Fine image matching refers to iterative matching around the position obtained by coarse image matching to achieve more accurate matching results. Besides, RANSAC is adopted to eliminate the outliers of image matching. After getting the result of image matching, we use PNP to estimate the position of the aircraft. The proposed position method has the advantages of high accuracy and reliability. The experimental results show that the average error of the position of the proposed method is 59%.
By making full use of the curvature of the earth and ground clutter, the ultra-low altitude flight technique can significantly increase the difficulty of detecting and intercepting unmanned aerial vehicles (UAVs), and...
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As an important device for target interception, The seeker is used to search, recognize and track the target autonomously. Infrared semi-strapdown seekers are widely used in applications due to their low cost and smal...
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A multi-branch parallel simulation method and an architecture of application system are proposed in this paper based on symbiotic potential, and method of construction and calibration of parallel battlefield based on ...
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Human beings perceive the world through the senses of sight,hearing,smell,taste,touch,space,and *** first five senses are prerequisites for people to *** sensing organs upload information to the nervous systems,includ...
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Human beings perceive the world through the senses of sight,hearing,smell,taste,touch,space,and *** first five senses are prerequisites for people to *** sensing organs upload information to the nervous systems,including the brain,for interpreting the surrounding ***,the brain sends commands to muscles reflexively to react to stimuli,including light,gas,chemicals,sound,and ***,as an emerging two-dimensional material,has been intensively adopted in the applications of various sensors and *** this review,we update the sensors to mimic five primary senses and actuators for stimulating muscles,which employ MXene-based film,membrane,and composite with other functional ***,a brief introduction is delivered for the structure,properties,and synthesis methods of ***,we feed the readers the recent reports on the MXene-derived image sensors as artificial retinas,gas sensors,chemical biosensors,acoustic devices,and tactile sensors for electronic ***,the actuators of MXene-based composite are ***,future opportunities are given to MXene research based on the requirements of artificial intelligence and humanoid robot,which may induce prospects in accompanying healthcare and biomedical engineering applications.
In order to solve the problem that the point feature tracking is not robust enough to reduce the accuracy of the system in a low-texture environment, this paper proposes a visual inertial odometry system based on poin...
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ISBN:
(数字)9781728186351
ISBN:
(纸本)9781728186368
In order to solve the problem that the point feature tracking is not robust enough to reduce the accuracy of the system in a low-texture environment, this paper proposes a visual inertial odometry system based on point-line features (PL-VINS). Firstly, the system improves the extraction and matching algorithm of line features to increase the speed and accuracy of the algorithm; then the line features are added to the front-end tracking and back-end optimization. Finally, the EuRoc public data set is used as the experimental object to prove the effectiveness of the algorithm.
Nonlinear control has led to several great achievements for attitude control in virtual simulation environments, where the system model can be simplified to meet the application condition of those traditional nonlinea...
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ISBN:
(数字)9781728176871
ISBN:
(纸本)9781728176888
Nonlinear control has led to several great achievements for attitude control in virtual simulation environments, where the system model can be simplified to meet the application condition of those traditional nonlinear control algorithms. However, only a few of those algorithms can be applied to a practical Hypersonic Aircraft system, which suffers from uncertainties, multi-constraints, and various noises. To solve those problems effectively, in this paper, a novel reinforcement learning framework based on PI2 is proposed, wherein three kernel techniques are introduced. Firstly, a generalized path- integral-control approach is proposed to obtain the numerical solution of a stochastic dynamic model, wherein the calculation of the gradient and matrix inversion is avoided to ensure fast and reliable training convergence. Secondly, an action smooth method is used to strengthen the ability of the controller to resist noise. Thirdly, a novel RL algorithm combined with soft constrained techniques is illustrated to address the constrained nonlinear control problem. Several experiments are carried out and analyzed to demonstrate the outstanding performance of the CS-PI2.
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