Large commercial complex projects have the characteristics of large roof area and high electricity price, and the development of distributed photovoltaic power generation has great potential. In this paper, a feasibil...
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This paper presents a FPGA-based hardware architecture for capturing real-time panoramic images and the parallel implementation of an image stitching algorithm based on the scale-invariant feature transform (SIFT) fea...
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This paper presents a FPGA-based hardware architecture for capturing real-time panoramic images and the parallel implementation of an image stitching algorithm based on the scale-invariant feature transform (SIFT) features. First, the system transfers the images captured by five CMOS sensors to the designed FPGA board through the FMC adapter plate. Then, the system employs the FPGA-based parallel computing to extract the SIFT features and detect the best matching region and points for image registration. Finally, in order to obtain the panoramic image with smooth changes at the junctions, images of the adjacent images are fused. Using the designed FPGA platform makes it possible to extract the SIFT and stitch the images in real-time, which is not realized in most panoramic imaging systems. The panoramic system, developed using the Xilinx Zynq®-7000 all programmable SOC, can capture video of 5*640*480 images at the speed of 60 fps. To enable high-speed image transfer from the imaging system to the host computer, the USB3.0 interface with the transmission speed of 359MB/s has been developed. The real-time efficiency of the parallel system will be demonstrated by the simulations and experiments. IEEE
This paper investigates controlling the commercialized Spykee mobile robot, using only brain electroencephalography (EEG) signals transmitted by the Emotiv Epoc Neuro Headset. The Spykee robot is equipped with a wirel...
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This paper is concerned with the design of networked controlsystems with random network data dropout. It presents a new control scheme, which is termed networked predictive control. This scheme mainly consists of the...
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作者:
Xia, YuanqingLiu, BoSchool of Automation
Key Laboratory of Intelligent Control and Decision of Complex Systems Beijing Institute of Technology Beijing 100081 China
Summary This paper is devoted to the detection of abrupt changes for multiple-input, multiple-output (MIMO) linear systems based on frequency domain data. The real discrete-time Fourier transform is used to map the me...
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This article studies the time-varying formation (TVF) problem of multiagent systems (MASs) with different time delays. By designing the control protocol, the followers could achieve the desired TVF. Considering differ...
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This paper proposed a novel dual-threshold computation method of Canny edge detector based on gradient magnitude histogram (GMH), targeting with the adaptive acquisition of low-/high-threshold for unimodal hysteresis ...
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ISBN:
(纸本)9781479908813
This paper proposed a novel dual-threshold computation method of Canny edge detector based on gradient magnitude histogram (GMH), targeting with the adaptive acquisition of low-/high-threshold for unimodal hysteresis thresholding. With the introduction of the bowstring concept, which accurately measures the tendency of the GMH on the whole, the dual-threshold computation is implemented by adaptive-searching two tangent points with transitional characteristics. This skillful algorithm of the dual-threshold computation method is further evaluated by using the receiver operating characteristics (ROC) curve evaluation method. The detailed comparison to the Otsu's method is presented and demonstrates the reliability and robust performance of the proposed dual-threshold computation method.
In this paper, we propose a time division multiple access(TDMA) based protocol that works on slightly modified IEEE802.15.4 network in star topology for secured and unsecured low latency deterministic networks(LLDN) f...
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ISBN:
(纸本)9781467374439
In this paper, we propose a time division multiple access(TDMA) based protocol that works on slightly modified IEEE802.15.4 network in star topology for secured and unsecured low latency deterministic networks(LLDN) for industrial controlsystems. This protocol ensures total superframe time as low as ten milliseconds as compared to minimum possible superframe time of 15.36 milliseconds. In these networks, Each end device transmits its data frame in their allotted timeslot. The timeslot and inter timeslot spacing is optimized for channel bandwidth utilization and reliable data frame exchange. While this TDMA based protocol eliminates the risk of frame collisions to great extent, MAC sub-layer tweaking improves the non-determinism of the network and increases its bandwidth efficiency. We also investigate the security impact on the performance of LLDN. A mathematical model is developed that takes empirical values as input and predicts the worst case arrival times of network devices at coordinator. Experiments were conducted to evaluate the suggested protocol and mathematical model.
Mapping UAVs have played a more important role in regional mapping than ever before, and coverage path planning is an important part of mapping tasks. However, there are few studies on single-region path planning in c...
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Mapping UAVs have played a more important role in regional mapping than ever before, and coverage path planning is an important part of mapping tasks. However, there are few studies on single-region path planning in complex polygonal region. In this paper, we proposed a method that searches the optimal yaw-angle and flight height of mapping UAVs based on particle swarm optimization algorithm. Compared with traditional algorithms such as cattle farming algorithm, there are less redundant coverage and turning, and the flight path planned by the algorithm in this paper is more reasonable and convenient for photographic processing.
This paper proposes a tightly-coupled lidar-GNSS-inertial fusion system that achieves accurate state estimation and mapping for robot *** system effectively fuses lidar points,GNSS measurements,and IMU data using the ...
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ISBN:
(数字)9789887581581
ISBN:
(纸本)9798350366907
This paper proposes a tightly-coupled lidar-GNSS-inertial fusion system that achieves accurate state estimation and mapping for robot *** system effectively fuses lidar points,GNSS measurements,and IMU data using the iterated error state Kalman filter algorithm to obtain precise,drift-free,and real-time *** optimize computational efficiency,an incremental tree structure,ikdtree,is employed for managing a local map,and different Kalman gain formulas are utilized to process GNSS and lidar point observations separately to lower the computation ***,a factor graph is introduced to optimize the pose *** selectively introducing keyframes based on the odometry estimation,the graph incorporates odometry,GNSS measurements,and loop closure constraints to optimize all keyframe poses,resulting in a precise trajectory and global ***,extensive experiments are conducted using the KITTI dataset and several real-world scenarios to validate the proposed *** experimental results demonstrate that our method achieves precise localization and mapping across diverse environments.
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