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.
The local map can update the local environment information in real time, which provides the environment information for the local dynamic planning of the robot. In this paper, a local cost map construction method base...
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The local map can update the local environment information in real time, which provides the environment information for the local dynamic planning of the robot. In this paper, a local cost map construction method based on 3D-LIDAR and camera is proposed. We use camera to detect lane lines in structured road and 3D-LIDAR to detect road boundaries in unstructured environment, and then use DS evidence reasoning to determine the current local road information. Dynamic obstacle information in the environment is obtained through 3D point cloud data segmentation, which is fused with the road information to get 3D point cloud information in the local range and generate local cost map according to it. Experiments show that the method in this paper can accurately extract the current road information whether in structured roads or unstructured roads. The fused local cost map can enable the robot to perform reasonable local planning and complete navigation on the current road.
This paper presents a novel five-phase double-stator permanent-magnet synchronous motor (DSPMSM). The motor is compacted with DSPMSM and fault-tolerant motor, so that the motor not only inherits the merits of double-s...
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This paper presents a novel five-phase double-stator permanent-magnet synchronous motor (DSPMSM). The motor is compacted with DSPMSM and fault-tolerant motor, so that the motor not only inherits the merits of double-stator which with high torque density and high utilization rate of the space, but also achieves fault tolerance. A new structure of the rotor is proposed for the DSPMSM. The DSPMSM proposed in the paper poses with high air-gap flux density, torque density and fault-tolerant capacity. control strategies and electromagnetic torque characteristics of the DSPMSM with completely loss of one and two phases are described. The fault-tolerant performance of the DSPMSM is analyzed by finite element method.
Formation control from optimal control strategy is derived based on the position estimation for second-order molded agents using only the relative *** the proposed strategy,agents can realize the convergence to the de...
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ISBN:
(纸本)9781479947249
Formation control from optimal control strategy is derived based on the position estimation for second-order molded agents using only the relative *** the proposed strategy,agents can realize the convergence to the desired formation configure if and only if the interaction graph for the agents has a spanning *** control input is added into the derived control strategy,with the help of detecting obstacles using the relative position and taking avoidance measures using the estimated position,it can also realize obstacle avoidance for agents between themselves.
In this paper, a monocular visual-inertial odometry that utilize both point and line features is deduced. Compared with point features, line features provide more geometric information of the environment, which are mo...
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In this paper, a monocular visual-inertial odometry that utilize both point and line features is deduced. Compared with point features, line features provide more geometric information of the environment, which are more reliable in textureless scenes. However, extracting line segment features from the image are very time consuming, which will affect the real-time performance of the system. To deal with this problem, EDLines line segment detector is introduced to replace the LSD *** properties of lines are utilized to reject the mismatching of line segment feature. Pl ¨ucker coordinates and orthonormal representation of lines are used to represent 3 D lines. Afterwards, we optimize the state by minimizing a cost function consists of pre-integrated IMU residuals and visual feature re-projection residuals in a sliding window optimization framework. The proposed odometry was tested on the public datasets. The results demonstrate that the presented system can operate in real time with high accuracy.
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