In this paper, we present a trajectory generation method for quadrotor while tracking a moving target with relative pattern. Compared to existing methods, safe flying zone, vehicle’s physical limits and smoothness ar...
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In this paper, we present a trajectory generation method for quadrotor while tracking a moving target with relative pattern. Compared to existing methods, safe flying zone, vehicle’s physical limits and smoothness are considered to ensure obstacles avoidance and real tracking flight. To tackle with the cluttered environment, a parallel Particle Swarm Optimization algorithm is applied to calculate the safe feasible waypoints for quadrotor with consideration of target’s predicted state and the realistic tracking pattern, as well as safety. Then, a multiple waypoints constraints motion planning method is applied and embed into a cost function for solving the problem of trajectories generation and robust tracking for quadrotor via convex optimization approach, ensuring the real-time planning, with the geometrical constraint of safe flight corridor for quadrotor. The effectiveness of proposed method is verified by numerical simulation experiments.
Comparing to the commonly used hydraulic three-axial shaking tables, multi-degree of freedom shaking systems implemented by Stewart platform have the merits of being portable, easy to install and with high load capaci...
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Comparing to the commonly used hydraulic three-axial shaking tables, multi-degree of freedom shaking systems implemented by Stewart platform have the merits of being portable, easy to install and with high load capacity, but are not well studied because of the inherent nonlinearity and strong coupling of Stewart platform. In order to replicate multi-degree of freedom road acceleration spectrum on Stewart platform, analysis of the system was carried out. Firstly, the system structure was introduced and the linearized platform kinematic equations, at the equilibrium position, were inducted. The models of actuators that drive the platform were simplified and the principles of three variable controller(TVC) were deduced briefly. Finally, MATLAB-Adams co-simulation environment was built to perform multi-degree of freedom road acceleration spectrum replication with TVC. The results show that it can reproduce high accuracy multi-degree of freedom road acceleration spectrum with TVC on Stewart platform.
The research of image deblurring plays an important role in the digital image *** order to reduce image blurring problems,a content constraint loss(CCL) function in the generative adversarial network(GAN)is *** SS...
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The research of image deblurring plays an important role in the digital image *** order to reduce image blurring problems,a content constraint loss(CCL) function in the generative adversarial network(GAN)is *** SSIM loss and the perceptual loss constitute the CCL function,which makes the trained generative model *** CCL function as the content constraint loss component and the adversarial loss component constitute the total *** total loss is optimized by the iterative training to further improve the stability of the network model,and the image blurring will be *** the test experiment of the open source image dataset MNIST,CIFAR10/100 and CELEBA,the CCL function is used as the content constraint loss component of the generative adversarial network,the effect of image deblurring has obvious promotion in the structural similarity measure and visual appearance.
In this paper we investigate an extension of Resource Constrained Projected Scheduling Problem(RCPSP): the Resource Constrained Project Scheduling Problem with Transfer Time under Resource Bundle. For this complex pro...
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In this paper we investigate an extension of Resource Constrained Projected Scheduling Problem(RCPSP): the Resource Constrained Project Scheduling Problem with Transfer Time under Resource Bundle. For this complex problem, the use of a parallel scheduling scheme is proposed. Such scheme has been successfully applied to the RCPSP. Introducing transfer time and resource bundle into RCPSP causes two problems, one is the possibility of resources significantly exceed the need of a task, the other is cooperation among unfamiliar members from different team may increase the makespan of the project. In order to deal with the problem, two new concepts are developed: task-related resource weight and collaboration coefficient. Some discussion of such concepts is given of and use them for new heuristic framework we proposed. A computational test is performed and the results show that the new heuristic is very effective in finding better solutions within a very short time.
Targets grouping is the basis of second-level information fusion,which can effectively assist commanders to make *** aerial targets grouping algorithm only takes the radar acquisition data at the current time as the o...
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Targets grouping is the basis of second-level information fusion,which can effectively assist commanders to make *** aerial targets grouping algorithm only takes the radar acquisition data at the current time as the object and cannot update the clustering results automatically.A grouping method combining dynamic time warping(DTW) and the algorithm Density-Based Spatial Clustering of Applications with Noise(DBSCAN) is *** DTW distance of each attribute historical time-series data is used to measure the similarity between ***,an improved DBSCAN algorithm is used for *** simulation results show that the method has better grouping effect and can automatically cluster regularly.
Incorporating the depth (D) information for RGB images has proven the effectiveness and robustness in semantic segmentation. However, the fusion between them is still a challenge due to their meaning discrepancy, in w...
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Kalman filter has been extensively applied in vast areas. However, the performance of Kalman filter rests on the accuracy of prior information such as model construction. In the integrated system of Strapdown Inertial...
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ISBN:
(纸本)9781538604915
Kalman filter has been extensively applied in vast areas. However, the performance of Kalman filter rests on the accuracy of prior information such as model construction. In the integrated system of Strapdown Inertial Navigation system (SINS)/Global Positioning system (GPS), the model construction is affected by a certain error sources. The most significant one is computational errors, which are caused by improper reference frame and the absence of true values. To solve the problem, this paper presents a modified system model which reduce the impact of computational errors by selecting computational frame as reference coordinate frame and removing all true values. Simulation results have demonstrated that modified system model effectively improves the performance of Kalman filter in SINS/GPS integrated system.
A mount of recent researches on scene parsing and semantic labeling, while few focus on obtaining joint semantic motion labeling. In this paper, we propose an approach to infer both the object class and motion status ...
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ISBN:
(纸本)9781509024100
A mount of recent researches on scene parsing and semantic labeling, while few focus on obtaining joint semantic motion labeling. In this paper, we propose an approach to infer both the object class and motion status for each pixel of images. First, we extract and match sparse image features to estimate ego-motion between two consecutive stereo images, the result of feature points grouping is used to segment moving object in U-disparity map. Second, a Fully Convolutional Neural Network is employed for semantic segmentation. Moreover, semantic cues are utilized to remove pixels have no potential to be moved in motion mask. Finally, we use a fully connected CRF to integrate motion into semantic segmentation. To validate the effectiveness of the proposed algorithm, we present experimental results with KITTI stereo images that contain moving objects.
Intersection detection is a critical capacity for an Unmanned Ground Vehicle (UGV) to drive safely in structured urban environment. Large-scale intersections stamped on maps have plenty of features for detection while...
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Intersection detection is a critical capacity for an Unmanned Ground Vehicle (UGV) to drive safely in structured urban environment. Large-scale intersections stamped on maps have plenty of features for detection while some unmapped small-scale urban intersections are hard to be identified. In this paper, we propose a novel intersection detection method conducted on the basis of Hidden Markov Model (HMM). This method is based on the intersection scan model to obtain the traversable directions to classify the intersection. The scan model is effective in dealing with both LIDAR and visual data. Combination of the scan model and the HMM can accurately estimate the traversable directions in consideration of both real-time and historic data. Results from simulations and real-world experiments have shown the functionality of the presented approach.
Rapidly growing urbanization is putting more pressure on the well-being of citizens and the environment. Applying the latest ICT technology to address urban transport challenges is a key strategy to release the new in...
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