Hair direction is an important external feature of hair, and recognising hair direction is a prerequisite for processing hair. In this paper, a new algorithm is proposed and systematically verified experimentally for ...
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ISBN:
(数字)9798331506100
ISBN:
(纸本)9798331506117
Hair direction is an important external feature of hair, and recognising hair direction is a prerequisite for processing hair. In this paper, a new algorithm is proposed and systematically verified experimentally for the problem of recognising hair direction. The main goal of this paper is to develop an algorithm that can identify hair direction in a complex image environment. A curve segment analysis method based on image skeletonisation is adopted, which is based on skeleton extraction, intersection identification, curve segmentation and direction prediction. In addition, this paper combines the technique of non-maximal value suppression and PCA analysis to improve the accuracy and stability of the estimation. In the experimental design, this paper chooses a representative image dataset to verify the effectiveness of this paper's algorithm. The experimental process includes the steps of image preprocessing, skeletonisation processing, intersection detection and merging, and direction prediction. The experimental results show that the method in this paper can accurately and effectively identify the hair direction. The main contribution of this paper is to propose a new hair direction recognition method and experimentally verify its effectiveness and accuracy in complex backgrounds.
Spatial frequency (SF) is a characteristic of an image that could dissociate course and fine shape information. Physiological and psychophysical studies widely investigated the role of various SF contents in image pro...
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Spatial frequency (SF) is a characteristic of an image that could dissociate course and fine shape information. Physiological and psychophysical studies widely investigated the role of various SF contents in image processing. Inspired by the primate brain structure, deep neural networks improved various computer vision tasks such as image classification. Physiological studies show that low SF (LSF) contents of an image could be processed faster to provide feedback to facilitate object recognition. However, this knowledge has not been considered in designing neural network structures. This study introduces SFNet, a new neural network structure that employs an LSF-based feedback mechanism. SFNet is a two-stream structure where one stream is used for LSF processing to provide feedback for image classification. The other stream combines the LSF-based feedback and the HSF processing to form the final decision. The role of the proposed LSF-based feedback in image classification is investigated utilizing the CIFAR100 dataset. The results show that SFNet improves the performance in the presence of SF filtering compared to the equivalent structures.
Path planning and tracking control are important modules of mobile robots, which have outstanding advantages in improving the flexibility of mobile robots. However, in the existing applications, these two modules are ...
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ISBN:
(纸本)9781665409858
Path planning and tracking control are important modules of mobile robots, which have outstanding advantages in improving the flexibility of mobile robots. However, in the existing applications, these two modules are usually processed separately, which makes the obstacle avoidance process of the mobile robot uncontrollable and reduces the adaptability of the application scenario. In order to realize collision-free high-precision trajectory tracking control of mobile robots in dynamic scenes, this paper proposes an adaptive MPC control method based on curvature constraints, which can improve the safety of operation and reduce the chattering caused by unreasonable paths in the process of operation. Firstly, according to the kinematic constraints of general mobile robots, the constraint model of mobile robot path planning is constructed. At the same time, the adaptive parameter adjustment rules are adopted to realize the balance between the calculation efficiency and the control cycle. Finally, a smooth safe path is obtained by re-fitting the planned path and reprocessing the nodes with excessive curvature. Compared with traditional methods, the proposed method has better advantages.
During the production process of cold-rolled hot-dip galvanizing,the slag on the surface of the zinc pot will affect the quality of the *** zinc slag is mostly collected manually or by robots at *** effect of manual s...
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During the production process of cold-rolled hot-dip galvanizing,the slag on the surface of the zinc pot will affect the quality of the *** zinc slag is mostly collected manually or by robots at *** effect of manual salvage is unstable and the operation is *** robot cannot identify the location of the zinc slag and can only salvage it according to a fixed rule,resulting in low *** response to the above problems,a zinc pot slag path planning method based on the greedy algorithm is proposed in this *** zinc pot area is divided,the image processing method is used to identify and locate the zinc slag to be *** the priority of the zinc pot,the obstacle avoidance problem and the restriction of the weight limit of the slag-removing tool are proposed in combination with the process *** three salvage strategies based on the greedy algorithm,the shortest distance,the maximum weight,and the minimum weight are proposed *** results show that the greedy algorithm strategy based on the shortest distance performs best,consumes the least energy,and the algorithm runs for a shorter *** can significantly improve the efficiency of zinc pot slag removal,realize intelligentcontrol of slag removal technology,and can be applied to the actual production of zinc pot slag removal.
With the rapid development of space crawling robotics technology, tactile perception, a significant source for the robot to sense the external environment, has become the preferred solution to gather information in sp...
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Firstly,the forward kinematics and inverse kinematics of a five axis manipulator are ***,an easyimplemented optimization method of trajectory planning based on seventh order polynomial interpolation is *** proposed op...
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Firstly,the forward kinematics and inverse kinematics of a five axis manipulator are ***,an easyimplemented optimization method of trajectory planning based on seventh order polynomial interpolation is *** proposed optimization method can capture the time optimal trajectory,while the actuators specifications including speed,acceleration of motor can be guaranteed as ***,simulation results validate the effectiveness and efficiency of proposed optimization *** research provides an insight for the application of trajectory optimization on the controller with low computing capability and real-time requirement.
In traditional impedance control model,the contact force can be reduced ***,there exists a tracking error at the stable state due to the existence of stiffness,which is not conducive to tackle tasks based on high perf...
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In traditional impedance control model,the contact force can be reduced ***,there exists a tracking error at the stable state due to the existence of stiffness,which is not conducive to tackle tasks based on high performance position control for ***,this paper proposes a novel dynamic interaction model:fractional order impedance control,to address this ***,an integral item is added into the traditional impedance model to eliminate the tracking ***,the idea of fractional order is introduced to make the orders of inertia,damping,and stiffness change from integers to fractions to achieve more significant compliant ***,simulation results validate the advantages of proposed fractional order impedance control and it can be also employed to absorb/increase,hold/keep,and dissipate/decrease system energy to achieve jumping,bouncing and friendly contact,***,stability analysis and three criterions of choosing and tuning 6 classic parameters in the proposed fractional order impedance control are both given out.
Learning tailored target representations for tracking is a promising direction in visual object tracking. Most state-of-the-art methods utilize autoencoders to generate representations by reconstructing the target'...
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We present an open-source software interface, called mc-naoqi, that allows to perform whole-body task-space Quadratic Programming based control, implemented in mc rtc framework, on the SoftBank robotics Europe humanoi...
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ISBN:
(数字)9781728176581
ISBN:
(纸本)9781728176598
We present an open-source software interface, called mc-naoqi, that allows to perform whole-body task-space Quadratic Programming based control, implemented in mc rtc framework, on the SoftBank robotics Europe humanoid robots. We describe the control interface, associated robot description packages, robot modules and sample whole-body controllers. We demonstrate the use of these tools in simulation for a robot interacting with a human model. Finally, we showcase and discuss the use of the developed open-source tools for running the human-robot close contact interaction experiments with real human subjects inspired from assistance scenarios.
The improvement of urban greening level makes sanitary work more complicated and difficult, especially, for the seasonal leaf cleaning on roads in the park, campus etc.. With the rapid development of computer vision, ...
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ISBN:
(纸本)9781665405362
The improvement of urban greening level makes sanitary work more complicated and difficult, especially, for the seasonal leaf cleaning on roads in the park, campus etc.. With the rapid development of computer vision, it is a feasible and innovative way to detect and clean the fallen leaves effectively with intelligent robot. However, since the irregular shape and size, uneven distribution of fallen leaves and complex outdoor conditions, especially the densely stacked leaves, even current advanced object detection algorithm has no satisfactory effect on detection of fallen leaves. To deal with the dense leaves detection problem and improve navigation efficiency, we propose a Non-Maximum Fusion(NMF) algorithm. NMF scales the high-confidence box with the pre-defined δ to fuse intersecting and adjacent boxes instead of supressing these boxes. The experiments on the fallen leaves data set shows that NMF improves the fallen leaves detection coverage significantly and the coverage reaches to 95%. Also, NMF greatly reduces the number of goal nodes for path planning. Since NMF functions at the back end of detector to process detection boxes without training, it can be intergrated into any fallen leaves detection pipeline easily.
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