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立体视觉测量中的一种摄像机标定方法 总被引:3,自引:0,他引:3
立体视觉测量方法已广泛应用于三维物体几何信息的获取中,针对摄像机标定过程中复杂的成像和跨变模型,提出了基于BP神经网络的立体视觉摄像机标定方法,并利用实际数据对其进行了实验测试。结果表明,该方法可以获得较高的标定精度。 相似文献
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采用可调节点径向基函数神经网络实现视觉伺服机器人摄像机标定.首先将基于leave-one-out准则的orthogonal forward selection算法扩展到多入多出的RBF网络,建立摄像机标定的RBF网络模型.通过应用卡内基-梅隆大学标定图像实验室提供的标定数据进行仿真试验,验证此方法的有效性.由于OFS-LOO算法可构造出具有稀疏隐层节点的RBF网络,使网络具有较好的泛化推广能力,同时RBF网络为局部逼近网络,因此,此标定方法具有较高的标定精度和较强的标定实时性,适用于视觉伺服的摄像机标定. 相似文献
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提出了一种介于传统标定和自标定的内外参数标定分离的方法。摄像机内部参数以透视成像模型为基础,用物理方法来提取;外参数标定时合理选取参考坐标系,通过实验分析求取两摄像头的外参数模型。该算法简单易懂,计算速度快,所需设备简单,实用性好。 相似文献
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在智能制造领域,工业机器人视觉测量技术应用广泛。针对常见的关节型6自由度工业机器人,采用平面模板法对其系统进行立体视觉标定;通过实验结果与工具箱处理过的结果进行对比,验证了标定的准确性取决于合理选择末端执行器不同姿势。给出了实验过程、标定结果分析,期望该方法为工程实践提供参考。 相似文献
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一种基于立体模板的双目视觉传感器现场标定方法 总被引:9,自引:12,他引:9
给出了一种基于立体标定模板的双目视觉摄像机内、外部参数现场标定方法.该方法采用理想小孔模型忽略摄像机镜头的非线性畸变,把透视变换矩阵中的元素作为未知数,在已知一组三维空间特征点坐标及其对应的图像点坐标时,利用线性算法求解出透视变换矩阵中的各个元素,进而得到所需的参数.最后采用立体标定模板对该标定算法进行了实验验证,用标定完成的立体视觉传感器对已知长度进行测量,相对精度达到了0.02%,取得了较为理想的结果.结果表明:该方法由于无需迭代,因此计算速度快,在测量现场只需摆放一次标定模板即可完成标定,可高精度地实现摄像机内、外部参数的现场标定. 相似文献
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摄像机标定是从二维图像提取三维空间信息的关键步骤。为了有效解决传统摄像机标定算法中的多参数和计算费时费力等问题,提高摄像机标定的精度和速度,首次将蚁群遗传算法应用于摄像机标定中。方法初期采用遗传算法过程生成信息素分布,后期利用蚁群算法正反馈求精确解,最后用优化后的BP神经网络来进行摄像机标定,充分发挥遗传算法的全局搜索能力和蚁群算法的正反馈收敛优势。 相似文献
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双目立体视觉测量系统的标定 总被引:2,自引:0,他引:2
考虑传统的自标定方法虽然无需场景信息即可实现摄像机标定,但是标定精度较低,故本文提出了一种新的大视场双目视觉测量系统自标定方法。该方法无需高精度标定板或者标定物,仅需利用空间中常见的平行线和垂直线建立摄像机参数与特征线间的约束方程,即可实现摄像机的内参数与旋转矩阵标定;同时利用空间中距离已知的3个空间点即可线性标定两摄像机间的平移向量。通过标定实验对本文提出的方法进行了验证。结果表明:该方法标定精度能够达到0.51%,可以较高精度地标定双目测量系统。由于避免了大视场测量系统标定中大型标定物制造困难,以及摄像机自标定过程中算法冗杂,标定精度不高等问题,该方法操作简便,精度较好,适用于大视场双目测量系统的在线标定。 相似文献
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STUDY ON INJECTION AND IGNITION CONTROL OF GASOLINE ENGINE BASED ON BP NEURAL NETWORK 总被引:4,自引:1,他引:4
Zhang Cuiping Yang QingfoCollege of Mechanical Engineering Taiyuan University of Technology Taiyuan China 《机械工程学报(英文版)》2003,16(4):441-444
According to advantages of neural network and characteristics of operating procedures ofengine, a new strategy is rapresented on the control of fuel injection and ignition timing of gasolineengine based on improved BP network algorithm. The optimum ignition advance angle and fuelinjection pulse band of engine under different speed and load are tested for the samples trainingnetwork, focusing on the study of the design method and procedure of BP neural network in engine 相似文献
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FORCE RIPPLE SUPPRESSION TECHNOLOGY FOR LINEAR MOTORS BASED ON BACK PROPAGATION NEURAL NETWORK 总被引:2,自引:0,他引:2
Various force disturbances influence the thrust force of linear motors when a linear motor (LM) is running. Among all of force disturbances, the force ripple is the dominant while a linear motor runs in low speed. In order to suppress the force ripple, back propagation(BP) neural network is proposed to learn the function of the force ripple of linear motors, and the acquisition method of training samples is proposed based on a disturbance observer. An off-line BP neural network is used mainly because of its high running efficiency and the real-time requirement of the servo control system of a linear motor. By using the function, the force ripple is on-line compensated according to the position of the LM. The experimental results show that the force ripple is effectively suppressed by the compensation of the BP neural network. 相似文献
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CAO Wanpeng BI Wei CHE Rensheng GUO Wenbo YE Dong 《机械工程学报(英文版)》2008,21(2):87-92
A new motion model and estimation algorithm is proposed to compute the general rigid motion object's 6-DOF motion parameters and center of rotation based on stereo vision. The object's 6-DOF motion model is designed from the rigid object's motion character under the two defined reference frames. According to the rigid object's motion model and motion dynamics knowledge, the corresponding motion algorithm to compute the 6-DOF motion parameters is worked out. By the rigid object pure rotation motion model and space sphere geometry knowledge, the center of rotation may be calculated after eliminating the translation motion out of the 6-DOF motion. The motion equations are educed based on the motion model and the closed-form solutions are figured out. To heighten the motion estimation algorithm's robust, RANSAC algorithm is applied to delete the outliers. Simulation and real experiments are conducted and the experiment results are analyzed. The results prove the motion model's correction and algorithm's validity. 相似文献
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Pan Feng Wang XuanyinState Key Laboratory of Fluid PowerTransmission Control Zhejiang University Hangzhou China 《机械工程学报(英文版)》2004,17(4):507-510
A new versatile camera calibration technique for machine vision using off-the-shelf cameras is described. Aimed at the large distortion of the off-the-shelf cameras, a new camera distortion rectification technology based on line-rectification is proposed. A full-camera-distortion model is introduced and a linear algorithm is provided to obtain the solution. After the camera rectification intrinsic and extrinsic parameters are obtained based on the relationship between the homograph and absolute conic. This technology needs neither a high-accuracy three-dimensional calibration block, nor a complicated translation or rotation platform. Both simulations and experiments show that this method is effective and robust. 相似文献
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ADAPTIVE LEARNING CONTROL OF CUTTING PARAMETERS FOR SCULPTURED SURFACE CUTTING BASED ON GENETIC ALGORITHMS AND NEURAL NETWORK 总被引:1,自引:0,他引:1
Fu Hongya Wang Yongzhang Lu Hua Fu Yunzhong Department of Mechanical Engineering Harbin Institute of Technology Harbin ChinaTakaaki Nagao University of Tokyo Japan 《机械工程学报(英文版)》2002,15(2):145-148
An adaptive learning control scheme intended to the on-line optimization of sculptured surface cutting process is presented. The scheme uses a back-propagation neural network to learn the relationships between process inputs and process states. The cutting parameters of the process model are optimized through a genetic algorithms(GA). The capacity of the proposed scheme for determining optimum process inputs under a variety of process conditions and optimization strategies is evaluated on the basis of milling of a sculptured surface using a ball-end mill. The experimental results show that the neural network could model the cutting process efficiently, and the cutting conditions such as spindle speed could be regulated for achieving high efficiency and high quality. Therefore the proposed approach can be well applied to the manufacturing of dies and molds. 相似文献
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基于RBF神经网络的齿轮箱故障诊断 总被引:1,自引:0,他引:1
阐述径向基函数(radial base function,RBF)神经网络的基本原理和算法,将其应用于齿轮箱故障诊断与识别,建立齿轮箱的BRF故障诊断模型,并与BP(back propagation)神经网络、学习率自适应BP神经网络进行对比分析研究。结果表明,RBF神经网络性能优于BP神经网络,具有较快的训练速度、较强的非线性映射能力和精度较高的故障识别能力,非常适用于齿轮箱的状态监测和故障诊断。但在具体应用中应当注意,RBF网络的训练样本必须含有一定的噪声,以提高网络的容噪性能;各类故障的训练样本数不能太少,否则RBF网络的故障分类能力很差。 相似文献
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基于神经网络响应面的疲劳裂纹扩展寿命的可靠性分析 总被引:5,自引:0,他引:5
当失效形式的极限状态方程中随机变量个数较多或非线性较高时,其形式很复杂,因此传统的计算失效概率的方法不再适用。针对疲劳裂纹扩展寿命失效概率计算的复杂性,提出基于神经网络响应面的可靠性分析方法。首先建立神经网络响应面模拟疲劳裂纹扩展寿命的极限状态方程,然后使用遗传算法(GA)计算可靠性指标。数值试验表明,本方法可以快速、精确地模拟疲劳裂纹扩展寿命的极限状态函数,进而计算出失效概率和可靠性指标。同其他模拟技术相比,在精度相同的情况下,神经网络响应面法可以大大减少模拟时间。 相似文献
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基于立体视觉和激光标记的空间物体位姿的快速定位算法 总被引:7,自引:0,他引:7
建立了一种4自由度双目立体视觉装置的传感器模型,根据空间两条相交射线唯一确定空间一点的原理,提出了在摄像机上加装激光源的方法,通过激光标记来解决目标物体上同一点在两幅CCD图像上对应点的快速匹配问题,从而很方便地求取目标物体的深度信息。最后,研究了目标物体空间位姿的图像定位算法,并通过确定的空间圆柱体位姿验证了该方法的正确性。 相似文献