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1.
基于Visual C++6.0的机器人控制系统软件实现   总被引:6,自引:0,他引:6  
三自由度插拔机器人控制系统软件根据开放式设计方法,采用Visual C 语言编制控制程序。负责底层伺服驱动的函数库以标准C给出,可以直接被调用;同时,控制软件内嵌入了机器人研究所自行开发的机器人结构化编程语言——HRL语言,用以实现目标规划,它也是基于Visual C 语言开发的。整个控制软件用以完成数据及状态显示、伺服驱动、机器人运动规划,插拔目标的搜索、定位、运动过程模拟显示等任务。  相似文献
2.
基于模板的快速目标搜索算法研究   总被引:3,自引:0,他引:3  
董慧颖 《控制工程》2002,9(3):87-89
对两种基于模板的快速目标搜索算法-四叉树法、模板膨胀法进行了研究,并与逐点匹配法做了比较,得出结论。根据相关匹配原理,采用四叉树法和快速模板膨胀匹配法,对目标进行快速搜索,可以较大地提高目标区域的搜索速度。  相似文献
3.
A Complexity-Level Analysis of the Sensor Planning Task for Object Search   总被引:2,自引:0,他引:2  
Object search is the task of searching for a given 3 D object in a given 3 D environment by a controllable camera. Sensor planning for object search refers to the task of how to select the sensing parameters of the camera so as to bring the target into the field of view of the camera and to make the image of the target to be easily recognized by the available recognition algorithms. In this paper, we study the task of sensor planning for object search from the theoretical point of view. We formulate the task and point out many of its important properties. We then analyze this task from the complexity level and prove that this task is NP-Complete.  相似文献
4.
基于形态学的快速图像搜索与识别算法   总被引:1,自引:0,他引:1  
介绍了一个无人直升机实时机器视觉系统的设计和实现,重点是图像的动态处理技术.以自适应门限值提取前景区域,通过扩展的连通分量提取算法实现了目标的快速搜索,最后基于几何特征对目标加以识别.通过在大量飞行中对目标的成功搜索和识别,证明了该算法的有效性.  相似文献
5.
面向病房巡视的服务机器人目标搜寻   总被引:1,自引:0,他引:1  
为了解决现阶段病房巡视任务中出现的巡护不及时等问题,利用服务机器人进行病房巡视,完成病人的基本信息验证、病人治疗信息获取等巡视任务.提出了基于叭叶斯理论的面向巡视任务的机器人控制策略,该策略利用机器人的当前位姿、规划的路径,与当前的视觉图像相结合,进行机器人控制;提出了由粗到细的多模式目标表示方法,融合RFID、特征和图像来表示目标,利用RFID进行目标的初步粗定位,对于经常移动的目标采用人工标记物或自身特征的方式表示,对于相对固定的目标利用模板图像表示,进一步缩小搜索范围;利用主动视觉计算显著性图引导视觉注意,并采用特征验证的方式进行目标最终定位;最后,基于定位的目标控制摄像头运动实现目标图像的抓取.实验结果表明,本文提出的方案可以较好地实现服务机器人的病房巡视.  相似文献
6.
This paper addresses multi-objective optimization from the viewpoint of real-world engineering designs with lots of specifications, where robust and global optimization techniques need to be applied. The problem used to illustrate the process is the design of non-linear control systems with hundreds of performance specifications. The performance achieved with a recent multi-objective evolutionary algorithm (MOEA) is compared with a proposed scheme to build a robust fitness function aggregation. The proposed strategy considers performances in the worst situations: worst-case combination evolution strategy (WCES), and it is shown to be robust against the dimensionality of specifications. A representative MOEA, SPEA-2, achieved a satisfactory performance with a moderate number of specifications, but required an exponential increase in population size as more specifications were added. This becomes impractical beyond several hundreds. WCES scales well against the problem size, since it exploits the similar behaviour of magnitudes evaluated under different situations and searches similar trade-offs for correlated objectives. Both approaches have been thoroughly characterized considering increasing levels of complexity, different design problems, and algorithm configurations.  相似文献
7.
针对实际比赛中足球机器人视觉系统不能快速、准确地搜索到目标物体的问题,分析了RGB空间模型的优缺点以及基于彩色HSI变换原理,结合足球机器人的实际情况采用了一种从RGB空间到HIS空间快速变换的方法对颜色信息进行处理.同时,通过分析以往的目标搜索方法的优缺点,提出了一种基于颜色索引表的顺序网格法和种子填充法相结合的目标搜索方法,并在足球机器人视觉系统中进行了实验.实验结果表明这种方法既在一定的程度上降低了噪声干扰的影响,又避免了逐个像素计算颜色值,大大降低了计算量,从而提高了系统的实时性和可靠性.  相似文献
8.
提出一种多搜索结果的三极管芯片图像匹配算法.首先利用金字塔搜索算法对目标图像进行分层搜索匹配,减少了图像的匹配计算量.其次在搜索过程中依次判断搜索目标是否符合要求,并消除重复结果.所提出的算法主要用于三极管芯片的粘片机及焊线机的图像识别系统中,试验证明该算法能满足设备的实时性和精度要求.  相似文献
9.
A new method for rotation-invariant template matching in gray scale images is proposed. It is based on the utilization of gradient information in the form of orientation codes as the feature for approximating the rotation angle as well as for matching. Orientation codes-based matching is robust for searching objects in cluttered environments even in the cases of illumination fluctuations resulting from shadowing or highlighting, etc. We use a two-stage framework for realizing the rotation-invariant template matching; in the first stage, histograms of orientation codes are employed for approximating the rotation angle of the object and then in the second stage, matching is performed by rotating the object template by the estimated angle. Matching in the second stage is performed only for the positions which have higher similarity results in the first stage, thereby pruning out insignificant locations to speed up the search. Experiments with real world scenes demonstrate the rotation- and brightness invariance of the proposed method for performing object search.  相似文献
10.
We consider the problem of efficiently finding an object with a mobile robot in an initially unknown, structured environment. The overall goal is to allow the robot to improve upon a standard exploration technique by utilizing background knowledge from previously seen, similar environments. We present two conceptually different approaches. Whereas the first method, which is the focus of this article, is a reactive search technique that decides where to search next only based on local information about the objects in the robot’s vicinity, the second algorithm is a more global and inference-based approach that explicitly reasons about the location of the target object given all observations made so far. While the model underlying the first approach can be learned from data of optimal search paths, we learn the model of the second method from object arrangements of example environments. Our application scenario is the search for a product in a supermarket. We present simulation and real-world experiments in which we compare our strategies to alternative methods and also to the performance of humans.  相似文献
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