共查询到18条相似文献,搜索用时 78 毫秒
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室内自主式移动机器人定位方法 总被引:3,自引:0,他引:3
定位是确定机器人在其工作环境中所处位置的过程.应用各种传感器感知信息实现可靠的定位是自主式移动机器人最基本、也是最重要的一项功能之一.本文对室内自主式移动机器人的定位技术进行了综述,介绍了当前自主式移动机器人定位方法的研究现状.同时,对国内外具有典型性的研究方法进行了较洋细的介绍,并重点提出了几种室内自主式移动机器人通用的定位方法,对其中的地图构造、位姿估计方法进行了详细介绍.最后,论述了自主式移动机器人定位系统与地图构造中所面临的主要问题及其解决方法并指出了该领域今后的研究方向. 相似文献
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室内移动机器人的视觉定位方法研究 总被引:6,自引:1,他引:6
针对地图未知的室内环境下的定位问题,提出了一种基于特征跟踪的视觉里程计方法.利用单目摄像头提取和跟踪环境特征点集,进而根据观测模型利用扩展卡尔曼滤波算法估算出机器人的位姿.办公室环境中的定位实验证明了方法的有效性. 相似文献
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设计了一种基于视场中单个目标点的视觉系统标定方法,任意选取视场中的一点作为目标点,以该目标点为基准,机器人作相对运动来获得多个特征点。建立图像系列对应点之间的几何约束关系及各坐标系之间的变换矩阵,确定变换矩阵关系式,进一步求解摄像机的内外参数。该标定方法只需提取场景中的一个景物点,对机器人的运动控制操作方便、算法实现简洁。实验结果验证了该方法的有效性。 相似文献
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An Agricultural Mobile Robot with Vision-Based Perception for Mechanical Weed Control 总被引:18,自引:0,他引:18
This paper presents an autonomous agricultural mobile robot for mechanical weed control in outdoor environments. The robot employs two vision systems: one gray-level vision system that is able to recognize the row structure formed by the crops and to guide the robot along the rows and a second, color-based vision system that is able to identify a single crop among weed plants. This vision system controls a weeding-tool that removes the weed within the row of crops. The row-recognition system is based on a novel algorithm and has been tested extensively in outdoor field tests and proven to be able to guide the robot with an accuracy of ±2 cm. It has been shown that color vision is feasible for single plant identification, i.e., discriminating between crops and weeds. The system as a whole has been verified, showing that the subsystems are able to work together effectively. A first trial in a greenhouse showed that the robot is able to manage weed control within a row of crops. 相似文献
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在基于单目视觉的自主导航中,由于农用轮式移动机器人相对于跟踪路径位姿的传统求解算法,往往存在忽视图像中各像素点权重不同和计算效率不理想等缺陷,因此,针对农田环境特点,在分析地面上直线路径透视成像特性的基础上,提出了一种农用轮式移动机器人相对位姿的求解方法。该方法首先建立起被跟踪路径在图像平面上的像素坐标与机器人相对位姿间的关系方程,然后结合Hough变换的思想直接求出位姿值。实验结果表明,该方法不仅可以有效地弥补传统算法的不足,而且测量精度也与当前其他类似研究的水平大致相当。 相似文献
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地面机器人结构光道路识别方法的研究 总被引:3,自引:7,他引:3
将结构光方法应用到地面移动机器人视觉道路识别中。首先阐述了结构光方法的原理,并根据结构光的特点,研究了在噪声干扰条件下的环境图像的处理、道路识别、路径规划等内容。实验表明,结构光方法能够满足移动机器人实时视觉道路识别的需要,具有简单快速的优点,有一定的实用意义。 相似文献
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基于地平面假设的移动机器人单路视觉运动估计存在鲁棒性和环境适应性较差、精度较低等缺
点,针对这一问题,本文首先介绍了拟全方位视觉系统的构成,并结合该视觉系统的特点给出了一种基于两
步运动的摄像头平行位姿参数标定方法.然后据此提出了一种基于拟全方位视觉的自主移动机器人自运动融
合估计方法.该方法能够借助机器人的非完整运动约束、地平面运行假设以及运动估计参数之间的相容性测
度等多种因素,对拟全方位视觉系统中的各路视觉估计进行性能综合评价;最终依据评价结果融合确定出具
有较高可信度和较强鲁棒性的运动估计参数.实验结果从鲁棒性、精度以及实时性等方面验证了本算法的有
效性. 相似文献
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提出了一种新颖的基于两个特征点的室内移动机器人定位方法。与已有的几何位姿估计方法或航标匹配方法不同,该方法不需要人工航标,也不需要准确的环境地图,只需一幅由传统的CCD相机拍摄的图像。从机器人接近的目标上选取相对于地面等高的两个点作为两个特征点。基于这两点建立一个目标坐标系。在相机平视且这两个特征点与相机投影中心相对于地面不是恰好等高的条件下,就可以根据这两个特征点在图像中的坐标确定机器人相对于目标坐标系的位置和运动方向。该方法非常灵活,适用范围广,可以大大简化机器人定位问题。试验结果表明这一新的方法不仅简单灵活而且具有很高的定位精度。 相似文献
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Gordon Wyeth 《Autonomous Robots》1998,5(3-4):381-394
This paper presents the design, implementation and evaluation of a trainable vision guided mobile robot. The robot, CORGI, has a CCD camera as its only sensor which it is trained to use for a variety of tasks. The techniques used for training and the choice of natural light vision as the primary sensor makes the methodology immediately applicable to tasks such as trash collection or fruit picking. For example, the robot is readily trained to perform a ball finding task which involves avoiding obstacles and aligning with tennis balls. The robot is able to move at speeds up to 0.8 ms-1 while performing this task, and has never had a collision in the trained environment. It can process video and update the actuators at 11 Hz using a single $20 microprocessor to perform all computation. Further results are shown to evaluate the system for generalization across unseen domains, fault tolerance and dynamic environments. 相似文献
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This paper presents the design, implementation and evaluation of a trainable vision guided mobile robot. The robot, CORGI, has a CCD camera as its only sensor which it is trained to use for a variety of tasks. The techniques used for train ing and the choice of natural light vision as the primary sensor makes the methodology immediately applicable to tasks such as trash collection or fruit picking. For example, the robot is readily trained to perform a ball finding task which involves avoiding obstacles and aligning with tennis balls. The robot is able to move at speeds up to 0.8 ms-1 while performing this task, and has never had a collision in the trained environment. It can process video and update the actuators at 11 Hz using a single $20 microprocessor to perform all computation. Further results are shown to evaluate the system for generalization across unseen domains, fault tolerance and dynamic environments. 相似文献