首页> 外文会议>IEEE Annual International Conference on CYBER Technology in Automation, Control, and Intelligent Systems >A Localization Method Based on Large Scene Tracking and Target Details Observation About Small Quadruped Robot Under Global Vision
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A Localization Method Based on Large Scene Tracking and Target Details Observation About Small Quadruped Robot Under Global Vision

机译:基于大场景跟踪和目标细节观测的全局视野下小型四足机器人定位方法

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This paper resolved the problem of observing the target's high definition details when the global camera observing a large range field, in the process of mobile robot's location and navigation under global vision in outdoor environment. Two cameras with different focal lengths were used. The fisheye camera with short focal lens was used for the observation of large scenes, and the camera with long focal lens fixed on a PAN/TILT Head was used for observing the target's details by amplifying it. In this paper, the Particle Filter Algorithm with the weighted RGB color histogram was used for tracking target in the image caught by the fish-eye camera. The OcamCalib Tool was used for calibrating the fish-eye camera in MATLAB, to establish a mapping model from the image coordinate system to the lens coordinate system, calculating the vector of the target in the lens coordinate system. This vector were used for calculating the rotation angle of two joint of the PAN/TILT Head. The rotation speed of the electromechanical actuator were controlled indirectly by three layers of loop, so that the PAN/TILT Head was rotated smoothly to the reference angle position. Using a long focal camera to amplify and observe the target, the QR code attached to the mobile robot was observed in high definition. Extracting the nested contours to calculate the direction of the QR code and the orientation of the robot. In the end, the effectiveness of the method is verified by experiments.
机译:本文解决了在室外环境下,在全球视野下移动机器人的定位和导航过程中,当全球摄像机观测大范围场时,观测目标的高清细节的问题。使用了两个具有不同焦距的相机。鱼眼镜头相机使用短焦距镜头,用于观察大型场景,而长焦镜头相机固定在PAN / TILT Head上,用于放大目标,以观察目标的细节。在本文中,使用具有加权RGB颜色直方图的粒子滤波算法来跟踪鱼眼镜头捕获的图像中的目标。 OcamCalib工具用于在MATLAB中校准鱼眼镜头,以建立从图像坐标系到镜头坐标系的映射模型,并在镜头坐标系中计算目标向量。该向量用于计算PAN / TILT Head的两个关节的旋转角度。机电执行器的转速由三层环间接控制,因此PAN / TILT Head可以平稳地旋转到参考角度位置。使用长焦距相机放大并观察目标,可以清晰地观察到附着在移动机器人上的QR码。提取嵌套轮廓以计算QR码的方向和机器人的方向。最后,通过实验验证了该方法的有效性。

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