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Trajectory Generation for Capturing a Moving Object in Predictable Environments

机译:在可预测环境中捕获运动物体的轨迹生成

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摘要

In the field of computer vision, it is a complex and demanding much task to detect and to track moving objects from a moving observer. However, in this paper a new scheme for a mobile robot to track and capture a moving object using images of a camera is proposed. The system consists of the following modules: data acquisition, feature extraction and visual tracking, and trajectory generation. And a single camera is used as visual sensors to capture image sequences of a moving object. The moving object is assumed to be a point-object and projected onto an image plane to form a geometrical constraint equation that provides position data of the object based on the kinematics of the active camera. Uncertainties in the position estimation caused by the point-object assumption are compensated using the Kalman filter. To generate the shortest time trajectory to capture the moving object, the linear and angular velocities are estimated and utilized. The experimental results of tracking and capturing of the target object with the mobile robot are presented.
机译:在计算机视觉领域中,检测和跟踪来自运动的观察者的运动物体是一项复杂而艰巨的任务。然而,在本文中,提出了一种新的方案,用于移动机器人使用摄像机的图像来跟踪和捕获运动对象。该系统由以下模块组成:数据获取,特征提取和视觉跟踪以及轨迹生成。单个摄像头用作视觉传感器来捕获运动对象的图像序列。假定移动对象是点对象,并且将其投影到图像平面上以形成几何约束方程式,该方程式将基于活动摄像机的运动学提供对象的位置数据。使用卡尔曼滤波器可以补偿由点对象假设引起的位置估计中的不确定性。为了生成最短的时间轨迹来捕获运动物体,需要估算和利用线速度和角速度。给出了利用移动机器人跟踪和捕获目标物体的实验结果。

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