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Real-time accurate ball trajectory estimation with amp;#x201C;asynchronousamp;#x201D; stereo camera system for humanoid Ping-Pong robot

机译:与&#x201c的实时准确的球轨迹估计;异步”人形乒乓球机器人的立体声相机系统

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Temporal asynchrony between two cameras in the vision system is a usual problem in practice. In some vision task such as estimating fast moving targets, the estimation error caused by the tiny temporal asynchrony will become non-ignorable essentials. This paper will address on the asynchrony in the stereo vision system of humanoid Ping-Pong robot, and present a real-time accurate Ping-Pong ball trajectory estimation algorithm. In our approach, the complex Ping-Pong ball motion model is simplified by a polynomial parameter function of time t due to the limited observing time interval and the requirement of real-time computation. We then use the perspective projection camera model to re-project the ball's parameter function on time t into its image coordinates on both cameras. Based on the assumption that the time gap of two asynchronous cameras will maintain a const during very short time interval, we can obtain the time gap value and also the trajectory parameters of the Ping-Pong ball in a short time interval by minimizing the errors between the images of the ball in each camera and their re-projection images from the modeled parameter function on time t. Comprehensive experiments on real Ping-Pong robot cases are carried out, the results show our approach is more proper for the vision system of humanoid Ping-Pong robot, when concerning the accuracy and real-time performance simultaneously.
机译:视觉系统中的两个摄像机之间的颞复曲面是实践中通常的问题。在一些视觉任务之类的诸如估计快速移动目标之类的任务中,由微小的时间异步引起的估计误差将成为不可知的必需品。本文将在人形Ping-Pong-Pong机器人立体声视觉系统中的Asynchrony地址,并提出了一种实时精确的乒乓球轨迹估计算法。在我们的方法中,由于有限的观察时间间隔和实时计算的要求,通过时间T的多项式参数函数简化了复杂的Ping Pong Ball运动模型。然后,我们使用透视投影摄像机模型将球参数函数重新投影在两个相机上的时间t中的图像坐标。基于假设两个异步摄像机的时间间隙将在非常短的时间间隔期间维持常数,我们可以通过最小化之间的误差来获得时间间隙值以及乒乓球的轨迹参数每个相机中的球的图像及其在时间t上的模型参数函数的重新投影图像。实验实验对真正的乒乓球机械案件进行了,结果表明我们的方法更适合人形Ping-Pong-Pong机器人的视觉系统,同时进行准确性和实时性能。

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