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A new way in intelligent recognition improves control accuracy and efficiency For spacecrafts' rendezvous and docking

机译:智能识别的一种新方法可以提高航天器的对接和对接的控制准确性和效率

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Spacecrafts rendezvous and docking (RVD) by human or autonomous control is a complicated and difficult problem especially in the final approach stage. Present control methods have their key technology weakness. It is a necessary, important and difficult step for RVD through human's aiming chaser spacecraft at target spacecraft in a coaxial line by a three-dimension bulge cross target. At present, there is no technology to quantify the alignment in image recognition direction. We present a new practical autonomous method to improve the accuracy and efficiency of RVD control by adding image recognition algorithm instead of human aiming and control. Target spacecraft has a bulge cross target which is designed for chaser spacecraft's aiming accurately and have two center points, one is a plate surface center point(PSCP), another is a bulge cross center point(BCCP), while chaser spacecraft has a monitoring ruler cross center point(RCCP) of the video telescope optical system for aiming. If the three center points are coincident at the monitoring image, the two spacecrafts keep aligning which is suitable for closing to docking. Using the trace spacecraft's video telescope optical system to acquire the real-time monitoring image of the target spacecraft's bulge cross target. Appling image processing and intelligent recognition algorithm to get rid of interference source to compute the three center points' coordinate and exact digital offset of two spacecrafts' relative position and attitude real-timely, which is used to control the chaser spacecraft pneumatic driving system to change the spacecraft attitude in six direction: up, down, front, back, left, right, pitch, drift and roll precisely. This way is also practical and economical because it needs not adding any hardware, only adding the real-time image recognition software into spacecrafts' present video system. It is suitable for autonomous control and human control.
机译:人类或自主控制的航天器与对接(RVD)是一个复杂和困难的问题,特别是在最终的方法阶段。目前的控制方法具有其关键技术的弱点。通过三维凸起交叉目标,通过人类瞄准追逐航天器的RVD在瞄准航天器中的必要,重要且难的步骤。目前,没有技术可以量化图像识别方向上的对准。我们提出了一种新的实际自主方法,通过添加图像识别算法而不是人体瞄准和控制来提高RVD控制的准确性和效率。目标宇宙飞船具有凸起的交叉目标,专为Chaser Spacocraft的瞄准而设计,具有两个中心点,一个是板表面中心点(PSCP),另一个是凸起交叉中心点(BCCP),而Chaser Spacecraft有一个监测尺用于瞄准的视频望远镜光学系统的交叉中心点(RCCP)。如果三个中心点在监测图像处重合,则两个航天器保持对准,该对准适合于关闭对接。使用Trace SpaceCraft的视频望远镜光学系统获取目标航天器凸起交叉目标的实时监控图像。应用图像处理和智能识别算法摆脱干扰源来计算三个中心点的坐标和精确数字偏移的两个航天器的相对位置和姿态实时,用于控制追逐宇宙飞船气动驱动系统改变六方向的航天器姿态:精确,向上,前,背部,左,右,螺距,漂移和滚动。这种方式也是实用且经济的,因为它不需要添加任何硬件,只能将实时图像识别软件添加到航天器的现有视频系统中。它适用于自主控制和人类对照。

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