空间机器人捕获非合作目标的轨迹预测

Dong-Chul Han, Panfeng Huang
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引用次数: 8

摘要

空间非合作目标的轨迹跟踪与预测一直是空间智能机器人在轨捕获任务中的关键技术。长期预测的困难不仅在于视觉测量设备可能受到机械臂的阻碍,而且在于复杂空间环境中未知的噪声统计。提出了一种基于视觉系统的鲁棒时频混合算法。扩展有限脉冲响应(EFIR)滤波器估计与旋转有关的状态,离散傅立叶变换(DFT)滤波器估计与平移有关的动力学参数。然后,我们将估计的状态和参数应用到自由漂浮物的动力学方程中,从而实现对运动的长期预测。最后通过地面机器人实验验证了该方法的正确性和有效性。结果表明,该方法可以快速准确地预测空间非合作目标的运动。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Trajectory prediction of space robot for capturing non-cooperative target
The trajectory tracking and prediction of space non-cooperative target has been the key technique in on-orbit capturing tasks of space intelligent robot. The difficulty of long-term prediction not only because visual measuring equipment may be obstructed by robotic arm but the noise statistics unknown in complex space environment. This paper proposes a robust hybrid Time/Frequency domain algorithm based on vision system. An Extended Finite Impulse Response (EFIR) filter estimates the states related to rotation and the Discrete Fourier Transform (DFT) filter estimates the dynamics parameters related to translation. Subsequently, we apply the estimated states and parameters to dynamic equations of free-floating object and then achieve the long-term prediction of the motion. An experiment with ground robot is presented to verify the correctness and effectiveness of the proposed method. The results show that the motion of space non-cooperative target can be predicted rapidly and accurately.
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