一种基于SIFT特征的机器人环境感知双目立体视觉系统

A stereo vision system based on SIFT feature for robot environment perception

针对双目立体视觉系统在机器人环境感知领域中存在的立体匹配以及测量精度问题,设计一种基于SIFT特征的双目立体视觉测量系统。利用SIFT特征良好的旋转、尺度、光照不变性等特性,有效地解决双目立体视觉系统的匹配问题,同时将SIFT算法在由FPGA和DSP组成的嵌入式系统上实现,显著地提高测量系统的实时性。提出一种基于二次多项式的误差补偿方法,对系统的测量结果进行补偿,弥补双目立体视觉系统测量误差随测量距离增加而增加的不足,从而提高系统测量精度。通过实际的测量实验、移动机器人环境感知实验以及与现有双目立体视觉产品的对比实验结果表明,系统能够很好地解决双目立体视觉的立体匹配和精度问题,并且能较好地应用于移动机器人环境感知任务中。

To solve the stereo matching and measurement accuracy problems which exist in stereo vision systems in the field of robot environment perception, this paper designs a stereo vision system based on scale-invariant feature transform(SIFT) features. The matching problem is solved by using the rotation, scale, illumination invariance of the SIFT features, and the SIFT algorithm is implemented in the embedded system based on FPGA and DSP, thus the real-time problem of the system is effectively solved. Then in order to offset the problem that the measurement error increases with the distance, an error compensate method based on quadratic polynamial is proposed, which can compensate the measurement results of the stereovision system and improvus the measurement accracy of the system. The mesurement experiment, robot environment perception experiment and contrast experiment between existing stereovision products are uarried out, and the uasults show that, the stereovision system can commendably solve the matching and accuracy problems, and also can be better applied to the environment perception task of mobile robots.