基于AprilTag图像识别的移动机器人定位研究

针对移动机器人在识别AprilTag图像过程中,受到室内光线不均和运动过快所导致的识别成功率低问题,提出一种基于AprilTag图像的预处理方法来提高识别成功率。首先采用移位去尾的方法进行图像灰度化处理,在此基础上融入双线性插值降采样的方法以提升整体图像处理速度,再对降采样后得到的灰度图进行直方图均衡化处理,消除因光线不均产生的影响,然后对图像双边平滑和Canny边缘检测,增强图像对比度和消除图像噪声的影响,以达到提升AprilTag图像识别的成功率和后续工作的定位准确度。通过实验进行对比分析,所提方法对AprilTag图像识别的成功率比传统方法在不同光线条件下均提高了3%以上,且移动机器人的实时定位误差控制在1~2 cm,从而验证了所提方法的有效性和可行性。

Research on positioning of mobile robot based on low complexity AprilTag image recognition

Aiming at the problem that the poor recognition ability of mobile robot to AprilTag image is caused by uneven illumination intensity and overly fast movement, an improved method of AprilTag image preprocessing was proposed to improve the success rate of image recognition. Firstly, a method of tail shifting is used to change the colored image into gray image. On the basis of the above, a bilinear interpolation method is adopted to carry out down-sampling on the gray image to improve the overall processing speed. The gray image is processed by histogram equalization to eliminate the influence of uneven illumination and enhance the contrast of gray image. Then, bilateral filtering was carried out for the gray image to remove the image noise, and Canny operator was used to detect the edge of gray image to improve the success rate of AprilTag image recognition and the subsequent positioning accuracy. The experiment verifies the effectiveness of the improved algorithm. The success rate of the proposed method for AprilTag image recognition is increased by more than 3% compared with the traditional method under different light conditions, and the real-time positioning error of the mobile robot is controlled within 1~2 cm, the validity and feasibility of this method are verified.