针对ORB(Oriented FAST and Rotated BRIEF)算法中的Steer BRIEF描述子只通过比较两个像素点的灰度信息来决定0/1编码,容易产生特征点误匹配现象,本文提出基于像素密度(pixel density)的ORB特征描述子算法,利用两幅图像中相同区域的某...针对ORB(Oriented FAST and Rotated BRIEF)算法中的Steer BRIEF描述子只通过比较两个像素点的灰度信息来决定0/1编码,容易产生特征点误匹配现象,本文提出基于像素密度(pixel density)的ORB特征描述子算法,利用两幅图像中相同区域的某一特征点邻域空间内像素密度的相似性原理,通过比较两个像素点的密度信息来决定0/1编码,计算误匹配率,验证了density-ORB算法在图像模糊、压缩、光照变化、视角变化等条件下的鲁棒性.实验结果表明,该算法减少了特征点的误匹配个数,特征点误匹配率比ORB算法降低了2.80%.展开更多
Precise localisation and navigation are the two most important tasks for mobile robots.Visual simultaneous localisation and mapping(VSLAM)is useful in localisation systems of mobile robots.The wide-angle camera has a ...Precise localisation and navigation are the two most important tasks for mobile robots.Visual simultaneous localisation and mapping(VSLAM)is useful in localisation systems of mobile robots.The wide-angle camera has a broad field of vision and more abundant information on images,so it is widely used in mobile robots,including legged robots.However,wide-angle cameras are more complicated than ordinary cameras in the design of visual localisation systems,and higher requirements and challenges are put forward for VSLAM technologies based on wide-angle cameras.In order to resolve the problem of distortion in wide-angle images and improve the accuracy of localisation,a sampling VSLAM based on a wide-angle camera model for legged mobile robots is proposed.For the predictability of the periodic motion of a legged robot,in the method,the images are sampled periodically,image blocks with clear texture are selected and the image details are enhanced to extract the feature points on the image.Then,the feature points of the blocks are extracted and by using the feature points of the blocks in the images,the feature points on the images are extracted.Finally,the points on the incident light through the normalised plane are selected as the template points;the relationship between the template points and the images is established through the wide-angle camera model,and the pixel coordinates of the template points in the images and the descriptors are calculated.Moreover,many experiments are conducted on the TUM datasets with a quadruped robot.The experimental results show that the trajectory error and translation error measured by the proposed method are reduced compared with the VINS-MONO,ORB-SLAM3 and Periodic SLAM systems.展开更多
文摘针对ORB(Oriented FAST and Rotated BRIEF)算法中的Steer BRIEF描述子只通过比较两个像素点的灰度信息来决定0/1编码,容易产生特征点误匹配现象,本文提出基于像素密度(pixel density)的ORB特征描述子算法,利用两幅图像中相同区域的某一特征点邻域空间内像素密度的相似性原理,通过比较两个像素点的密度信息来决定0/1编码,计算误匹配率,验证了density-ORB算法在图像模糊、压缩、光照变化、视角变化等条件下的鲁棒性.实验结果表明,该算法减少了特征点的误匹配个数,特征点误匹配率比ORB算法降低了2.80%.
基金National Natural Science Foundation of China,Grant/Award Number:61702320。
文摘Precise localisation and navigation are the two most important tasks for mobile robots.Visual simultaneous localisation and mapping(VSLAM)is useful in localisation systems of mobile robots.The wide-angle camera has a broad field of vision and more abundant information on images,so it is widely used in mobile robots,including legged robots.However,wide-angle cameras are more complicated than ordinary cameras in the design of visual localisation systems,and higher requirements and challenges are put forward for VSLAM technologies based on wide-angle cameras.In order to resolve the problem of distortion in wide-angle images and improve the accuracy of localisation,a sampling VSLAM based on a wide-angle camera model for legged mobile robots is proposed.For the predictability of the periodic motion of a legged robot,in the method,the images are sampled periodically,image blocks with clear texture are selected and the image details are enhanced to extract the feature points on the image.Then,the feature points of the blocks are extracted and by using the feature points of the blocks in the images,the feature points on the images are extracted.Finally,the points on the incident light through the normalised plane are selected as the template points;the relationship between the template points and the images is established through the wide-angle camera model,and the pixel coordinates of the template points in the images and the descriptors are calculated.Moreover,many experiments are conducted on the TUM datasets with a quadruped robot.The experimental results show that the trajectory error and translation error measured by the proposed method are reduced compared with the VINS-MONO,ORB-SLAM3 and Periodic SLAM systems.
