Wang B R, Jin Y L, Shao D L, Xu Y
College of Mechanical and Electrical Engineering, China Jiliang University, Hangzhou, Zhejiang 310018, China ; Department of Control Science and Engineering, Zhejiang University, Hangzhou, Zhejiang 310007, China.
College of Mechanical and Electrical Engineering, China Jiliang University, Hangzhou, Zhejiang 310018, China.
ScientificWorldJournal. 2014 Jan 29;2014:130806. doi: 10.1155/2014/130806. eCollection 2014.
Image jitters occur in the video of the autonomous robot moving on bricks road, which will reduce robot operation precision based on vision. In order to compensate the image jitters, the affine transformation kinematics were established for obtaining the six image motion parameters. The feature point pair detecting method was designed based on Eigen-value of the feature windows gradient matrix, and the motion parameters equation was solved using the least square method and the matching point pairs got based on the optical flow. The condition number of coefficient matrix was proposed to quantificationally analyse the effect of matching errors on parameters solving errors. Kalman filter was adopted to smooth image motion parameters. Computing cases show that more point pairs are beneficial for getting more precise motion parameters. The integrated jitters compensation software was developed with feature points detecting in subwindow. And practical experiments were conducted on two mobile robots. Results show that the compensation costing time is less than frame sample time and Kalman filter is valid for robot vision jitters compensation.
