Locating and Tracking Algorithm of Biomimetic Eye Based on Backpropagation Neural Network
LI Zhen1, FAN Binghui1, WANG Xin1, YU Lianbo1, WANG Chuanjiang1,2, SUN Shixing1
1. College of Electrical Engineering and Automation, Shandong University of Science and Technology, Qingdao 266590, China;
2. School of Control Science and Engineering, Shandong University, Jinan 250061, China
李镇, 樊炳辉, 王鑫, 于连波, 王传江, 孙石兴. 基于BP神经网络的仿生眼定位追踪算法[J]. 机器人, 2017, 39(1): 63-69.DOI: 10.13973/j.cnki.robot.2017.0063.
LI Zhen, FAN Binghui, WANG Xin, YU Lianbo, WANG Chuanjiang, SUN Shixing. Locating and Tracking Algorithm of Biomimetic Eye Based on Backpropagation Neural Network. ROBOT, 2017, 39(1): 63-69. DOI: 10.13973/j.cnki.robot.2017.0063.
Abstract：In order to realize rapid locating and tracking of a mobile target in the field of view by a biomimetic eye platform, a algorithm to maintain the target on the center of the video frames of two industrial cameras in real-time through joint rotation of each rotational degree of freedom on the biomimetic eye platform is proposed. A binocular biomimetic eye platform with 5 rotational degrees of freedom is designed based on the structural characteristics of human eyes and head. Backpropagation (BP) neural network is adopted to correct the error of binocular 3D measurement based on the dynamically changing external parameters, and the joint space algorithm is utilized to solve the rotation angle of each rotational degree of freedom. The experimental results show that the mean absolute error of the measured value after BP network correction is 2.1849 mm and the average relative error is 0.0051. The method proposed can improve the accuracy of 3D measurement and calculate the joint rotation angle in real time.
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