基于双目视觉机器人自定位与动态目标定位  

Self Localization and Dynamic Target Localization of Robot Based on Binocular Vision

作　　者：卢洪军[1] 

机构地区：[1]沈阳工业大学信息科学与工程学院,辽宁沈阳110870

出　　处：《沈阳大学学报（自然科学版）》2017年第1期37-42,共6页Journal of Shenyang University：Natural Science

基　　金：国家自然科学基金资助项目(60695054);辽宁省高等学校优秀科技人才支持计划(LR2015045)

摘　　要：针对基于双目视觉自定位与动态目标定位极易受复杂环境(如噪声、机器人发生遮挡、光照变化等)的干扰导致移动机器人定位精度低的问题,提出基于HSV颜色模型特征准确分割出人工路标,根据视差原理确定机器人位置.同时提出一种双目机器人基于Harris算子实现在复杂环境下对动态目标精确定位的方法,利用帧间差分法将运动目标检测出来,采用Harris算子在该运动目标上提取特征点,并获得视差值,从而精确的计算出运动目标的位置.实验结果表明,利用该方法进行自定位与目标定位能够克服外界干扰,具有较强的适应性,且算法的实时性好.Aiming at the fact that,the mobile robot based on binocular vision is very easy to be disturbed by the complex environment,such as the influence of noise,illumination change and the occlusion of the robot,which will seriously affect the positioning accuracy of the self localization and the moving objects,the color feature of the HSV model is proposed to accurately segment the artificial landmarks,and the robot position is determined according to the principle of parallax.A method was proposed based on Harris operator which is accurate to the position of a moving object in a complex environment.The dynamic object is detected by the frame difference method.Harris operator was used to extract the feature points on the moving objects,so as to obtain the disparity value,and then to calculate the position of the moving objects.The experimental results show that the self localization and target localization can overcome the external disturbance and have strong adaptability by using this method.The algorithm has good real-time performance.

关 键 词：双目视觉 目标定位 HARRIS算子 帧间差分法 HSV模型 

分 类 号：TP391.4[自动化与计算机技术—计算机应用技术]