摘要
针对球形机器人定位问题,提出了基于立体视觉的球形机器人定位方法.通过双目相机采集环境图像序列,提取Shi-Tomasi特征点,计算尺度不变特征变换(SIFT)特征描述符,并利用欧氏距离进行立体匹配;通过KLT算法进行特征点跟踪;采用解析法求解机器人在前后帧图像之间的位姿变化量;同时采用特征点筛选、RANSAC算法和卡尔曼滤波等方法,提高运动估计的准确性和鲁棒性.实验结果验证了所提出方法的可行性.
An approach based on stereovision is proposed for ball-shaped robot localization. Shi-Tomasi detector, scale invariant feature transform（SIFT） descriptor and KLT tracker are used to extract and track the features from image sequence taken by a stereo camera. Euclidean distance between SIFT descriptors Of features in both images is computed for stereo matching. An efficient closed-form method is adopted to estimate the frame-to-frame incremental motion in real time. Moreover, additional techniques, including bucketing of features, RANSAC based outlier rejection and Kalman filtering, are applied to improve accuracy and robustness of the estimated motion. The experimental results demonstrate the feasibility of the proposed stereovision-based localization.
出处
《控制与决策》
EI
CSCD
北大核心
2013年第4期632-636,640,共6页
Control and Decision
基金
国家自然科学基金项目(50775013)
中央高校基本科研业务费专项资金项目(2009RC0601)
高等学校科技创新工程重大项目培育项目(708011)
关键词
立体视觉定位
特征提取
运动估计
球形机器人
stereovision-based localization
feature extraction
motion estimation
ball-shaped robot
