机器人2015，Vol.37Issue(5)：557-565,9.DOI:10.13973/j.cnki.robot.2015.0557
基于快速视觉里程计和大回环局部优化模型的改进VSLAM算法
Improved VSLAM Algorithm Based on Fast Visual Odometry and Large Loop Local Optimization Model
李永锋 1张国良 1王蜂 1汤文俊 1姚二亮1
作者信息
- 1. 第二炮兵工程大学,陕西 西安 710025
- 折叠
摘要
Abstract
An improved visual simultaneous localization and mapping (VSLAM) algorithm based on fast visual odometry and large loop local optimization model is proposed in terms of the accuracy and real-time performance of autonomous localization in mobile robot VSLAM. First of all, the error function of color GICP (color supported generalized iterative closest point) is improved based on the uncertainty analysis on the feature points. Frame-to-model approach is utilized to achieve fast registration between data sets and model sets. And the model sets are updated through Kalman filtering and the weighting method. The accuracy of pose estimation is improved through the above steps. Secondly, a large local loop optimization model based on model-to-model registration is proposed and g2o is combined to optimize the accumulated error of the pose estimation quickly, which improves the accuracy and efficiency of autonomous localization further. The offline contrast experiments based on the datasets and the online experiments based on actual scenes show that, with the proposed algorithm, not only the accuracy of autonomous localization and map in mobile robot VSLAM are improved effectively, but also the real-time performance is guaranteed.关键词
同步定位与地图创建/视觉里程计/colorGICP(colorsupportedgeneralizediterativeclosestpoint)/卡Key words
simultaneous localization and mapping/visual odometry/color GICP (color supported generalized iterative分类
信息技术与安全科学引用本文复制引用
李永锋,张国良,王蜂,汤文俊,姚二亮..基于快速视觉里程计和大回环局部优化模型的改进VSLAM算法[J].机器人,2015,37(5):557-565,9.
