基于紧耦合的视觉惯性定位方法

惯性测量单元(IMU)受自身温度、零偏、振动等因素干扰,积分时位姿容易发散,并且机器人快速移动时,单目视觉定位精度较差,为此研究了一种基于紧耦合的视觉惯性即时定位与地图构建(SLAM)方法.首先研究了视觉里程计(VO)定位问题,为减少特征点的误匹配,采用基于快速特征点提取和描述的算法(ORB)特征点的提取方法.然后构建...

Visual inertial positioning method based on tight coupling

The inertial measurement unit(IMU)is disturbed by its own temperature,bias,vibration and other factors,so the pose is easy to diverge when integrating,and the monocular vision positioning accuracy is poor when the robot moves rapidly.Therefore,this paper studies a visual inertial synchronous simultaneous localization and mapping(SLAM)method based on tight coupling.Firstly,the location problem of visualodometry(VO)is studied.In order to reduce the mismatching of feature points,the feature points extraction method based on Oriented FAST and Rotated BRIEF(ORB)is adopted.Then the mathematical model of IMU is constructed,and the discrete integral of the motion model is obtained by using the median method.Finally,the pose of monocular vision is aligned with IMU trajectory,and the optimal state estimation of robot motion is obtained by nonlinear optimization based on sliding window.The two experiments were verified by constructing the simulation scene ard comparing with the monocular ORB-SLAM algorithm.The results show that the proposed method is better than visual odometer alone,and the positioning accuracy is controlled at about 0.4 m,which is 30%higher than the traditional tracking model.