中文摘要：

提出了一种鲁棒的基于无迹卡尔曼滤波器的摄像机（视觉传感器）-惯性测量单元相对位姿标定方法.为了减小重力加速度对标定精度的影响,该方法采用迭代卡尔曼滤波器对惯性传感器坐标系下的重力加速度进行实时估计.仿真实验和真实数据实验表明,在系统初始误差较大或系统受到严重非线性因素干扰时,该方法仍能够对视觉传感器和惯性测量单元之间的6自由度相对位姿进行精确标定.

英文摘要：

A robust method for determining the relative pose between the camera（vision sensor） and the inertial measurement unit based on the unscented Kalman filter（UKF） is presented.To reduce the impact of gravity acceleration on the calibration result,the method uses iterated Kalman filter to obtain the real-time estimate of gravity acceleration in the inertial sensor coordinate frames.Simulation and experimental results show that,when there are large initial systematic errors or the system is disturbed by serious non-linear noises,the proposed method is still valid and precise for calibrating the 6-DOF relative pose between the visual sensor and the inertial measurement unit.