为了解决机器人同时定位，地图构建与目标跟踪(SLAMOT)过程中的多源，异构传感器空间一致性观测问题，提出了基于信息融合的摄像机与激光测距传感器联合标定优化方法。完成基于误差传播公式的激光扫描点图像平面投影不确定范围判定，并利用协方差交集算法实现基于运动物体检验方法和基于Camshift方法的图像坐标系下目标状态融合。在此基础上，利用目标图像平面投影方向误差构造目标函数，通过非线性优化方法实现摄像机与激光测距仪标定参数优化。实验验证了设计方法能有效提高目标跟踪以及多传感器参数标定的准确性。相关成果能够为基于多传感器信息融合的机器人同时定位，地图构建与目标跟踪滤波方法研究提供观测值支持。

In order to solve the problem of spatial observation consistency from heterogeneous multi-sensor in the process of simultaneous localization, mapping and object tracking (SLAMOT), a calibration optimization method of camera and laser range measuring sensor based on information fusion is proposed. Uncertain arera of laser scanning point image plane projection is determined based on error propagation formula, and a covariance intersection based method which fuses informations come from moving object detection and Camshift method to object state estimation is designed. On this basis, the objective function is constructed with bearing error of object image projection, and calibration parameters of camera and laser range finder are optimized using nonlinear optimization method. Experiments show that the designed method improves accuracy of both object tracking and multi-sensors calibration. The method offers measurements which support further research of SLAMOT filter based on multi-sensor information fusion.