针对人与机器人共存的服务空间中人的定位跟踪问题，提出了一种基于分布式激光雷达协作感知的全局定位跟踪方法。分别对各台激光雷达获取的数据进行统计检验，将其分为静态数据和动态数据，利用静态数据完成各台激光雷达的位置标定，实现背景消除。动态数据通过无线网络传送到服务器，将来自同一时刻不同激光雷达的动态数据组成观测数据的一帧，实现数据的同步与融合。对获取的每帧数据进行基于迭代最近点算法的轮廓模型匹配，区分各个目标。采用基于位置-速度的关联门对相邻两帧的检测目标进行关联，实现对各动态目标的跟踪。实验验证了该方法在解决人的定位与跟踪问题的有效性，与基于视觉的定位跟踪方法相比，本系统在定位精度和跟踪成功率上优势明显。

To solve the problem of human localization and tracking in the service space of human-robot coexistence, a novel method based on collaborative perception using distributed laser radars for human tracking is proposed. First, laser data obtained from each of radars is evaluated statistically, separately. All data are divided into static data and dynamic data. Static data are employed to calibrate the laser radars for background subtraction. Dynamic data are then sent to server computer by wireless network. Data from different radars at the same moment are formed into one frame to realize data synchronization and integration. Finally, contour model matching based interative closest point algorithm is implemented on each frame of laser data to distinguish the targets. To realize human tracking, targets between two frames are associated using association gate based on their positions and speeds. Experimental results demonstrate the effectiveness of the proposed method in solving the problem of human localization and tracking. Compared to vision-based tracking methods, the system performs better in terms of localization accuracy and tracking success rate.