污水管道系统作为城市公共基础设施重要的一部分，需定期对其检测以维持正常功能，由于污水管道环境特殊，现有技术难以检测管内情况。提出了一种污水管道机器人定位系统，可定位管内机器人和管道缺陷的位置。针对污水管道普遍高水位或满水的现状，该系统以动力声呐机器人为载体，并提出一种UKF-RTS算法，融合惯性测量单元（inertial measurement unit, IMU）和计米器两种传感器数据，计算出机器人位姿。设计实验对该系统进行了验证，结果表明，此系统可以精确定位机器人在管内的位置，准确计算出管道内缺陷的位置，精度可达4.6%，相较于单传感器系统和其他融合算法可达到更高的精度，结合单层声呐点云数据，可生成管道三维点云模型，具有较高实用价值。

Sewer systems, as an important part of urban public infrastructure, require regular inspection of the pipelines to maintain normal function. Due to the special characteristics of the sewer environment, it is difficult to detect the situation inside the pipe with existing technologies. A robot localization system for sewer was proposed, which can locate the position of the robot and pipe defects. To address the challenges posed by sewers, which are often high or filled with water, a powered sonar robot was used and the UKF-RTS algorithm was introduced. This algorithm fuses data from two sensors of IMU(inertial measurement unit) and odometry to calculate the displacement and attitude of the robot. Experiments were designed to validate the system. The result shows that this system can accurately locate the position of the robot in the pipe, precisely calculate the position of defects in the pipe with an accuracy of up to 4.6%. It can achieve higher accuracy compared with single-sensor systems and other fusion algorithms, and combined with the 2D sonar point cloud data, it can generate a 3D point cloud model of the pipe, which has a high practical value.