High accuracy 3D surface information is required for many construction robotics tasks such as automated cement polishing or robotic plaster spraying. However, consumer-grade depth cameras currently found in the market are not accurate enough for these tasks where millimeter (mm)-level accuracy is required. This paper presents SL Sensor, a structured light sensing solution capable of producing high fidelity point clouds at 5 Hz by leveraging on phase shifting profilometry (PSP) codification techniques. The SL Sensor was compared with to two commercial depth cameras - the Azure Kinect and RealSense L515. Experiments showed that the SL Sensor surpasses the two devices in both precision and accuracy for indoor surface reconstruction applications. Furthermore, to demonstrate SL Sensor's ability to be a structured light sensing research platform for robotic applications, a motion compensation strategy was developed that allows the SL Sensor to operate during linear motion when traditional PSP methods only work when the sensor is static. Field experiments show that the SL Sensor is able to produce highly detailed reconstructions of spray plastered surfaces. The robot operating system (ROS)-based software and a sample hardware build of the SL Sensor are made open-source with the objective to make structured light sensing more accessible to the construction robotics community.

许多建筑机器人任务（例如自动水泥抛光或机器人石膏喷涂）都需要高精度的 3D 表面信息。然而，目前市场上的消费级深度相机对于这些需要毫米 (mm) 级精度的任务来说不够准确。本文介绍了 SL Sensor，这是一种结构光传感解决方案，能够利用相移轮廓测量 (PSP) 编码技术产生 5 Hz 的高保真点云。将 SL 传感器与两个商业深度相机 - Azure Kinect 和 RealSense L515 进行了比较。实验表明，SL 传感器在室内表面重建应用中的精度和准确度均超过了这两种设备。此外，为了演示 SL Sensor' 由于能够成为机器人应用的结构光传感研究平台，因此开发了一种运动补偿策略，当传统的 PSP 方法仅在传感器静止时才工作时，该策略允许 SL 传感器在线性运动期间工作。现场实验表明，SL 传感器能够对喷涂表面进行高度详细的重建。基于机器人操作系统 (ROS) 的软件和 SL 传感器的示例硬件构建是开源的，目的是使建筑机器人社区更容易使用结构光传感。现场实验表明，SL 传感器能够对喷涂表面进行高度详细的重建。基于机器人操作系统 (ROS) 的软件和 SL 传感器的示例硬件构建是开源的，目的是使建筑机器人社区更容易使用结构光传感。现场实验表明，SL 传感器能够对喷涂表面进行高度详细的重建。基于机器人操作系统 (ROS) 的软件和 SL 传感器的示例硬件构建是开源的，目的是使建筑机器人社区更容易使用结构光传感。