  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. All documentation and code is available
at https://github.com/ethz-asl/sl_sensor/ .
