An Easy-to-Use System for Tracking Robotic Platforms Using Time-of-Flight Sensors in Lab Environments

The acquisition of accurate tracking data is a common problem in scientific research. When developing new algorithms and AI networks for the localization and navigation of mobile robots and MAVs, they need to be evaluated against true observations. Off-the-shelf systems for capturing ground truth data often come at a high cost, since they typically include multiple expensive sensors and require a special setup. We see the need for a simpler solution and propose an easy-to-use system for small scale tracking data acquisition in research environments using a single or multiple sensors with possibly already available hardware. The system is able to track mobile robots moving on the ground, as well as MAVs that are flying through the room. Our solution works with point clouds and allows the use of Time-of-Flight based sensors like LiDAR. The results show that the accuracy of our system is sufficient to use as ground truth data with a low-centimeter mean error.