Microdrone-based Indoor Mapping with Graph SLAM

The proposed methodology was validated for several indoor environments. We investigated the performance of our drone against a multi-layer LI-DAR-carrying macrodrone, a vision-aided navigation helmet, and ground truth obtained with a terrestrial laser scanner. The experimental results indicated that our SLAM system is capable of creating quality exploration maps of small indoor spaces, and handling of the loop-closure problem.

The accumulated drift without loop closure was on average 1.1% (0.35 m) over a 31 m long ac-quisition trajectory. Moreover, the comparison results demonstrated that our flying microdrone provided a comparable performance to the multi-layer LIDAR-based macrodrone given the low deviation between the point clouds built by both drones. About 85 % of the cloud-to-cloud distances were less than 10 cm.

Date Submitted: 2023-11-21