An Alternative Raw Data Acquisition Approach for Reconstruction of LOD3 Models

Visual, autonomous, object-based outdoor vehicle localization premise detailed object-based maps. Semantic-rich and qualitative Level of detail 3 (LOD3) building models fulfill these requirements, but only a few real-world city models are available. These models are mainly reconstructed by LiDAR, have a cost benefit, scalability and reconstruction-complexity problem. Challenging the issues, we propose an alternative data acquisition approach for LOD3 model reconstruction primarily based on images. Thus, we created a moveable handcart mounted height-adjustable, high-precision gimbal. The gimbal enables 360 \(^{\circ }\) poses of camera, LiDAR rangefinder, inertial measuring unit. Additionally, GNSS RTK is used for absolute positioning. Our system is capable to record data and ground truth data for system validation in one step. The paper is about the system design, data processing and validation of the proposed reconstruction approach. Resulting real-world reconstruction accuracies are in the millimeter to low centimeter range. So, our system is compared in discussion with competing systems.