Registration of non-uniform density 3D laser scans for mapping with micro aerial vehicles
We present a mapping system for non-uniform density 3D point clouds acquired by MAVs. To compensate for the different densities, we approximate the underlying surface. The extracted surface information is used to efficiently align the point clouds. We use the same surface-based error metric in a multi-edge pose graph optimization. We demonstrate 3D mapping with MAVs and superior performance to a single-edge system.
registration mapping micro aerial vehicles approximate surface reconstruction generalized-icp