This approach addresses two difficulties simultaneously: 1)

the range limitation of mobile robot sensors and 2) the difficulty of detecting buildings in

monocular aerial images. With the suggested method building outlines can be detected

faster than the mobile robot can explore the area by itself, giving the robot an ability to

“see” around corners. At the same time, the approach can compensate for the absence

of elevation data in segmentation of aerial images. Our experiments demonstrate that

ground-level semantic information (wall estimates) allows to focus the segmentation of

the aerial image to find buildings and produce a ground-level semantic map that covers

a larger area than can be built using the onboard sensors.-This approach addresses two difficulties simultaneously: 1) the range limitation of mobile robot sensors and 2) the difficulty of detecting buildings inmonocular aerial images. With the suggested method building outlines can be detectedfaster than the mobile robot can explore the area by itself, giving the robot an ability to