Abstract: A method comprises capturing, with a vehicle vision sensor, a color image of a landing site including landing surface markers; converting the color image to a gray scale image; and performing multi-scale-binarization to detect multiple edges of the gray scale image and produce binary images. The method determines contours of edges of the binary images having closed shapes, detects closed shapes of contours of edges having four corners, and verifies whether four-sided candidate contours are valid as potential landing surface markers. If more than one contour is associated with a valid ID within a surface marker library, then the contour within the smallest window size is selected. If multiple contours with the same window size can be associated with a valid ID, then a mean of corresponding corners of multiple contours is computed. The method then performs corner refinement of valid four-sided candidate contours identified as potential landing surface markers.

Abstract: A method comprises providing a vehicle landing pad with a reference frame origin at a center thereof, and X and Y axes through the reference frame origin; arranging a first group of markers, each having a first size, on the pad such that the first group of markers form a first convex hull about the center of the pad; and arranging a second group of markers, each having a second size less than the first size, on the pad such that the second group of markers form a second convex hull within the first convex hull. The first and second groups of markers are located symmetrically with respect to the center of the pad along the X and Y axes so as to yield a position estimation solution for landing a vehicle having a highest accuracy when compared with placing markers at other locations along the X and Y axes.

Abstract: Systems and methods for low-cost HAGL measurement and terrain database updates are provided. In one example, a system includes an image capturing device configured to capture first and second images and a navigation system configured to generate pose data. The system further includes processor(s) communicatively coupled to the image capturing device and the navigation system and a non-transitory, computer-readable medium communicatively coupled to the processor(s) that stores instruction(s) which, when executed by the processor(s), cause the processor(s) to: estimate optical flow between the first and second images; determine rigid flow per image for each depth bin of a group of depth bins based on the pose data, wherein each depth bin corresponds to a particular depth range; and generate a dense depth map by determining a depth bin, for each pixel, that minimizes a difference between the estimated optical flow and the determined rigid flow for the respective pixel.

Abstract: A method comprises capturing, with a vehicle vision sensor, a color image of a landing site including landing surface markers; converting the color image to a gray scale image; and performing multi-scale-binarization to detect multiple edges of the gray scale image and produce binary images. The method determines contours of edges of the binary images having closed shapes, detects closed shapes of contours of edges having four corners, and verifies whether four-sided candidate contours are valid as potential landing surface markers. If more than one contour is associated with a valid ID within a surface marker library, then the contour within the smallest window size is selected. If multiple contours with the same window size can be associated with a valid ID, then a mean of corresponding corners of multiple contours is computed. The method then performs corner refinement of valid four-sided candidate contours identified as potential landing surface markers.