POINT CLOUD VISUALIZATION OF ACCEPTABLE HELICOPTER LANDING ZONES BASED ON 4D LIDAR

• US 20130282208A1
• Filed: 04/24/2012
• Published: 10/24/2013
• Est. Priority Date: 04/24/2012
• Status: Active Grant

• Current Assignee: Harris Corporation (L3Harris Technologies, Inc.)
• Original Assignee: Exelis Incorporated (L3Harris Technologies, Inc.)
• Inventors: MENDEZ-RODRIGUEZ, JAVIER, Rodgers, Christopher T.
• Granted Patent: US 8,600,589 B2
• Time in Patent Office: Days
• US Class Current: 701/16
• CPC Class Codes: G01S 17/88 Lidar systems specially adapted for specific applications
• CPC Class Codes: G01S 17/89 for mapping or imaging
• CPC Class Codes: G01S 17/933 of aircraft or spacecraft
• CPC Class Codes: G01S 7/4802 using analysis of echo signal for target characterisation; Target signature; Target cross-section
• CPC Class Codes: G05D 1/0676 specially adapted for landing
• CPC Class Codes: G08G 5/025 Navigation or guidance aids radar or analogous systems specially adapted for landing purposes G01S13/913

Abstract

A processor calculates a safe landing zone for an aircraft. The processor executes the following steps: (a) converting 4D point cloud data into Cartesian coordinates to form a height map of a region; (b) segmenting the height map to form boundaries of an object in the region; and (c) determining maximum height within the boundaries of the object. Also included are (d) determining if the maximum height is greater than a predetermined height to form a vertical obstruction (VO) in the region; and (e) determining if the VO is in the line of sight (LOS) of the aircraft to classify the landing zone as safe or unsafe. The processor further includes the step of: (f) forming a slope map over the height map.

Claims

1. A method of selecting a safe landing zone for an aircraft comprising the steps of:

receiving, from a LADAR or LIDAR system, 4 dimensional (4D) point cloud data as sequential image frames;

referencing, by a processor, each image frame to geographic coordinates;

selecting, by a processor, a land region in each image frame;

first filtering the land region, by a processor, to select a landing zone for the aircraft; and

second filtering the landing zone, by a processor, to select a safe landing zone for the aircraft.

2. The method of claim 1 wherein receiving the 4D point cloud data includes receiving the 4D point cloud data from a LADAR or LIDAR system.

3. The method of claim 1 wherein referencing each image frame includes

using a global positioning system (GPS) or an inertial system to transform the 4D point cloud data into x, y, z geographic coordinates as a function of time, t.

4. The method of claim 1 wherein selecting the land region includes

determining whether a portion of an image frame includes a land region or a water region, and

preventing further processing of the portion, after determining that the portion is a water region.

5. The method of claim 4 including the step of:

transferring, by a processor, the portion of the image frame to the step of first filtering, after determining that the portion is a land region.

6. The method of claim 1 wherein first filtering includes the steps of:

forming, by a processor, a height map of the land region, the height map including pixel values of height over the land region,

detecting, by a processor, edges of an object in the height map, the edges forming boundaries of the object,

finding, by a processor, a maximum height within the boundaries of the object, and

classifying the object as a vertical obstruction (VO), by a processor, if the maximum height is larger than a predetermined VO threshold value.

7. The method of claim 6 wherein detecting the edges includes the steps of:

applying a fast Fourier transform (FFT) over the height map to obtain height in a frequency domain,

calculating gradients of the height in the frequency domain, wherein the gradients define the edges, and

representing the edges as “

ones” and

other portions of the height map as “

zeroes”

.

8. The method of claim 7 further including the steps of:

forming, by a processor, a slope map over the height map, in which a slope of a pixel of interest is based on 4-neighbors of pixels surrounding the pixel of interest, and

determining, by a processor, roughness over the height map, in which roughness includes a standard deviation of height values greater than 0.3.

9. The method of claim 1 wherein

first filtering includes the steps of:

forming a VO map representing vertical obstructions in the land region,

forming a slope map representing slopes of data points in the land region; and

second filtering includes the step of;

moving a mask, defined by a predetermined area for landing, over the land region to select the safe landing zone for the aircraft,

wherein the safe landing zone includes (a) VOs that are less than a predetermined height within the moving mask and (b) slopes that are less than a standard deviation of height less than 0.3 within the moving mask.

10. The method of claim 9 further including the steps of:

calculating, by a processor, a funnel extending from a center of a landing zone, wherein the funnel is defined by a line of sight (LOS) projected from the aircraft to the center of the landing zone, and having a height formed by an altitude of the aircraft above the landing zone, and

classifying, by a processor, the landing zone as a safe landing zone, when a VO is outside the funnel.

11. The method of claim 1 wherein

first filtering and second filtering are performed by parallel processors.

12. The method of claim 11 wherein

the first and second filtering are executed during a time period sufficient to provide landing visualization in real-time.

13. The method of claim 1 wherein the aircraft is a helicopter.

14. A system for determining a landing zone for an aircraft comprising:

a processor for receiving 4 dimensional (4D) point cloud data from a sensor including a LADAR or LIDAR sensor, the data defined by sequential image frames,

the processor converting each image frame into Cartesian coordinates (x, y, z) to form a height map, in which x and y are a function of a scanning angle of the sensor and z is height,

the processor configured to segment the height map into boundaries of a respective object in the image frame,

the processor configured to find a maximum height within the boundaries of the respective object to form a vertical obstruction (VO) map, and

the processor configured to mathematically move a mask over the VO map, wherein the mask is based on a predetermined landing area required for the aircraft; and

a visualization system for displaying the mask over the VO map for landing the aircraft.

15. The system of claim 14 wherein

the processor is configured to perform the following tasks:

calculating a funnel extending from a center of a landing zone, wherein the funnel is defined by a line of sight (LOS) projected from the aircraft to the center of the landing zone, and having a height formed by an altitude of the aircraft above the landing zone, and

classifying the landing zone as a safe landing zone, when a VO is outside the funnel.

16. The system of claim 14 wherein

the aircraft is a helicopter.

17. A processor for calculating a safe landing zone for an aircraft, the processor executing the following steps:

(a) converting 4D point cloud data into Cartesian coordinates to form a height map of a region, wherein the 4D point cloud data is received from a LADAR or LIDAR sensor;

(b) segmenting the height map to form boundaries of an object in the region;

(c) determining maximum height within the boundaries of the object,

(d) determining if the maximum height is greater than a predetermined height to form a vertical obstruction (VO) in the region; and

(e) determining if the VO is in the line of sight (LOS) of the aircraft to classify the landing zone as safe or unsafe.

18. The processor of claim 17 executing the following additional steps:

(f) determining whether the 4D point cloud data is that of land or water; and

(g) preventing execution of steps (a) through (e), if the 4D point cloud data is that of water.

19. The processor of claim 17 comprising:

a first processor for executing step (a) and

a second processor for executing at least step (b),

wherein the first and second processors are configured to execute the steps in parallel.

20. The processor of claim 17 including the step of:

providing a map of the landing zone to a visualization system during a time period sufficient for real-time landing of the aircraft.