METHOD FOR CONTROLLING A SURFACE-MODIFYING MACHINE

• US 20070214687A1
• Filed: 05/24/2005
• Published: 09/20/2007
• Est. Priority Date: 05/24/2004
• Status: Active Grant

• Current Assignee: Leica Geosystems AG (Hexagon AB)
• Original Assignee: Leica Geosystems AG (Hexagon AB)
• Inventors: Woon, Clement, Schneider, Klaus, Nix, Martin, Stegmaier, Peter
• Granted Patent: US 7,899,598 B2
• Time in Patent Office: Days
• US Class Current: 37/415
• CPC Class Codes: E02F 3/842 using electromagnetic, optical or photoelectric beams, e.g. laser beams
• CPC Class Codes: E02F 9/2045 Guiding machines along a predetermined path for graders E02F3/841; machines for construction of roads E01C19/004
• CPC Class Codes: G06T 17/05 Geographic models
• CPC Class Codes: G06T 17/30 Polynomial surface description

Abstract

The invention relates to a method for controlling a surface-modifying machine, wherein information on the desired condition and on the actual condition of ground to be prepared is provided and is used to derive control statements for the machine based on a comparison of the desired and the actual condition. The information on the actual condition is represented by a point cloud as a spatial distribution of discrete surface points. In order to derive control statements, at least two surface points each from the point cloud are used for every horizontal position so that non-differentiated information can be derived that for example also allow to identify various planes.

Claims

1-11. -11. (canceled)

12. A method for controlling a surface-modifying machine, the method comprising the acts of:

providing information about the desired condition of a surface to be prepared;

providing a point cloud recorded by a distance-measuring scanner system as a spatial distribution of discrete surface points and as information about the actual condition of the surface;

deriving a control instruction for the machine by comparison of desired condition and point cloud; and

controlling the machine according to the derived control instruction,

wherein, for a spatial position, the comparison of desired condition and point cloud uses at least two surface points of the point cloud, in particular links said surface points with one another, when deriving the control instruction.

13. The method as claimed in claim 12, wherein the comparison of desired condition and point cloud for each spatial position of the desired condition uses surface points of at least two spatial positions of the actual condition when deriving the control instruction.

14. The method as claimed in claim 12, wherein at least one surface, in particular one plane, which represents or approximates a possible actual surface of the actual condition is coordinated with the at least two surface points.

15. The method as claimed in claim 14, wherein the assigned surface is derived by at least one of the following methods:

least squares method, fuzzy logic method, image processing method, pattern recognition, and heuristic method.

16. The method as claimed in claim 12, wherein, for each spatial position of the actual condition, the spatial difference, in particular height difference, of at least two assigned surface points is used when deriving the control instruction.

17. The method as claimed in claim 12, wherein the provision of the point cloud includes an update of the point cloud while carrying out the method, in particular by scanning of a prepared surface section.

18. The method as claimed in claim 17, wherein the scanning of a prepared surface section is through a LIDAR scan.

19. The method as claimed in claim 17, wherein, on provision of the point cloud, fitting of the prepared surface section into the point cloud is effected by at least one of:

image processing methods, pattern recognition methods, and absolute referencing of the scan fixed point.

20. The method as claimed in claim 12, wherein the point cloud is composed of distinguishable subsets of surface points, in particular a characterizing quantity being coordinated with the respective subsets.

21. The method as claimed in claim 20, wherein the characterizing quantity is at least one of a time mark and a spectral range.

22. The method as claimed in claim 12, wherein the number of surface points which is coordinated with the spatial position is variable, in particular as a function of at least one of time and location.

23. The method as claimed in claim 12, wherein the surface points coordinated with a spatial position are aggregated, in particular by the use of a weighting function.

24. A computer program product as a record on a data medium, the product comprising:

information provided about the desired condition of a surface to be prepared;

a point cloud recorded by a distance-measuring scanner system as a spatial distribution of discrete surface points and as information about the actual condition of the surface;

a control instruction for the machine derived by comparison of desired condition and point cloud; and

a machine controlled according to the derived control instruction,

wherein, for a spatial position, the comparison of desired condition and point cloud uses at least two surface points of the point cloud, in particular links said surface points with one another, when the control instruction is derived.

25. The product as claimed in claim 24, wherein the comparison of desired condition and point cloud for each spatial position of the desired condition uses surface points of at least two spatial positions of the actual condition when deriving the control instruction.

26. The product as claimed in claim 24, wherein at least one surface, in particular one plane, which represents or approximates a possible actual surface of the actual condition is coordinated with the at least two surface points.

27. The product as claimed in claim 26, wherein the assigned surface is derived by at least one of the following methods:

least squares method, fuzzy logic method, image processing method, pattern recognition, and heuristic method.

28. The product as claimed in claim 24, wherein, for each spatial position of the actual condition, the spatial difference, in particular height difference, of at least two assigned surface points is used when deriving the control instruction.

29. The product as claimed in claim 24, wherein the provision of the point cloud includes an update of the point cloud while carrying out the method, in particular by scanning of a prepared surface section.

30. The product as claimed in claim 29, wherein the scanning of a prepared surface section is through a LIDAR scan.

31. The product as claimed in claim 29, wherein, on provision of the point cloud, fitting of the prepared surface section into the point cloud is effected by at least one of:

image processing methods, pattern recognition methods, and absolute referencing of the scan fixed point.

32. The product as claimed in claim 24, wherein the point cloud is composed of distinguishable subsets of surface points, in particular a characterizing quantity being coordinated with the respective subsets.

33. The product as claimed in claim 32, wherein the characterizing quantity is at least one of a time mark and a spectral range.

34. The product as claimed in claim 24, wherein the number of surface points which is coordinated with the spatial position is variable, in particular as a function of at least one of time and location.

35. The product as claimed in claim 24, wherein the surface points coordinated with a spatial position are aggregated, in particular by the use of a weighting function.