Uncalibrated dynamic mechanical system controller

• US 6,278,906 B1
• Filed: 01/27/2000
• Issued: 08/21/2001
• Est. Priority Date: 01/29/1999
• Status: Expired due to Fees

• Current Assignee: Georgia Tech Research Corporation (University System of Georgia)
• Original Assignee: Georgia Tech Research Corporation (University System of Georgia)
• Inventors: Piepmeier, Jennelle Armstrong, McMurray, Gary Von, Lipkin, Harvey
• Primary Examiner(s): Grant, William
• Assistant Examiner(s): RODRIGUEZ, PAUL L
• Application Number:
  US09/492,613
• Time in Patent Office: 572 Days
• Field of Search: 700/250, 700/251, 700/253, 700/258, 700/263, 700/56, 700/59, 700/63, 700/245, 700/29, 700/30, 700/31, 318/568.16, 318/568.13, 318/568.11
• US Class Current: 700/250
• CPC Class Codes: B25J 9/1607 Calculation of inertia, jacobian matrixes and inverses
• CPC Class Codes: B25J 9/1697 Vision controlled systems
• CPC Class Codes: G05B 13/024 in which a parameter or coefficient is automatically adjusted to optimise the performance
• CPC Class Codes: G05B 13/042 in which a parameter or coefficient is automatically adjusted to optimise the performance
• CPC Class Codes: G05B 19/404 characterised by control arrangements for compensation, e.g. for backlash, overshoot, tool offset, tool wear, temperature, machine construction errors, load, inertia G05B19/19, G05B19/41 take precedence
• CPC Class Codes: G05B 2219/39062 Calculate, jacobian matrix estimator
• CPC Class Codes: G05B 2219/39397 Map image error directly to robot movement, position with relation to world, base not needed, image based visual servoing

Abstract

An apparatus and method for enabling an uncalibrated, model independent controller for a mechanical system using a dynamic quasi-Newton algorithm which incorporates velocity components of any moving system parameter(s) is provided. In the preferred embodiment, tracking of a moving target by a robot having multiple degrees of freedom is achieved using an uncalibrated model independent visual servo control. Model independent visual servo control is defined as using visual feedback to control a robot'"'"'s servomotors without a precisely calibrated kinematic robot model or camera model. A processor updates a Jacobian and a controller provides control signals such that the robot'"'"'s end effector is directed to a desired location relative to a target on a workpiece.

Claims

1. A method for calculating control data for controlling a first parameter of a system, comprising the steps of:

receiving data that represents a measurement of said first parameter in said system;

translating said data using at least rate of change information of said first parameter using a dynamic quasi-Newton algorithm; and

producing a translation model, wherein said translation model enables control of said first parameter so that said first parameter converges toward a predefined second parameter.

2. The method of claim 1, wherein said translation model is a linear mathematical Jacobian.

3. The method of claim 1, wherein said translation model is a non-linear mathematical Jacobian.

4. The method of claim 1, wherein said predefined second parameter is chosen from the group consisting of a distance, a specific location, a specific temperature, a temperature range, a specific pressure, a pressure range, a specific volume, and a volume range.

5. The method of claim 1, further comprising the step of producing at least one control signal for a controller, based upon said translation model, and without creating and using a kinematic model of said system.

6. The method of claim 1, wherein said translation model includes at least velocity information associated with said first parameter.

7. The method of claim 6, wherein said velocity information is modified by addition of a number.

8. The method of claim 6, wherein said velocity information is modified by multiplication by a number.

9. The method of claim 6, wherein said velocity information is modified by integration.

10. The method of claim 6, wherein said system has a workpiece and a robot having at least one degree of freedom based upon at least one moveable connector on said robot, said first parameter represents a distance between an end-effector of said robot and a target point associated with said workpiece, and said rate of change information includes velocity information associated with said workpiece.

11. The method of claim 6, wherein said system has a workpiece and a robot having at least one degree of freedom based upon at least one moveable connector on said robot, said first parameter represents a distance between an end-effector of said robot and a target point associated with said workpiece, and said rate of change information includes velocity information associated with said target point.

12. The method of claim 6, wherein said system has a workpiece and a robot having at least one degree of freedom based upon at least one moveable connector on said robot, said first parameter represents a distance between an end effector of said robot and a target point associated with said workpiece, and said rate of change information includes velocity information associated with said end effector.

13. The method of claim 6, wherein said system has a workpiece, a camera and a robot having at least one degree of freedom based upon at least one moveable connector on said robot, said first parameter represents a distance between an end effector of said robot and a target point associated with said workpiece, and said rate of change information includes velocity information associated with said camera.

14. The method of claim 6, wherein said system has a workpiece and a robot having at least one degree of freedom based upon at least one moveable connector on said robot, said first parameter represents a distance between an end effector of said robot and a target point associated with said workpiece, and said velocity information comprises an angle for each at least one moveable connector of said robot and a corresponding time associated with said angle.

15. The method of claim 14, wherein said at least one moveable connector has a joint.

16. The method of claim 1, wherein said second parameter represents a predefined distance threshold.

17. The method of claim 1, wherein said second parameter represents a predefined location having a parameter value of zero.

18. The method of claim 17, wherein said first parameter represents a distance between a first point and a second point and said system has a robot having at least one degree of freedom based upon at least one moveable connector, said method further comprising the steps of:

acquiring at least one image of said first point and said second point;

producing an error signal from said at least one image, said error signal representing a displacement between said first point and said second point;

producing said translation model as a mathematical dynamic Broyden Jacobian update, said mathematical dynamic Broyden Jacobian update comprising at least one angle with a corresponding time for said error signal;

producing control data for said system based upon at least one future error signal derived from a dynamic Broyden Jacobian update, said control data comprising said at least one angle and said corresponding time information; and

adjusting said moveable connector according to said control data.

19. The method of claim 1, wherein said first parameter represents a distance between a first point and a second point.

20. The method of claim 19, wherein said second point is moving and said method further comprises the step of adjusting said translation model based upon movement of said second point.

21. The method of claim 19, wherein said system has a robot and a workpiece.

22. The method of claim 21, wherein said first point is on said robot and said second point is a target point on said workpiece.

23. The method of claim 22, wherein said first point is an end-effector on said robot.

24. The method of claim 1, further comprising the step of sensing said data.

25. The method of claim 24, wherein said predefined second parameter is any one of the following:

a distance, a specific location, a specific temperature, a temperature range, a specific pressure, a pressure range, a specific volume, a volume range.

26. The method of claim 24, wherein the sensing step employs a visual detection system.

27. The method of claim 26, wherein said visual detection system employs at least one camera.

28. The method of claim 27, wherein said at least one camera is moving.

29. The method of claim 1, further comprising the step of determining control data for a controller from said translation model, said controller configured to control said first parameter.

30. The method of claim 29, wherein said control data comprises an angular position of a moveable connector associated with said system and a time associated with said angular position.

31. The method of claim 30, further comprising the step of adjusting said moveable connector according to said control data.

32. The method of claim 1, wherein said translation model includes a dynamic Broyden Jacobian update.

33. The method of claim 32, wherein said translation model includes a dynamic recursive least squares Jacobian update.

34. The method of claim 1, wherein said translation model includes a dynamic recursive least squares Jacobian update.

35. A method for calculating control data for controlling a first parameter of a system, comprising the steps of:

receiving data that represents a measurement of said first parameter in said system;

translating said data using at least rate of change information of said first parameter; and

producing a translation model that includes a dynamic Broyden Jacobian update, wherein said translation model enables control of said first parameter so that said first parameter converges toward a predefined second parameter.

36. The method of claim 35, wherein said translation model includes a dynamic recursive least squares Jacobian update.

37. A method for calculating control data for controlling a first parameter of a system, comprising the steps of:

receiving data that represents a measurement of said first parameter in said system;

translating said data using at least rate of change information of said first parameter; and

producing a translation model that includes a dynamic recursive least squares Jacobian update, wherein said translation model enables control of said first parameter so that said first parameter converges toward a predefined second parameter.

38. A method for controlling a system having at least one degree of freedom based upon at least one moveable connector so that said system learns how to track such that a first point tracks a second point that is moving, comprising the steps of:

acquiring at least one image of said first point and said second point;

producing an error signal from said at least one image, said error signal representing a displacement between said first point and said second point in said image;

producing a translation model using a dynamic quasi-Newton algorithm for converting image space coordinates into system space coordinates, said translation model having at least velocity information pertaining to said first point and said second point; and

causing said first point to track said moving second point by producing control data for said first point based upon at least one future error signal and said translation model.

39. The apparatus of claim 38, wherein said translation model includes a dynamic Broyden Jacobian update.

40. The method of claim 38, wherein said step of producing the translation model includes using a dynamic Broyden Jacobian update.

41. The method of claim 38, wherein said step of producing the translation model further includes using a dynamic recursive least squares Jacobian update.

42. The method of claim 41, wherein said translation model includes a dynamic recursive least squares Jacobian update.

43. An apparatus for controlling a first parameter in a system, comprising:

a receiver which receives data that represents a measurement of said first parameter in said system;

a translator which translates said data using a dynamic quasi-Newton algorithm and at least rate of change information of said first parameter; and

a translation model based upon translation of said data.

44. The apparatus of claim 43, wherein said translation model is created without a kinematic model of said system.

45. The apparatus of claim 43, wherein said translation model includes at least velocity information associated with said first parameter.

46. The apparatus of claim 45, wherein said system has a workpiece and a robot having at least one degree of freedom based upon at least one moveable connector on said robot, said first parameter represents a distance between a first point and a second point, and said velocity information comprises an angle for each at least one moveable connector of said robot and a corresponding time associated with said angle.

47. The apparatus of claim 46, wherein said at least one moveable connector has a joint.

48. The apparatus of claim 46, wherein said first point is an end effector of said robot and said second point is a target point associated with said workpiece.

49. The apparatus of claim 46, further comprising a controller, said controller producing at least one control signal for controlling said first parameter.

50. The apparatus of claim 49, wherein said second point is moving and translator adjusts said translation model based upon movement of said second point.

51. The apparatus of claim 50, wherein said at least one control signal adjusts said at least one moveable connector so that said apparatus learns how to track and tracks said moving second point.

52. The apparatus of claim 51, wherein said at least one control signal adjusts said at least one moveable connector causing said first point to converge toward a predefined distance of said second point.

53. The apparatus of claim 50, further comprising:

a visual detector, said visual detector acquiring at least one image of said first point and said second point; and

an error signal generator producing an error signal from said at least one image, each said error signal representing a displacement between said first point and said second point.

54. The apparatus of claim 53, said control signal is based upon at least one future error signal derived from a dynamic Broyden Jacobian update.

55. The apparatus of claim 43, wherein said translation model includes a dynamic Broyden Jacobian update.

56. The apparatus of claim 55, wherein said translation model includes a dynamic recursive least squares Jacobian update.

57. The apparatus of claim 43, wherein said translation model includes a dynamic recursive least squares Jacobian update.

58. An apparatus for controlling a first parameter in a system, comprising:

a receiver which receives data that represents a measurement of said first parameter in said system;

a translator which translates said data using at least rate of change information of said first parameter; and

a translation model based upon translation of said data that includes a dynamic Broyden Jacobian update.

59. The apparatus of claim 58, wherein said translation model includes a dynamic recursive least squares Jacobian update.

60. An apparatus for controlling a first parameter in a system, comprising:

a receiver which receives data that represents a measurement of said first parameter in said system;

a translator which translates said data using at least rate of change information of said first parameter; and

a translation model based upon translation of said data that includes a dynamic recursive least squares Jacobian update.

61. A computer readable medium having a program for a first parameter in a system, the program comprising:

logic configured to receive data that represents a measurement of said first parameter in said system;

logic configured to translate said data using a dynamic quasi-Newton algorithm and using at least rate of change information of said first parameter; and

logic configured to generate a translation model based upon translation of said data.

62. The program as defined in claim 61, wherein said logic configured to generate said translation model includes a dynamic Broyden Jacobian update.

63. The program as defined in claim 62, wherein said logic configured to generate said translation model includes a dynamic recursive least squares Jacobian update.

64. The program as defined in claim 61, wherein said logic configured to generate said translation model includes a dynamic recursive least squares Jacobian update.

65. A computer readable medium having a program for a first parameter in a system, the program comprising:

logic configured to receive data that represents a measurement of said first parameter in said system;

logic configured to translate said data using at least rate of change information of said first parameter; and

logic configured to generate a translation model based upon translation of said data that includes a dynamic Broyden Jacobian update.

66. The program as defined in claim 65, further comprising logic to include at least velocity information associated with the first parameter.

67. The program as defined in claim 66, further comprising:

logic to control a robot having at least one degree of freedom based upon at least one moveable connector on said robot;

logic configured to interpret said first parameter as a distance between a first point and a second point; and

logic configured to determine said velocity information as an angle for each at least one moveable connector of said robot and a corresponding time associated with said angle.

68. The program as defined in claim 67, further comprising logic configured to generate a control signal to control adjustment of said moveable connector of said robot such that said first point converges toward to a predefined distance of said second point.

69. The program as defined in claim 68, wherein said second point is moving.

70. The program as defined in claim 69, further comprising:

logic to interpret an image from a visual detector, said visual detector acquiring at least one image of said first point and said second point; and

logic configured to generate an error signal from said at least one image, each said error signal representing a displacement between said first point and said second point.

71. The program as defined in claim 70, wherein said logic configured to generate a control signal is based upon at least one future error signal derived from a dynamic Broyden Jacobian update.

72. The program as defined in claim 70, wherein said logic configured to generate a control signal is based upon at least one future error signal derived from a dynamic recursive least squares Jacobian update.

73. The program as defined in claim 65, wherein said logic configured to generate said translation model includes a dynamic recursive least squares Jacobian update.

74. A computer readable medium having a program for a first parameter in a system, the program comprising:

logic configured to receive data that represents a measurement of said first parameter in said system;

logic configured to translate said data using at least rate of change information of said first parameter; and

logic configured to generate a translation model based upon translation of said data that includes a dynamic recursive least squares Jacobian update.