Touch sensitive robotic gripper

• US 9,605,952 B2
• Filed: 09/12/2014
• Issued: 03/28/2017
• Est. Priority Date: 03/08/2012
• Status: Active Grant

• Current Assignee: Quality Manufacturing Inc. (Integrated Aerospace Manufacturing LLC)
• Original Assignee: Quality Manufacturing Inc. (Integrated Aerospace Manufacturing LLC)
• Inventors: Rose, Jeffrey A., Rose, James Adam, Rose, Stephen D., Cooper, Raymond, Sweda, Jeffrey John
• Primary Examiner(s): Amin, Bhavesh V
• Application Number:
  US14/485,180
• Publication Number:
  US 20150019013A1
• Time in Patent Office: 928 Days
• Field of Search: 700245-264
• US Class Current: 1/1
• CPC Class Codes: B25J 13/08 by means of sensing devices, e.g. viewing or touching devices
• CPC Class Codes: B25J 15/0028 with movable, e.g. pivoting gripping jaw surfaces
• CPC Class Codes: B25J 15/10 with three or more finger members B25J15/0009 takes precedence
• CPC Class Codes: B25J 9/1612 characterised by the hand, wrist, grip control
• CPC Class Codes: G01B 21/20 for measuring contours or curvatures, e.g. determining profile
• CPC Class Codes: G01L 1/16 using properties of piezoelectric devices
• CPC Class Codes: G05D 1/021 specially adapted to land vehicles
• CPC Class Codes: Y02P 90/02 Total factory control, e.g. smart factories, flexible manufacturing systems [FMS] or integrated manufacturing systems [IMS]
• CPC Class Codes: Y10S 901/01 Mobile robot
• CPC Class Codes: Y10S 901/27 Arm part
• CPC Class Codes: Y10S 901/28 Joint
• CPC Class Codes: Y10S 901/31 Gripping jaw
• CPC Class Codes: Y10S 901/46 Sensing device
• CPC Class Codes: Y10S 901/47 Optical

Abstract

A displacement measuring cell may be used to measure linear and/or angular displacement. The displacement measuring cell may include movable and stationary electrodes in a conductive fluid. Electrical property measurements may be used to determine how far the movable electrode has moved relative to the stationary electrode. The displacement measuring cell may include pistons and/or flexible walls. The displacement measuring cell may be used in a touch-sensitive robotic gripper. The touch-sensitive robotic gripper may include a plurality of displacement measuring cells mechanically in series and/or parallel. The touch-sensitive robotic gripper may be include a processor and/or memory configured to identify objects based on displacement measurements and/or other measurements. The processor may determine how to manipulate the object based on its identity.

Claims

1. A robotic foot comprising:

one or more shear sensors configured to measure a shear force against a bottom of the robotic foot;

a plurality of displacement measuring cells configured to support the robotic foot and measure a contour of a surface in contact with the bottom of the robotic foot;

a plurality of force sensors, each force sensor in series with a corresponding displacement measuring cell of the plurality of displacement measuring cells; and

a processor configured to;

receive measurements from the one or more shear sensors, and

calculate a coefficient of friction between the robotic foot and a surface in contact with the bottom of the robotic foot.

2. The robotic foot of claim 1, further comprising:

a pressure sensor configured to measure a fluid pressure of a fluid in the robotic foot, wherein the processor is configured to determine at least one of a robot weight and a robot load from the fluid pressure.

3. The robotic foot of claim 1, wherein the one or more shear sensors includes at least one a transducer selected from the group consisting of an electromagnetically coupled coil, an optoelectronic sensor, a quartz sensor, a capacitive sensor, and a fiber optic sensor.

4. The robotic foot of claim 1, wherein at least one of the force sensor or the corresponding displacement measuring cell in series therewith includes a sensor selected from the group consisting of a series elastic actuator, a linear variable differential transformer, a rotary variable differential transformer, a strain gauge, a polyvinylidene fluoride (PVDF) sensor, a force-sensing resistor, a vacuum diode force sensor, a capacitive tactile sensor, a piezoelectric force sensor.

5. The robotic foot of claim 1, wherein the processor is configured to determine at least one of a robot weight and a robot load from a plurality of displacement measurements received from the plurality of displacement measuring cells.

6. The robotic foot of claim 5, wherein the processor is configured to calculate the load at each of the plurality of displacement measuring cells.

7. The robotic foot of claim 1, wherein the processor is configured to calculate the coefficient of friction at each of the plurality of displacement measuring cells.

8. The robotic foot of claim 1, wherein the processor is configured to calculate the coefficient of friction by:

determining a total robot weight including load from readings from a pressure transducer and at least one joint encoder;

measuring the shear force against the bottom of the foot; and

calculating the coefficient of friction from at least one of the total robot weight including load, the shear force, a foot angle indicated by the at least one joint encoder, a pressure indicated by a pressure transducer, and a velocity.

9. The robotic foot of claim 8, wherein the processor is further configured to calculate the coefficient of friction by:

measuring displacement of the plurality of displacement measuring cells;

measuring a cell pressure at each of the plurality of displacement measuring cells with at least one pressure transducer;

determining a pressure distribution profile from the plurality of displacement measuring cells;

equalizing pressures of the plurality of displacement measuring cells with at least one pressure reducing valve; and

calculating a geography of the surface.

10. The robotic foot of claim 8, wherein the processor is further configured to determine the coefficient of friction by:

adjusting an angle of the foot to conform to the surface; and

calculating the angle of the foot by measuring an angle of an ankle joint with an encoder, and

wherein the processor is configured to calculate the coefficient of friction based on the angle of the foot.

11. The robotic foot of claim 10, wherein the processor is further configured to:

calculate a momentum of a robot coupled to the robotic foot; and

determine a maximum acceleration and a maximum velocity based on at least one of the calculated coefficient of friction, the total robot weight including load, a weight distribution, a pressure distribution, a body angle, the foot angle, the shear force, a contact area between the foot and the surface, and a ground slope.

12. The robotic foot of claim 11, wherein the processor is further configured to tilt a body of the robot based on at least one of the momentum, a current acceleration, the maximum velocity, the maximum acceleration, and the ground slope.

13. The robotic foot of claim 1, wherein the processor is further configured to measure movement of the surface by measuring at least one of a shift in an ankle joint, a change in shear sensor deflection, a change in measured displacement by the plurality of displacement measuring cells, and a change in pressure distribution of the plurality of displacement measuring cells.

14. The robotic foot of claim 1, wherein the plurality of displacement measuring cells comprise a plurality of linear potentiometers.

15. The robotic foot of claim 1, wherein a flexible material comprising the bottom of the foot comprises the one or more shear sensors, and wherein the shear sensors are coupled to a rigid skeletal component.

16. The robotic foot of claim 15, further comprising a rigid layer coupled to the rigid skeletal component;

and a separating layer between the flexible material and the rigid layer, wherein the separating layer is selected from the group consisting of a gas, a liquid, and a gel.

17. The robotic foot of claim 15, the one or more shear sensors are self-contained in the flexible substrate.

18. The robotic foot of claim 1, wherein the processor is configured to:

calculate a ground slope from a signal from at least one encoder indicating at least one of a knee angle, an ankle angle, an ankle location, and a hip angle; and

tilt a body of a robot coupled to the robotic foot based on at least one of the coefficient of friction, the ground slope, a velocity of the robot, and an acceleration of the robot.

19. The robotic foot of claim 1, wherein the processor is configured to calculate a ground slope from a first horizontal and a first vertical position of the robotic foot relative to a second horizontal and a second vertical position of another robotic foot of a same robot that includes the robotic foot, and wherein the processor determines the first and second horizontal and vertical positions from hip and knee angles.

20. The robotic foot of claim 1, wherein the one or more shear sensors each comprise a cantilever perpendicular to the surface.

21. The robotic foot of claim 1, wherein the one or more shear sensors each comprise at least one of a PVDF sensor and a piezoresistive sensor.

22. The robotic foot of claim 1, wherein the processor is further configured to select a walking algorithm based on the calculated coefficient of friction.

23. The robotic foot of claim 1, wherein the processor is further configured to:

detect a loss of traction based on the shear force; and

calculate an updated coefficient of friction based on the loss of traction.

24. The robotic foot of claim 1, wherein the processor is configured to monitor instantaneous shear force measurements and update the calculated coefficient of friction based on the instantaneous shear force measurements.

25. The robotic foot of claim 1, wherein the processor is further configured to compare the calculated coefficient of friction with one or more stored coefficients of friction saved in a storage device.

26. The robotic foot of claim 1, wherein the processor is further configured to calibrate the shear force for a plurality of different surfaces.

27. A method for determining frictional properties of a surface in contact with a bottom of a robotic foot, the method comprising:

receiving, at a processor, shear force measurements for the bottom of the foot from one or more shear sensors;

measuring a contour of the surface in contact with the bottom of the robotic foot with a plurality of displacement measuring cells configured to support the robotic foot;

measuring pressure with a plurality of force sensors, each force sensor in series with a corresponding displacement measuring cell of the plurality of displacement measuring cells; and

calculating, using the processor, a coefficient of friction between the foot and the surface in contact with the bottom of the foot.

28. The method of claim 27, further comprising determining at least one of a robot weight and a robot load from a fluid pressure of a fluid in the robotic foot.

29. The method of claim 27, wherein measuring pressure includes taking measurements with at least one force sensor sensor selected from the group consisting of a series elastic actuator, a linear variable differential transformer, a rotary variable differential transformer, a strain gauge, a polyvinylidene fluoride (PVDF) sensor, a force-sensing resistor, a vacuum diode force sensor, a capacitive tactile sensor, a piezoelectric force sensor.

30. The method of claim 27, further comprising determining at least one of a robot weight and a robot load from a plurality of displacement measurements received from the plurality of displacement measuring cells.

31. The method of claim 30, wherein determining at least one of a robot weight and a robot load comprises determining the load at each of the plurality of displacement measuring cells, and wherein calculating the coefficient of friction comprises calculating the coefficient of friction at each of the plurality of displacement measuring cells.

32. The method of claim 27, wherein calculating the coefficient of friction comprises:

determining a total robot weight including load from readings from the plurality of force sensors and at least one joint encoder;

measuring the shear force against the bottom of the foot; and

calculating the coefficient of friction from at least one of the total robot weight including load, the shear force, a foot angle indicated by the at least one joint encoder, a pressure indicated by the plurality of force sensors, and a velocity.

33. The method of claim 32, wherein calculating the coefficient of friction comprises:

measuring displacement of the plurality of displacement measuring cells;

measuring a cell pressure at each of the plurality of displacement measuring cells with a corresponding one of the plurality of force sensors;

determining a pressure distribution profile from the plurality of displacement measuring cells;

equalizing pressures of the plurality of displacement measuring cells with at least one pressure reducing valve; and

calculating a geography of the surface.

34. The method of claim 32, further comprising:

determining a load on the foot;

calculating a unit pressure on each of the plurality of displacement measuring cells; and

calculating a coefficient of friction for each of the plurality of displacement measuring cells based on the unit pressure.

35. The method of claim 32, wherein calculating the coefficient of friction comprises:

adjusting an angle of the robotic foot to conform to the surface; and

calculating the angle of the robotic foot by measuring an angle of an ankle joint with an encoder, and

wherein the processor is configured to calculate the coefficient of friction based on the angle of the foot.

36. The method of claim 35, further comprising:

calculating a momentum of a robot coupled to the robotic foot; and

determining a maximum acceleration and a maximum velocity based on at least one of the calculated coefficient of friction, the total robot weight including load, a weight distribution, a pressure distribution, a body angle, the foot angle, the shear force, a contact area between the foot and the surface, a velocity, and a ground slope.

37. The method of claim 36, further comprising tilting a body of the robot based on at least one of the momentum, a current acceleration, the maximum velocity, the maximum acceleration, and the ground slope.

38. The method of claim 29, further comprising measuring movement of the surface by measuring at least one of a shift in an ankle joint, a change in shear sensor deflection, and a change in pressure distribution of the plurality of displacement measuring cells.

39. The method of claim 27, further comprising:

calculating a ground slope from a signal from at least one encoder indicating at least one of a knee angle, an ankle angle, and a hip angle; and

tilting a body of a robot coupled to the robotic foot based on at least one of the coefficient of friction, the ground slope, a velocity of the robot, a load on the robot, and an acceleration of the robot.

40. The method of claim 27, further comprising calculating a ground slope from a first horizontal and a first vertical position of the robotic foot relative to a second horizontal and a second vertical position of another robotic foot of a same robot that includes the robotic foot, wherein the first and second horizontal and vertical positions are determined from hip and knee angles.

41. The method of claim 27, further comprising:

detecting a loss of traction based on the shear force; and

calculating an updated coefficient of friction based on the loss of traction.

42. The method of claim 27, further comprising monitoring instantaneous shear force measurements and updating the calculated coefficient of friction based on the instantaneous shear force measurements.

43. The method of claim 27, further comprising comparing the calculated coefficient of friction with one or more stored coefficients of friction saved in a storage device.

44. The method of claim 27, further comprising calibrating the shear force for a plurality of different surfaces.

45. The method of claim 27, further comprising measuring a ground compression rate.

46. The method of claim 45, wherein measuring the ground compression rate comprises measuring a rate of descent of the robotic foot.

47. The method of claim 45, wherein measuring the ground compression rate comprises measuring a rate of descent of a linear displacement sensor in the foot.

48. The method of claim 45, wherein measuring the ground compression rate comprises computing a ratio of a rate of descent of a linear displacement sensor to a rate of descent of the robotic foot.

49. The method of claim 48, further comprising comparing the ratio to one or more stored values to determine a ground surface material.

50. The method of claim 49, further comprising calibrating the stored values for different ground surface materials.

51. The method of claim 49, further comprising storing compression ratios for a plurality of materials and robot weights, wherein comparing the ratio comprises comparing the ratio to stored compression ratios associated with a current robot weight.

52. The method of claim 49, wherein the one or more stored values correspond to a ground surface material selected from the group consisting of mud, snow, sand, and concrete.

53. The method of claim 27, further comprising selecting a walking algorithm based on the calculated coefficient of friction.

54. The method of claim 27, further comprising selecting a walking algorithm based on at least one of an angle of the ground, the coefficient of friction, an angle of the foot, and a ground compression rate.

55. A non-transitory computer readable storage medium comprising program code configured to cause a processor to perform a method for determining frictional properties of a surface in contact with a bottom of a robotic foot, the method comprising:

receiving shear force measurements for the bottom of the robotic foot from one or more shear sensors;

determining at least one of a robot weight and a robot load;

calculating a coefficient of friction between the robotic foot and the surface in contact with the bottom of the robotic foot by measuring displacement of a plurality of displacement measuring cells;

measuring a cell pressure at each of the plurality of displacement measuring cells with at least one pressure transducer

determining a pressure distribution profile from the plurality of displacement measuring cells;

equalizing pressures of the plurality of displacement measuring cells with at least one pressure reducing valve; and

calculating a geography of the surface.