Pedestrian Navigation Apparatus and Method

• US 20070260418A1
• Filed: 03/11/2005
• Published: 11/08/2007
• Est. Priority Date: 03/12/2004
• Status: Active Grant

• Current Assignee: ‎Vectronix AG
• Original Assignee: ‎Vectronix AG
• Inventors: Verhaert, Koen, Ladetto, Quentin
• Granted Patent: US 7,747,409 B2
• Time in Patent Office: Days
• US Class Current: 702/150
• CPC Class Codes: G01C 21/1654 with electromagnetic compass
• CPC Class Codes: G01C 22/006 Pedometers
• CPC Class Codes: G06F 3/011 Arrangements for interaction with the human body, e.g. for user immersion in virtual reality blind teaching G09B21/00

Abstract

The motion of a pedestrian is evaluated by determining at least one position of at least one identified portion of the pedestrian, projecting the positions(s) on at least one plane, and deriving the motion from the position(s) projected on the at least one plane. Typically the position(s) are determined in three-dimensions, e.g. of the feet. It is possible to project on two different planes to provide three-dimensional navigation information.

Claims

1. Method of determining the motion of a pedestrian, comprising the steps of:

determining at least one position of at least one identified portion of the pedestrian,

projecting said position(s) on at least one plane, and

deriving the motion from the position(s) projected on said at least one plane.

2. Method according to claim 1, wherein said at least one position is determined as a three-dimensional position of said at least one identified portion of the pedestrian.

3. Method according to claim 1, wherein said determining step comprises determining the position of each foot of said pedestrian, whereby the projected positions of the feet express a distance between said feet along said at least one plane.

4. Method according to claim 1, wherein said determining step comprises producing a vector in three-dimensional space of a line between at least first and second body portions of said pedestrian, e.g. respective feet of said pedestrian, and wherein said projecting step comprises projecting said three-dimensional vector as a two-dimensional vector onto said at least one plane.

5. Method according to claim 1, wherein said projecting step comprises projecting a three-dimensional vector on at least one plane using goniometric mathematics, to produce a two-dimensional projection vector onto said at least one plane.

6. Method according to claim 1, wherein said projecting step comprises producing a two-dimensional vector on a said plane, and further comprises projecting said two-dimensional vector to one dimension along a line corresponding to a determined direction.

7. Method according to claim 6, wherein said line corresponds is a line of current azimuth of said pedestrian, or direction of general displacement of said pedestrian, or of averaged step direction.

8. Method according to claim 1, wherein said determining step comprises determining the position of each foot of said pedestrian,

the method further comprising:

detecting a situation in which said pedestrian has completed a step, and

performing said deriving step for a situation where said pedestrian has completed a step, thereby obtaining a step length, or extent of a step, along said at least one plane.

9. Method according to claim 1, wherein at least one said plane is a plane containing at least one axis corresponding to an axis of a reference coordinate system on which said motion is to be expressed, or is a plane having a component along said axis of a reference coordinate system on which said motion is to be expressed.

10. Method according to claim 1, wherein said at least one said plane comprises a ground, or horizontal, plane containing North-South and West-East axes.

11. Method according to claim 1, wherein at least one said plane is a vertical plane, or a plane having a vertical component.

12. Method according to claim 1, wherein said motion to be determined is a displacement of said pedestrian in three dimensions, and wherein said projecting step comprises projecting said position(s) on at least a first plane on which first and second dimensions of said three dimensions can be expressed, e.g. corresponding to North-South and West-East directions, and on a second plane on which the third of said three dimensions can be expressed, e.g. corresponding to a vertical direction.

13. Method according to claim 1, wherein said type of motion determined is at least one of:

i) a step direction and ii) a distance traveled by said pedestrian along a step direction, iii) a displacement in a two dimensional reference system, iv) a displacement in a three dimensional reference system.

14. Method according to claim 1, further comprising:

determining a line of azimuth of said pedestrian, or line of average direction of steps made by the pedestrian,

deriving, from said determining and projecting steps, individual step vectors, and

projecting said individual step vectors on said line of azimuth or of average direction.

15. Method according to claim 1, wherein said at least one position of at least one identified portion of the pedestrian is determined by sensor means worn by said pedestrian and adapted to deliver data in respect of at least one of:

quaternion calculation,

calculation of limb orientation;

calculation of joint position;

step detection;

step orientation calculation;

step length calculation;

pattern recognition.

16. Method according to claim 1, wherein data for said determining step is acquired by sensor means worn by said pedestrian on:

upper leg portions of each leg,

lower leg portions of each leg, and

optionally, a lower back, waist, or trunk portion.

17. Method according to claim 1, wherein said determining step comprises determining relative positions of identified upper and lower leg positions for each leg of said pedestrian.

18. Method according to claim 1, wherein said determining step comprises determining a distance between two lower leg portions and/or two feet of said pedestrian.

19. Method according to claim 1, wherein said determining step comprises determining an identified position at a lower back, waist or trunk portion of said pedestrian.

20. The method according to claim 1, further comprising establishing a situation in which said pedestrian has completed a step movement on the basis of at least one criterion among:

a measurement of the three-dimensional position of each foot of said pedestrian,

a measurement of distance between feet of said pedestrian,

detection of a situation in which at least one foot of said pedestrian is in a state of no acceleration,

shock measurements,

and of carrying out said projecting step and/or said deriving step as a function of establishing a completed step movement.

21. The method according to claim 1, further comprising establishing a situation in which said pedestrian has completed a step movement on the basis of a separation between two feet of said pedestrian, by:

determining a substantially vertical component of said separation,

the occurrence or crossing of a substantially zero value of said substantially vertical component, and of carrying out said projecting step and/or said deriving step as a function of establishing a completed step movement.

22. Method according to claim 1, further comprising establishing a situation in which said pedestrian has completed a step movement on the basis of the point of maximum horizontal distance between the feet of said pedestrian, by:

obtaining a distance measurement between said two feet, and

identifying a completed step movement as the occurrence of a maximum value in said distance measurement,

and of carrying out said projecting step and/or said deriving step as a function of establishing a completed step movement.

23. The method according to claim 1, comprising the step implementing an autonomous human motion pattern recognition algorithm, with a database of minimum and maximum values for at least one parameter used in said pattern and/or a model used in conjunction with said pattern.

24. Method according to claim 1, comprising the step of implementing a minimal trimmed three-dimensional ergonomic model containing at least one critical parameter based on three-dimensional joint positions and limb orientation.

25. Method according to claim 1, comprising the step of using a pattern recognition algorithm and of applying weighting coefficients per pattern on identified parameters based on at least one dynamic characteristic and/or at least one boundary condition of human motion patterns, whereby a score for each pattern is calculated per step made by said pedestrian, the highest score being used as the pattern to select for said algorithm.

26. Method according to claim 1, further comprising a calibration phase for sensor means or sensor signal processing means carried by said pedestrian comprising providing positional references by:

having the pedestrian oriented at a determined azimuth, preferably North,

having the pedestrian standing still in that orientation for a determined period of time,

optionally having the pedestrian make at least one forward step and holding the new position for a determined period of time, making at least one side step holding the new position for a determined period of time,

27. Method according to claim 1, comprising the step of equipping said pedestrian with a set of sensors at selected body portions, each sensor being capable of delivering a respective quaternion, said method further comprising the steps of:

converting said quaternions into a rotation matrix,

calculating a sensor alignment matrix,

deriving at least one of;

pattern recognition,

a step distance,

orientation,

on the basis of said rotation matrix and/or said sensor alignment matrix.

28. Method according to claim 1, comprising deriving real navigation azimuth of said pedestrian, comprising:

placing first sensor means on the pedestrian, preferably on the back substantially at hip level, to derive an absolute orientation, or a line of sight, azimuth of said pedestrian, e.g. the pedestrian'"'"'s facing direction relative to North or an external reference direction;

placing a plurality of second sensor means on selected body portions to determine relative azimuth of said body portions, and

combining the data from said first and second sensor means to produce a real navigation azimuth.

29. Method according to claim 28, wherein data from said second sensor means is used to determine a step direction of said pedestrian, said combining step comprising adding the determined step direction to the orientation, or line of sight azimuth to obtain a real navigation azimuth along the step direction.

30. Method according to claim 1, wherein said determined motion comprises pedestrian navigation information based step length data, said method further comprising the steps of:

operating an autonomous pedestrian navigation apparatus operating by dead reckoning, said autonomous pedestrian navigation apparatus being worn by said pedestrian and capable of delivering displacement information, notably distance traveled and/or trajectory,

using sensor means worn by said pedestrian to determine from body positions a detected step length data,

providing said step length data as input to said autonomous pedestrian navigation,

optimizing the accuracy of the displacement information of said autonomous pedestrian navigation apparatus on the basis of said inputted detected step length.

31. Method according to claim 30, further comprising the steps of:

deriving from said sensor means relative azimuth data (relative to a determined orientation or line of sight of said pedestrian), and

providing said relative azimuth data as data input to said autonomous pedestrian navigation apparatus.

32. Method according to claim 30, wherein said autonomous pedestrian navigation apparatus is provided with internal means for determining step length on the basis of step model data and algorithms,

and wherein said step length data from said sensor means is used by said autonomous pedestrian navigation apparatus instead of relying on said internal means for determining step length.

41. A computer program, or a carrier containing program code, said program or said program code being executable by processor means to perform the method according to claim 1.

33. Method of determining the motion of a pedestrian, comprising the steps of:

determining a relative separation between identified body portions of the pedestrian, and

deriving from said relative separation a projection on at least one plane over which said pedestrian evolves or over a plane having a component along a direction over which said pedestrian evolves.

34. Apparatus for determining the motion of a pedestrian comprising:

means for determining at least one position of at least one identified portion of the pedestrian,

means for projecting said position(s) on at least one plane, and

means for deriving the motion from the position(s) projected on said at least one plane.

36. Apparatus according to claim 34, adapted for deriving real navigation azimuth of said pedestrian, comprising:

first sensor means adapted to be worn above the legs of the pedestrian, preferably on the back substantially at hip level, to derive an absolute orientation, or a line of sight, azimuth of said pedestrian, e.g. the pedestrian'"'"'s facing direction relative to North or an external reference direction;

a plurality of second sensor means on selected body portions to determine relative azimuth of said body portions, and

means for combining the data from said first and second sensor means to produce a real navigation azimuth.

37. Apparatus according to claim 36, comprising means:

responsive to data from said second sensor means to determine a step direction of said pedestrian,

and wherein said combining means comprises means for adding the determined step direction to the orientation, or line of sight azimuth to obtain a real navigation azimuth along the step direction.

38. Apparatus according to claim 34, wherein said determined motion comprises pedestrian navigation information based step length data, said apparatus further comprising:

an autonomous pedestrian navigation apparatus operating by dead reckoning, said autonomous pedestrian navigation apparatus being adapted to be worn by said pedestrian and being capable of delivering displacement information, notably distance traveled and/or trajectory,

sensor means adapted to be worn by said pedestrian to determine from body positions a detected step length data,

means for inputting said step length data as input to said autonomous pedestrian navigation, and

means for optimizing the accuracy of the displacement information of said autonomous pedestrian navigation apparatus on the basis of said inputted detected step length.

39. Apparatus according to claim 38, further comprising:

means for deriving from said sensor means relative azimuth data (relative to a determined orientation or line of sight of said pedestrian), and

means for inputting said relative azimuth data to said autonomous pedestrian navigation apparatus.

35. (canceled)

40. Apparatus for determining the motion of a pedestrian, comprising:

means for determining a relative separation between identified body portions of the pedestrian, and

means for deriving from said relative separation a projection on at least one plane over which said pedestrian evolves or having a component along a direction over which said pedestrian evolves.