AUTOMATIC CORRECTION OF PAST POSITION ERRORS FOR LOCATION AND INVENTORY TRACKING

• US 20100332125A1
• Filed: 09/07/2010
• Published: 12/30/2010
• Est. Priority Date: 07/05/2005
• Status: Active Grant

• Current Assignee: Mi-Jack Products Incorporated (Lanco International, Inc.)
• Original Assignee: ContainerTrac, Inc. (Lanco International, Inc.)
• Inventors: Huang, Jihua, Tan, Han-Shue
• Granted Patent: US 8,838,374 B2
• Time in Patent Office: Days
• US Class Current: 701/207
• CPC Class Codes: G01S 19/39 the satellite radio beacon positioning system transmitting time-stamped messages, e.g. GPS [Global Positioning System], GLONASS [Global Orbiting Navigation Satellite System] or GALILEO
• CPC Class Codes: G01S 19/393 Trajectory determination or predictive tracking, e.g. Kalman filtering
• CPC Class Codes: G01S 19/396 Determining accuracy or reliability of position or pseudorange measurements
• CPC Class Codes: G01S 19/485 whereby the further system is an optical system or imaging system
• CPC Class Codes: G01S 19/49 whereby the further system is an inertial position system, e.g. loosely-coupled
• CPC Class Codes: G01S 5/02585 at least one of the measurements being a non-radio measurement

Abstract

A method is provided for calibrating past position estimates from a positioning system that provides real-time position estimates of a mobile object. The method first stores the real-time position estimates, which as time goes by become past position estimates and naturally form a first past trajectory depicting the past movement of the mobile object. Subsequently, a calibrated past trajectory is determined, which includes calibrated past position estimates that correspond to the same time instances as the past positions in the first past trajectory. When real-time positions have low qualities, this method calibrates them at a later time by using (higher-quality) real-time positions both before and after them. Errors in the past positions are then corrected based on the calibrated past trajectory. When used with event detectors that indicate inventory transactions, this method can correct position errors associated with inventory events so as to improve the performance of inventory tracking.

Claims

1. A method for calibrating past position estimates from a positioning system that provides real-time position estimates of a mobile object, comprising

storing the real-time position estimates as first past positions and aggregating the first past positions to form a first past trajectory, wherein the first past trajectory comprises at least three first past positions;

generating a calibrated past trajectory based on the first past trajectory, wherein the calibrated past trajectory comprises second past positions and at least one of the second past positions is determined by using at least one of the first past positions that corresponds to an earlier time instance;

whereby the second past positions approximate actual past positions of the mobile object better than the first past positions and the calibrated past trajectory depicts past movement of the mobile object more accurately than the first past trajectory.

2. The method in claim 1, wherein each of the first past positions comprises at least a pair of position values corresponding to the mobile object'"'"'s position in a two-degree-of-freedom coordinate system, a heading angle corresponding to traveling direction of the mobile object, and a traveling speed of the mobile object.

3. The method in claim 1, where in the generation of the calibrated past trajectory further comprises computing at least one temporary past trajectory based on mathematical models and combining the temporary past trajectories with the first past trajectory to generate the calibrated past trajectory.

4. The method in claim 1, wherein the generation of the calibrated past trajectory involves at least one of the following:

employing models that depict movement of the mobile object, wherein at least one model takes the first past positions as input;

applying estimation formulas that include mathematic terms accounting for accumulated effects of noise and errors in the first past positions;

estimating and reducing noise and errors by modeling the noise and errors as well as propagation of the noise and errors in trajectory calibration process; and

fitting the calibrated past trajectory to selected segments of the first past trajectory by calibrating parameters.

5. The method in claim 1, wherein the generation of the calibrated past trajectory further comprises iterations of computing temporary past trajectories until the temporary past trajectories satisfy pre-determined criteria, wherein

the first iteration determines a first temporary past trajectory based on the first past trajectory;

each subsequent iteration uses the temporary past trajectory determined in the preceding iteration as an input to determine a subsequent temporary past trajectory; and

the temporary past trajectory determined in the last iteration is the calibrated past trajectory.

6. The method in claim 1, wherein the generation of the calibrated past trajectory further comprises

selecting a segment of the first past trajectory, wherein the segment has a length smaller or equal to length of the first part trajectory;

computing a calibrated past trajectory based on the selected segment of the first past trajectory, wherein the calibrated past trajectory corresponds to same time instances as the segment of the first past trajectory.

7. The method in claim 1, wherein each of the first past positions further comprises a confidence level indicating its accuracy and trustworthiness;

and the generation of the calibrated past trajectory incorporates the confidence levels of the first past positions, whereby the first past positions that have higher confidence levels have more effects on the generation of the calibrated past trajectory.

8. The method in claim 2, wherein

each first past position further comprises an angular velocity of the mobile object;

and

the generation of the calibrated past trajectory further comprises calibrating the heading angle of the first past positions based on the angular velocity and using the calibrated heading angle to compute the calibrated past trajectory.

9. The method in claim 8, wherein the calibration of the heading angle further comprises estimating and approximately removing noise and errors in at least one of the following:

the heading angle and the angular velocity of the mobile object.

10. The method in claim 9, wherein

the noise and errors comprise a bias and a gain offset in the angular velocity, as well as an error in the heading angle of at least one of the most recent first past position and the earliest first past position, and

the noise and errors are estimated by formulating an optimization problem and employing optimization techniques to determine estimates of the noise and errors.

11. The method in claim 8, wherein the calibration of the heading angles further comprises

determining whether the mobile object was moving along a straight road or a curvy road based on the angular velocity in the first past positions and

fitting the calibrated past heading angles to the heading angles in the first past positions, wherein

when the mobile object is determined to be moving along a straight road, the calibrated heading angles are determined based on the heading angles in both the most recent first past position and the earliest first past position in the selected segment,

when the mobile object is determined to be moving along a curvy road, the calibrated heading angles are determined based on calibrated angular velocities, wherein the calibration of the angular velocity comprises determining a gain offset in the angular velocity computing a change in heading angle based on bias-removed angular velocities, and comparing the change with a difference between the heading angle of the most recent first past position and the heading angle of the earliest first past position.

12. The method in claim 1, wherein the generation of the calibrated past trajectory further comprises an iterative process including:

selecting a segment of the first past trajectory;

computing a calibrated past trajectory based on the selected segment of the first past trajectory, wherein the calibrated past trajectory corresponds to same time instances as the segment of the first past trajectory and at least one of the second past positions is determined by using at least one of the first past positions that corresponds to an earlier time instance;

evaluating the trustworthiness of the calibrated past trajectory; and

outputting the calibrated past trajectory if the calibrated past trajectory is determined to be trustworthy in the evaluating step, or extending the segment of the first past trajectory to include more first past positions if the evaluating step determines the calibrated past trajectory is not trustworthy and continuing to next iteration to re-compute the calibrated past trajectory until one of the following criteria is met;

the calibrated past trajectory is trustworthy or a pre-defined number of iterations has been executed,

whereby when one of the criteria is met, a last one of the iterations is output as the calibrated past trajectory.

13. The method in claim 12, wherein the trustworthiness of the calibrated past trajectory is determined based on at least one of the following indexes:

a deviation index that indicates differences between the first past trajectory and the calibrated past trajectory;

a smoothness index that indicates smoothness of the calibrated past trajectory;

a first consistency index that indicates consistency between a first travel distance based on the first past trajectory and a second travel distance based on the calibrated past trajectory; and

a second consistency index that indicates consistency between a first heading angle change based on the first past trajectory and a second heading angle change based on the calibrated past trajectory.

14. The method in claim 12, where in the generated calibrated past trajectory is further integrated with calibrated past trajectories generated at earlier time instances to form an integrated past trajectory.

15. A method for calibrating and correcting past position estimates from a positioning system that provides real-time position estimates of a mobile object, comprising:

storing the real-time position estimates as first past positions and aggregating the first past positions to form a first past trajectory, wherein the first past trajectory comprises at least three first past positions;

generating a calibrated past trajectory based on the first past trajectory, wherein the calibrated past trajectory comprises second past positions and at least one of the second past positions is determined by using at least one of the first past position that corresponds to an earlier time instance; and

correcting errors in the first past positions by first comparing the calibrated past trajectory with the first past trajectory to identify the errors and generating correction data that corrects the errors.

16. The method in claim 15, wherein the generation of the correction data further comprises comparing the identified errors with pre-determined thresholds, identifying time instances corresponding to the errors that exceed the pre-determined thresholds, and providing second past positions that corresponds to the identified time instances as the correction data.

17. A position tracking system for tracking and correcting inventory positions, comprising

a positioning unit associated with a mobile object for providing first position estimates of the mobile object in real time;

a data storage unit for storing the first position estimates as first past positions;

an event management module for detecting occurrences of events by employing event detection means, associating each event with a corresponding first position estimate indicating the position associated with the event, and generating a first event trajectory for the event based on the corresponding first position estimate, wherein the first event trajectory comprises at least three first past positions;

a past trajectory generation module for generating calibrated event trajectories based on the first event trajectory, wherein the calibrated event trajectories comprise second past positions and at least one of the second past positions is determined by using at least one of the first past positions that corresponds to an earlier time instance; and

an error correction module for comparing the calibrated event trajectories from the past trajectory generation module with the first event trajectory to identify errors in the first past positions and generating correction data for correcting the errors,

whereby the errors in the corresponding first past positions of the detected events are corrected and the positions associated with the events are accurate.

18. The system in claim 17, wherein the events represent transactions of inventory items and comprise at least one of the following transactions:

picking up an inventory item and dropping off an inventory item.

19. The system in claim 17, wherein the position tracking system further comprises a reporting module connected to the error correction module for providing messages indicating the errors in the first past positions as stored in the data storage unit.