Method and apparatus for using unique landmarks to locate industrial vehicles at start-up

• US 9,206,023 B2
• Filed: 11/14/2013
• Issued: 12/08/2015
• Est. Priority Date: 08/26/2011
• Status: Active Grant

• Current Assignee: Crown Equipment Corporation
• Original Assignee: Crown Equipment Corporation
• Inventors: Wong, Lisa, Graham, Andrew Evan, Goode, Christopher W., Waltz, Lucas B.
• Primary Examiner(s): Jabr, Fadey
• Assistant Examiner(s): Mahne, Kevin P
• Application Number:
  US14/079,842
• Publication Number:
  US 20140058612A1
• Time in Patent Office: 754 Days
• Field of Search: None
• US Class Current: 1/1
• CPC Class Codes: B66F 9/063 Automatically guided
• CPC Class Codes: G01C 21/206 specially adapted for indoor navigation
• CPC Class Codes: G01S 17/08 for measuring distance only indirect measurement G01S17/46; active triangulation systems G01S17/48
• CPC Class Codes: G01S 17/86 Combinations of lidar systems with systems other than lidar, radar or sonar, e.g. with direction finders
• CPC Class Codes: G01S 17/875 for determining attitude
• CPC Class Codes: G01S 5/08 Position of single direction-finder fixed by determining direction of a plurality of spaced sources of known location
• CPC Class Codes: G01S 5/16 using electromagnetic waves other than radio waves
• CPC Class Codes: G05D 1/0234 using optical markers or beacons optical beacons per se G01S1/70
• CPC Class Codes: G05D 1/0274 using mapping information stored in a memory device navigation using map-matching G01C21/30
• CPC Class Codes: G06F 17/00 Digital computing or data processing equipment or methods, specially adapted for specific functions information retrieval, database structures or file system structures therefor G06F16/00
• CPC Class Codes: G07C 5/08 Registering or indicating performance data other than driving, working, idle, or waiting time, with or without registering driving, working, idle or waiting time

Abstract

A method and apparatus for using unique landmarks to position industrial vehicles during start-up. In one embodiment, a method of using pre-positioned objects as landmarks to operate an industrial vehicle is provided. The method comprises identifying a start-up scenario from sensor data, wherein the start-up scenario comprises a unique marker start-up or a pre-positioned object start-up. in response to the identified start-up scenario, either a unique marker or pre-positioned object is identified within a physical environment, wherein the pre-positioned object or unique marker corresponds with a sub-area of the physical environment. The industrial vehicle pose is determined in response to the identity of the pre-positioned object or unique marker and the industrial vehicle is operated based on the determined industrial vehicle pose.

Claims

1. A method of operating an industrial vehicle in a navigation system, wherein the method comprises:

providing the industrial vehicle, one or more sensors coupled to the industrial vehicle, a mobile computer operably coupled to the industrial vehicle, and an environment based navigation module comprised in the mobile computer;

utilizing the mobile computer coupled to the industrial vehicle to process measurement data from the sensors, wherein the measurement data is indicative of the presence of pre-positioned objects or landmarks within a range of the sensors;

utilizing the mobile computer coupled to the industrial vehicle to determine initial pose prediction data for the industrial vehicle from the measurement data, wherein

the initial pose prediction data is sufficient to determine a sub-area of a physical environment in which the industrial vehicle is positioned, but

the initial pose prediction data is insufficient to determine a location of the industrial vehicle within the determined sub-area;

utilizing the mobile computer coupled to the industrial vehicle to select a sub-area of the physical environment based on the initial pose prediction data and obtain a sub-area map from an overview map of the physical environment based on the initial pose prediction data;

utilizing the mobile computer coupled to the industrial vehicle to refine the initial pose prediction data for the industrial vehicle using the sub-area map and features observable by the sensors from the selected sub-area to generate a new pose; and

utilizing the new pose, the sensors, and the environment based navigation module of the mobile computer to navigate the industrial vehicle through the physical environment.

2. A method as claimed in claim 1 wherein the selected sub-area comprises a block stacked area of the physical environment and method further comprises utilizing the mobile computer coupled to the industrial vehicle to develop a new start-up pose estimate by triggering a start-up task wherein:

the industrial vehicle is driven by the environment based navigation module of the mobile computer to scan a pre-positioned object in the block stacked area of the physical environment;

the pre-positioned object is uniquely identifiable through a feature that can be sensed by the sensors coupled to the industrial vehicle;

the mobile computer operably coupled to the industrial vehicle accesses the position of the pre-positioned object and uses the position to develop the new start-up pose estimate.

3. A method as claimed in claim 2 wherein the mobile computer coupled to the industrial vehicle accesses the position of the pre-positioned object from placed object data or by requesting a location of the pre-positioned object from an system external to the mobile computer.

4. A method as claimed in claim 1 wherein the overview map comprises a plurality of sub-area maps, the initial pose prediction data comprises relative positions of features sensed using the sensors, and the method comprises:

utilizing the mobile computer coupled to the industrial vehicle to determine if the industrial vehicle is in a particular sub-area of the physical environment by evaluating relative positions of sensed features against the sub-area maps; and

utilizing the sub-area map and the environment based navigation module of the mobile computer to navigate the industrial vehicle to a location where the initial pose prediction data is refined by the mobile computer coupled to the industrial vehicle.

5. A method as claimed in claim 4 wherein the location to which the industrial vehicle is navigated to refine the initial pose prediction data comprises a pre-positioned object.

6. A method as claimed in claim 4 wherein the location to which the industrial vehicle is navigated to refine the initial pose prediction data comprises an end of a row of block stacked products.

7. A method as claimed in claim 1 wherein:

the overview map comprises a model of block-stacked object rows data;

the initial pose prediction data comprises relative positions of features sensed using the sensors; and

the method comprises utilizing the mobile computer coupled to the industrial vehicle to determine if the industrial vehicle is in a sub-area corresponding to blocked-stacked object rows by evaluating the relative positions of the sensed features against the model of block-stacked object rows data.

8. A method as claimed in claim 7 wherein:

the initial pose prediction data is insufficient to determine in which of a plurality of rows of products the industrial vehicle is positioned; and

the method comprises utilizing the mobile computer coupled to the industrial vehicle to select a candidate row of blocked stacked product in the sub-area using pre-positioned product information that matches feature information received from the sensors.

9. A method as claimed in claim 8 wherein the candidate row may be inaccurate and the method further comprises utilizing the environment based navigation module of the mobile computer to navigate the industrial vehicle to a location where the initial pose prediction data is refined by the mobile computer coupled to the industrial vehicle.

10. A method as claimed in claim 9 wherein the location to which the industrial vehicle is navigated to refine the initial pose prediction data comprises a pre-positioned object or an end of a row of block stacked products.

11. A method as claimed in claim 1 wherein:

the overview map comprises a racking aisle model provided in data of the overview map;

the initial pose prediction data comprises relative positions of features sensed using the sensors; and

the method comprises utilizing the mobile computer coupled to the industrial vehicle to determine if the industrial vehicle is in a sub-area corresponding to a racking aisle by matching relative positions of the sensed features against the racking aisle model.

12. A method as claimed in claim 1 wherein the observable features are selected from landmarks comprising walls, rack protectors, racking legs, placed unique navigational markers, or combinations thereof.

13. A method as claimed in claim 1 wherein:

the observable features comprise pre-positioned objects; and

the mobile computer coupled to the industrial vehicle accesses a position of the pre-positioned object from placed object data or by requesting a location of the pre-positioned object from an system external to the mobile computer.

14. A method as claimed in claim 13 wherein the placed object data comprises object identity and object pose.

15. A method as claimed in claim 13 wherein:

the pre-positioned object comprises a pallet or product load;

the mobile computer coupled to the industrial vehicle accesses a position of the pallet or product load by scanning, picking up, or otherwise engaging the pallet or product load and retrieving a known location of the pallet or product load from a warehouse management system database.

16. A method as claimed in claim 13 wherein:

the sensors of the industrial vehicle comprise a laser scanner;

the pre-positioned object comprises a barcode; and

the method comprises scanning the barcode with the laser scanner to identify the pre-positioned object.

17. A method as claimed in claim 13 wherein:

the sensors of the industrial vehicle comprise a camera configured to capture images of the pre-positioned objects;

the pre-positioned object comprises a label; and

the method comprises identifying the pre-positioned object from the label captured in an image of the pre-position object.

18. A method as claimed in claim 17 wherein the label is a barcode.

19. A method as claimed in claim 13 wherein:

the sensors of the industrial vehicle comprise an RFID tag reader;

the pre-positioned object comprises an RFID tag; and

the method comprises interrogating the RFID tag with the RFID tag reader to identify the pre-positioned object.

20. A method as claimed in claim 13 wherein:

the sensors comprise an camera configured to capture images of the pre-positioned objects; and

the method comprises utilizing the mobile computer of the industrial vehicle to identify the pre-positioned object from an image of a pre-positioned object captured by the camera.

21. A method as claimed in claim 13 wherein the pre-positioned object is identified by a specific shape or unique feature sensed by the sensors of the industrial vehicle.

22. A method as claimed in claim 1 wherein the sensors coupled to the industrial vehicle comprise a laser scanner and a camera.

23. A method as claimed in claim 1 wherein the method comprises starting-up the industrial vehicle such that the industrial vehicle has no information about its pose or its location relative to particular sub-areas of the environment prior to utilizing the mobile computer to process measurement data from the sensors.

24. A method as claimed in claim 1 wherein the sub-area map comprises one or more features and prior to refining the initial pose prediction data of the industrial vehicle, the method comprises eliminating features from the sub-area map which are not observable to the sensors.

25. A method as claimed in claim 1 wherein the features observable by the sensors comprise a plurality of beacons arranged in a known and unique constellation.

26. A method as claimed in claim 1 wherein the features observable by the sensors comprise unique navigational markers coupled to racking protectors at an end of the row of blocked stacked products.

27. A method as claimed in claim 1 wherein:

the overview map comprises positions of racking legs;

the initial pose prediction data comprises relative positions of features sensed using the sensors; and

the method comprises utilizing the mobile computer coupled to the industrial vehicle to determine if the industrial vehicle is in a sub-area corresponding to a racking aisle by matching the relative positions of the pre-positioned objects and racking legs sensed using the sensors against the positions of racking legs from the overview map.

28. A method of operating an industrial vehicle in a navigation system, wherein the method comprises:

providing the industrial vehicle, one or more sensors coupled to the industrial vehicle, a mobile computer operably coupled to the industrial vehicle, wherein the mobile computer comprises an environment based navigation module and an environment based navigation module comprised in the mobile computer;

utilizing the mobile computer coupled to the industrial vehicle to process measurement data from the sensors, wherein the measurement data is indicative of the presence of at least one pre-positioned object within a range of the sensors;

utilizing the mobile computer coupled to the industrial vehicle to develop an initial pose estimate, wherein

the initial pose estimate is sufficient to determine a sub-area of a physical environment in which the industrial vehicle is positioned, but

the initial pose estimate insufficient to determine a location of the industrial vehicle within the determined sub-area;

utilizing the mobile computer coupled to the industrial vehicle to select a sub-area based on the initial pose estimate and obtain a sub-area map from an overview map of the environment based on the initial pose estimate;

utilizing the sub-area map and data from the sensors coupled to the industrial vehicle to navigate the industrial vehicle to the pre-positioned object;

accessing a position of the pre-positioned object from placed object data associated with the pre-positioned object or from a warehouse management system in communication with the mobile computer;

developing a new pose estimate for the industrial vehicle using the accessed position of the pre-positioned object; and

utilizing the new pose estimate, data from the sensors, and the environment based navigation module of the mobile computer to navigate the industrial vehicle through the physical environment.

29. A method as claimed in claim 28 wherein:

the measurement data processed after starting-up the industrial vehicle comprises a plurality of pre-positioned objects; and

the environment based navigation module obtains position data for the pre-positioned objects from a map manager in communication with the mobile computer.

30. A method of generating a pose of an industrial vehicle prior to navigation, wherein the method comprises:

providing the industrial vehicle, one or more sensors coupled to the industrial vehicle, a mobile computer operably coupled to the industrial vehicle, and an environment based navigation module comprised in the mobile computer,

utilizing the mobile computer coupled to the industrial vehicle to process measurement data of the surrounding physical environment within a range of the sensors;

utilizing the mobile computer coupled to the industrial vehicle to determine initial pose prediction data for the industrial vehicle from the measurement data, wherein

the initial pose prediction data is sufficient to determine a sub-area of a physical environment in which the industrial vehicle is positioned, but

the initial pose prediction data is insufficient to determine a location of the industrial vehicle within the determined sub-area,

utilizing the mobile computer coupled to the industrial vehicle to select a sub-area based on the initial pose prediction data and obtain a sub-area map from an overview map of the physical environment based on the initial pose prediction data; and

utilizing the sub-area map, data from the sensors coupled to the industrial vehicle, and the environment based navigation module of the mobile computer to drive the industrial vehicle to a pre-positioned object;

scanning the pre-positioned object with the sensors;

accessing a position of the pre-positioned object from placed object data associated with the pre-positioned object or from a warehouse management system in communication with the mobile computer;

generating a new pose of the industrial vehicle by utilizing the mobile computer coupled to the industrial vehicle to refine the initial pose prediction data for the industrial vehicle using the sub-area map and the accessed position of the pre-positioned object; and

wherein the industrial vehicle does not navigate the physical environment until the new pose is generated.