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Title:
AUTONOMOUS DRONE INVENTORY OF PALLETED COLLECTIONS PLACED WITHIN PALLET BAYS OF AN INDOOR WAREHOUSE
Document Type and Number:
WIPO Patent Application WO/2022/132025
Kind Code:
A1
Abstract:
A system (1-00) or method for autonomous drone inventory of palleted collections (30) of inventory items placed within pallet bays (32) of multi-tiered racks (3-00) of an indoor warehouse. A navigation module is configured to store a programmable flight path (62A to 62E) passing alongside a pre-selection of pallet bays (32), navigate flight of an electric drone (10) along the programmable flight path (62A to 62E), during the flight along the programmable flight path (62A to 62E) capture a stream of images (33) of pallet labels (31) placed on the palleted collections (30), and associate each image with a location determined from the location markers (61). A recognition processor (23) is configured to recognize a pallet identifier (25A) on each of the pallet labels (31) captured within the stream of images (33) and link the pallet identifier (25A) to one of the pallet bays (32).

Inventors:
YAP CHIN KOK (SG)
YEO WEN DA (SG)
SUNDAR GOVIND (SG)
YAP LI SHENG (SG)
Application Number:
PCT/SG2020/050743
Publication Date:
June 23, 2022
Filing Date:
December 14, 2020
Export Citation:
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Assignee:
YCH GROUP PTE LTD (SG)
International Classes:
B64C39/02; G05D1/10; G06Q10/08; G06Q50/28; B64D47/08; G01C21/00; G06K9/00
Domestic Patent References:
WO2018057629A12018-03-29
Foreign References:
US20190062055A12019-02-28
US20180094935A12018-04-05
Attorney, Agent or Firm:
YUSARN AUDREY (SG)
Download PDF:
Claims:
CLAIMS

1. An autonomous drone inventory system for an indoor warehouse with a plurality of location markers, the indoor warehouse storing a plurality of palleted collections of inventory items on multi-tiered racks, each palleted collection including a pallet label displaying a pallet identifier, each palleted collection located in a pallet bay associated with a bay identifier, each pallet bay locatable by at least one of a plurality of location markers mounted in the indoor warehouse, the system comprising:

(a) an electric drone including a propulsion system, a directional camera, and a data output;

(b) a navigation module configured to:

(i) store a three-dimensional map of the multi-tiered racks and a programmable flight path configured to pass alongside a pre-selection of pallet bays on the multi-tiered racks;

(ii) navigate the electric drone along the programmable flight path;

(iii) aim the directional camera toward the pallet label of each palleted collection located along the programmable flight path, wherein the directional camera captures a stream of images during the programmable flight path; and

(iv) associate each of the images in the stream of images with an image location and an image timestamp;

(c) a computing device with a data input, a user interface, and a recognition processor;

(i) wherein the data input is configured for data communication with the data output of the electric drone to receive the stream of images captured by the directional camera of the electric drone along the programmable flight path;

(ii) wherein the recognition processor is configured to offload or execute a recognition process, the recognition process including the steps of:

(1) recognizing each pallet identifier from the pallet labels captured within the stream of images;

(2) identifying the bay identifier of each pallet identifier captured within the stream of images based upon the image location associated with at least one of the images employed to recognize the pallet identifier; and

(3) creating and storing a pallet location record within a flight inventory database for each pallet identifier recognized within the stream of images; and

25 (iii) wherein each pallet location record memorializes, for each pallet identifier identified by the recognition processor from the stream of images during a programmable flight path:

(1) the pallet identifier identified by the recognition processor;

(2) the bay identifier for the pallet bay associated with the pallet identifier; and

(3) the image timestamp of at least one of the images employed to recognize the pallet identifier;

(d) a server with a warehouse database,

(i) wherein the warehouse database includes:

(1) a plurality of inventory records, each inventory record including a linked inventory identifier and an inventory description; and

(2) a plurality of pallet content records, each pallet content record including a linked pallet identifier and a list of inventory identifiers associated with the linked pallet identifier; and

(ii) wherein the server is configured to:

(1) download or link to each pallet location record of the flight inventory database;

(2) link each pallet location record with one of the pallet content records via a first cross reference between:

(a) the pallet identifier in the pallet location record of the flight inventory database; and

(b) the linked pallet identifier in one of the pallet content records of the warehouse database; and

(3) link each pallet content record with at least one of the inventory records via a second cross reference between:

(a) each of the inventory identifiers listed in each pallet content record of the warehouse database; and

(b) the linked inventory identifier of each of the inventory records of the warehouse database; and (e) a reporting module configured to:

(i) determine the bay identifier associated with each inventory identifier via the first cross reference;

(ii) determine the inventory description associated with each linked inventory identifier via the second cross reference; and

(iii) output an inventory location report listing each inventory identifier linked with:

(1) the bay identifier associated with the inventory identifier as determined by the first cross reference; and

(2) the inventory description associated with the linked inventory identifier as determined by the second cross reference.

2. The system of claim 1,

(a) wherein each pallet content record includes a current location identifier inputted into the warehouse database through a warehouse inventory system; and

(b) wherein the reporting module is further configured to:

(i) check for any errors between:

(1) the bay identifier of each palleted collection in the pallet location records of the flight inventory database; and

(2) the current location identifier of each palleted collection in the pallet content records of the warehouse database; and

(ii) flag each error in the inventory location report.

3. The system of claim 1,

(a) wherein each pallet label includes:

(i) a QR code design identifying a first pallet identifier, the QR code design having side dimensions in the range of 10 to 30 centimeters;

(ii) a linear barcode design identifying a second pallet identifier; and

(iii) an RFID tag identifying a third pallet identifier; and

(b) wherein associations between the first pallet identifier, the second pallet identifier, and the third pallet identifier are stored in at least one of:

(i) the flight inventory database; and

(ii) the warehouse database.

4. The system of claim 1, wherein each location marker mounted in the indoor warehouse identifies at least one of a launch point, an aisle, a tier, a column, and a pallet bay.

5. The system of claim 1, wherein location markers mounted in the indoor warehouse include at least one of:

(a) a launch point marker;

(b) a plurality of near field communication beacons identifiable by a near field communication sensor mounted on the electric drone;

(c) a plurality of visual location labels,

(i) wherein the visual location labels include at least one of a QR label, and an ArUco label, and a linear barcode label; and

(ii) wherein the navigation module is configured to identify each visual location label in at least one of:

(1) the stream of images from the directional camera; and

(2) an alternative stream of images captured by a navigational camera mounted on the electric drone; and

(d) a plurality of warehouse fixtures identified on the three-dimensional map of the multitiered racks, wherein the navigation module is configured to identify each warehouse fixture in at least one of:

(i) the stream of images from the directional camera;

(ii) the alternative stream of images from the navigational camera; and

(iii) a LIDAR sensor data stream from a LIDAR sensor mounted on the electric drone.

6. The system of claim 1,

(a) wherein the stream of images captured by the directional camera is downloaded in real time from the electric drone to the computing device via a data pathway during navigation of the electric drone through the programmable flight path;

(b) wherein the data pathway passes:

(i) wirelessly from the data output of the electric drone to a router in the indoor warehouse; and

(ii) from the router to the data input of the computing device; and

(c) wherein the computing device is configured to display the stream of images on the user interface of the computing device in real time.

28

7. The system of claim 1,

(a) wherein an alternate stream of images is captured by a navigational camera mounted on the electric drone and downloaded in real time from the electric drone to the computing device via a data pathway during navigation of the electric drone through the programmable flight path;

(b) wherein the data pathway passes:

(i) wirelessly from the data output of the electric drone to a router in the indoor warehouse; and

(ii) from the router to the data input of the computing device; and

(c) wherein the computing device is configured to display the alternate stream of images on the user interface of the computing device in real time.

8. The system of claim 1,

(a) wherein each programmable flight path commences and finishes at a dedicated staging area with a charging dock; and

(b) wherein each navigation of the electric drone through the programmable flight path to capture the stream of images is pre-scheduled by the navigation module.

9. The system of claim 1, wherein software and hardware of the navigation module is stored or mounted within at least one of:

(a) the electric drone;

(b) the computing device; and

(c) the server.

10. The system of claim 1,

(a) wherein the recognition processor of the computing device is configured to direct the upload of the stream of images to the server;

(b) wherein the recognition processor offloads the recognition process to the server; and

(c) wherein the flight inventory database is located on the server.

11. A computer-implemented method for conducting an autonomous drone inventory of an indoor warehouse with a plurality of location markers, the indoor warehouse storing a plurality of palleted collections of inventory items on multi-tiered racks, each palleted collection including a pallet label displaying a pallet identifier, each palleted collection

29 located in a pallet bay associated with a bay identifier, each pallet bay locatable by at least one of a plurality of location markers mounted in the indoor warehouse, the method comprising the steps of

(a) maintaining an electric drone including a propulsion system, a directional camera, and a data output;

(b) configuring a navigation module to:

(i) store a three-dimensional map of the multi-tiered racks and a programmable flight path configured to pass alongside a pre-selection of pallet bays on the multi-tiered racks;

(ii) navigate the electric drone along the programmable flight path;

(iii) aim the directional camera toward the pallet label of each palleted collection located along the programmable flight path, wherein the directional camera captures a stream of images during the programmable flight path; and

(iv) associate each of the images in the stream of images with an image location and an image timestamp;

(c) maintaining a computing device with a data input, a user interface, and a recognition processor;

(i) wherein the data input is configured for data communication with the data output of the electric drone to receive the stream of images captured by the directional camera of the electric drone along the programmable flight path;

(ii) wherein the recognition processor is configured to offload or execute a recognition process, the recognition process including the steps of

(1) recognizing each pallet identifier from the pallet labels captured within the stream of images;

(2) identifying the bay identifier of each pallet identifier captured within the stream of images based upon the image location associated with at least one of the images employed to recognize the pallet identifier; and

(3) creating and storing a pallet location record within a flight inventory database for each pallet identifier recognized within the stream of images; and

(iii) wherein each pallet location record memorializes, for each pallet identifier identified by the recognition processor from the stream of images during a programmable flight path:

(1) the pallet identifier identified by the recognition processor;

30 (2) the bay identifier for the pallet bay associated with the pallet identifier; and

(3) the image timestamp of at least one of the images employed to recognize the pallet identifier;

(d) maintaining a warehouse database including:

(i) a plurality of inventory records, each inventory record including a linked inventory identifier and an inventory description; and

(ii) a plurality of pallet content records, each pallet content record including a linked pallet identifier and a list of inventory identifiers associated with the linked pallet identifier;

(e) downloading or linking to each pallet location record of the flight inventory database;

(f) linking each pallet location record with one of the pallet content records via a first cross reference between:

(i) the pallet identifier in the pallet location record of the flight inventory database; and

(ii) the linked pallet identifier in one of the pallet content records of the warehouse database;

(g) linking each pallet content record with at least one of the inventory records via a second cross reference between:

(i) each of the inventory identifiers listed in each pallet content record of the warehouse database; and

(ii) the linked inventory identifier of each of the inventory records of the warehouse database;

(h) determining the bay identifier associated with each inventory identifier via the first cross reference;

(i) determining the inventory description associated with each linked inventory identifier via the second cross reference; and

(j) outputting an inventory location report listing each inventory identifier linked with:

(i) the bay identifier associated with the inventory identifier as determined by the first cross reference; and

(ii) the inventory description associated with the linked inventory identifier as determined by the second cross reference.

31

12. The system of claim 11,

(a) wherein each pallet content record includes a current location identifier inputted into the warehouse database through a warehouse inventory system; and

(b) wherein the reporting module is further configured to:

(i) check for any errors between:

(1) the bay identifier of each palleted collection in the pallet location records of the flight inventory database; and

(2) the current location identifier of each palleted collection in the pallet content records of the warehouse database; and

(ii) flag each error in the inventory location report.

13. The system of claim 11,

(a) wherein each pallet label includes:

(i) a QR code design identifying a first pallet identifier, the QR code design having side dimensions in the range of 10 to 30 centimeters;

(ii) a linear barcode design identifying a second pallet identifier; and

(iii) an RFID tag identifying a third pallet identifier; and

(b) wherein associations between the first pallet identifier, the second pallet identifier, and the third pallet identifier are stored in at least one of:

(i) the flight inventory database; and

(ii) the warehouse database.

14. The method of claim 11, wherein each location marker mounted in the indoor warehouse identifies at least one of a launch point, an aisle, a tier, a column, and a pallet bay.

15. The method of claim 11, wherein location markers mounted in the indoor warehouse include at least one of:

(a) a launch point marker;

(b) a plurality of near field communication beacons identifiable by a near field communication sensor mounted on the electric drone;

(c) a plurality of visual location labels,

(i) wherein the visual location labels include at least one of a QR label, and an ArUco label, and a linear barcode label; and

32 (ii) wherein the navigation module is configured to identify each visual location label in at least one of

(1) the stream of images from the directional camera; and

(2) an alternative stream of images captured by a navigational camera mounted on the electric drone; and

(d) a plurality of warehouse fixtures identified on the three-dimensional map of the multitiered racks, wherein the navigation module is configured to identify each warehouse fixture in at least one of

(i) the stream of images from the directional camera;

(ii) the alternative stream of images from the navigational camera; and

(iii) a LIDAR sensor data stream from a LIDAR sensor mounted on the electric drone.

16. The method of claim 11,

(a) wherein the stream of images captured by the directional camera is downloaded in real time from the electric drone to the computing device via a data pathway during navigation of the electric drone through the programmable flight path;

(b) wherein the data pathway passes:

(i) wirelessly from the data output of the electric drone to a router in the indoor warehouse; and

(ii) from the router to the data input of the computing device; and

(c) wherein the computing device is configured to display the stream of images on the user interface of the computing device in real time.

17. The method of claim 11,

(a) wherein an alternate stream of images is captured by a navigational camera mounted on the electric drone and downloaded in real time from the electric drone to the computing device via a data pathway during navigation of the electric drone through the programmable flight path;

(b) wherein the data pathway passes:

(i) wirelessly from the data output of the electric drone to a router in the indoor warehouse; and

(ii) from the router to the data input of the computing device; and

(c) wherein the computing device is configured to display the alternate stream of images on the user interface of the computing device in real time.

33

18. The method of claim 11,

(a) wherein each programmable flight path commences and finishes at a dedicated staging area with a charging dock; and (b) wherein each navigation of the electric drone through the programmable flight path to capture the stream of images is pre-scheduled by the navigation module.

19. The method of claim 11, wherein software and hardware of the navigation module is stored or mounted within at least one of: (a) the electric drone;

(b) the computing device; and

(c) a server.

20. The method of claim 11, (a) wherein the recognition processor of the computing device is configured to direct the upload of the stream of images to a server;

(b) wherein the recognition processor offloads the recognition process to the server; and

(c) wherein the flight inventory database is located on the server.

34

Description:
AUTONOMOUS DRONE INVENTORY OF PALLETED COLLECTIONS

PLACED WITHIN PALLET BAYS OF AN INDOOR WAREHOUSE

TECHNICAL CONTRIBUTION

The present disclosure relates to inventory systems for indoor warehouses. More particularly, the present disclosure relates to autonomous drone inventory of palleted collections placed within pallet bays of an indoor warehouse.

BACKGROUND

Indoor warehouses organize multiple inventory items within palleted collections for storage. The contents of each palleted collection is recorded into a warehouse database, with pallet content records listing the inventory identifiers of the individual inventory items assembled into each palleted collection. The palleted collection are typically given a physical pallet label representing a pallet identifier. The pallet identifier is printed as a pallet label in a machine readable format such as a QR code or a linear barcode. Storage locations within the warehouse are identified using location labels representing location identifiers (also in a machine readable format such as a QR code or a linear barcode).

Warehouse inventory systems (employing barcode readers) are used by warehouse staff to memorialize the storage locations of the palleted items. Each time the palleted collection is moved to a new storage location, a barcode reader in data communication with the warehouse database is used by warehouse staff to update the warehouse database by scanning in both a current location identifier of the new storage location and the pallet identifier of the palleted collection. When a palleted collection arriving at a shipping dock is moved to a pallet bay on a shelf of a multi-tiered rack, a first record memorializing the move will be entered into the warehouse database using the warehouse inventory system. When the palleted collection is moved from the pallet bay to a different location (such as back to the shipping dock), a second record memorializing this second move will be entered into the warehouse database. In this manner, the location of each inventory item within the indoor warehouse is known at all times. To maintain the integrity of the warehouse database records, supplemental inventory checks (or inventory audits) are periodically performed. These supplemental inventory checks are often performed by warehouse staff via a time-intensive manual inspection of the palleted collections within the indoor warehouse. Excessive height of the multi-tiered racks, narrow aisles, and ongoing activity of forklifts within the indoor warehouse can make these supplemental inventory checks both time-consuming and potentially dangerous.

Recent technology advances in electric drone technology has enabled alternative methods of performing the supplemental inventory checks within indoor warehouses. One example reference is PCT Patent Application WO2015035428 with international filing date 26 June 2014 and entitled “AIRBORNE SCANNING SYSTEM AND METHOD”. As described in this application, the electric drone is flown by a human pilot to a first pallet bay. Hovering before the first pallet bay, the electric drone reads the pallet label of the palleted collection and transmits the pallet identifier of the pallet label back to a computing device (or base station) for validation. Upon validation of the pallet identifier, the base station updates the warehouse database and directs the electric drone to the next pallet bay to repeat the process. In essence, the electric drone replaces the physical movements of a warehouse staff worker with the physical movements of an electric drone.

Supplemental inventory processes performed by electric drones in the prior art are ineffective due to their excessive need for human guidance and slow progress (stopping and hovering at each pallet bay) through the indoor warehouse. Electric drones have a limited flight time, often in the range of only ten to twenty minutes. Stopping and hovering at each pallet bay and relying on skilled human piloting of the electric drones limits the effectiveness of the prior art. The prior art poses difficulties in implementation of supplemental inventories, given the 24/7 activity within indoor warehouses and the ever increasing size of multi-tiered indoor warehouses. What is needed is a system and method for performing an autonomous drone inventory using a preset programmable flight path and a barcode reading capability (and database integration protocol) that does not require discontinuous movement of the electric drone in its path through the indoor warehouse. In essence, a system and method is needed wherein an electric drone can conduct an unfettered fly through an indoor warehouse along the tiers of multi-tiered racks to collect pallet identifier information in a short timeframe that does not significantly interfere with the ongoing operations of the indoor warehouse.

SUMMARY

In its most general form, the invention is a system or method for autonomous drone inventory of palleted collections of inventory items placed within pallet bays of multitiered racks of an indoor warehouse. A navigation module is configured to store a programmable flight path passing alongside a pre-selection of pallet bays, navigate flight of an electric drone along the programmable flight path, during the flight along the programmable flight path capture a stream of images of pallet labels placed on the palleted collections, and associate each image with a location determined from the location markers. A recognition processor is configured to recognize a pallet identifier on each of the pallet labels captured within the stream of images and link the pallet identifier to one of the pallet bays. A reporting module outputs an inventory location report identifying the pallet bay storing each inventory item.

A first embodiment of the invention is an autonomous drone inventory system for an indoor warehouse with a plurality of location markers, the indoor warehouse storing a plurality of palleted collections of inventory items on multi-tiered racks, each palleted collection including a pallet label displaying a pallet identifier, each palleted collection located in a pallet bay associated with a bay identifier, each pallet bay locatable by at least one of a plurality of location markers mounted in the indoor warehouse, the system comprising: (a) an electric drone including a propulsion system, a directional camera, and a data output; (b) a navigation module; (c) a computing device with a data input, a user interface, and a recognition processor; (d) a server with a warehouse database; and (e) a reporting module. The navigation module is configured to: (i) store a three- dimensional map of the multi-tiered racks and a programmable flight path configured to pass alongside a pre-selection of pallet bays on the multi-tiered racks; (ii) navigate the electric drone along the programmable flight path; (iii) aim the directional camera toward the pallet label of each palleted collection located along the programmable flight path, wherein the directional camera captures a stream of images during the programmable flight path; and (iv) associate each of the images in the stream of images with an image location and an image timestamp. The data input is configured for data communication with the data output of the electric drone to receive the stream of images captured by the directional camera of the electric drone along the programmable flight path. The recognition processor is configured to offload or execute a recognition process, the recognition process including the steps of: (1) recognizing each pallet identifier from the pallet labels captured within the stream of images; (2) identifying the bay identifier of each pallet identifier captured within the stream of images based upon the image location associated with at least one of the images employed to recognize the pallet identifier; and (3) creating and storing a pallet location record within a flight inventory database for each pallet identifier recognized within the stream of images. Each pallet location record memorializes, for each pallet identifier identified by the recognition processor from the stream of images during a programmable flight path: (1) the pallet identifier identified by the recognition processor; (2) the bay identifier for the pallet bay associated with the pallet identifier; and (3) the image timestamp of at least one of the images employed to recognize the pallet identifier. The warehouse database includes: (1) a plurality of inventory records, each inventory record including a linked inventory identifier and an inventory description; and (2) a plurality of pallet content records, each pallet content record including a linked pallet identifier and a list of inventory identifiers associated with the linked pallet identifier. The server is configured to: (1) download or link to each pallet location record of the flight inventory database; (2) link each pallet location record with one of the pallet content records via a first cross reference; (3) link each pallet content record with at least one of the inventory records via a second cross reference. The first cross reference is between: (a) the pallet identifier in the pallet location record of the flight inventory database; and (b) the linked pallet identifier in one of the pallet content records of the warehouse database. The second cross reference is between: (a) each of the inventory identifiers listed in each pallet content record of the warehouse database; and (b) the linked inventory identifier of each of the inventory records of the warehouse database. The reporting module is configured to: (i) determine the bay identifier associated with each inventory identifier via the first cross reference; (ii) determine the inventory description associated with each linked inventory identifier via the second cross reference; and (iii) output an inventory location report. The inventory location report lists each inventory identifier linked with: (1) the bay identifier associated with the inventory identifier as determined by the first cross reference; and (2) the inventory description associated with the linked inventory identifier as determined by the second cross reference.

A second embodiment of the invention is computer-implemented method for conducting an autonomous drone inventory of an indoor warehouse with a plurality of location markers, the indoor warehouse storing a plurality of palleted collections of inventory items on multi-tiered racks, each palleted collection including a pallet label displaying a pallet identifier, each palleted collection located in a pallet bay associated with a bay identifier, each pallet bay locatable by at least one of a plurality of location markers mounted in the indoor warehouse. The method comprising the steps of: (a) maintaining an electric drone including a propulsion system, a directional camera, and a data output; (b) configuring a navigation module; (c) maintaining a computing device with a data input, a user interface, and a recognition processor; (d) maintaining a warehouse database; (e) downloading or linking to each pallet location record of the flight inventory database; (f) linking each pallet location record with one of the pallet content records via a first cross reference; (g) linking each pallet content record with at least one of the inventory records via a second cross reference; (h) determining the bay identifier associated with each inventory identifier via the first cross reference; (i) determining the inventory description associated with each linked inventory identifier via the second cross reference; and (j) outputting an inventory location report. The navigation module is configure to: (i) store a three-dimensional map of the multi-tiered racks and a programmable flight path configured to pass alongside a pre-selection of pallet bays on the multi-tiered racks; (ii) navigate the electric drone along the programmable flight path; (iii) aim the directional camera toward the pallet label of each palleted collection located along the programmable flight path, wherein the directional camera captures a stream of images during the programmable flight path; and (iv) associate each of the images in the stream of images with an image location and an image timestamp. The data input is configured for data communication with the data output of the electric drone to receive the stream of images captured by the directional camera of the electric drone along the programmable flight path. The recognition processor is configured to offload or execute a recognition process, the recognition process including the steps of (1) recognizing each pallet identifier from the pallet labels captured within the stream of images; (2) identifying the bay identifier of each pallet identifier captured within the stream of images based upon the image location associated with at least one of the images employed to recognize the pallet identifier; and (3) creating and storing a pallet location record within a flight inventory database for each pallet identifier recognized within the stream of images. Each pallet location record memorializes, for each pallet identifier identified by the recognition processor from the stream of images during a programmable flight path: (1) the pallet identifier identified by the recognition processor; (2) the bay identifier for the pallet bay associated with the pallet identifier; and (3) the image timestamp of at least one of the images employed to recognize the pallet identifier. The warehouse database includes: (i) a plurality of inventory records, each inventory record including a linked inventory identifier and an inventory description; and (ii) a plurality of pallet content records, each pallet content record including a linked pallet identifier and a list of inventory identifiers associated with the linked pallet identifier. The first cross reference is between: (i) the pallet identifier in the pallet location record of the flight inventory database; and (ii) the linked pallet identifier in one of the pallet content records of the warehouse database. The second cross reference is between: (i) each of the inventory identifiers listed in each pallet content record of the warehouse database; and (ii) the linked inventory identifier of each of the inventory records of the warehouse database. The inventory location report lists each inventory identifier linked with: (i) the bay identifier associated with the inventory identifier as determined by the first cross reference; and (ii) the inventory description associated with the linked inventory identifier as determined by the second cross reference. Technical objects of the invention include: (a) pre-programming the flight path of the electric drone through the indoor warehouse using location markers mounted in the indoor warehouse for navigation of the electric drone; (b) collecting a stream of images of pallet labels and location information during a continuous fly through along the tiers of the multi-tiered racks, unfettered by stop and hover requirements; (c) performing a recognition processing step upon a stream of images taken by the electric drone without impact to the flight path or flight time of the electric drone; and (d) cross referencing flight inventory data records to warehouse database records to obtain the location of inventory items within the pallet bays of the multi-tiered racks.

BRIEF DESCRIPTION OF THE DRAWINGS

Embodiments of the present disclosure are described herein with reference to the drawings in which:

FIG. 1 is a block diagram representing an autonomous drone inventory system in an embodiment of the invention.

FIG. 2 is an illustration of the collection and processing of a stream of images of pallet labels in an embodiment of the invention.

FIG. 3 is an illustration of a programmable flight path navigated by an electric drone within a multi-tiered racks of an indoor warehouse using location markers in an embodiment of the invention.

FIG. 4 is a flowchart of the steps taken in an embodiment of the invention.

DETAILED DESCRIPTION

In the following detailed description, reference is made to the accompanying drawings, which form a part hereof. The illustrative embodiments described in the detailed description, drawings and claims are not meant to be limiting. Other embodiments can be utilized, and other changes can be made, without departing from the spirit or scope of the subject matter presented herein. Unless specified otherwise, the terms “comprising,” “comprise,” “including” and “include” used herein, and grammatical variants thereof, are intended to represent “open” or “inclusive” language such that they include recited elements but also permit inclusion of additional, un-recited elements.

As used herein, the software and hardware of a “computing device” may be implemented within a dedicated electric drone control unit, a smart phone, a tablet, a laptop, a single stand-alone computer, or a stand-alone server.

As used herein, a “user interface” may be implemented by a display monitor, a keyboard, a mouse, a touch screen, a touch pad, and/or similarly directed means. The user interface may be configured by a dedicated electric drone control unit, a smart phone, a tablet, a laptop, a single stand-alone computer, or a stand-alone server.

As used herein, the software and hardware of a “server” may be implemented within a single stand-alone computer, a stand-alone server, multiple dedicated servers, and/or a virtual server running on a larger network of servers and/or a cloud-based service.

As used herein, a “database” may store data to and access data from a single stand-alone computer, a laptop, a tablet, a data server, multiple dedicated data servers, a cloud-based service, and/or a virtual server running on a network of servers. As discussed in the description, the use of the term “database” indicate a collection of tables, records, and/or linkage information for the data records. As depicted in the description and figures, each database can be maintained separately and/or maintained collectively in a single database or through linkages to other database. The databases depicted in the description and figures can be on the same server or on separate servers. Data links between tables can be links in one database or links between separate databases. FIG. l is a block diagram representing the autonomous drone inventory system 1-00 in an embodiment of the invention. The data output 12 of an electric drone 10 is in data communication with a data input 21 of a computing device 20 through a router 41. As depicted in FIG. 1, the data output 12 and the data input 21 are both wireless transceivers. The computing device 20 is also in data communication with a server 50 via the router 41 and a network 40. The server 50 includes a warehouse database 51. The warehouse database 51 includes pallet content records 52 and inventory records 53. The computing device 20 includes a user interface 22, a recognition processor 23, and a flight inventory database. The electric drone 10 includes a directional camera 13 for capturing an image of a pallet label 31 placed on a palleted collection 30. The palleted collection 30 is located in a pallet bay 32.

While the data output 12 of the electric drone 10 depicted in FIG. 1 is a wireless transceiver, the invention can also use wired data exchange, such as with the electric drone 10 at its dedicated staging area during battery charging.

FIG. 2 is an illustration of the collection and processing of stream of images 33 of pallet labels 31 in an embodiment of the invention. As in FIG. 1, FIG. 2 depicts an electric drone 10 with a directional camera 13 capturing an image of a pallet label 31 placed on a palleted collection 30. The data output 12 of the electric drone 10 is configured to transfer a stream of images 33 of pallet labels 31 to a recognition processor 23. Information derived from the recognition processor 23 is organized in pallet location records of a flight inventory database 24. Each pallet location record includes a pallet identifier 25A, a bay identifier 25B, and an image timestamp 25C. A warehouse database

51 includes pallet content records 52 and inventory records 53. The pallet content records

52 each include a linked pallet identifier 52A, a list of inventory identifiers 52B, and a current location identifier 52C. The inventory records 53 each include a linked inventory identifier 53A and an inventory description 53B.

In FIG. 2, each pallet location record 25 is linked to an associated pallet content record 52 via a first cross reference of: (i) the pallet identifier 25A of the pallet location record; and (ii) the linked pallet identifier 52A of the pallet content records 52. These two record fields are meant to both identify the same pallet collection. The pallet identifiers 25A and the linked pallet identifier 52A fields can be the same number or the same alphanumeric identifier. Alternatively, these fields can be linkable via an algorithm, a hash, an encryption process, a masked version of one field, or an additional record crossreferencing table for the two fields (hereafter “linkable equivalent”).

In FIG. 2, each pallet content record 52 is linked to an associated inventory record 53 via a second cross reference of (i) each of the inventory identifiers 52B listed in each pallet content record 52; and (ii) the linked inventory identifier 53A of the inventory records 53. These two record fields are meant to both identify the same inventory items. The listed inventory identifiers 52B and linked inventory identifiers 53A fields can use the same number or the same alphanumeric identifier. Alternatively, these fields can be linkable via a linkable equivalent (as defined above).

The data for the bay identifier 25B for a specific palleted collection 30 is taken from the results of the autonomous drone inventory. The data for the current location identifier 52C is created by a warehouse inventory system (such as via manual barcoding by warehouse staff) during operations within the indoor warehouse. These two identifiers can be identical or linkable equivalents. In the absence of errors by warehouse staff or the autonomous drone inventory system 1-00, the bay identifier 25B of the pallet location record 25 created from the results of an autonomous drone inventory for a specific palleted collection 30 should be the same (or linkable equivalent) of the current location identifier 52C of the pallet content records 52 for that specific palleted collection 30. E.g., following standard operating procedure, the warehouse staff should update the location of a palleted collection 30 in the warehouse database 51 using the warehouse inventory system each time the palleted collection 30 is moved. If the palleted collection 30 is correctly placed in a pallet bay 32 and the warehouse database 51 records are accurate, then the autonomous drone inventory results should confirm such. If there has been an incorrect placement of a palleted collection 30 or an incorrect warehouse database 51 record entry, then this error should likewise be evident from the autonomous drone inventory results. Hence, the autonomous drone inventory system 1-00 is useful as a supplemental inventory (or audit) of the warehouse database 51 records. As errors are found, the autonomous drone inventory results can be utilized to update warehouse operation procedures, faulty equipment, warehouse staff supervision, and/or warehouse staff training to minimize future errors. Hence initial implementation or usage of the invention is likely to result in a high error hit rate. As the errors discovered by the autonomous drone inventories and the causes of the errors are addressed, the hit rate of errors will fall off. Even with a low hit rate of errors, continued usage of the invention is helpful in providing ongoing oversight of the warehouse database 51 record accuracy and oversight of the proper execution of warehouse procedures by warehouse staff.

Note that frequent usage of the invention has the advantage of providing multiple autonomous drone inventory results which may be useful to determine the date and/or time when an error occurred (such as when a palleted collection 30 went missing or when its location was improperly recorded into the warehouse database 51 using the warehouse inventory system).

Electric drone 10 flight times must be minimized. Many jurisdictions required human observation of all indoor flights of electric drone 10 and the removal of human personnel from the areas under the flight path. Also the flight time of electric drones 10 is often only ten to twenty minutes in length (with battery recharge times often hours in length required there between). Smooth, orderly, predictable, and short time length flights of the electric drones 10 is therefore a critical feature of the invention.

The invention allows the recognition processing and assembly of flight inventory database 24 data records to be performed asynchronously from the capture of images of the pallet labels 31 by the electric drones 10. Errors between the bay identifier 25B and the current location identifier 52C for a palleted collection 30, for instance, will not slow or alter the programmable flight path (62A to 62E).

The database record-keeping tasks performed by the invention are intentionally separated from the electric drone’s 10 task of collecting the stream of images 33. This separation allows the programmable flight path (62A to 62E) and electric drone 10 components to be optimized for a rapid collection of quality images of the pallet labels 31. The supplemental inventory performed by the electric drones 10 is therefore not disruptive to the operations of the indoor warehouse.

The recognition processing in the invention is decoupled from the collection of the stream of images 33. Therefore slow data upload/download speeds or temporary glitches in the recognition processing are not factors that impact the success of the invention. A programmable flight path (62A to 62E), for instance, may be conducted once per day or several times per day without significant impact upon the operations of the indoor warehouse. Between each supplemental inventory, the system 1-00 is given more than sufficient time to perform recognition processing, database record updates, and reporting.

Furthermore, between each supplemental inventory performed by the electric drone 10, warehouse staff can address data inconsistencies flagged by the inventory location report. E.g., the warehouse staff may be directed to manually inspect palleted collections 30 flagged in the inventory location report to research the causes of the errors and correct those errors.

FIG. 3 is an illustration of a programmable flight path (62A to 62E) navigated by an electric drone 10 within a multi-tiered racks 3-00 of an indoor warehouse using location markers 61 in an embodiment of the invention. The multi-tiered rack 3-00 depicted in FIG. 3 includes three columns (columns A, B, and C) from left to right. The multi-tiered rack 3-00 depicted in FIG. 3 includes four tiers (tiers 1, 2, 3, and 4) from bottom to top. Location markers 61 are mounted on the multi-tiered racks 3-00 at locations notated by: (i) Al, A2, A3, and A4 in the first column; (ii) Bl, B2, B3, and B4 in the second column; and (iii) Cl, C2, and C3 in the third column. A programmable flight path (62A, 62B, 62C, 62D, and 62E) of the electric drone 10 is depicted as following right to left in along the topmost tier 4, then left to right along tier 3, then right to left along tier 2, and then left to right along bottom tier 1. The programmable flight path (62A to 62E) is intended to pass along each pallet label 31 placed on the palleted collections 30 located in the pallet bays 32. Note that as used in this patent specification, pallet bay 32 is a term used to indicate the location where a palleted collection 30 is placed on the multi-tiered racks 3-00. E.g., each pallet bay 32 is not necessarily afforded its own enclosed area in a column. Similar to the depiction in FIG. 3, a shelf area on a tier of one column may include two palleted collections 30 side by side. With variance in the sizing of inventory items and pallet configurations, the pallet bay 32 dimensions may vary within an indoor warehouse. In its most general form, the pallet bay 32 term is used to indicate a location where a palleted collection 30 can reside.

The location markers 61 in FIG. 3 are depicted as near field communication beacons. The location markers 61 can also be visual location labels (identified via the directional camera 13 and/or a navigational camera) or warehouse fixtures (identified via the directional camera 13, a navigational camera, and/or a LIDAR sensor). The location markers 61 can also be launch point markers on the floor of each aisle, each launch point marker indicating a launch point for the electric drone 10 in the aisle.

RFID tags are not suitable generally as location markers 61 in an indoor warehouse. The RFID reader protocols often include asynchronous reading of RFID tags located in an area. Also the metal in the multi-tiered racks 3-00 tends to interfere with the RF signals used for RFID tag identification.

The location markers 61 in FIG. 3 are organized by tiers and columns on the multi-tiered racks 3-00. The location markers 61 can also be mounted on other fixtures of the indoor warehouse and/or the floor of the indoor warehouse. The location markers 61 can also be mounted in grid organizations other than by aisle, tier, or column. Combinations of different types of locations can be used in unison also to identify a pallet bay 32.

The navigation module can also leverage the inertial navigation system of the electric drone 10 to assist with the determination of the electric drone’ s 10 x, y, and z axis location within the indoor warehouse. The inertial navigation system can include multi-axis accelerometers, magnetometers, and/or speed measuring devices. The electric drone 10, for instance, can be place at a launch point indicated by a launch point marker facing a predefined direction then directed though all, or a portion, of the programmable flight path (62A to 62E). Inertial navigation may be augmented by a laser scanner, LIDAR and/or height sensors mounted on the electric drone 10.

As depicted in FIG. 3, the system 1-00 is likely to include more pallet bays 32 than location markers 61. A location marker can be as simple as a launch point marker for a launch point of the electric drone 10, where the launch point marker can be, for instance, an “X” painted on the floor at one end of each aisle. To assist the inertial navigation system, the electric drone 10 can be pointed in an initial direction at launch.

GPS is not suitable for an indoor warehouse given the overhead roofing and multi-tiered racks 3-00 blocking or distorting the GPS satellite signals.

The programmable flight path (62A to 62E) can be updated based on the observed effectiveness and speed of previous flights. An effective programmable flight path (62A to 62E) will balance the benefits of a short flight time with the need to adequately gather quality images of the pallet labels 31 during flight. Thus in-field optimizations made by warehouse staff to the programmable flight path (62A to 62E) are likely to be productive. Possible adjustments to the programmable flight path (62A to 62E) could include: (i) reducing or increasing the distance between the directional camera 13 and the pallet labels 31 during flights; (ii) matching of the speed of the electric drone 10 across the tiers with the imaging capabilities of the directional camera 13; (iii) switching between use of real time data downloads during the flight of the stream of images 33 and alternatively employing post-flight data downloads of the stream of images 33 at the electric drone’s 10 dedicated staging area during battery charging; and/or (iv) reducing or increasing the length of the electric drone’s 10 flight to account for deterioration of battery storage or propulsion system 11 efficacy of the electric drone 10.

FIG. 4 is a flowchart of the steps taken in an embodiment of the invention. Steps 4-01 to 4-09 are listed below. 4-01 install location markers 61 within the indoor warehouse with sufficient density to permit identification of all pallet bays 32 using sensor information collected along the programmable flight path (62A to 62E) by location sensors mounted on the electric drone 10

4-02 create and store a three-dimensional map identifying each pallet bay 32 in the multi-tiered racks 3-00 and the location markers 61 installed within the indoor warehouse

4-03 create and store a programmable flight path (62A to 62E) for the electric drone 10 such that each pallet label 31 along the programmable flight path (62A to 62E) can be adequately captured by a directional camera 13 mounted on the electric drone 10 within the flight time of a single battery charge of the electric drone 10 4-04 pre-schedule the programmable flight path (62A to 62E) during a time the path of the programmable flight path (62A to 62E) is clear

4-05 on the user interface 22 of the computing device 20, monitor the flight of the electric drone 10 along the programmable flight path (62A to 62E) using a download of the stream of images 33 in real time

4-06 image process the stream of images 33 to identify each palleted collection 30 by its pallet label 31 captured in the images and link each pallet identifier 25A with its location in a pallet bay 32

4-07 return electric drone 10 to its dedicated staging area for battery charging, maintenance, and/or data download of stream of images 33

4-08 run an inventory location report from: (i) a first cross reference 54 of the pallet identifier 25A of the location records 25 in the flight inventory database 24 with the linked pallet identifier 52A of the pallet content records 52 of the warehouse database 51; and (ii) a second cross reference 55 to the inventory records 53 of a warehouse database 51

4-09 manually check errors flagged in the inventory location report using warehouse staff, update pallet content records 52 or inventory records 53 to reconcile any errors

As noted in Step 4-09 the results of the autonomous drone inventory are useful to identifying any errors in the pallet content records 52 or inventory records 53. One possible error is an absence of a specific palleted collection 30 at a specific pallet bay 32. E.g., the current location identifier 52C field of the associated pallet content record 52 indicates that the specific palleted collection 30 should be located at a specific pallet bay 32 but the autonomous drone inventory results do not locate it at that pallet bay 32 location. A second possible error would be the presence of a specific palleted collection

30 at a specific pallet bay 32 when the current location identifier indicates the specific palleted collection 30 should be located elsewhere.

In its most general form, the invention is a system 1-00 or method for autonomous drone inventory of palleted collections 30 of inventory items placed within pallet bays 32 of multi-tiered racks 3-00 of an indoor warehouse. A navigation module is configured to store a programmable flight path (62A to 62E) passing alongside a pre-selection of pallet bays 32, navigate flight of an electric drone 10 along the programmable flight path (62A to 62E), during the flight along the programmable flight path (62A to 62E) capture a stream of images 33 of pallet labels 31 placed on the palleted collections 30, and associate each image with a location determined from the location markers 61. A recognition processor 23 is configured to recognize a pallet identifier 25A on each of the pallet labels

31 captured within the stream of images 33 and link the pallet identifier 25A to one of the pallet bays 32. A reporting module outputs an inventory location report identifying the pallet bay 32 storing each inventory item.

A first embodiment of the invention is an autonomous drone inventory system 1-00 for an indoor warehouse with a plurality of location markers 61, the indoor warehouse storing a plurality of palleted collections 30 of inventory items on multi-tiered racks 3- 00, each palleted collection 30 including a pallet label 31 displaying a pallet identifier 25A, each palleted collection 30 located in a pallet bay 32 associated with a bay identifier 25B, each pallet bay 32 locatable by at least one of a plurality of location markers 61 mounted in the indoor warehouse, the system 1-00 comprising: (a) an electric drone 10 including a propulsion system 11, a directional camera 13, and a data output 12; (b) a navigation module; (c) a computing device 20 with a data input 21, a user interface 22, and a recognition processor 23; (d) a server 50 with a warehouse database 51; and (e) a reporting module. The navigation module is configured to: (i) store a three-dimensional map of the multi-tiered racks 3-00 and a programmable flight path (62A to 62E) configured to pass alongside a pre-selection of pallet bays 32 on the multi-tiered racks 3- 00; (ii) navigate the electric drone 10 along the programmable flight path (62A to 62E); (iii) aim the directional camera 13 toward the pallet label 31 of each palleted collection 30 located along the programmable flight path (62A to 62E), wherein the directional camera 13 captures a stream of images 33 during the programmable flight path (62A to 62E); and (iv) associate each of the images in the stream of images 33 with an image location and an image timestamp 25C. The data input 21 is configured for data communication with the data output 12 of the electric drone 10 to receive the stream of images 33 captured by the directional camera 13 of the electric drone 10 along the programmable flight path (62A to 62E). The recognition processor 23 is configured to offload or execute a recognition process, the recognition process including the steps of: (1) recognizing each pallet identifier 25A from the pallet labels 31 captured within the stream of images 33; (2) identifying the bay identifier 25B of each pallet identifier 25A captured within the stream of images 33 based upon the image location associated with at least one of the images employed to recognize the pallet identifier 25A; and (3) creating and storing a pallet location record within a flight inventory database 24 for each pallet identifier 25A recognized within the stream of images 33. Each pallet location record memorializes, for each pallet identifier 25A identified by the recognition processor 23 from the stream of images 33 during a programmable flight path (62A to 62E): (1) the pallet identifier 25A identified by the recognition processor 23; (2) the bay identifier 25B for the pallet bay 32 associated with the pallet identifier 25A; and (3) the image timestamp 25C of at least one of the images employed to recognize the pallet identifier 25A. The warehouse database 51 includes: (1) a plurality of inventory records 53, each inventory record 53 including a linked inventory identifier 53A and an inventory description 53B; and (2) a plurality of pallet content records 52, each pallet content record 52 including a linked pallet identifier 52A and a list of inventory identifiers 52B associated with the linked pallet identifier 52A. The server 50 is configured to: (1) download or link to each pallet location record of the flight inventory database 24; (2) link each pallet location record with one of the pallet content records 52 via a first cross reference; (3) link each pallet content record 52 with at least one of the inventory records 53 via a second cross reference. The first cross reference is between: (a) the pallet identifier 25A in the pallet location record of the flight inventory database 24; and (b) the linked pallet identifier 52A in one of the pallet content records 52 of the warehouse database 51. The second cross reference is between: (a) each of the inventory identifiers 52B listed in each pallet content record 52 of the warehouse database 51; and (b) the linked inventory identifier 53A of each of the inventory records 53 of the warehouse database 51. The reporting module is configured to: (i) determine the bay identifier 25B associated with each inventory identifier 52B via the first cross reference; (ii) determine the inventory description 53B associated with each linked inventory identifier 53A via the second cross reference; and (iii) output an inventory location report. The inventory location report lists each inventory identifier 52B linked with: (1) the bay identifier 25B associated with the inventory identifier 52B as determined by the first cross reference; and (2) the inventory description 53B associated with the linked inventory identifier 53A as determined by the second cross reference.

A second embodiment of the invention is computer-implemented method for conducting an autonomous drone inventory of an indoor warehouse with a plurality of location markers 61, the indoor warehouse storing a plurality of palleted collections 30 of inventory items on multi-tiered racks 3-00, each palleted collection 30 including a pallet label 31 displaying a pallet identifier 25A, each palleted collection 30 located in a pallet bay 32 associated with a bay identifier 25B, each pallet bay 32 locatable by at least one of a plurality of location markers 61 mounted in the indoor warehouse. The method comprising the steps of: (a) maintaining an electric drone 10 including a propulsion system 11, a directional camera 13, and a data output 12; (b) configuring a navigation module; (c) maintaining a computing device 20 with a data input 21, a user interface 22, and a recognition processor 23; (d) maintaining a warehouse database 51; (e) downloading or linking to each pallet location record of the flight inventory database 24; (f) linking each pallet location record with one of the pallet content records 52 via a first cross reference; (g) linking each pallet content record 52 with at least one of the inventory records 53 via a second cross reference; (h) determining the bay identifier 25B associated with each inventory identifier 52B via the first cross reference; (i) determining the inventory description 53B associated with each linked inventory identifier 53A via the second cross reference; and (j) outputting an inventory location report. The navigation module is configure to: (i) store a three-dimensional map of the multi-tiered racks 3-00 and a programmable flight path (62A to 62E) configured to pass alongside a pre-selection of pallet bays 32 on the multi-tiered racks 3-00; (ii) navigate the electric drone 10 along the programmable flight path (62A to 62E); (iii) aim the directional camera 13 toward the pallet label 31 of each palleted collection 30 located along the programmable flight path (62A to 62E), wherein the directional camera 13 captures a stream of images 33 during the programmable flight path (62A to 62E); and (iv) associate each of the images in the stream of images 33 with an image location and an image timestamp 25C. The data input 21 is configured for data communication with the data output 12 of the electric drone 10 to receive the stream of images 33 captured by the directional camera 13 of the electric drone 10 along the programmable flight path (62A to 62E). The recognition processor 23 is configured to offload or execute a recognition process, the recognition process including the steps of (1) recognizing each pallet identifier 25A from the pallet labels 31 captured within the stream of images 33; (2) identifying the bay identifier 25B of each pallet identifier 25A captured within the stream of images 33 based upon the image location associated with at least one of the images employed to recognize the pallet identifier 25A; and (3) creating and storing a pallet location record within a flight inventory database 24 for each pallet identifier 25A recognized within the stream of images 33. Each pallet location record memorializes, for each pallet identifier 25A identified by the recognition processor 23 from the stream of images 33 during a programmable flight path (62A to 62E): (1) the pallet identifier 25A identified by the recognition processor 23; (2) the bay identifier 25B for the pallet bay 32 associated with the pallet identifier 25A; and (3) the image timestamp 25C of at least one of the images employed to recognize the pallet identifier 25A. The warehouse database 51 includes: (i) a plurality of inventory records 53, each inventory record 53 including a linked inventory identifier 53A and an inventory description 53B; and (ii) a plurality of pallet content records 52, each pallet content record 52 including a linked pallet identifier 52A and a list of inventory identifiers 52B associated with the linked pallet identifier 52A. The first cross reference is between: (i) the pallet identifier 25A in the pallet location record of the flight inventory database 24; and (ii) the linked pallet identifier 52A in one of the pallet content records 52 of the warehouse database 51. The second cross reference is between: (i) each of the inventory identifiers 52B listed in each pallet content record 52 of the warehouse database 51; and (ii) the linked inventory identifier 53A of each of the inventory records 53 of the warehouse database 51. The inventory location report lists each inventory identifier 52B linked with: (i) the bay identifier 25B associated with the inventory identifier 52B as determined by the first cross reference; and (ii) the inventory description 53B associated with the linked inventory identifier 53A as determined by the second cross reference.

In an alternative of the first and second embodiment of the invention: (a) each pallet content record 52 includes a current location identifier 52C inputted into the warehouse database 51 through a warehouse inventory system; and (b) the reporting module is further configured to check for errors and flag errors in the inventory location report. The check for errors is between: (1) the bay identifier 25B of each palleted collection 30 in the pallet location records 25 of the flight inventory database 24; and (2) the current location identifier 52C of each palleted collection 30 in the pallet content records 52 of the warehouse database 51.

In an alternative of the first and second embodiment of the invention, each pallet label 31 includes: (i) a QR code design identifying a first pallet identifier, the QR code design having side dimensions in the range of 10 to 30 centimeters; (ii) a linear barcode design identifying a second pallet identifier; and (iii) an RFID tag identifying a third pallet identifier. The associations between the first pallet identifier, the second pallet identifier, and the third pallet identifier are stored in at least one of: (i) the flight inventory database 24; and (ii) the warehouse database 51.

The large sizing of the QR code (10 to 30 centimeters) minimizes the practical limitations of an indoor warehouse environment. For instance, palleted collections 30 may reside in the indoor warehouse for months or years, thereby suffering distorting from the collecting of dirt, dust, and/or moisture. Also wrapping materials used to hold the inventory items together or the pallet label 31 in place may cause visual distortion. With a larger QR code, for instance, wrinkles or blotches in the QR code are less likely to cause mis-reads or failed-reads for the QR code. These alternative identifying means are helpful in assisting the logistical demands of an indoor warehouse. The invention, for instance, is likely to rely on equipment and software from multiple vendors. The electric drone 10 and computing device 20 are likely to be purchased from a separate vendor from the providers of the warehouse database 51. Warehouse workers may be using RFID or linear barcode readers in most of their interactions with the palleted items. It is possible that the large QR codes on the pallet labels 31 are only used by the autonomous drone inventory system 1-00.

In an alternative of the first and second embodiment of the invention, each location marker 61 mounted in the indoor warehouse identifies at least one of a launch point, an aisle, a tier, a column, and a pallet bay 32. This type of placement of the location markers 61 creates a robust foundation for the design of the three-dimensional map and the programmable flight path (62A to 62E). It also enables more precision in the location of each pallet bay 32. A predetermined location or a launch point marker can be used to indicate the launch point; a launch point marker can be, for instance, a “X” marked on the floor at one end of each aisle.

In an alternative of the first and second embodiment of the invention, location markers 61 mounted in the indoor warehouse include at least one of: (a) a launch point marker; (b) a plurality of near field communication beacons identifiable by a near field communication sensor mounted on the electric drone 10; (c) a plurality of visual location labels; and (d) a plurality of warehouse fixtures identified on the three-dimensional map of the multi-tiered racks 3-00. The visual location labels include at least one of a QR label, and an ArUco label, and a linear barcode label. The navigation module is configured to identify each visual location label in at least one of: (1) the stream of images 33 from the directional camera 13; and (2) an alternative stream of images 33 captured by a navigational camera mounted on the electric drone 10. The navigation module is configured to identify each warehouse fixture in at least one of: (i) the stream of images 33 from the directional camera 13; (ii) the alternative stream of images 33 from the navigational camera; and (iii) a LIDAR sensor data stream from a LIDAR sensor mounted on the electric drone 10. For simplicity, each aisle can be cordoned off and its pallet bays 32 scanned separately in a series of separate aisle flights. This approach can simplify the designs of the navigation module, the three-dimensional map, and the programmable flight path (62A to 62E). In this approach, the three-dimensional map is a compilation of separate aisle maps and the programmable flight path (62A to 62E) is a compilation of separate aisle flights. This approach may be more effective for conducting an inventory during working hours of the indoor warehouse (which for many warehouses is 24 / 7), as the inconvenience to warehouse staff is minimized. Also, safety is enhanced because operation of the electric drone 10 during each separate aisle flight within a single aisle can be easily observed by designated warehouse staff for each separate aisle flight of the programmable flight path (62A to 62E).

In an alternative of the first and second embodiment of the invention, the stream of images 33 captured by the directional camera 13 is downloaded in real time from the electric drone 10 to the computing device 20 via a data pathway during navigation of the electric drone 10 through the programmable flight path (62A to 62E). The data pathway passes: (i) wirelessly from the data output 12 of the electric drone 10 to a router 41 in the indoor warehouse; and (ii) from the router 41 to the data input 21 of the computing device 20. The computing device 20 is configured to display the stream of images 33 on the user interface 22 of the computing device 20 in real time.

In an alternative of the first and second embodiment of the invention, an alternate stream of images is captured by a navigational camera mounted on the electric drone 10 and downloaded in real time from the electric drone 10 to the computing device 20 via a data pathway during navigation of the electric drone 10 through the programmable flight path (62A to 62E). The data pathway passes: (i) wirelessly from the data output 12 of the electric drone 10 to a router 41 in the indoor warehouse; and (ii) from the router 41 to the data input 21 of the computing device 20. The computing device 20 is configured to display the alternate stream of images on the user interface 22 of the computing device 20 in real time. This embodiment has the advantage of using the stream of images 33 from an alternate stream of images taken by a navigation camera. The alternate stream of images thus can be dedicated to an optimal viewing angle of the flight (likely parallel to the direction of flight of the electric drone 10). In some jurisdictions, warehouse safety and/or electric drone 10 flight safety rules may require this manner of dedicated real time forward viewing angle during programmable flight path (62A to 62E) operation.

In an alternative of the first and second embodiment of the invention: (a) each programmable flight path (62A to 62E) commences and finishes at a dedicated staging area with a charging dock; and (b) each navigation of the electric drone 10 through the programmable flight path (62A to 62E) to capture the stream of images 33 is prescheduled by the navigation module.

This embodiment is advantageous for efficient charging of the electric drone 10 between flights. In a large indoor warehouse, the battery storage time of an electric drone 10 may require multiple flights interspersed between battery recharging cycles to perform an inventory of the entire indoor warehouse. The dedicated staging area can also be placed in a secure location protecting the electric drone 10 from theft, vandalism, and equipment movement within the indoor warehouse.

In an alternative of the first and second embodiment of the invention, software and hardware of the navigation module is stored or mounted within at least one of: (a) the electric drone 10; (b) the computing device 20; and (c) a server 50.

Specifics of the navigation equipment and protocols for electric drones 10 differs between vendors. Some vendors include provide full autonomous navigation capability within the electronics and firmware of the electric drone 10. Other vendors split the navigation processing responsibility between the electric drone 10 and a computing device 20 (such as a laptop running the vendor’s navigation software). The invention is meant to be compatible with this type of flexibility in the design of the electric drones 10. The electric drones 10 are primarily tasked with flying the programmed flight path and capturing the stream of images 33 of the pallet labels 31. In an alternative of the first and second embodiment of the invention: (a) the recognition processor 23 of the computing device 20 is configured to direct the upload of the stream of images 33 to a server 50; (b) the recognition processor 23 offloads the recognition process to the server 50; and (c) the flight inventory database 24 is located on the server 50.

The invention allows the recognition processing of the stream of images 33 to be performed on the computing device 20 or offloaded to a server 50. The advantage of performing the recognition processing at the computing device 20 is that the results of an autonomous drone inventory can be performed locally within the indoor warehouse without uploading the stream of images 33 to a server 50 through the network 40. The disadvantage, however, is that the computing device 20 (which could be a laptop or a smart phone) may not have sufficient processing power, stored battery power, or data storage to perform the recognition processing in a reasonable amount of time.

With improvements in data uploads speeds and the inexpensive options provided by cloud service providers, performance of the recognition processing at a server 50 may be a better option for many implementations of the invention, especially for larger indoor warehouses or indoor warehouses with a high volume of individual palleted collections 30. As part of the recognition processing, an audit copy of the stream of images 33 can be archived at the server 50 for each autonomous drone inventory.

While various aspects and embodiments have been disclosed herein, it will be apparent that various other modifications and adaptations of the invention will be apparent to the person skilled in the art after reading the foregoing disclosure without departing from the spirit and scope of the invention and it is intended that all such modifications and adaptations come within the scope of the appended claims. The various aspects and embodiments disclosed herein are for purposes of illustration and are not intended to be limiting, with the true scope and spirit of the invention being indicated by the appended claims.