Baiting method and apparatus for pest control

• US 10,045,523 B2
• Filed: 04/10/2015
• Issued: 08/14/2018
• Est. Priority Date: 04/10/2014
• Status: Active Grant

• Current Assignee: Ninox Robotics Pty Ltd.
• Original Assignee: Ninox Robotics Pty Ltd.
• Inventors: Ehrlich, Marcus, Vogelnest, Daniel
• Primary Examiner(s): COLEMAN, STEPHEN P
• Application Number:
  US15/302,621
• Publication Number:
  US 20170027155A1
• Time in Patent Office: 1,222 Days
• Field of Search: None
• CPC Class Codes: A01M 25/006 Poison applicators, i.e. mobile devices for disposing poison wherever required, e.g. into holes, burrows, walls or ground
• CPC Class Codes: A01M 31/002 Detecting animals in a given area
• CPC Class Codes: B64C 39/024 of the remote controlled vehicle type, i.e. RPV
• CPC Class Codes: B64U 2101/00 UAVs specially adapted for particular uses or applications
• CPC Class Codes: B64U 2101/30 for imaging, photography or videography
• CPC Class Codes: B64U 2201/10 autonomous, i.e. by navigating independently from ground or air stations, e.g. by using inertial navigation systems [INS]
• CPC Class Codes: G01S 13/08 Systems for measuring distance only indirect measurement G01S13/46
• CPC Class Codes: G01S 17/08 for measuring distance only indirect measurement G01S17/46; active triangulation systems G01S17/48
• CPC Class Codes: G01S 17/88 Lidar systems specially adapted for specific applications
• CPC Class Codes: G06Q 10/06 Resources, workflows, human or project management; Enterprise or organisation planning; Enterprise or organisation modelling
• CPC Class Codes: G06Q 50/02 Agriculture; Fishing; Forestry; Mining
• CPC Class Codes: G06V 10/255 Detecting or recognising potential candidate objects based on visual cues, e.g. shapes
• CPC Class Codes: G06V 20/13 Satellite images

Abstract

A system for carrying out pest baiting, comprises an unmanned aerial vehicle (UAV) which is controllable to record image data over a predefined flight path, the image data being captured by an image recording device. A computer processing arrangement is operable to evaluate the recorded image data to determine pest related data associated with an animal species identified as a pest, and to subsequently determine a baiting program for eradication of the animal species based on the determined pest data.

Claims

1. A method for controlling the population of an animal species identified as a pest, comprising the steps of:

controlling an unmanned aerial vehicle (UAV) to record image data over a predefined flight path, the image data being captured by an image recording device;

inputting the image data into an image processing apparatus which is programmed to automatically recognise one or more features that are predefined as being relevant for baiting the animal species,

implementing a computer algorithm that is configured to determine a baiting program comprising one or more baiting parameters based on the recognised features, the parameters comprising at least one of flight path, bait type, bait amount and bait location(s) for the delivery of a bait which is poisonous to the animal species; and

implementing the baiting program.

2. A method in accordance with claim 1, wherein implementing the baiting program comprises controlling a UAV to deliver the bait in accordance with the determined baiting program.

3. A non-transitory computer readable medium storing computer program code comprising at least one instruction which, when implemented by a computing system, is operable to carry out the method in accordance with claim 1.

4. A method in accordance with claim 1, further comprising recording spatial data over the predefined flight path and wherein the spatial data is additionally evaluated for feature recognition by the image processing apparatus.

5. A method in accordance with claim 4, wherein the spatial data is captured by at least one of a LIDAR and RADAR scanner.

6. A method in accordance with claim 1, wherein the image data comprises multi-spectral image data.

7. A method in accordance with claim 6, wherein the image recording device is operable to track movement of the identified animal species, based on detection thereof from the evaluated recorded image data.

8. A method in accordance with claim 6, wherein the image recording device is mounted on a gimbal which is in turn coupled to the UAV.

9. A method in accordance with claim 1, further comprising performing a feature extraction process on the recorded image data and comparing extracted features against a set of known useful features for recognition thereof.

10. A method in accordance with claim 9, wherein the set of known useful features comprise features indicative of at least one of the following objects:

targeted pest species;

targeted pest habitat;

non-targeted pest species;

terrain type;

landmark.

11. A method in accordance with claim 9, further comprising implementing a machine learning process for recognition of unknown features.

12. A method in accordance with claim 1, wherein the UAV is automatically controlled to fly over the predefined flight path.

13. A method in accordance with claim 12, wherein the UAV is powered by a battery and wherein the UAV is controlled to return to the base for recharging the battery either at some predetermined time or in response to the battery levels falling below a predefined threshold.

14. A method in accordance with claim 12, wherein the UAV is operable to automatically navigate changes in terrain for avoiding collision while operating over the flight path.

15. A method in accordance with claim 12, wherein, after having flown of the predetermined flight path, the UAV is further controlled to fly to a base station where the image data is collected for evaluation.

16. A method in accordance with claim 15, wherein the UAV is programmed to wirelessly communicate the image data to a base station while in operation.

17. A method in accordance with claim 1, wherein the computer algorithm process the feature data to determine one or more regions in which the animal species and/or corresponding habitats for the animal species were identified.

18. A method in accordance with claim 17, wherein the computer algorithm process the feature data to determine an actual or predicted number of the identified animal species.

19. A method in accordance with claim 18, wherein the bait location(s) corresponds to region(s) in which the animal species was identified.

20. A method in accordance with claim 19, wherein the bait location(s) is an anticipated location for the animal species.

21. A method in accordance with claim 19, wherein the amount of the bait for delivery is based on the determined number of the animal species.

22. A system for carrying out pest baiting, comprising:

an unmanned aerial vehicle (UAV) which is controllable to record sensory data over a predefined flight path, the sensory data being captured by at least one of an image recording device and spatial data sensor;

an image processing apparatus for receiving the sensory data and which is programmed to automatically recognise one or more features that are predefined as being relevant for baiting the animal species; and

a computer processing arrangement implementing an algorithm that is configured to determine a baiting program comprising one or more baiting parameters based on the recognised features, the parameters comprising at least one of flight path, bait type, bait amount and bait location(s) for the delivery of a bait which is poisonous to the animal species.