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NZ765470B2 - Produce orientor - Google Patents
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NZ765470B2 - Produce orientor - Google Patents

Produce orientor Download PDF

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Publication number
NZ765470B2
NZ765470B2 NZ765470A NZ76547019A NZ765470B2 NZ 765470 B2 NZ765470 B2 NZ 765470B2 NZ 765470 A NZ765470 A NZ 765470A NZ 76547019 A NZ76547019 A NZ 76547019A NZ 765470 B2 NZ765470 B2 NZ 765470B2
Authority
NZ
New Zealand
Prior art keywords
item
produce
food item
dimensional
food
Prior art date
Application number
NZ765470A
Other versions
NZ765470A (en
Inventor
David Bullock
Brian Dunne
Brandon Evers
Mason Mcinnis
Russ Mitchell
Daniel Nelson
Original Assignee
Atlas Pacific Engineering Company
Filing date
Publication date
Application filed by Atlas Pacific Engineering Company filed Critical Atlas Pacific Engineering Company
Priority claimed from PCT/US2019/000008 external-priority patent/WO2019177680A1/en
Publication of NZ765470A publication Critical patent/NZ765470A/en
Publication of NZ765470B2 publication Critical patent/NZ765470B2/en

Links

Classifications

    • A—HUMAN NECESSITIES
    • A23—FOODS OR FOODSTUFFS; TREATMENT THEREOF, NOT COVERED BY OTHER CLASSES
    • A23N—MACHINES OR APPARATUS FOR TREATING HARVESTED FRUIT, VEGETABLES OR FLOWER BULBS IN BULK, NOT OTHERWISE PROVIDED FOR; PEELING VEGETABLES OR FRUIT IN BULK; APPARATUS FOR PREPARING ANIMAL FEEDING- STUFFS
    • A23N4/00—Machines for stoning fruit or removing seed-containing sections from fruit, characterised by their stoning or removing device
    • A23N4/12—Machines for stoning fruit or removing seed-containing sections from fruit, characterised by their stoning or removing device for coring fruit
    • A23N4/14—Machines for stoning fruit or removing seed-containing sections from fruit, characterised by their stoning or removing device for coring fruit for apples, pears or the like
    • A—HUMAN NECESSITIES
    • A23—FOODS OR FOODSTUFFS; TREATMENT THEREOF, NOT COVERED BY OTHER CLASSES
    • A23N—MACHINES OR APPARATUS FOR TREATING HARVESTED FRUIT, VEGETABLES OR FLOWER BULBS IN BULK, NOT OTHERWISE PROVIDED FOR; PEELING VEGETABLES OR FRUIT IN BULK; APPARATUS FOR PREPARING ANIMAL FEEDING- STUFFS
    • A23N7/00—Peeling vegetables or fruit
    • A23N7/02—Peeling potatoes, apples or similarly shaped vegetables or fruit
    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B25—HAND TOOLS; PORTABLE POWER-DRIVEN TOOLS; MANIPULATORS
    • B25J—MANIPULATORS; CHAMBERS PROVIDED WITH MANIPULATION DEVICES
    • B25J11/00—Manipulators not otherwise provided for
    • B25J11/0045—Manipulators used in the food industry
    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B25—HAND TOOLS; PORTABLE POWER-DRIVEN TOOLS; MANIPULATORS
    • B25J—MANIPULATORS; CHAMBERS PROVIDED WITH MANIPULATION DEVICES
    • B25J15/00—Gripping heads and other end effectors
    • B25J15/02—Gripping heads and other end effectors servo-actuated
    • B25J15/0206—Gripping heads and other end effectors servo-actuated comprising articulated grippers
    • B25J15/022—Gripping heads and other end effectors servo-actuated comprising articulated grippers actuated by articulated links
    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B25—HAND TOOLS; PORTABLE POWER-DRIVEN TOOLS; MANIPULATORS
    • B25J—MANIPULATORS; CHAMBERS PROVIDED WITH MANIPULATION DEVICES
    • B25J15/00—Gripping heads and other end effectors
    • B25J15/08—Gripping heads and other end effectors having finger members
    • B25J15/12—Gripping heads and other end effectors having finger members with flexible finger members
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01B—MEASURING LENGTH, THICKNESS OR SIMILAR LINEAR DIMENSIONS; MEASURING ANGLES; MEASURING AREAS; MEASURING IRREGULARITIES OF SURFACES OR CONTOURS
    • G01B11/00—Measuring arrangements characterised by the use of optical techniques
    • G01B11/24—Measuring arrangements characterised by the use of optical techniques for measuring contours or curvatures
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N33/00—Investigating or analysing materials by specific methods not covered by groups G01N1/00 - G01N31/00
    • G01N33/02—Food
    • G01N33/025—Fruits or vegetables
    • G—PHYSICS
    • G06—COMPUTING OR CALCULATING; COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T2207/00—Indexing scheme for image analysis or image enhancement
    • G06T2207/10—Image acquisition modality
    • G06T2207/10024—Color image
    • G—PHYSICS
    • G06—COMPUTING OR CALCULATING; COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T2207/00—Indexing scheme for image analysis or image enhancement
    • G06T2207/10—Image acquisition modality
    • G06T2207/10028—Range image; Depth image; 3D point clouds
    • G—PHYSICS
    • G06—COMPUTING OR CALCULATING; COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T2207/00—Indexing scheme for image analysis or image enhancement
    • G06T2207/30—Subject of image; Context of image processing
    • G06T2207/30108—Industrial image inspection
    • G06T2207/30128—Food products
    • G—PHYSICS
    • G06—COMPUTING OR CALCULATING; COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T7/00—Image analysis
    • G06T7/50—Depth or shape recovery
    • G06T7/55—Depth or shape recovery from multiple images
    • G—PHYSICS
    • G06—COMPUTING OR CALCULATING; COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T7/00—Image analysis
    • G06T7/70—Determining position or orientation of objects or cameras
    • G06T7/73—Determining position or orientation of objects or cameras using feature-based methods
    • G06T7/75—Determining position or orientation of objects or cameras using feature-based methods involving models
    • G—PHYSICS
    • G06—COMPUTING OR CALCULATING; COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T7/00—Image analysis
    • G06T7/90—Determination of colour characteristics
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
    • H04N23/00—Cameras or camera modules comprising electronic image sensors; Control thereof
    • H04N23/90—Arrangement of cameras or camera modules, e.g. multiple cameras in TV studios or sports stadiums

Abstract

method of automatically orienting symmetric and asymmetric produce items, such as apples for example, is provided. Individual items of produce are manipulated by a programmable manipulator within the view of one or more depth imaging cameras. Digital three dimensional characterizations of the surface of the produce items are generated by the depth imaging camera or cameras and are utilized by a computer connected to the depth imaging camera or cameras to locate the stem and blossom of each produce item. Asymmetric produce items, such as apples with dropped shoulders as well as symmetric produce items can be properly oriented and processed automatically.

Claims (20)

We claim:
1. A method of orienting food items for processing, comprising: imaging a food item, creating a digital three dimensional characterization of the surface of said food item, utilizing said digital three dimensional characterization of the surface of said food item to locate a stem and a blossom in three-dimensional space, and determining a proper orientation for the food item by comparing said three dimensional characterization of the surface of said food item to a plurality of three dimensional models of properly oriented food items stored in a digital library, and orienting said food item to the proper orientation by: rotating said food item about a first axis until a stem and a blossom lie in a pre- determined first plane; and rotating said food item about a second axis until said stem and said blossom lie along a pre-determined line.
2. The method of claim 1 wherein said food item is an apple having a stem indent in which said stem is located and a blossom indent in which said blossom is located and wherein a principal axis of curvature algorithm is utilized to locate said stem indent and said blossom indent.
3. The method of claim 1 or 2, wherein said digital three dimensional characterization is a three dimensional model of the surface of said food item, and wherein an iterative closest point algorithm is utilized to compare said generated three dimensional model with said stored three dimensional models of properly oriented food items and to cause a programmable manipulator to correct the orientation of the food item based on the comparison.
4. The method of any one of claims 1 to 3, wherein a manipulator grips said food item using the fin ray effect.
5. The method of any one of claims 1 to 4, wherein a manipulator utilizes an orienting cup with two off-center drive wheels beneath said orienting cup to cause said food item to rotate to present the entire surface of said food item to said depth imaging camera.
6. The method of any one of claims 1 to 5, wherein said imaging is performed by an RGB-D camera.
7. The method of any one of claims 1 to 6, wherein two or more depth imaging cameras are utilized to image said food item.
8. The method of any one of claims 1 to 7, wherein four RGB-D cameras are positioned around said food item, and each camera generates a three dimensional model of the food item.
9. The method of any one of claims 1 to 8, where said manipulator follows a preset motion pattern to present the entire surface of the food item to the camera.
10. The method of any one of claims 1 to 9, wherein the position of a manipulator is tracked using encoders.
11. The method of any one of claims 1 to 10, wherein said food item is an apple.
12. The method of any one of claims 1 to 11, wherein one or more RGB-D cameras are utilized to detect the color of any bruises to said food items that require that food item to be either separated for special processing or to be discarded.
13. A method of automatically orienting produce items comprising the steps: imaging a produce item as said produce item is manipulated to create a three dimensional characterization of said produce item, comparing, using an iterative closest point algorithm, the created digital three dimensional characterization of the surface of said produce item with a digital library of a plurality of three dimensional models of properly oriented asymmetric and symmetric produce items to locate a closest match between the created digital three dimensional characterization of the surface of said produce item and one of three dimensional models in the digital library, and correcting the orientation of said produce item to a proper orientation based on the located closest match.
14. The method of claim 13, wherein said correcting further comprises: actuating a manipulator to correct the orientation of said produce item to said proper orientation.
15. The method of claim 13 or 14, wherein said correcting uses a manipulator to grip said produce item using a fin ray effect.
16. The method of any one of claims 13 to 15, wherein said correcting uses a manipulator that comprises an orienting cup with two off-center drive wheels beneath said orienting cup to cause said produce item to rotate to present the entire surface of said produce item to said depth imaging camera.
17. A system of automatically orienting produce items comprising: an imager configured to image each produce item, and a data processor configured to create a digital three dimensional characterization of the surface of a produce item being imaged and utilize said digital three dimensional characterization of the surface of said produce item being manipulated, wherein said data processor is configured to determine a proper orientation of said produce item using an iterative closest point algorithm and to actuate a manipulator to correct the orientation of said produce item to the proper orientation.
18. The system of claim 17 further comprising: a programmable manipulator to manipulate an orientation of said produce item.
19. The system of claim 18, wherein: each produce item has a stem and a blossom; the programmable manipulator corrects the orientation of said produce item to the proper orientation by: rotating said produce item about a first pre-determined axis until said stem and said blossom lie in a first pre-determined plane; and rotating said produce item about a second pre-determined axis until said stem and said blossom lie along a pre-determined line.
20. The system of claim 19 further comprising: a data store storing a digital library of a plurality of three dimensional models of properly oriented produce items; wherein the iterative closest point algorithm is utilized to compare said generated three dimensional model with said stored three dimensional models of properly oriented produce items.
NZ765470A 2019-03-08 Produce orientor NZ765470B2 (en)

Applications Claiming Priority (2)

Application Number Priority Date Filing Date Title
US201862761243P 2018-03-14 2018-03-14
PCT/US2019/000008 WO2019177680A1 (en) 2018-03-14 2019-03-08 Produce orientor

Publications (2)

Publication Number Publication Date
NZ765470A NZ765470A (en) 2024-07-05
NZ765470B2 true NZ765470B2 (en) 2024-10-08

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