Perception systems and methods for identifying and processing a variety of objects

Abstract
A drop perception system is disclosed that includes an open housing structure having an internal volume, an open top and an open bottom, and a plurality of perception units positioned to capture perception data within the internal volume at a plurality of locations between the open top and the open bottom of the open housing.
Description
BACKGROUND

The invention generally relates to perception systems, and relates in particular to scanning systems for use in connection with robotic and other sortation systems that are intended to be used in dynamic environments requiring the robotic or other sortation system to accommodate processing a variety of types of objects.


For example many order fulfillment operations achieve high efficiency by employing a process called wave picking. In wave picking, orders are picked from warehouse shelves and placed at locations (e.g., into bins) containing multiple orders that are sorted downstream. At the sorting stage individual articles are identified, and multi-article orders are consolidated, for example into a single bin or shelf location, so that they may be packed and then shipped to customers. The process of sorting these articles has traditionally been done by hand. A human sorter picks an article from an incoming bin, finds a barcode on the object, scans the barcode with a handheld barcode scanner, determines from the scanned barcode the appropriate bin or shelf location for the article, and then places the article in the so-determined bin or shelf location where all articles for that order have been defined to belong. Automated systems for order fulfillment have also been proposed. See for example, U.S. Patent Application Publication No. 2014/0244026, which discloses the use of a robotic arm together with an arcuate structure that is movable to within reach of the robotic arm.


Other ways of identifying items by code scanning either require manual processing, or require that the code location be controlled or constrained so that a fixed or robot-held code scanner (e.g., barcode scanner) can reliably detect it. Manually operated barcode scanners are generally either fixed or handheld systems. With fixed systems, such as those used at point-of-sale systems, the operator holds the article and places it in front of the scanner so that the barcode faces the scanning device's sensors, and the scanner, which scans continuously and decodes any barcodes that it can detect. If the article is not immediately detected, the person holding the article typically needs to vary the position or rotation of the object in front of the fixed scanner, so as to make the barcode more visible to the scanner. For handheld systems, the person operating the scanner looks for the barcode on the article, and then holds the scanner so that the article's barcode is visible to the scanner, and then presses a button on the handheld scanner to initiate a scan of the barcode.


Automatic barcode scanners are similarly either fixed or hand-held systems, and the same principles apply. In the case of barcode scanners typically used in industrial applications, the possible positions of barcodes must be tightly controlled so that they are visible to the one or more scanners. For example, one or more barcode scanners may be placed in fixed locations relative to a conveyor so that they can scan items, typically boxes, as they pass by scanners. See, for example, U.S. Pat. No. 5,495,097. In these installations the range of placement of the barcodes is comparatively limited as the barcodes are on labels affixed to one of four sides or top or bottom (e.g., if upside down) of a box, which can be presented using simple mechanical means, at orientations optimal for scanning.


In all of these cases, the systems employ sensors, cameras or laser reflectivity sensors, as well as software to detect barcodes and decode them. These methods have inherent limitations that include the range of distances of orientations relative to the detection system, over which they are able to reliably scan barcodes. Firstly, the barcode must be facing the scanner; secondly the range to the barcode must be such that individual elements can be reliably distinguished; and, thirdly, the tilt and skew of the barcode must be such that individual elements can be reliably distinguished. The types of sensors employed, and the robustness of the software detection and decoding schemes determine these performance parameters.


There remains a need, therefore, for an object identification system for robotic and other sortation systems that is able to accommodate the automated identification and processing of a variety of objects in a variety of orientations.


SUMMARY

In accordance with an embodiment, the invention provides a drop perception system that includes an open housing structure having an internal volume, an open top and an open bottom, and a plurality of perception units positioned to capture perception data within the internal volume at a plurality of locations between the open top and the open bottom of the open housing.


In accordance with another embodiment, the invention provides a perception system for assisting in identifying an object, the perception system including a plurality of perception units that are each positioned to be directed toward different portions of an object path that an object takes as the object travels through the perception system without assistance by any mechanical conveyance system in contact with the object.


In accordance with a further embodiment, the invention provides a drop perception system for identifying an object, the drop perception system including a plurality of perception units that are each positioned to be directed toward different portions of an object path that an object may take as the object falls through the drop perception system, and each perception unit is engageable to provide perception data regarding the object.


In accordance with a further embodiment, the invention provides a method of sorting objects. The method includes the steps of dropping an object into a perception system that includes a plurality of perception units that are each positioned to be directed toward different portions of a path that the object may take as the object falls through the perception unit, and engaging the perception units to capture perception data associated with the object.





BRIEF DESCRIPTION OF THE DRAWINGS

The following description may be further understood with reference to the accompanying drawings in which:



FIG. 1 shows an illustrative isometric diagrammatic view of a perception system in accordance with an embodiment of the present invention;



FIG. 2 shows a front illustrative diagrammatic view of the perception system of FIG. 1;



FIG. 3 shows an illustrative isometric diagrammatic view of a perception system in accordance with another embodiment of the present invention;



FIG. 4 shows an illustrative elevated rear view of the perception system of FIG. 3;



FIG. 5 shows an illustrative front view of the perception system of FIG. 3 taken along line 5-5 thereof;



FIG. 6 shows an illustrative side view of the perception system of FIG. 3 taken along line 6-6 thereof;



FIG. 7 shows an illustrative top view of the perception system of FIG. 3;



FIG. 8 shows an illustrative linear diagrammatic view of a portion of the inside of the perception system of FIG. 3;



FIGS. 9A-9H show illustrative linear diagrammatic views of the inside of the perception system of FIG. 3 showing different stages of illumination and perception data captures;



FIGS. 10A-10C show illustrative views of a flowchart showing an operation of the perception system of FIG. 3;



FIG. 11 shows an illustrative diagrammatic view of a lighting system used in the perception system of FIG. 3;



FIG. 12 shows an illustrative diagrammatic view of an image capture system used in the perception system of FIG. 3;



FIGS. 13A-13R show illustrative views of images taken by the perception system of FIG. 3 (FIGS. 13A, 13C, 13E, 13G, 13I, 13K, 13M, 130, 13Q) as well as associated processed image data (FIGS. 13B, 13D, 13F, 13H, 13J, 13L, 13N, 13P, 13R);



FIG. 14 shows a sortation system including the perception system of FIG. 3 together with infeed devices and a sortation device;



FIG. 15 shows a sortation system including the perception system of FIG. 3 together with an item position/orientation adjustment device including an underside perception unit, as well as a sortation device; and



FIG. 16 shows a sortation system including the perception system of FIG. 3 together with an item position/orientation adjustment device including a fan, as well as a sortation device.





The drawings are shown for illustrative purposes only.


DETAILED DESCRIPTION

In accordance with an embodiment, the invention provides a novel object perception system for the purposes of automatically sorting individual objects in a set. In applications such as order fulfillment, articles or goods are collected into heterogeneous sets and need to be sorted. Individual objects need to be identified and then routed to object-specific locations. The described systems reliably automate the identification of such objects by employing automated scanners. The scanners look for a variety of codes such as indicia (e.g., barcodes, radio frequency tags, Stock Keeping Unit (SKU), Universal Product Code (UPC), Digimarc DWCode, etc.).


Operating in conjunction with a robotic pick and place system, systems in accordance with various embodiments of the invention automate part of the sorting process, in particular the step of identifying picked objects. Instead of a person picking the object from a bin for example, a robotic arm picks an article from a bin. The object is passed in front of a plurality of barcode scanners, and then, having obtained identification codes for the object, the object is then routed to the appropriate bin or shelf location. Since barcode scanners employ cameras or lasers to scan 1D or 2D symbologies printed on labels affixed to objects, the barcodes must be visible to the scanner's sensors for successful scanning in order to automatically identifying items in a heterogeneous stream of arbitrary objects, as in a jumbled set of objects found in a bin.


Whereas fixed industrial scanners require that the object's barcode be situated so that its barcode is visible to a scanner, the robotic arm of the present invention may pick an object out of a heterogeneous collection of objects where the barcode is not visible and drop the object into a perception system of the present invention. In other embodiments, the system may provide that objects are dropped into the perception system by providing a feed conveyor positioned above the perception system, and providing that objects are singulated on the conveyor. The result is an automated barcode scanning system for arbitrary objects in a heterogeneous stream of objects that can be used to accurately and reliably identify the objects.


Sorting for order fulfillment is one application for automatically identifying objects from a heterogeneous object stream. Barcode scanners have a wide variety of further uses including identifying the stock keeping unit of an article, or tracking parcels. The described systems may have many uses in the automatic identification and sortation of objects.


In accordance with various embodiments, therefore, the invention provides a method for determining the identity of an object from a collection of objects, as well as a method for scanning the barcode of an object employing one or more scanners and a sortation system for differently processing different objects. The invention further provides a method for determining the placement of fixed barcode scanners so as to maximize the probability of successfully scanning an object selected by a robot end-effector in accordance with certain embodiments, as well as a method for determining whether multiple objects are dropped into the scanner at the same time.


An important aspect is the ability to identify via barcode or other visual markings of objects by employing a perception system into which objects may be dropped. Automated scanning systems would be unable to see barcodes on objects that are presented in a way that their barcodes are not exposed or visible. As shown in FIG. 1, a perception system 10 in accordance with an embodiment of the present invention may include an open housing 12 through which an object may be dropped. Inside the hosing is a plurality of perception units 14 (e.g., eight or twelve) that are generally directed toward the interior of the housing from many different directions. The housing may also include a plurality of lights 16 that are timed to provide bright dispersed light at the times that each of the perception units 14 take pictures of a falling object 18. Each perception unit 14 may, for example, take a hundred images while an object is falling from directions as indicated at A in FIG. 2. The detection units 14 may be connected to a processing system 20 that reviews each of the images in search of a unique identifier such as a barcode. The perception units may include cameras (e.g., 2D or 3D) or scanners (e.g., a laser reflectivity scanner other type of barcode reader (such as 1D or 2D barcode scanners, or radio frequency ID scanner), and the processing system 20 may include the associated software to process the perception data. Some cameras are directed horizontally, while others are directed upward, and some are directed downward as shown. The system 10 may also include entry detection units that provide a curtain of, e.g., infrared illumination by a source 22 across the opening as well as a detector 24 for detecting a break in the illumination. The detection units therefor provide a signal that an object has entered the drop scanner 10.


The perception system may be used in certain embodiments, with a robotic system that may include a robotic arm equipped with sensors and computing, that when combined is assumed herein to exhibit the following capabilities: (a) it is able to pick objects up from a specified class of objects, and separate them from a stream of heterogeneous objects, whether they are jumbled in a bin, or are singulated on a motorized or gravity conveyor system; (b) it is able to move the object to arbitrary places within its workspace; (c) it is able to place objects in an outgoing bin or shelf location in its workspace; and, (d) it is able to generate a map of objects that it is able to pick, represented as a candidate set of grasp points in the workcell, and as a list of polytopes enclosing the object in space.


The allowable objects are determined by the capabilities of the robotic system. Their size, weight and geometry are assumed to be such that the robotic system is able to pick, move and place them. These may be any kind of ordered goods, packages, parcels, or other articles that benefit from automated sorting. Each object is associated with a stock keeping unit (SKU), which identifies the item.


The manner in which inbound objects arrive may be for example, in one of two configurations: (a) inbound objects arrive piled in bins of heterogeneous objects; or (b) inbound articles arrive by a moving conveyor. The collection of objects includes some that have exposed bar codes and other objects that do not have exposed bar codes. The robotic system is assumed to be able to pick items from the bin or conveyor. The stream of inbound objects is the sequence of objects as they are unloaded either from the bin or the conveyor.


The manner in which outbound objects are organized is such that objects are placed in a bin, shelf location or cubby, into which all objects corresponding to a given order are consolidated. These outbound destinations may be arranged in vertical arrays, horizontal arrays, grids, or some other regular or irregular manner, but which arrangement is known to the system. The robotic pick and place system is assumed to be able to place objects into all of the outbound destinations, and the correct outbound destination is determined from the SKU of the object.


It is assumed that the objects are marked in one or more places on their exterior with a visually distinctive mark such as a barcode or radio-frequency identification (RFID) tag so that they may be identified with a scanner. The type of marking depends on the type of scanning system used, but may include 1D or 2D barcode symbologies. Multiple symbologies or labeling approaches may be employed. The types of scanners employed are assumed to be compatible with the marking approach. The marking, either by barcode, RFID tag, or other means, encodes a symbol string, which is typically a string of letters and numbers. The symbol string uniquely associates the object with a SKU.


The operations of the systems described above are coordinated by the central control system 20. This system determines from symbol strings the SKU associated with an object, as well as the outbound destination for the object. The central control system is comprised of one or more workstations or central processing units (CPUs). The correspondence between SKUs and outbound destinations is maintained by the central control system in a database called a manifest. The central control system maintains the manifest by communicating with a warehouse management system (WMS).


During operation, the broad flow of work may be generally as follows. First, the system is equipped with a manifest that provides the outbound destination for each inbound object. Next, the system waits for inbound objects to arrive either in a bin or on a conveyor. The robotic system may pick one item at a time from the input bin, and may drop each item into the perception system discussed above. If the perception system successfully recognizes a marking on the object, then the object is then identified and forwarded to a sorting station or other processing station. If the object is not identified, the robotic system may either replace the object back onto the input conveyor and try again, or the conveyor may divert the object to a human sortation bin to be reviewed by a human.


The sequence of locations and orientations of the perception units are chosen so as to minimize the average or maximum amount of time that scanning takes. Again, if the object cannot be identified, the object may be transferred to a special outbound destination for unidentified objects, or it may be returned to the inbound stream. This entire procedure operates in a loop until all of the objects in the inbound set are depleted. The objects in the inbound stream are automatically identified, sorted, and routed to outbound destinations.


In accordance with an embodiment therefore, the invention provides a system for sorting objects that arrive inbound bins and that need to be placed into a shelf of outbound bins, where sorting is to be based on a unique identifier symbol. Key specializations in this embodiment are the specific design of the perception system so as to maximize the probability of a successful scan, while simultaneously minimizing the average scan time. The probability of a successful scan and the average scan time make up key performance characteristics. These key performance characteristics are determined by the configuration and properties of the perception system, as well as the object set and how they are marked.


The two key performance characteristics may be optimized for a given item set and method of barcode labeling. Parameters of the optimization for a barcode system include how many barcode scanners, where and in what orientation to place them, and what sensor resolutions and fields of view for the scanners to use. Optimization can be done through trial and error, or by simulation with models of the object.


Optimization through simulation employs a barcode scanner performance model. A barcode scanner performance model is the range of positions, orientations and barcode element size that a barcode symbol can be detected and decoded by the barcode scanner, where the barcode element size is the size of the smallest feature on the barcode. These are typically rated at a minimum and maximum range, a maximum skew angle, a maximum pitch angle, and a minimum and maximum tilt angle.


Typical performance for camera-based barcode scanners are that they are able to detect barcode symbols within some range of distances as long as both pitch and skew of the plane of the symbol are within the range of plus or minus 45 degrees, while the tilt of the symbol can be arbitrary (between 0 and 360 degrees). The barcode scanner performance model predicts whether a given barcode symbol in a given position and orientation will be detected.


The barcode scanner performance model is coupled with a model of where barcodes would expect to be positioned and oriented. A barcode symbol pose model is the range of all positions and orientations, in other words poses, in which a barcode symbol will expect to be found. For the scanner, the barcode symbol pose model is itself a combination of an article gripping model, which predicts how objects will be held by the robotic system, as well as a barcode-item appearance model, which describes the possible placements of the barcode symbol on the object. For the scanner, the barcode symbol pose model is itself a combination of the barcode-item appearance model, as well as an inbound-object pose model, which models the distribution of poses over which inbound articles are presented to the scanner. These models may be constructed empirically, modeled using an analytical model, or approximate models may be employed using simple sphere models for objects and a uniform distributions over the sphere as a barcode-item appearance model.



FIG. 3 shows a perception system 30 in accordance with another embodiment of the present invention that includes a structure 32 having an opening 34. The structure 32 includes a plurality of rows of sources (e.g., illumination sources such as LEDs) 36 as well as a plurality of image perception units (e.g., cameras) 38. The sources 36 are provided in rows, and each is directed toward the center of the opening. The perception units 38 are also generally directed toward the opening, although, as with the embodiment of FIGS. 1 and 2, some cameras are directed horizontally, while others are directed upward, and some are directed downward. The system 30 also includes an entry source (e.g., infrared source) 40 as well as an entry detector (e.g., infrared detector 42) for detecting when an object has entered the detection system 30.


The LEDs and cameras therefore encircle the inside of the structure 32, and the cameras are positioned to view the interior via windows that may include a glass or plastic covering (e.g., 44). The structure 32 may be suspended by loop hooks 46 or placed over an opening and hang by brackets 48.



FIG. 8 shows a portion of the interior of the scanner 30, where the sections are show laid out linearly. The cameras 38′ each include a camera portion 50 as well as an angled mirror 52 that provides the desired field of view within the structure 32. Similarly, FIGS. 9A-9H diagrammatically and linearly, show the interior of the structure 32 within the scanning region. As soon as the entry detector 40, 42 senses that an item has entered the scanning region, the LEDs and cameras follow a sequence of steps that capture many images. In particular, as shown at 51 in FIG. 9A, a first set of LEDs 36 are illuminated, and a first set of cameras 38 are engaged to take a number of pictures (a first set of images) of the interior of the scanner. As shown at 53 in FIG. 9B, a second set of LEDs 36 are illuminated, and a second set of cameras 38 (in this case one camera) are engaged to take a number of pictures (a second set of images) of the interior of the scanner. As shown at 54 in FIG. 9C, a third set of LEDs 36 are illuminated, and a third set of cameras 38 are engaged to take a number of pictures (a third set of images) of the interior of the scanner. As shown at 55 in FIG. 9D, a fourth set of LEDs 36 are illuminated, and a fourth set of cameras 38 are engaged to take a number of pictures (a fourth set of images) of the interior of the scanner. As shown at 56 in FIG. 9E, a fifth set of LEDs 36 are illuminated, and a fifth set of cameras 38 are engaged to take a number of pictures (a fifth set of images) of the interior of the scanner. As shown at 57 in FIG. 9F, a sixth set of LEDs 36 are illuminated, and a sixth set of cameras 38 are engaged to take a number of pictures (a sixth set of images) of the interior of the scanner. As shown at 58 in FIG. 9G, a seventh set of LEDs 36 are illuminated, and a seventh set of cameras 38 are engaged to take a number of pictures (a seventh set of images) of the interior of the scanner. As shown at 59 in FIG. 9H, an eighth set of LEDs 36 are illuminated, and an eighth set of cameras 38 are engaged to take a number of pictures (an eighth set of images) of the interior of the scanner. Again, the openings in the structure through which the cameras capture images may include a transparent glass or plastic 44. Each of the rows of LEDs 36 may also include a covering of transparent glass or plastic that is separate from the glass or plastic 44 of the openings to avoid light being transmitted through the glass to any detectors 38. Also, the outside of the structure may be covered (except for the top and bottom openings) with a protective film 33 (e.g., an amber film) as shown in FIG. 5, that filters some of the wavelengths of the LEDs for the protection of any persons in the area.


With further reference to FIGS. 10A-10C, the process begins (step 1000) with the entry detectors 40, 42 detecting whether an object has entered the scanner (step 1002). Once this happens, the first set of lights are turned on and the first set of cameras begin capturing images (step 1004). The first sets of lights and cameras are then turned off. A first set of captured images are then sent to a processing core for processing (step 1006). The second set of lights are turned on and the second set of cameras begin capturing images (step 1008). The second sets of lights and cameras are then turned off. A second set of captured images are then sent to another processing core for processing (step 1010). The third set of lights are turned on and the third set of cameras begin capturing images (step 1012). The third sets of lights and cameras are then turned off. A third set of captured images are then sent to another processing core for processing (step 1014). The fourth set of lights are turned on and the fourth set of cameras begin capturing images (step 1016). The fourth sets of lights and cameras are then turned off. A fourth set of captured images are then sent to another processing core for processing (step 1018). The fifth set of lights are turned on and the fifth set of cameras begin capturing images (step 1020). The fifth sets of lights and cameras are then turned off. A fifth set of captured images are then sent to another processing core for processing (step 1022). The sixth set of lights are turned on and the sixth set of cameras begin capturing images (step 1024). The sixth sets of lights and cameras are then turned off. A sixth set of captured images are then sent to another processing core for processing (step 1026). The seventh set of lights are turned on and the seventh set of cameras begin capturing images (step 1028). The seventh sets of lights and cameras are then turned off. A seventh set of captured images are then sent to another processing core for processing (step 1030). The eighth set of lights are turned on and the eighth set of cameras begin capturing images (step 1032). The eighth sets of lights and cameras are then turned off. A eighth set of captured images are then sent to another processing core for processing (step 1034).


The above process may be repeated any number, m, of times (e.g., 50) (step 1036). After all m repeats have finished, the system confirms that the item has exited the scanner (step 1038). The system then determines whether any codes were found (step 1040), and if not reports and error that no codes were found (step 1046). If a codes was found, the system collects all codes found (step 1042) and determines whether all codes match each other (step 1044). If not, the system reports that more than one item was placed in the scanner (step 1050). If all codes found match each other, the system determines whether more than one item was placed in the scanner (step 1048) by determining whether too much space exists between regions of an item. If so, the system reports that more than one item was placed in the scanner (step 1050). If not, the system reports the identification of the code that was found (step 1052) and engages a sorting path associated with the code that was found (step 1054). If no code was found (step 1046) or if the system detects that more than item was in the scanner (step 1050), the system may ask whether the operator wishes to try the scan again (or may be programmed to do so) (step 1056). If yes, then the system returns the item(s) to the input stream ahead of the drop scanner (step 1058). If not, the system moves the item(s) to a manual sort location for sorting by a person (step 1060).



FIG. 11 shows an illustrative diagrammatic view of the control system for the lights in the system of FIG. 3. In particular, a processor 62 is coupled to the structure 32 such that a light controller 66 is directed by a timing unit 60 to provide lighting control signals to a distribution control unit 64 in the structure 32, where the distribution control unit 64 provides individual control to each of the plurality of sets of LEDs 36. As shown in FIG. 11, the processor 62 also includes a camera controller 74 that is coupled to the timing unit 60. The camera controller communicates via core processors 72 to camera controllers 70 on the structure 32, and each camera controller communicates with sets 68 of cameras 38. The controllers 70 control both the triggering of the cameras as well as receive captured image data for processing by each of the respective core processors 72. The results of the core processors 72 are provided to an output identification unit 76.



FIGS. 13A-13R show captured images as well as associated processed image data for nine images during the movement of two items through the drop scanner of FIG. 3. In particular, no items are seen in FIG. 13A, and the associated processing image data shown in FIG. 13B shows no signal. In FIG. 13C, an item appears in the image, and the associated processed image data in FIG. 13D shows the image of the item. As shown in FIG. 13E, a second item appears in the field of view, and the associated processing image data shown in FIG. 13F shows the second item. In this image (as well as in the processed image data of FIGS. 13H and 13J), the system would detect that more than one item has been dropped in the scanner because too much area would appear between the two items. As shown in FIG. 13G, the second item continues to appear in the field of view, and the associated processing image data is shown in FIG. 13H. Similarly, as shown in FIG. 13I, the second item continues to appear in the field of view but begins to move closer to the first item, and the associated processing image data is shown in FIG. 13J. As shown in FIG. 13K, the second item has moved even closer to the first item, and the associated processing image data is shown in FIG. 13L. As shown in FIGS. 13M and 130, the second item has moved very close to the first item, and the associated processing image data is shown respectively in FIGS. 13N and 13P. FIG. 13Q shows that the items are leaving or have left the scanner, and the associated processing image data is shown in FIG. 13R. The capture of multiple images is therefore important to identifying whether more than one item is presented at one time in the scanner 32.


As discussed above, the output of the processor provides a signal indicative of the identified code of the item in the scanner, and based on this, a sortation system may immediately take action consistent with having the item routed in the desired direction or processing path. For example, FIG. 14 shows a sortation system employing a scanning unit of FIG. 3. Items may be dropped into the scanner by any means, such as but not including a robotic arm 86 (dropping an item 84) or an input conveyor 90 (dropping an item 88). In the case of a robotic arm 86, the end effector may employ deflection sensors 85 for detecting whether the item 84 is moving (e.g., swinging) with respect to the robotic arm 86 (and if so, wait until the movement ceases) prior to dropping the item into the scanner 32.


The scanner 32 is coupled to the processor 62 as discussed above, and an output sortation control signal 63 is provided to a sortation system, such as for example, a controller 96 of a conveyor 94 that provides direction routing of items (e.g., 92) to any of a plurality of bins, containers or locations 98, 104, for example by moving in either direction as indicated at C. Items 100 and 102, for example had been routed to location 98, and item 106 had been routed to location 104.


The system may also include an interrupting system that interrupts the falling of an object through the perception system. The interrupting system may be useful, for example, where the item to be scanned is a plastic bag (either opaque or transparent), and particularly, where the identifier code (such as a barcode) is not visible or readily visible by the perception units, for example if the bag is folded and obscures the barcode. With reference to FIG. 15, in this case, the interrupter element may cause the bag to become flattened by an interrupter plate 120. The interrupter plate 120 may include a further detection unit 124 under a transparent window in the interrupter element 120 to detect identifier indicia that is facing the interrupter element, as well as lights 126 that are illuminated when the detection unit 124 is capturing images as discussed above. The interrupter unit 120 may also be provided on a hinged stand 122 that permits the interrupter element to be moved into or out of the path of an item falling from the scanning unit 32. The interrupter unit 120 may be provided inside of or below the scanning unit 32. Again, the scanner 32 is coupled to the processor 62 as discussed above, and an output sortation control signal is provided to a sortation system, such as for example, a controller of a conveyor 94 that provides direction routing of items (e.g., 92) to any of a plurality of bins, containers or locations 98, 104, for example by moving in either direction as indicated at C.


In other embodiments, the system may include an interrupting element that urges lighter items upward in a reverse direction for a short time. With reference to FIG. 16, in this case, the interrupter element may cause a light bag to be urged upward by a fan 144 attached to a motor 142 that provides upward air pressure through a screen 140. The fan 144 may be provided inside of or below the scanning unit 32. Again, the scanner 32 is coupled to the processor 62 as discussed above, and an output sortation control signal is provided to a sortation system, such as for example, a controller of a conveyor 94 that provides direction routing of items (e.g., 92) to any of a plurality of bins, containers or locations 98, 104, for example by moving in either direction as indicated at C.


Those skilled in the art will appreciate that numerous modifications and variations may be made to the above disclosed embodiments without departing from the spirit and scope of the present invention.

Claims
  • 1. A method of processing an object, said method comprising: dropping the object into a perception system through an open top of the perception system, the perception system including a housing having an interior defined between the open top and an open bottom, a first perception unit mounted to the housing proximate the open top and a second perception unit mounted to the housing proximate the open bottom; directing reflected illumination from the object via at least one upper mirror within the housing proximate the open top toward the first perception unit as the object falls through the interior of the housing; capturing first perception data of the object falling through the interior of the housing by the first perception unit; directing reflected illumination from the object via at least one lower mirror within the housing proximate the open bottom toward the second perception unit as the object continues to fall through the interior of the housing; capturing second perception data of the object falling through the interior of the housing by the second perception unit; and identifying unique indicia on the object responsive to any of the first perception data and the second perception data, wherein the first perception unit and the second perception unit are any of a camera and a scanner, and the first perception data and the second perception data are any of images captured by the camera and scanned data captured by the scanner.
  • 2. The method as claimed in claim 1, wherein the scanner is a radio frequency ID scanner.
  • 3. The method as claimed in claim 1, wherein the scanner is a barcode scanner.
  • 4. The method as claimed in claim 1 wherein the scanner is a laser reflectivity scanner.
  • 5. The method as claimed in claim 1, wherein the method further includes detecting the object entering the perception system.
  • 6. The method as claimed in claim 1, wherein the perception system further includes a plurality of illumination sources.
  • 7. The method as claimed in claim 6, wherein the plurality of illumination sources include a plurality of LEDs.
  • 8. The method as claimed in claim 1, wherein the method further includes the step of diverting the object received from the perception system toward one of a plurality of routes responsive to the unique indicia.
  • 9. A drop perception system for processing one or more objects, said drop perception system comprising: a housing having an interior defined between an open top and an open bottom, wherein one or more objects are dropped into the housing through the open top and exit the housing through the open bottom; a first perception unit mounted to the housing proximate the open top and a second perception unit mounted to the housing proximate the open bottom; at least one upper mirror within the housing proximate the open top, said at least one upper mirror for directing reflected illumination from the one or more objects toward the first perception unit as the one or more objects fall through the interior of the housing, said first perception unit for capturing first perception data of the one or more objects falling through the interior of the housing; at least one lower mirror within the housing proximate the open bottom, said at least one lower mirror for directing reflected illumination from the one or more objects toward the second perception unit as the one or more objects continue to fall through the interior of the housing, said second perception unit for capturing second perception data of the one or more objects falling through the interior of the housing; and identifying means for identifying whether more than one unique indicia is captured by any of the first perception data and the second perception data, thereby indicating that more than one object is falling through the interior of the housing, wherein the first perception unit and the second perception unit are any of a camera and a scanner, and the first perception data and the second perception data are any of images captured by the camera and scanned data captured by the scanner.
  • 10. The drop perception system as claimed in claim 9, wherein the scanner is a radio frequency ID scanner.
  • 11. The drop perception system as claimed in claim 9, wherein the scanner is a barcode scanner.
  • 12. The drop perception system as claimed in claim 9 wherein the scanner is a laser reflectivity scanner.
  • 13. The drop perception system as claimed in claim 9, further comprising an entry detector for detecting the one or more objects entering the open top of the housing.
  • 14. The drop perception system as claimed in claim 9, wherein the drop perception system further includes a plurality of illumination sources.
  • 15. The drop perception system as claimed in claim 14, wherein the plurality of illumination sources include a plurality of LEDs.
  • 16. The drop perception system as claimed in claim 9, wherein the drop perception system is mounted above a conveyor that diverts the object dropped through the drop perception system toward one of a plurality of routes responsive to the unique indicia.
  • 17. A system for processing one or more objects, comprising: a drop perception system that includes: a housing having an interior defined between an open top and an open bottom, wherein one or more objects are dropped into the housing through the open top and exit the housing through the open bottom; a first perception unit mounted to the housing proximate the open top and a second perception unit mounted to the housing proximate the open bottom; at least one upper mirror within the housing proximate the open top, said at least one upper mirror for directing reflected illumination from the one or more objects toward the first perception unit as the one or more objects fall through the interior of the housing, said first perception unit for capturing first perception data of the one or more objects falling through the interior of the housing; at least one lower mirror within the housing proximate the open bottom, said at least one lower mirror for directing reflected illumination from the one or more objects toward the second perception unit as the one or more objects continue to fall through the interior of the housing, said second perception unit for capturing second perception data of the one or more objects falling through the interior of the housing; and identifying means for identifying whether more than one unique indicia is captured by any of the first perception data and the second perception data; and diverting means for routing any objects from the drop perception system responsive to whether more than one unique indicia is captured, wherein the first perception unit and the second perception unit are any of a camera and a scanner, and the first perception data and the second perception data are any of images captured by the camera and scanned data captured by the scanner.
  • 18. The system as claimed in claim 17, wherein the scanner is a radio frequency ID scanner.
  • 19. The system as claimed in claim 17, wherein the scanner is a barcode scanner.
  • 20. The system as claimed in claim 17 wherein the scanner is a laser reflectivity scanner.
  • 21. The system as claimed in claim 17, wherein the drop perception system further includes an entry detector for detecting one or more objects entering the open top of the housing.
  • 22. The system as claimed in claim 17, wherein the drop perception system further includes a plurality of illumination sources.
  • 23. The system as claimed in claim 22, wherein the plurality of illumination sources include a plurality of LEDs.
  • 24. The system as claimed in claim 17, wherein the diverting means includes a direction routing conveyor.
  • 25. A drop perception system, comprising: a housing having an interior defined between an open top and an open bottom, wherein one or more objects are dropped into the housing through the open top and exit the housing through the open bottom; a first perception unit mounted to the housing proximate the open top; at least one upper mirror within the housing proximate the open top, said at least one upper mirror for directing reflected illumination from the one or more objects toward the first perception unit as the one or more objects fall through the interior of the housing, said first perception unit for capturing first perception data of the one or more objects falling through the interior of the housing; a second perception unit mounted to the housing proximate the open bottom for detecting reflected illumination from the one or more objects as the one or more objects falling through the interior of the housing, said second perception unit for capturing second perception data of the one or more objects falling through the interior of the housing; and identifying means for identifying whether more than one unique indicia is captured by any of the first perception data and the second perception data prior to the one or more objects exiting the housing through the open bottom, wherein the first perception unit and the second perception unit are any of a camera and a scanner, and the first perception data and the second perception data are any of images captured by the camera and scanned data captured by the scanner.
  • 26. The drop perception system as claimed in claim 25, wherein the scanner is a radio frequency ID scanner.
  • 27. The drop perception system as claimed in claim 25, wherein the scanner is a barcode scanner.
  • 28. The drop perception system as claimed in claim 25 wherein the scanner is a laser reflectivity scanner.
  • 29. The drop perception system as claimed in claim 25, wherein the drop perception system further includes an entry detector for detecting the one or more objects entering the open top of the housing.
  • 30. The drop perception system as claimed in claim 25, wherein the drop perception system further includes a plurality of illumination sources.
  • 31. The drop perception system as claimed in claim 30, wherein the plurality of illumination sources include a plurality of LEDs.
  • 32. The perception system as claimed in claim 25, wherein the drop perception system is mounted above a conveyor that diverts the one or more objects dropped from the drop perception system toward one of a plurality of routes responsive to the unique indicia.
  • 33. A drop perception system, comprising: a housing having an interior defined between an open top and an open bottom, wherein one or more objects are dropped into the housing through the open top and exit the housing through the open bottom; a first perception unit mounted to the housing proximate the open top for detecting reflected illumination from the one or more objects as the one or more objects fall through the interior of the housing, said first perception unit for capturing first perception data of the one or more objects falling through the interior of the housing; a second perception unit mounted to the housing proximate the open bottom; at least one lower mirror the housing proximate the open bottom, said at least one lower mirror for directing reflected illumination from the one or more objects toward the second perception unit as the one or more objects fall through the interior of the housing, said second perception unit for capturing second perception data of the one or more objects falling through the interior of the housing; and identifying means for identifying whether more than one unique indicia is captured by any of the first perception data and the second perception data prior to the one or more objects exiting the housing through the open bottom, wherein the first perception unit and the second perception unit are any of a camera and a scanner, and the first perception data and the second perception data are any of images captured by the camera and scanned data captured by the scanner.
  • 34. The drop perception system as claimed in claim 33, wherein the scanner is a radio frequency ID scanner.
  • 35. The drop perception system as claimed in claim 33, wherein the scanner is a barcode scanner.
  • 36. The drop perception system as claimed in claim 33 wherein the scanner is a laser reflectivity scanner.
  • 37. The drop perception system as claimed in claim 33, wherein the drop perception system further includes an entry detector for detecting the one or more objects entering the open top of the housing.
  • 38. The drop perception system as claimed in claim 33, wherein the drop perception system further includes a plurality of illumination sources.
  • 39. The drop perception system as claimed in claim 38, wherein the plurality of illumination sources include a plurality of LEDs.
  • 40. The drop perception system as claimed in claim 33, wherein the drop perception system is mounted above a conveyor that diverts the one or more objects toward one of a plurality of routes responsive to the unique indicia.
PRIORITY

The present application is a continuation of U.S. patent application Ser. No. 16/407,965, filed May 9, 2019; which is a continuation of U.S. patent application Ser. No. 15/901,656, filed Feb. 21, 2018; which is a continuation of U.S. patent application Ser. No. 15/228,692, filed Aug. 4, 2016, now U.S. Pat. No. 9,937,532, issued Apr. 10, 2018; which claims priority to U.S. Provisional Patent Application Ser. No. 62/269,640 filed Dec. 18, 2015, the disclosures of which are hereby incorporated by reference in their entireties.

US Referenced Citations (173)
Number Name Date Kind
3734286 Simjian May 1973 A
3864566 Simpson et al. Feb 1975 A
4186836 Wassmer et al. Feb 1980 A
4704694 Czerniejewski Nov 1987 A
4722653 Williams et al. Feb 1988 A
4759439 Hartlepp Jul 1988 A
4819784 Sticht Apr 1989 A
4846335 Hartlepp Jul 1989 A
4895242 Michel Jan 1990 A
5190162 Hartlepp Mar 1993 A
5495097 Katz Feb 1996 A
5648709 Maeda Jul 1997 A
5713473 Satake Feb 1998 A
5742420 Peng Apr 1998 A
5794788 Massen Aug 1998 A
5794789 Payson et al. Aug 1998 A
5839566 Bonnet Nov 1998 A
5875434 Matsuoka et al. Feb 1999 A
5996316 Kirschner Dec 1999 A
6059092 Jerue et al. May 2000 A
6060677 Ulrichsen et al. May 2000 A
6076023 Sato Jun 2000 A
6079570 Oppliger et al. Jun 2000 A
6087608 Schlichter Jul 2000 A
6124560 Roos et al. Sep 2000 A
6208908 Boyd et al. Mar 2001 B1
6246023 Kugle Jun 2001 B1
6323452 Bonnet Nov 2001 B1
6390756 Isaacs et al. May 2002 B1
6401936 Isaacs et al. Jun 2002 B1
6505093 Thatcher et al. Jan 2003 B1
6579053 Grams et al. Jun 2003 B1
6685031 Takizawa Feb 2004 B2
6688459 Bonham et al. Feb 2004 B1
6705528 Good Mar 2004 B2
6721444 Gu et al. Apr 2004 B1
6762382 Danelski Jul 2004 B1
6946612 Morikawa Sep 2005 B2
7313464 Perreault et al. Dec 2007 B1
7347376 Biss et al. Mar 2008 B1
7474939 Oda et al. Jan 2009 B2
7516848 Shakes et al. Apr 2009 B1
8662314 Jones et al. Mar 2014 B2
8718814 Clark et al. May 2014 B1
8776694 Rosenwinkel et al. Jul 2014 B2
8811722 Perez Cortes et al. Aug 2014 B2
8823801 Jacobson Sep 2014 B2
8874270 Ando Oct 2014 B2
8972049 Tidhar et al. Mar 2015 B2
9102053 Suzuki Aug 2015 B2
9102055 Konolige et al. Aug 2015 B1
9102336 Rosenwinkel Aug 2015 B2
9120622 Elazary et al. Sep 2015 B1
9227323 Konolige et al. Jan 2016 B1
9256775 Yasunaga Feb 2016 B1
9259844 Xu et al. Feb 2016 B2
9266237 Nomura Feb 2016 B2
9283680 Yasuda et al. Mar 2016 B2
9364865 Kim Jun 2016 B2
9381645 Yarlagadda et al. Jul 2016 B1
9481518 Neiser Nov 2016 B2
9486926 Kawano Nov 2016 B2
9492923 Wellman et al. Nov 2016 B2
9604363 Ban Mar 2017 B2
9751693 Battles et al. Sep 2017 B1
9821464 Stiernagle et al. Nov 2017 B2
9878349 Crest et al. Jan 2018 B2
9926138 Brazeau et al. Mar 2018 B1
9937532 Wagner et al. Apr 2018 B2
9962743 Bombaugh et al. May 2018 B2
9975148 Zhu et al. May 2018 B2
10007827 Wagner Jun 2018 B2
10029865 McCalib, Jr. et al. Jul 2018 B1
10058896 Hicham et al. Aug 2018 B2
10127514 Napoli Nov 2018 B2
10737299 Wagner Aug 2020 B2
11046530 Koga Jun 2021 B2
20010056313 Osborne, Jr. Dec 2001 A1
20020092801 Dominguez Jul 2002 A1
20020147568 Wenzel et al. Oct 2002 A1
20020169698 Chien Nov 2002 A1
20020179502 Cerutti et al. Dec 2002 A1
20030029946 Lieber et al. Feb 2003 A1
20030034281 Kumar Feb 2003 A1
20030038065 Pippin et al. Feb 2003 A1
20040261366 Gillet et al. Dec 2004 A1
20050002772 Stone Jan 2005 A1
20050268579 Natterer Dec 2005 A1
20060022824 Olsen, III et al. Feb 2006 A1
20060045672 Maynard et al. Mar 2006 A1
20060070929 Fry et al. Apr 2006 A1
20060182543 Schaefer Aug 2006 A1
20060190356 Nemet Aug 2006 A1
20070043468 Schaefer et al. Feb 2007 A1
20070209976 Worth et al. Sep 2007 A1
20080046116 Khan et al. Feb 2008 A1
20080181485 Beis et al. Jul 2008 A1
20080181753 Bastian et al. Jul 2008 A1
20100125361 Mougin et al. May 2010 A1
20100260380 Kaeser et al. Oct 2010 A1
20100292841 Wickham Nov 2010 A1
20100318216 Faivre et al. Dec 2010 A1
20110144798 Freudelsperger Jun 2011 A1
20110184555 Kosuge et al. Jul 2011 A1
20110238207 Bastian, II et al. Sep 2011 A1
20110243707 Dumas et al. Oct 2011 A1
20110320036 Freudelsperger Dec 2011 A1
20120118699 Buchmann et al. May 2012 A1
20120177465 Koholka Jul 2012 A1
20120219397 Baker Aug 2012 A1
20130051696 Garrett Feb 2013 A1
20130051969 Takeuchi et al. Feb 2013 A1
20130202195 Perez Cortes Aug 2013 A1
20130235372 Voss Sep 2013 A1
20130245824 Barajas et al. Sep 2013 A1
20140067127 Gotou Mar 2014 A1
20140105719 Mueller et al. Apr 2014 A1
20140166549 Ito et al. Jun 2014 A1
20140305847 Kudrus Oct 2014 A1
20140360924 Smith Dec 2014 A1
20150057793 Kawano Feb 2015 A1
20150073589 Khodl et al. Mar 2015 A1
20150081090 Dong Mar 2015 A1
20150081091 Blomquist et al. Mar 2015 A1
20150217937 Marquez Aug 2015 A1
20150224650 Xu et al. Aug 2015 A1
20150283586 Dante et al. Oct 2015 A1
20150306634 Maeda et al. Oct 2015 A1
20150352721 Wicks et al. Dec 2015 A1
20150375398 Penn et al. Dec 2015 A1
20150378345 Winkler Dec 2015 A1
20160136816 Pistorino May 2016 A1
20160221762 Schroader Aug 2016 A1
20160228921 Doublet et al. Aug 2016 A1
20160243704 Vakanski et al. Aug 2016 A1
20160244262 O'Brien et al. Aug 2016 A1
20160379076 Nobuoka et al. Dec 2016 A1
20170024896 Houghton et al. Jan 2017 A1
20170043953 Battles et al. Feb 2017 A1
20170050315 Henry et al. Feb 2017 A1
20170066597 Hiroi Mar 2017 A1
20170080566 Stubbs et al. Mar 2017 A1
20170087731 Wagner et al. Mar 2017 A1
20170128986 Sterkel May 2017 A1
20170136632 Wagner et al. May 2017 A1
20170137232 Messner May 2017 A1
20170157648 Wagner et al. Jun 2017 A1
20170157649 Wagner Jun 2017 A1
20170173638 Wagner et al. Jun 2017 A1
20170225330 Wagner et al. Aug 2017 A1
20180075406 Kingston et al. Mar 2018 A1
20180085788 Engel et al. Mar 2018 A1
20180127219 Wagner et al. May 2018 A1
20180148272 Wagner et al. May 2018 A1
20180186572 Issing Jul 2018 A1
20180265291 Wagner et al. Sep 2018 A1
20180265298 Wagner et al. Sep 2018 A1
20180265311 Wagner et al. Sep 2018 A1
20180273295 Wagner et al. Sep 2018 A1
20180273296 Wagner et al. Sep 2018 A1
20180273297 Wagner et al. Sep 2018 A1
20180273298 Wagner et al. Sep 2018 A1
20180282065 Wagner et al. Oct 2018 A1
20180282066 Wagner et al. Oct 2018 A1
20180312336 Wagner et al. Nov 2018 A1
20180327198 Wagner et al. Nov 2018 A1
20180330134 Wagner et al. Nov 2018 A1
20180333749 Wagner et al. Nov 2018 A1
20190022702 Vegh et al. Jan 2019 A1
20190047786 Suzuki Feb 2019 A1
20190102712 Duca Apr 2019 A1
20190329979 Wicks et al. Oct 2019 A1
20210061563 Ueda et al. Mar 2021 A1
Foreign Referenced Citations (53)
Number Date Country
2006204622 Mar 2007 AU
1033604 Jul 1989 CN
1671489 Sep 2005 CN
101482879 Jul 2009 CN
101971221 Feb 2011 CN
102363354 Feb 2012 CN
102430530 May 2012 CN
102621155 Aug 2012 CN
202539084 Nov 2012 CN
103129783 Jun 2013 CN
103942518 Jul 2014 CN
104093650 Oct 2014 CN
104137051 Nov 2014 CN
108700869 Oct 2018 CN
3919865 Dec 1990 DE
19510392 Sep 1996 DE
102004001181 Aug 2005 DE
102004013353 Oct 2005 DE
102005061309 Jul 2007 DE
102007023909 Nov 2008 DE
102007038834 Feb 2009 DE
102010002317 Aug 2011 DE
102012102333 Sep 2013 DE
102014111396 Feb 2016 DE
0235488 Sep 1987 EP
837415 Apr 1998 EP
1995192 Nov 2008 EP
2053350 Apr 2009 EP
2511653 Oct 2012 EP
2823899 Jan 2015 EP
2084531 Apr 1982 GB
2356383 May 2001 GB
2507707 May 2014 GB
S54131278 Oct 1979 JP
S63310406 Dec 1988 JP
H0395001 Apr 1991 JP
H05324662 Dec 1993 JP
H08157016 Jun 1996 JP
2002175543 Jun 2002 JP
2003150230 May 2003 JP
2007182286 Jul 2007 JP
2008037567 Feb 2008 JP
101413393 Jun 2014 KR
2005022076 Mar 2005 WO
WO-2005022076 Mar 2005 WO
2007009136 Jan 2007 WO
2010034044 Apr 2010 WO
2010099873 Sep 2010 WO
2011038442 Apr 2011 WO
2014166650 Oct 2014 WO
2015118171 Aug 2015 WO
2015162390 Oct 2015 WO
2017036780 Mar 2017 WO
Non-Patent Literature Citations (37)
Entry
Notice on the Second Office and the Second Office Action, along with its English translation, issued by the China National Intellectual Property Administration in related Chinese Patent Application No. 201680081764.5 dated Apr. 13, 2021, 14 pages.
Examiner's Report issued by the Canadian Intellectual Property Office dated Dec. 7, 2020 in related Canadian Patent Application No. 2,998,544, 4 pages.
Examiner's Report issued by the Innovation, Science and Economic Development Canada in related Canadian Patent Application No. 3,009,102 dated Jan. 12, 2021, 3 pages.
International Preliminary Report on Patentability issued by the International Bureau of WIPO in related International Application No. PCT/US2016/050949 dated Mar. 13, 2018, 10 pages.
International Search Report and Written Opinion issued by the International Searching Authority in related International Application No. PCT/US2016/050949 dated Dec. 8, 2016, 13 pages.
International Search Report and Written Opinion issued by the International Searching Authority in related International Application No. PCT/US2016/066786 dated Mar. 20, 2017, 14 pages.
International Preliminary Report on Patentability issued by the International Bureau of WIPO in related International Application No. PCT/US2016/066786 dated Jun. 19, 2018, 11 pages.
Non-Final Office Action issued by the U.S. Patent and Trademark Office dated May 22, 2017 in related U.S. Appl. No. 15/228,692, 13 pages.
Bohg, Jeannette, et al., “Data-Driven Grasp Synthesis—A Survey,” Transactions on Robotics, pp. 289-309, Apr. 14, 2016.
Rembold, Derk et al., “Object Turning for Barcode Search,” Proceedings of the 2000 1EEE/RSK—Int'l Conf. on Intelligent Robots and Systems, p. 1267, Oct. 31, 2000.
Cipolla, Roberto et al., “Visually Guided Grasping in Unstructured Environments,” Journal of Robotics and Autonomous Systems, pp. 337-346, Mar. 3, 2001.
Klingbeil, Ellen et al., “Grasping with Application to an Autonomous Checkout Robot,” Proceedings—IEEE Int'l Conf. on Robotics and Automation, pp. 2837-2844, May 9, 2011.
Non-Final Office Action issued by the U.S. Patent and Trademark Office dated Jun. 18, 2019 in related U.S. Appl. No. 15/982,238, 27 pages.
Final Office Action issued by the U.S. Patent and Trademark Office dated Nov. 7, 2019 in related U.S. Appl. No. 15/982,238, 15 pages.
First Examiner's Report issued by the Canadian Intellectual Property Office dated Jan. 21, 2019 in related Canadian Patent Application No. 2,998,544, 4 pages.
Examiner's Report issued by the Canadian Intellectual Property Office on Jan. 6, 2020 in related Canadian Patent Application No. 2,998,544, 4 pages.
Communication pursuant to Rules 161(1) and 162 EPC issued by the European Patent Office dated Apr. 18, 2018, in related European Patent Application No. 16778496.6, 3 pages.
Communication pursuant to Rules 161(1) and 162 EPC issued by the European Patent Office dated Aug. 9, 2018, in related European Patent Application No. 16826518.9, 3 pages.
First Examiner's Report issued by the Canadian Intellectual Property Office dated Apr. 15, 2019 in related Canadian Patent Application No. 3,009,102, 3 pages.
Wikipedia, “Machine Vision,” Wikipedia.org, Mar. 1, 2017 (https://en.wikipedia.org/w/index.php?title=Machine_vision&oldid=768036938).
Wikipedia, “Automatic Identification and Data Capture,” Wikipedia.org, Mar. 10, 2017 (https://en.wikipedia.org/w/index.php?title=Automatic-idenification_and_data_capture&oldid=0769563714).
Non-Final Office Action issued by the U.S. Patent and Trademark Office dated Apr. 25, 2017 in related U.S. Appl. No. 15/260,837, 28 pages.
Final Office Action issued by the U.S. Patent and Trademark Office dated Oct. 11, 2017 in related U.S. Appl. No. 15/260,837, 32 pages.
Non-Final Office Action issued by the U.S. Patent and Trademark Office dated Mar. 21, 2019 in related U.S. Appl. No. 15/901,656, 10 pages.
Non-Final Office Action issued by the U.S. Patent and Trademark Office dated Oct. 22, 2019 in related U.S. Appl. No. 15/901,656, 13 pages.
Examiner's Report issued by the Canadian Intellectual Property Office dated Mar. 6, 2020 in related Canadian Patent Application No. 3,009,102, 3 pages.
Examiner's Report issued by the Innovation, Science and Economic Development Canada (Canadian Intellectual Property Office) dated Nov. 5, 2021 in related Canadian Patent Application No. 2,998,544, 4 pages.
Notice on the Third Office and the Third Office Action, along with its English translation, issued by the China National Intellectual Property Administration in related Chinese Patent Application No. 201680081764.5 dated Oct. 20, 2021, 12 pages.
First Office Action, and its English translation, issued by the China National Intellectual Property Administration dated May 6, 2020 in related Chinese Patent Application No. 201680065881.2, 23 pages.
First Office Action, and its English translation, issued by the China National Intellectual Property Administration dated Jun. 24, 2020 in related Chinese Patent Application No. 201680081764.5, 18 pages.
Notice on the Second Office Action, and the Second Office Action, issued by the China National Intellectual Property Administration in related Chinese Patent Application No. 201680065881.2 dated Jan. 29, 2021, 7 pages.
Communication pursuant to Article 94(3) EPC issued by the European Patent Office in related European Patent Application No. 16778496.6 dated Feb. 24, 2021, 6 pages.
Communication pursuant to Article 94(3) EPC issued by the European Patent Office in related European Patent Application No. 16826518.9 dated Mar. 4, 2021, 10 pages.
Examiner's Report issued by the Innovation, Science and Economic Development Canada (Canadian Intellectual Property Office) in related Canadian Patent Application No. 3,009,102 dated Dec. 31, 2021, 4 pages.
Non-Final Office Action issued by the United States Patent and Trademark Office in related U.S. Appl. No. 16/800,587 dated Feb. 11, 2022, 27 pages.
Notice on Grant of Patent Right for Invention and Search Report, along with its English translation, issued by the China National Intellectual Property Administration in related Chinese Patent Application No. 201680081764.5 dated Mar. 3, 2022, 8 pages.
Communication pursuant to Article 94(3) EPC issued by the European Patent Office in related European Patent Application No. 16826518.9 dated Mar. 22, 2022, 8 pages.
Related Publications (1)
Number Date Country
20200368785 A1 Nov 2020 US
Provisional Applications (1)
Number Date Country
62269640 Dec 2015 US
Continuations (3)
Number Date Country
Parent 16407965 May 2019 US
Child 16900158 US
Parent 15901656 Feb 2018 US
Child 16407965 US
Parent 15228692 Aug 2016 US
Child 15901656 US