DETAILED ACTION
Notice of Pre-AIA or AIA Status
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
Claim Rejections - 35 USC § 101
35 U.S.C. 101 reads as follows:
Whoever invents or discovers any new and useful process, machine, manufacture, or composition of matter, or any new and useful improvement thereof, may obtain a patent therefor, subject to the conditions and requirements of this title.
Claims 21-40 are rejected under 35 U.S.C. 101 because the claimed invention is directed a judicial exception (i.e., an abstract idea) without significantly more.
Step 1 – Statutory Categories
As indicated in the preamble of the claim, the examiner finds the claim is directed to a process, machine, manufacture, or composition of matter.(Claims 21-27 are processes and Claims 28-40 are machines). Accordingly, step 1 is satisfied.
Step 2A – Prong 1: was there a Judicial Exception Recited
Claim 28 (and similarly Claims 21 and 35) recites the following abstract concepts that are found to include “abstract idea.” Any additional elements will be analyzed under Step 2A-Prong 2 and Step 2B:
An apparatus comprising at least one processor and at least one non- transitory memory comprising program code, the at least one non-transitory memory and the program code configured to, with the at least one processor, cause the apparatus to:
generate one or more three-dimensional item cells corresponding to each of one or more items in a pallet (See MPEP2106.04(a)(2)(II)(C) Certain Methods of Organizing Human Activity, a series of instructions of how to hedge risk, Bilski v. Kappos, 561 U.S. 593, 595, 95 USPQ2d 1001, 1004 (2010).);
determine one or more removal locations for the one or more items in the pallet utilizing a trained predictive machine learning model (See MPEP2106.04(a)(2)(II)(C) Certain Methods of Organizing Human Activity, a series of instructions of how to hedge risk, Bilski v. Kappos, 561 U.S. 593, 595, 95 USPQ2d 1001, 1004 (2010). And MPEP2106.04(a)(2)(III) – Mental Processes, PEG Example 47, Claim 2, discretizing continuous training data to generate input data by processes including rounding, binning, or clustering continuous data, which may be practically performed in the human mind using observation, evaluation, judgment, and opinion); and
cause one or more movements of the one or more items to the one or more removal locations (See MPEP2106.04(a)(2)(II)(C) Certain Methods of Organizing Human Activity, a series of instructions of how to hedge risk, Bilski v. Kappos, 561 U.S. 593, 595, 95 USPQ2d 1001, 1004 (2010).).
Claim 28 (and similarly Claims 21 and 35) is directed to a series of steps to cause items to be moved to removal locations, which is managing personal behavior and thus grouped as a certain method of organizing human interactions and using mental processes. The mere nominal recitation of apparatus, processor, and non-transitory memory comprising code does not take the claim out of the method of organizing human interactions. Thus, Claim 28 (and similarly Claims 21 and 35) recites an abstract idea.
Step 2A – Prong 2: Can the Judicial Exception Recited be integrated into a practical application
Limitations that are indicative of integration into a practical application:
Improvements to the functioning of a computer, or to any other technology or technical field - see MPEP 2106.05(a)
Applying or using a judicial exception to effect a particular treatment or prophylaxis for a disease or medical condition – see Vanda Memo
Applying the judicial exception with, or by use of, a particular machine - see MPEP 2106.05(b)
Effecting a transformation or reduction of a particular article to a different state or thing - see MPEP 2106.05(c)
Applying or using the judicial exception in some other meaningful way beyond generally linking the use of the judicial exception to a particular technological environment, such that the claim as a whole is more than a drafting effort designed to monopolize the exception - see MPEP 2106.05(e) and Vanda Memo
Limitations that are not indicative of integration into a practical application:
Adding the words “apply it” (or an equivalent) with the judicial exception, or mere instructions to implement an abstract idea on a computer, or merely uses a computer as a tool to perform an abstract idea - see MPEP 2106.05(f)
Adding insignificant extra-solution activity to the judicial exception - see MPEP 2106.05(g)
Generally linking the use of the judicial exception to a particular technological environment or field of use – see MPEP 2106.05(h)
The identified abstract idea of exemplary Claim 28 (and similarly Claims 21 and 35) is not integrated into a practical application. The additional elements are: apparatus, processor, and non-transitory memory comprising code that implements the underlying abstract idea. These additional elements are broadly recited computer elements that do not add a meaningful limitation to the abstract idea because they amount to merely using a computer as a tool to perform an abstract idea - see MPEP 2106.05(f).
Accordingly, alone and in combination, these additional elements do not integrate the abstract idea into a practical application. Claim 28 (and similarly Claims 21 and 35) is directed to an abstract idea.
Step 2B – Significantly More Analysis
Claim 28 (and similarly Claims 21 and 35) does not include additional elements that are sufficient to amount to significantly more than the judicial exception because, when considered separately and in combination, steps a) generating one or more three-dimensional item cells corresponding to each of one or more items in a pallet, b) determining one or more removal locations for the items int the pallet utilizing a trained predictive machine learning model, and c) causing one or more movements to the one or more items to the one or more removal locations, do not add significantly more to the exception because they amount to merely using a computer as a tool to perform an abstract idea - see MPEP 2106.05(f). Claim 28 (and similarly Claims 21 and 35) is ineligible.
Claim 22 (and similarly Claims 29 and 36) recites the abstract idea of organizing human activity. See MPEP 2106.04(a)(2)(II).
Claim 23 (and similarly Claims 30 and 37) recites the abstract idea of organizing human activity. See MPEP 2106.04(a)(2)(II).
Claim 24 (and similarly Claims 31 and 38) recites the abstract idea of organizing human activity. See MPEP 2106.04(a)(2)(II).
Claim 25 (and similarly Claims 32 and 39) recites the abstract idea of organizing human activity. See MPEP 2106.04(a)(2)(II).
Claim 26 (and similarly Claims 33 and 40) recites the abstract idea of organizing human activity. See MPEP 2106.04(a)(2)(II).
Claim 27 (and similarly Claim 34) recites the abstract idea of organizing human activity. See MPEP 2106.04(a)(2)(II).
Claim Rejections - 35 USC § 103
In the event the determination of the status of the application as subject to AIA 35 U.S.C. 102 and 103 (or as subject to pre-AIA 35 U.S.C. 102 and 103) is incorrect, any correction of the statutory basis (i.e., changing from AIA to pre-AIA ) for the rejection will not be considered a new ground of rejection if the prior art relied upon, and the rationale supporting the rejection, would be the same under either status.
The following is a quotation of 35 U.S.C. 103 which forms the basis for all obviousness rejections set forth in this Office action:
A patent for a claimed invention may not be obtained, notwithstanding that the claimed invention is not identically disclosed as set forth in section 102, if the differences between the claimed invention and the prior art are such that the claimed invention as a whole would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention pertains. Patentability shall not be negated by the manner in which the invention was made.
Claim(s) 21-40 is/are rejected under 35 U.S.C. 103 as being unpatentable over US Pat Pub 2022/0402139 “Pidaparthi”, in view of US Pat 11,514,386 “Soles”.
As per Claims 21, 28, and 35, Pidaparthi discloses a computer-implemented method, an apparatus, and a computer program product comprising:
determining, by the one or more processors, one or more removal locations for the one or more items in the pallet utilizing a trained predictive machine learning model (Pidaparthi: [0059] a machine learning process to model a state of a pallet such as to generate a model of a stack on the pallet. determining an efficient (e.g., maximizing/optimizing an efficiency) manner for palletizing/de-palletizing one or more items); and
causing, by the one or more processors, one or more movements of the one or more items to the one or more removal locations (Pidaparthi: [0062] picking strategy may include an indication of a picking location (e.g., a location on the item at which the robotic arm 102 is to engage the item such as via the end effector). The picking strategy may include a force to be applied to pick the item and/or a holding force by which the robotic arm 102 is to grasp the item while moving the item from a source location to the destination location).
Pidaparthi fails to disclose a computer-implemented method, an apparatus, and a computer program product comprising:
generating, by one or more processors, one or more three-dimensional item cells corresponding to each of one or more items in a pallet.
Soles teaches a computer-implemented method, an apparatus, and a computer program product comprising:
generating, by one or more processors, one or more three-dimensional item cells corresponding to each of one or more items in a pallet (Soles: See Fig. 4-10, showing 3D object placement representations within a packing volume teaching a 3D object-position model. Column 12, lines 17-32, a packing plan may comprise a configuration for placing objects within a packing area in preparation for shipment. A packing area may comprise a two-dimensional or three-dimensional shape defining the space inside of which objects may be placed. Additionally, or in the alternative, a packing area comprises a three-dimensional volume having one or more outer surfaces that define the volume inside of which objects are to be placed. Column 14, lines 61-67 and Column 15, lines 1-13, generating picklists, packing plans, and instructions for moving any object (including, for example, items, packages, and containers) onto any packing surface or into any packing volume. For example, warehouse management system 110 may generate picklists, packing plans, and instructions for packing items, packages, or containers into a box, shipping container, transportation vehicle 156, or onto a shelf, pallet, staging area, designated location, or the like. According to some embodiments, an object may simultaneously act as more than one of an item, package, or container, according to particular needs. For example, an object may be a container for receiving one or more packages, in one instance, an item for packing into one or more packages, in a second instance, and/or a package for receiving one or more items, in another instance. For example, a pallet may be a container for receiving one or more packages and simultaneously be a package for packing onto a truck, Column 20, lines 1-46 the displayed group of selectable menu options 502-506 comprise packing patterns that are predetermined based on the group of objects to be packed and the type and/or shape of the packing area including, for example, the size, weight, crushability, required orientation, and/or other attributes of the objects such that the predetermined packing patterns generate a configuration with structured layers and stacks suitable for the objects and packing area to be packed. … In response to selecting a packing pattern from menu 500, warehouse management system 110 generates a packing plan for packing a group of objects in a packing area according to the selected packing pattern. The packing plan is used to generate packing instructions which may be transmitted to one or more instruction rendering devices 120 which renders and displays visual elements comprising representations of objects aligned with the packing area and indicating where in the packing area the objects are to be placed. According to embodiments, representations of objects may comprise, for example, a translucent shape displayed to appear in the approximate size, shape, and orientation of the object and in a location within the packing area where the object is to be packed. Additionally, instructions may comprise directions, feedback, and other visual elements, as described in more detail below.
The claims do not expressly require segmentation of each item into multiple voxels/cells. For example the claim says “one or more” three-dimensional item cells, therefore, a single 3D bounded item volume/representation may satisfy the limitation; and Soles teaches generating a 3D object representation with size, shape, orientation, and location within a 3D packing volume.).
Therefore, it would have been obvious to one of ordinary skill in the art at the time the invention was filed to modify Pidaparthi to include generating three-dimensional cells as taught by Soles, when determining one or more placement locations on a pallet as taught by Pidaparthi with the motivation of packing objects in a particular configuration to avoid damage during shipment (Soles: Column 1, lines 32-45).
As per Claims 22, 29, and 36, Pidaparthi discloses a computer-implemented method, an apparatus, and a computer program product, wherein each of the one or more removal locations comprises one or more three-dimensional pallet cells (Pidaparthi: [0043]).
As per Claims 23, 30, and 37, Pidaparthi discloses a computer-implemented method, an apparatus, and a computer program product, wherein, when determining the one or more removal locations, the computer-implemented method further comprises:
determining, by the one or more processors, one or more location scores associated with the one or more removal locations (Pidaparthi: [0038]).
As per Claims 24, 31, and 38, Pidaparthi discloses a computer-implemented method, an apparatus, and a computer program product, wherein the one or more location scores correspond to one or more pallet configurations associated with one or more pallets (Pidaparthi: [0038]).
As per Claims 25, 32, and 39, Pidaparthi discloses a computer-implemented method, an apparatus, and a computer program product, wherein, when determining the one or more removal locations, the computer-implemented method further comprises:
determining, by the one or more processors, a first removal location for a first item of the one or more items that is associated with a first item volume (Pidaparthi: [0071]); and
subsequent to determining the first removal location, determining, by the one or more processors, a second removal location for a second item of the one or more items that is associated with a second item volume larger than the first item volume (Pidaparthi: [0071]).
As per Claims 26, 33, and 40, Pidaparthi discloses a computer-implemented method, an apparatus, and a computer program product, wherein the first item volume is the smallest among item volumes associated with the one or more items (Pidaparthi: [0071]).
As per Claims 27 and 39, Pidaparthi discloses a computer-implemented method and an apparatus, wherein the one or more removal locations are associated with one or more removal identifiers, wherein the computer- implemented method further comprises:
determining, by the one or more processors, a removal sequence based on the one or more removal identifiers (Pidaparthi: [0043]).
Conclusion
Any inquiry concerning this communication or earlier communications from the examiner should be directed to REVA R MOORE whose telephone number is (571)270-7942. The examiner can normally be reached M-Th: 9:00-6:00.
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If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Fahd Obeid can be reached at 571-270-3324. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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/REVA R MOORE/ Examiner, Art Unit 3627
/FAHD A OBEID/ Supervisory Patent Examiner, Art Unit 3627
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