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 .
The Amendment, filed on 07/28/2026, has been received and made ofrecord. In response to the Non-Final Office Action, dated 04/28/2026, Claims 1, 3-4, 6-7 and 15-16 are amended, Claims 2 and 12 are cancelled, Claims 1, 3-11 and 13-20 are pending in current application.
Response to Remarks/Arguments
Applicants’ arguments filed on 07/28/2026 have been fully considered.
IDS dated 06/19/2026 has not been considered because the Foreign document number “1120200000675” cited in IDS, dated 06/19/2026, doesn’t match with NPL document and/or Foreign References documents that the applicant filed on 06/19/2026.
In the Arguments/Remarks:
Re: Claim Objection
Claim objections have been withdrawn in view of amendments.
Re: Drawing/Specification Objections
Drawing Objections have been withdrawn in view of amendments.
Re: Claim interpretation Under 35 U.S.C. § 112(f)
Regarding Claim Interpretation Under 35 U.S.C. 112(f), there are no remarks filed, and the examiner has maintained the same Claim interpretation Under 35 U.S.C. § 112(f), set forth in the previous office action.
Re: Rejection of the Claims Under 35 U.S.C. § 103
Applicants’ arguments filed on July 28, 2026 have been fully considered but they are not persuasive.
With regard to independent claim 1, the Applicant argues on page 7of the Applicant’s Remarks that Wagner et al. fails to disclose or suggest the multidimensional matrix structure as defined in independent claim 1. This argument is moot because there is no such “multidimensional matrix structure” defined in claim 1, instead the claim 1 cites “multidimensional database”. Claim Language is examined and analyzed according to its broadest reasonable interpretation in light of the disclosure without reading the Specification into the claim language. . See In re Van Geuns, 988 F.2d 1181, 26 USPQ2d 1057 (Fed. Cir. 1993).The cited prior art, Wagner teaches multidimensional database (see Para. [0082], discloses “3D data regarding the object”, and see Para. [0085]-[0087], discloses “a database that stores dimensions data, and classify item/object based on the data”, and see Para. [0099], [0006]-[0008], discloses “the system using mass, volume, dimensions, shape, etc., data to determine the object class”, same as the claimed invention.
Based on the above explanation, the cited prior art, Wagner teaches the features to those of argued above for independent claim 1.
The same reasoning as applied to the independent claims above also applies to their corresponding dependent claims.
Claim Interpretation
The following is a quotation of 35 U.S.C. 112(f):
(f) Element in Claim for a Combination. – An element in a claim for a combination may be expressed as a means or step for performing a specified function without the recital of structure, material, or acts in support thereof, and such claim shall be construed to cover the corresponding structure, material, or acts described in the specification and equivalents thereof.
The following is a quotation of pre-AIA 35 U.S.C. 112, sixth paragraph:
An element in a claim for a combination may be expressed as a means or step for performing a specified function without the recital of structure, material, or acts in support thereof, and such claim shall be construed to cover the corresponding structure, material, or acts described in the specification and equivalents thereof.
The claims in this application are given their broadest reasonable interpretation using the plain meaning of the claim language in light of the specification as it would be understood by one of ordinary skill in the art. The broadest reasonable interpretation of a claim element (also commonly referred to as a claim limitation) is limited by the description in the specification when 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, is invoked.
As explained in MPEP § 2181, subsection I, claim limitations that meet the following three-prong test will be interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph:
(A) the claim limitation uses the term “means” or “step” or a term used as a substitute for “means” that is a generic placeholder (also called a nonce term or a non-structural term having no specific structural meaning) for performing the claimed function;
(B) the term “means” or “step” or the generic placeholder is modified by functional language, typically, but not always linked by the transition word “for” (e.g., “means for”) or another linking word or phrase, such as “configured to” or “so that”; and
(C) the term “means” or “step” or the generic placeholder is not modified by sufficient structure, material, or acts for performing the claimed function.
Use of the word “means” (or “step”) in a claim with functional language creates a rebuttable presumption that the claim limitation is to be treated in accordance with 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph. The presumption that the claim limitation is interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, is rebutted when the claim limitation recites sufficient structure, material, or acts to entirely perform the recited function.
Absence of the word “means” (or “step”) in a claim creates a rebuttable presumption that the claim limitation is not to be treated in accordance with 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph. The presumption that the claim limitation is not interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, is rebutted when the claim limitation recites function without reciting sufficient structure, material or acts to entirely perform the recited function.
Claim limitations in this application that use the word “means” (or “step”) are being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, except as otherwise indicated in an Office action. Conversely, claim limitations in this application that do not use the word “means” (or “step”) are not being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, except as otherwise indicated in an Office action.
This application includes one or more claim limitations that do not use the word “means,” but are nonetheless being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, because the claim limitation(s) uses a generic placeholder that is coupled with functional language without reciting sufficient structure to perform the recited function and the generic placeholder is not preceded by a structural modifier. Such claim limitation(s) is/are: “transport device” and “sensor unit” in Claim 20; have has been interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, because they use a generic placeholder “means for” coupled with functional language without reciting sufficient structure to achieve the function.
Because this/these claim limitation(s) is/are being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, it/they is/are being interpreted to cover the corresponding structure described in the specification as performing the claimed function, and equivalents thereof.
A review of the specification filed 12/12/2024, in para. [0053], cites “The sensor unit 12 can, for example, be an optical sensor, in particular a camera.” Therefore, “the sensor unit is interpreted as any optical sensor.
Further, review of the original specification, filed 12/12/2024, Para. [0037], cites “a belt conveyor as a transport device”, and/or in para. [0036], cites “a vacuum suction gripper as a transport device”, in para. [0038], cites “rollers as a transport device.”
If applicant does not intend to have this/these limitation(s) interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, applicant may: (1) amend the claim limitation(s) to avoid it/them being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph (e.g., by reciting sufficient structure to perform the claimed function); or (2) present a sufficient showing that the claim limitation(s) recite(s) sufficient structure to perform the claimed function so as to avoid it/them being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph.
Examiner's Note
Examiner has cited particular paragraphs/ columns and line numbers or figures in the references as applied to the claims below for the convenience of the applicant. Although the specified citations are representative of the teachings in the art and are applied to the specific limitations within the individual claim, other passages and figures may apply as well. It is respectfully requested from the applicant, in preparing the responses, to fully consider the references in entirety as potentially teaching
all or part of the claimed invention, as well as the context of the passage as taught by the prior art or disclosed by the examiner. Applicant is reminded that the Examiner is entitled to give the broadest reasonable interpretation to the language of the claims. Furthermore, the Examiner is not limited to Applicants' definition which is not specifically set forth in the claims.
Claim Rejections - 35 USC § 102
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 the appropriate paragraphs of 35 U.S.C. 102 that form the basis for the rejections under this section made in this Office action:
A person shall be entitled to a patent unless –
(a)(1) the claimed invention was patented, described in a printed publication, or in public use, on sale, or otherwise available to the public before the effective filing date of the claimed invention.
Claims 1, 3-11 and 13-20 are rejected under 35 U.S.C. 102(a)(1) as being anticipated by Wagner et al. (US 2020/0130935 A1, this reference is from IDS filed on 07/14/2025) (hereinafter Wagner).
Claim 1. Wagner teaches a method for handling at least one piece good (See Para. [0007]-[0009], discloses “a method of processing objects”), comprising:
determining or obtaining at least one piece good information of the at least one piece good (See Para. [0007], “determined object information associated with the object”, and/or see Para. [0059], “a generalization or description of a packaging, e.g., shape, size, weight, length, width, height, circumference or center or mass [also construed as at least one piece good information as claimed], may be provided as an association event);
assigning the at least one piece good to a piece good class, where the piece good class is obtained from a database based on the piece good information (See Para. [0007], [0099], discloses “classifying the object based on provided and determined object information”, and/or see para. [0104], “the object classification system may assign a different class to the object that allows for faster or riskier motion planning, less precise grasp planning, higher and less precise release characteristics can be implemented”);
determining at least one manipulation parameter for the at least one piece good based on the piece good class (See para. [0057], “determine the efficacy and speed [i.e., one of a manipulation parameter] of a picking station” and/or see Para. [0055]-[0056],[0100], discloses “if the grasped object having heavy weight [i.e., one of a piece good class], the system changes the vacuum level [i.e., one of a manipulation parameter] for a successful grasp and acquisition”, and/or see Para. [0059], “a generalization or description of a packaging, e.g., shape, size, weight, length, width, height, circumference or center or mass, may be provided as an association event, and the system may act in accordance with the closest association event parameters”, and/or see Para. [0110], “due to new packaging of the SKU [i.e., piece good class], the dimensions have changed [i.e., manipulation parameter], and must be grasped using a small cup size.”); and
handling the piece good based on the at least one manipulation parameter (See Para. [0070], “There might be a variety of robot types for handling different item classes, or the robots might be capable of changing effectors, from one size vacuum cup to another”, and/or see Para. [0100], [0115], “for heavier items/object [construed as piece good class] may require a larger vacuum cup [constitute more suction pressure, which is construed as one of the manipulation parameter] and/or move slowly [i.e., another manipulation parameter as claim]. Furthermore, fragile object [i.e., piece good class] might be assigned to a specific person at a manual object processing station, and objects that require another skillset may go to a different person at a manual processing station”, and/or see Para. [0101], “The routing system 550 uses the class information provided by the object classification system 510 along with system information 556 to determine an optimal destination and route to the destination [construed as one of a manipulation parameter]”, and/or see Para. [0108], “the system correctly classifies the product as a cereal box, identical in its handling properties with several cereal boxes already well known to the system. The system is immediately able to process the new SKU, based on its experience with similar products, and its ability to correctly recognize that similarity”, and/or see Para. [0115], “a certain class of items may be usually handled well, but perhaps some of the items are heavier than average. The system has learned to handle them without dropping by moving more slowly”);
wherein the database is a multidimension database (See Para. [0060], “the system might recognize the object and index information in the database”, and/or see Para. [0085], “The worker or system sensors might produce additional information, such as images, weight, and dimensions that are stored in the system software database”. Additionally, see Para. [0082], “3D data regarding the object”, and see Para. [0085]-[0087], discloses “a database that stores dimensions data, and classify item/object based on the data”, and see Para. [0099], [0006]-[0008], discloses “the system using mass, volume, dimensions, etc., data to determine the object class”), and wherein the assignment of the at least one piece good to the piece good class is carried out based on at least two piece good information items (See Para. [0099], “The object classification system 510 uses the first and second sets of information to assign a specific class to the item”).
Claim 3. Wagner teaches the method according to claim 1, wherein, during the assignment, several piece goods with the at least one piece good information are assigned to the piece good class (See Para. [0008], [0099], “assigning the object to a class based on the first set of information and the second set of information”, Para. [0006], “processing objects in the assigned class”, and/or see Para. [0112], “the system learns better grasp behaviors, for all items in the class”, and Para. [0115], discloses “a certain class of items”, hence several piece goods with same piece goods information are assigned to same piece goods class).
Claim 4. Wagner teaches the method according to claim 3, wherein manipulation parameters are identical for the several piece goods of the piece good class (See Para. [0060], “For new objects similar to previously handled objects, the processes predict what are expected to be good routing and handling parameters”, and/or See Para. [0108], “the system correctly classifies the product as a cereal box, identical in its handling properties with several cereal boxes already well known to the system. The system is immediately able to process the new SKU, based on its experience with similar products, and its ability to correctly recognize that similarity”, and/or see Para. [0115], “the heavier items [i.e., same class of similar items] are now handled quickly [i.e., manipulation parameter] and productivity is restored.”).
Claim 5. Wagner teaches the method according to claim 4, wherein the step relating to determining or obtaining at least one piece good information of the at least one piece good occurs in time before the step relating to handling the piece good based on the at least one manipulation parameter (See Para. [0060], “The system may predict object-specific parameters for new objects based on previously seen objects. For new objects similar to previously handled objects, the processes predict what are expected to be good routing and handling parameters”, same as claimed).
Claim 6. Wagner teaches the method according to claim 5, wherein the piece good information comprises at least one parameter about a past tampering and/or a past tampering attempt of the at least one piece good (See Para. [007], [0066], discloses “determine whether the transfer operation was successful, and the type of failure when necessary, and this information is stored in the system database”, and see Para. [0087], “If the initial grasp fails, the system might adjust the process parameters to discourage future grasps at the same location. If the object is dropped during the picking process, the system might adjust the motions to be less aggressive. If damage is noted, parameters might be adjusted for more careful drops, or a different picking station, or a different size vacuum cup”, and/or see Para. [0112], “the system learns better grasp behaviors, for all items in the class, and it does so quickly since it can aggregate experience gained across the entire class”).
Claim 7. Wagner teaches the method according to claim 6, wherein the at least one piece good or similar piece good includes a mail piece (See Para. [0042], [0072], [0089], [0106]-[0107], discloses “the system may be to sort and ship/mail goods [i.e., mail piece] to perform order fulfillment”).
Claim 8. Wagner teaches the method according to claim 6, wherein the piece goods information comprises success of a previous tampering attempt (See Para. [0049]-[0050], [0055]-[0056], “The system uses previously successful arrangements to process objects and collects data about these arrangements to improve the model. At this stage, safe and gradual alterations to the arrangements are made that compound over millions of picks”).
Claim 9. Wagner teaches the method according to claim 8, wherein the success of a previous tampering attempt is determined by a comparison of an expectation and an actual result (See Para. [0066]-[0067], “a reward feedback process, a system may learn from actions that do not achieve positive performance, and learn from actions that do achieve positive performance”, and/or see Para. [0083], “compare statistics from when the same item or similar item was previously gripped. The system may also compare the obtained values, and if the difference lies above a certain threshold, then the system may rule the instance as an instance of picking more than one of the item”).
Claim 10. Wagner teaches the method according to claim 8, further comprising:
adding piece good classes to the database (See Para. [0086], [0087], “class of items are saved in the system database”).
Claim 11. Wagner teaches the method according to claim 10, wherein the adding piece good classes to the database is completed after handling of the piece goods (See Para. [0058], discloses “using previously recorded data based on similar SKUs “, and see Para. [0087], discloses “A similar process is followed each time the object is handled, so that the system builds up in the database a record of all its experience. As this record grows, the item's class will be determined with greater confidence, and other information including process parameters will also be refined”).
Claim 13. Wagner teaches the method according to claim 1, wherein manipulation parameters are identical for all piece goods of a piece goods class (See Para. [0060], “For new objects similar to previously handled objects, the processes predict what are expected to be good routing and handling parameters”, and/or See Para. [0108], “the system correctly classifies the product as a cereal box, identical in its handling properties with several cereal boxes already well known to the system. The system is immediately able to process the new SKU, based on its experience with similar products, and its ability to correctly recognize that similarity”, and/or see Para. [0115], “the heavier items [i.e., same class of similar items] are now handled quickly [i.e., manipulation parameter] and productivity is restored”).
Claim 14. Wagner teaches the method according to claim 1, wherein the step relating to determining or obtaining at least one piece good information of the at least one piece good occurs in time before the step relating to handling the piece good based on the at least one manipulation parameter (See Para. [0060], “The system may predict object-specific parameters for new objects based on previously seen objects. For new objects similar to previously handled objects, the processes predict what are expected to be good routing and handling parameters”, same as claimed).
Claim 15. Wagner teaches the method according to claim 1, wherein the piece good information comprises at least one parameter about a past tampering and/or a past tampering attempt of the at least one piece good (See Para. [007], [0066], discloses “determine whether the transfer operation was successful, and the type of failure when necessary, and this information is stored in the system database”, and see Para. [0087], “If the initial grasp fails, the system might adjust the process parameters to discourage future grasps at the same location. If the object is dropped during the picking process, the system might adjust the motions to be less aggressive. If damage is noted, parameters might be adjusted for more careful drops, or a different picking station, or a different size vacuum cup”, and/or see Para. [0112], “the system learns better grasp behaviors, for all items in the class, and it does so quickly since it can aggregate experience gained across the entire class”).
Claim 16. Wagner teaches the method according to claim 15, wherein the at least one piece good includes a mail piece (See Para. [0042], [0072], [0089], [0106]-[0107], discloses “the system may be to sort and ship/mail goods [i.e., mail piece] to perform order fulfillment”).
Claim 17. Wagner teaches the method according to claim 1, wherein the piece goods information comprises success of a previous tampering attempt (See Para. [0049]-[0050], [0055]-[0056], “The system uses previously successful arrangements to process objects and collects data about these arrangements to improve the model. At this stage, safe and gradual alterations to the arrangements are made that compound over millions of picks”).
Claim 18. Wagner teaches the method according to claim 17, wherein the success of a previous tampering attempt is determined by a comparison of an expectation and an actual result (See Para. [0066]-[0067], “a reward feedback process, a system may learn from actions that do not achieve positive performance, and learn from actions that do achieve positive performance”, and/or see Para. [0083], “compare statistics from when the same item or similar item was previously gripped. The system may also compare the obtained values, and if the difference lies above a certain threshold, then the system may rule the instance as an instance of picking more than one of the item”).
Claim 19. Wagner teaches the method according to claim 1, further comprising:
adding piece good classes to the database (See Para. [0086], [0087], “class of items are saved in the system database”).
Claim 20. Wagner teaches a system for handling at least one piece good, comprising:
at least one transport device for handling piece goods (See Fig. 4 and 21, at least Para. [0089], [0090], discloses “conveyors [i.e., transport device] that carry the packages to robotic picking stations”); and
a sensor unit configured to carry out the method according claim 1 (See Para. [0089], [0099], discloses “sensors including cameras and optical bar code scanners to measure features such as mass, volume, dimensions, shape, stiffness, color, images, etc.”, and/or see Para. [0102], “the system inputs 570 can include inputs from sensors, such as depth sensors, 3d Cameras, RGB cameras, flow sensors, pressure sensors, positional or force sensors attached to the effector, weight sensors, microphones, or other feedback sensors to evaluate whether the interaction of the system with the object is successful or unsuccessful.”).
Conclusion
Applicants’ amendment necessitated the new ground(s) of rejection presented in this Office action. Accordingly, THIS ACTION IS MADE FINAL. See MPEP § 706.07(a). Applicant is reminded of the extension of time policy as set forth in 37 CFR 1.136(a).
A shortened statutory period for reply to this final action is set to expire THREE MONTHS from the mailing date of this action. In the event a first reply is filed within TWO MONTHS of the mailing date of this final action and the advisory action is not mailed until after the end of the THREE-MONTH shortened statutory period, then the shortened statutory period will expire on the date the advisory action is mailed, and any nonprovisional extension fee (37 CFR 1.17(a)) pursuant to 37 CFR 1.136(a) will be calculated from the mailing date of the advisory action. In no event, however, will the statutory period for reply expire later than SIX MONTHS from the mailing date of this final action.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to B M M HANNAN whose telephone number is (571)270-0237. The examiner can normally be reached MONDAY-FRIDAY at 8:30AM-5:30PM.
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If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Adam Mott can be reached at 5712705376. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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/B M M HANNAN/Primary Examiner, Art Unit 3657
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