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 .
Status of Claims
Claims 1-20 were previously pending and subject to a non-final rejection dated February 26, 2026. In Response, submitted May 26, 2026, claims 1-20 were cancelled, and claims 21-40 were added. Therefore, claims 21-40 are currently pending and subject to the following final rejection.
Response to Arguments
Applicant’s remarks on Page 9 of the Response do not address the previous rejection of claims over 112(a) and 112(b), however these rejections are withdrawn in light of the amended claims.
Applicant’s remarks on Page 9 of the Response, regarding the previous rejection of the claims under 35 U.S.C. 101, have been fully considered and are not found persuasive.
On Page 9 of the Response, Applicant argues “Independent claim 21 is believed to be allowable over the prior art. It particularly recites patent eligible subject matter since it states 'controlling the delivery robot to travel via a selected delivery path having a shortest predicted delivery time.' The remaining claims depend from and add further features to one of the independent claims. It is respectfully submitted that these dependent claims are allowable by reason of depending from an allowable claim, as well as for adding new features, and that it is not necessary to separately address these dependent claims at this time.”
Examiner notes, as discussed further in the detailed rejection below, the “travel[ling] via a selected delivery path having a shortest predicted delivery time” is a recitation of the abstract idea. “Controlling the delivery robot” appears to simply amount to providing instructions to be carried out beyond the scope of the invention, and therefore fails to integrate the abstract idea into a practical application or amount to significantly more.
Applicant’s remarks on Pages 9 of the Response, regarding the previous rejection of the claims under 35 U.S.C. 103, have been fully considered and are found persuasive in part.
On Page 9 of the Response, “The new independent claims 30 and 38 are essentially based on claim 20, which the Examiner considers allowable. See Office Action, page 45.”
Examiner notes, claim 20 was not indicated as allowable, but rather as “novel and non-obvious over the prior art”, which is wholly separate from allowability. As indicated below and in the previous office action, claims indicated as “novel and non-obvious” are still subject to other applicable rejection of the office action, such as 101.
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.
Claim 30 invokes means plus function interpretation under 35 U.S.C. 112(f) due to the recitation of “a data analyzer comprising”, “a people counter configured to obtain information about a number of people”, “a crowdedness analyzer configured to determine crowdedness of elevator sections and entry-and-exit gate section”, “a traffic analyzer configured to determine traffic information”, “a path analyzer configured to calculate latency information”, “a delivery time prediction unit configured to: predict delivery times [… and] detect that the traffic information and the latency information cannot be calculated”, and “a delivery path determining unit configure to: generate prioritized delivery paths [… and] determine the delivery path” with no corresponding recitation of structure, material, or act for performing the claimed function. The “a data analyzer”, “a people counter”, “a crowdedness analyzer”, “a traffic analyzer”, “a path analyzer”, “a delivery time prediction unit”, and “a delivery path determining unit” are defined in the specification as “the terms ‘unit’, ‘part’ or ‘portion’, ‘-er’, and ‘module’ in the specification refer to a unit that processes at least one function or operation, which may be implemented by hardware, software, or a combination of hardware and software” “the apparatus 100 for predicting a delivery time and a delivery path based on crowd estimation may include a prediction unit 110, a sensor interface 120, data analyzer 130, a robot service interface 140 and a training unit 150” “The data analyzer 130 may include a people counter 131, a crowdedness analyzer 132 and the traffic analyzer 133. The people counter 131 may collect the people counting information for each of the plurality of paths through a camera sensor, a lidar sensor, and a thermal imaging sensor. The people counting information may include the number of persons within the specific space identified through a camera sensor, or the like. The crowdedness analyzer 132 may calculate crowdedness of each of the plurality of paths based on the people counting information. The more persons on the path, the greater the crowdedness may be. The crowdedness analyzer 132 may collect crowdedness of a specific section including the elevator section and the entry-and-exit gate section on the paths based on entry and exit log data obtained from the elevator sensor and the entry-and-exit gate sensor. Each of the plurality of paths may include a plurality of specific sections. The crowdedness analyzer 132 may calculate the crowdedness of corresponding sections based on real-time records of entry and exit of the elevator and/or the entry-and-exit gate. That is, the more records of entry and exit there are, the greater the crowdedness maybe.” “The prediction unit 110 may include a path analyzer 111, a delivery time prediction unit 112 and a delivery path determining unit 113” “at least some configurations or functions of an apparatus and method for predicting a robot the delivery time and a robot delivery path based on crowd estimation according to an embodiment may be implemented as a program or software executable by the computing device 900, and program or software may be stored in a computer-readable medium … may be implemented by using hardware or circuitry of the computing device 900, or may also be implemented as separate hardware or circuitry that maybe electrically connected to the computing device 900.” in paras. 34, 47, 55-59, 67, and 127-128. Claims depending on the above are also invoked by way of their dependency.
Claim 33 invokes means plus function interpretation under 35 U.S.C. 112(f) due to the recitation of “a training unit configured to compare the predicted delivery time and an actual delivery time” with no corresponding recitation of structure, material, or act for performing the claimed function. The “training unit” is defined in the specification as “the terms ‘unit’, ‘part’ or ‘portion’, ‘-er’, and ‘module’ in the specification refer to a unit that processes at least one function or operation, which may be implemented by hardware, software, or a combination of hardware and software” “the apparatus 100 for predicting a delivery time and a delivery path based on crowd estimation may include a prediction unit 110, a sensor interface 120, data analyzer 130, a robot service interface 140 and a training unit 150.” “the training unit 150 may compare the predicted delivery time with respect to the finally determined delivery path and an actual delivery time, update the delivery time prediction model based on the comparison result when the comparison result satisfies a specific criterion, and store the comparison result in the database DB when the comparison result does not satisfy the specific criterion.” in paras. 34, 45, and 84. Claims depending on the above are also invoked by way of their dependency.
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.
Because these claim limitation(s) are being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, they are being interpreted to cover the corresponding structure described in the specification as performing the claimed function, and equivalents thereof.
If applicant does not intend to have these limitations interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, applicant may: (1) amend the claim limitations to avoid 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 limitations recite sufficient structure to perform the claimed function so as to avoid them being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph.
Claim Rejections - 35 USC § 112
The following is a quotation of the first paragraph of 35 U.S.C. 112(a):
(a) IN GENERAL.—The specification shall contain a written description of the invention, and of the manner and process of making and using it, in such full, clear, concise, and exact terms as to enable any person skilled in the art to which it pertains, or with which it is most nearly connected, to make and use the same, and shall set forth the best mode contemplated by the inventor or joint inventor of carrying out the invention.
The following is a quotation of the first paragraph of pre-AIA 35 U.S.C. 112:
The specification shall contain a written description of the invention, and of the manner and process of making and using it, in such full, clear, concise, and exact terms as to enable any person skilled in the art to which it pertains, or with which it is most nearly connected, to make and use the same, and shall set forth the best mode contemplated by the inventor of carrying out his invention.
Claims 21-29, 36, and 37 are rejected under 35 U.S.C. 112(a) or 35 U.S.C. 112 (pre-AIA ), first paragraph, as failing to comply with the written description requirement. The claim(s) contains subject matter which was not described in the specification in such a way as to reasonably convey to one skilled in the relevant art that the inventor or a joint inventor, or for applications subject to pre-AIA 35 U.S.C. 112, the inventor(s), at the time the application was filed, had possession of the claimed invention.
Claim 21 recites “controlling the delivery robot to travel via a selected delivery path”
Examiner initially notes that while there is no haec verba requirement, newly added claim limitations must be supported in the specification through express, implicitly, or inherent disclosure (MPEP 2183). Further, when an explicit limitation in a claim "is not present in the written description whose benefit is sought it must be shown that a person of ordinary skilled would have understood, at the time the patent application was filed, that the description requires the limitation," Hyatt v. Boone, 146 F.3d 1348,1353, 47 USPQ2d 1128, 1131 (Fed. Cir. 1998), MPEP 2163.
Examiner notes that Paragraph [0041] of Applicant’s Specification states that “The delivery robot 10 may move inside the building according to a stored movement path plan”.
That is, no description or support is found in the Applicant’s specification or claims regarding how the movement of the delivery robot is controlled by claimed invention. Rather, the delivery paths appear to act as mere instruction provided to the delivery robot to be carried out beyond the scope of the claimed invention.
Claims 22-29 are rejected by virtue of dependency.
Claim 36 recites “the apparatus is a server” and claim 37 recites “the apparatus is a cloud based server”.
Examiner initially notes that while there is no haec verba requirement, newly added claim limitations must be supported in the specification through express, implicitly, or inherent disclosure (MPEP 2183). Further, when an explicit limitation in a claim "is not present in the written description whose benefit is sought it must be shown that a person of ordinary skilled would have understood, at the time the patent application was filed, that the description requires the limitation," Hyatt v. Boone, 146 F.3d 1348,1353, 47 USPQ2d 1128, 1131 (Fed. Cir. 1998), MPEP 2163.
Examiner notes that Paragraph [0123]-[0124] of Applicant’s Specification states that “an apparatus and method for predicting robot the delivery time and robot delivery path based on crowd estimation according to embodiments may be implemented by using a computing device 900. The computing device 900 may include at least one of a processor 910, a memory 930, the user interface input device 940, the user interface output device 950 and a storage device 960 that communicate through a bus 920. The computing device 900 may also include a network interface 970 electrically connected to a network 90. The network interface 970 may transmit or receive signals with other entities through the network 90.”
That is, no description or support is found in the Applicant’s specification or claims describing the ‘apparatus” as anything more than generic components communicating via a bus.
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 to an abstract idea without significantly more.
Step 1
Claims 21-29 are directed to a method (i.e., a process); claims 30-37 are directed to an apparatus (i.e., a machine) as interpreted above; claims 38-40 are directed to a method (i.e., a process). Therefore, claims 21-40 all fall within the one of the four statutory categories of invention as interpreted.
Step 2A, Prong One
Independent claim 21 substantially recites receiving a stored movement path plan including a plurality of candidate delivery paths to a destination;
collecting crowd estimation information associated with the plurality of candidate delivery paths;
determining crowdedness of elevator sections and entry-and-exit gate sections based on entry and exit log data obtained;
determining traffic information for each candidate delivery path based on: (i) information about a number of people collected, and (ii) the crowdedness;
predicting delivery times respectively corresponding to the candidate delivery paths based on the traffic information and latency information; and
travelling via a selected delivery path having a shortest predicted delivery time,
wherein the selected delivery path is dynamically updated during the delivery according to real-time updated traffic information.
Independent claim 30 substantially recites (i) obtaining information about a number of people;
(ii) determining crowdedness of elevator sections and entry-and-exit gate sections based on entry and exit log data obtained, and
(iii) determining traffic information corresponding to a plurality of candidate delivery paths based on the information about the number of people and a crowdedness;
calculating latency information corresponding to the plurality of candidate delivery paths;
predicting delivery times respectively corresponding to the plurality of candidate delivery paths based on the traffic information and the latency information;
detecting that the traffic information and the latency information cannot be calculated due to a defect or an error; and
in response to detecting the defect or the error, predicting average delivery times respectively corresponding to the plurality of candidate delivery paths based on: (i) historical traffic information including the crowdedness and the information about the number of people stored during a predetermined time period, and (ii) historical average latency information; and
generating prioritized delivery paths based on the predicted average delivery times;
determining an initial delivery path as a first delivery path having a highest priority; and
dynamically changing the initial delivery path to a second delivery path having a subsequent priority according to real-time updated traffic information while performing delivery.
Independent claim 38 substantially recites receiving a stored movement path plan including a plurality of candidate delivery paths to a destination;
collecting crowd estimation information associated with the plurality of candidate delivery paths along the plurality of candidate delivery paths;
determining traffic information and latency information respectively corresponding to the plurality of candidate delivery paths based on the crowd estimation information;
predicting delivery times respectively corresponding to the plurality of candidate delivery paths based on the traffic information and the latency information;
determining a selected delivery path having a shortest predicted delivery time among the plurality of candidate delivery paths;
detecting that the traffic information and the latency information cannot be calculated due to a defect or error; and
in response to detecting that the traffic information and the latency information cannot be calculated:
predicting average delivery times respectively corresponding to the plurality of candidate delivery paths based on: (i) historical traffic information including crowdedness and information about a number of people stored during a predetermined time period, and (ii) historical average latency information;
generating a plurality of prioritized delivery paths based on the predicted average delivery times;
determining an initial delivery path as a first delivery path having a highest priority; and
dynamically changing the initial delivery path to a second delivery path having a subsequent priority according to real-time updated traffic information while performing delivery.
The limitations stated above are processes/functions that under broadest reasonable interpretation covers “certain methods of organizing human activity” (commercial interactions) of “predicting a delivery time and a delivery path based on crowd estimation” (specification, para. 2). Therefore, the claim recites an abstract idea.
Step 2A, Prong Two
The judicial exception is not integrated into a practical application. Claims 1 and 11 as a whole amount to: (i) merely invoking generic components as a tool to perform the abstract idea or “apply it” (or an equivalent), (ii) generally links the use of a judicial exception to a particular technological environment or field of use, and (iii) adds insignificant extra-solution activity to the judicial exception. The claim recites the additional elements of: (i) sensors associated with the plurality of candidate delivery paths (for collecting data) (claim 21) / at least one sensor (for collecting data) (claim 30) / a plurality of sensors disposed along the plurality of candidate delivery paths (for collecting data) (claim 38), (ii) a data analyzer (claim 30), (iii) a path analyzer (claim 30), (iv) a delivery time prediction unit (claim 30), (v) a delivery path determining unit (claim 30), (vi) a delivery robot (claims 21, 30, 38), (vii) at least a camera sensor (claims 21, 30), (viii) an elevator sensor (claims 21, 30), (ix) an entry-and-exit gate sensor (claims 21, 30), (x) a thermal imaging sensor (claims 21, 30), (xi) controlling the delivery robot (claim 21), (xii) a people counter (claim 30), (xiii) a crowdedness analyzer (claim 30), (xiv) a traffic analyzer (claim 30).
The additional element of (i) sensors associated with the plurality of candidate delivery paths (for collecting data) / at least one sensor (for collecting data) / a plurality of sensors disposed along the plurality of candidate delivery paths (for collecting data), (vi) a delivery robot, (vii) at least a camera sensor, (viii) an elevator sensor, (ix) an entry-and-exit gate sensor, (x) a thermal imaging sensor, (xi) controlling the delivery robot is recited at a high-level of generality (See Para. 48 of Applicant’s Specification disclosing the sensors on the plurality of paths (for collecting data) / the sensor (for collecting data), the at least a camera sensor, the elevator sensor, the entry-and-exit gate sensor, and the thermal imaging sensor, Para. 40 disclosing the delivery robot, Para. 41 disclosing controlling the delivery robot) when viewed as whole/ordered combination, do no more than generally link the use of the judicial exception to a particular technological environment or field of use (i.e., data sensors and delivery robots) (See MPEP 2106.05(h)). Furthermore, (i) sensors associated with the plurality of candidate delivery paths (for collecting data) / at least one sensor (for collecting data) / a plurality of sensors disposed along the plurality of candidate delivery paths (for collecting data), when viewed as whole/ordered combination, amounts to insignificant extra-solution activity (e.g., pre-solution activity), such as mere data gathering (See MPEP 2106.05(g)).
The additional elements of (ii) a data analyzer, (iii) a path analyzer, (iv) a delivery time prediction unit, (v) a delivery path determining unit, (xii) a people counter, (xiii) a crowdedness analyzer, (xiv) a traffic analyzer are recited at a high-level of generality (See Paras. 34 and 47 of Applicant's Specification discussing the data analyzer, Paras. 34, 47, and 67 discussing the path analyzer, a delivery time prediction unit, and a delivery path determining unit, Paras. 34, 55, 56 discussing the people counter, Paras. 34, 55, 57-58 discussing the crowdedness analyzer, Paras. 34, 55, 62 discussing the traffic analyzer), such that, when viewed as whole/ordered combination, it amounts to no more than mere instruction to apply the judicial exception using generic computer components or “apply it” (See MPEP 2106.05(f)).
Accordingly, these additional elements, when viewed as a whole/ordered combination [See Figures 2 and 3 showing all the additional elements (i) sensors associated with the plurality of candidate delivery paths (for collecting data) / at least one sensor (for collecting data) / a plurality of sensors disposed along the plurality of candidate delivery paths (for collecting data), (ii) a data analyzer, (iii) a path analyzer, (iv) a delivery time prediction unit, (v) a delivery path determining unit, (vi) a delivery robot, (vii) at least a camera sensor, (viii) an elevator sensor, (ix) an entry-and-exit gate sensor, (x) a thermal imaging sensor, (xi) controlling the delivery robot, (xii) a people counter, (xiii) a crowdedness analyzer, (xiv) a traffic analyzer in combination], do not integrate the abstract idea into a practical application because it does not impose any meaningful limits on practicing the abstract idea. Thus, the claim is directed to an abstract idea.
Step 2B
As discussed above with respect to Step 2A Prong Two, the additional elements amount to no more than: (i) “apply it” (or an equivalent), (ii) generally link the use of a judicial exception to a particular technological environment or field of use, and (iii) add insignificant extra-solution activity (e.g., pre-solution activity, such as mere data gathering) to the judicial exception, and are not a practical application of the abstract idea. The same analysis applies here in Step 2B, i.e., (i) merely invoking the generic components as a tool to perform the abstract idea or “apply it” (See MPEP 2106.05(f)); (ii) generally linking the use of a judicial exception to a particular technological environment or field of use (See MPEP 2106.05(h)), and (iii) adding insignificant extra-solution activity (e.g., pre-solution activity, such as mere data gathering) to the judicial exception (See MPEP2106.05(g)), does not integrate the abstract idea into a practical application at Step 2A or provide an inventive concept at Step 2B.
Furthermore, the (i) sensors associated with the plurality of candidate delivery paths (for collecting data) / at least one sensor (for collecting data) / a plurality of sensors disposed along the plurality of candidate delivery paths (for collecting data), when viewed as whole/ordered combination, amounts to insignificant extra-solution activity (e.g., pre-solution activity), such as mere data gathering (See MPEP 2106.05(g)). The (i) sensors on the plurality of paths/a sensor is/are recited at a high-level of generality and performs generic computer functions (i.e., transmitting data over a network) that are well-understood, routine and conventional activities previously known in the industry (See MPEP 2106.05(d)(II)). Additionally, Para. 48 of Applicant' s PG Publication, generically disclose the sensors on the plurality of paths/a sensor, as “various sensors 50 including a camera sensor, a thermal imaging sensor, a lidar sensor, an elevator sensor, a robot sensor, and an entry-and-exit gate sensor installed in the delivery robot 10, the elevator 20, the CCTV 30, and the entry-and-exit gate 40” at a high-level of generality demonstrating the well-understood, routine, conventional nature of the (i) sensors on the plurality of paths/a sensor collecting data.
Therefore, the additional elements of: elements (i) sensors associated with the plurality of candidate delivery paths (for collecting data) / at least one sensor (for collecting data) / a plurality of sensors disposed along the plurality of candidate delivery paths (for collecting data), (ii) a data analyzer, (iii) a path analyzer, (iv) a delivery time prediction unit, (v) a delivery path determining unit, (vi) a delivery robot, (vii) at least a camera sensor, (viii) an elevator sensor, (ix) an entry-and-exit gate sensor, (x) a thermal imaging sensor, (xi) controlling the delivery robot, (xii) a people counter, (xiii) a crowdedness analyzer, (xiv) a traffic analyzer, do not integrate the abstract idea into a practical application at Step 2A or provide an inventive concept at Step 2B. Thus, even when viewed as a whole/ordered combination [See Figure. 1 showing all the additional elements (i) sensors associated with the plurality of candidate delivery paths (for collecting data) / at least one sensor (for collecting data) / a plurality of sensors disposed along the plurality of candidate delivery paths (for collecting data), (ii) a data analyzer, (iii) a path analyzer, (iv) a delivery time prediction unit, (v) a delivery path determining unit, (vi) a delivery robot, (vii) at least a camera sensor, (viii) an elevator sensor, (ix) an entry-and-exit gate sensor, (x) a thermal imaging sensor, (xi) controlling the delivery robot, (xii) a people counter, (xiii) a crowdedness analyzer, (xiv) a traffic analyzer in combination], nothing in the claims adds significantly more (i.e., an inventive concept) to the abstract idea. Thus, claims 21, 30, and 38 are ineligible.
Dependent Claims 23-28, 31, and 32 merely narrow the previously recited abstract idea limitations. For reasons described above with respect to claims 21 and 30 these judicial exceptions are not meaningfully integrated into a practical application or significantly more than the abstract idea. Thus, claims 23-28, 31, and 32 are also ineligible.
Step 2A, Prong Two
Dependent Claim 22 further narrows the previously recited abstract idea limitations. Claim 22 also recites the additional elements of a CCTV, a lidar sensor, and a robot sensor which are recited at a high-level of generality (See Para. 48 of the Applicants Specification disclosing the CCTV, the lidar sensor and, the robot sensor) such that when viewed as whole/ordered combination, the additional elements do no more than generally link the use of the judicial exception to a particular technological environment or field of use (i.e. data sensors) (See MPEP 2106.05(h)).
Accordingly, the additional elements, when viewed individually and as a whole/ordered combination, do not integrate the abstract idea into a practical application because they do not impose any meaningful limits on practicing the abstract idea. Thus, the claims are directed to an abstract idea.
Step 2B
As discussed above with respect to Step 2A Prong Two, the additional element amounts to no more than: generally linking the use of a judicial exception to a particular technological environment or field of use, and is not a practical application of the abstract idea. The same analysis applies here in Step 2B, i.e., (i) generally linking the use of a judicial exception to a particular technological environment or field of use (See MPEP 2106.05(h)), does not integrate the abstract idea into a practical application at Step 2A or provide an inventive concept at Step 2B.
Therefore, the additional elements of a CCTV, a lidar sensor, and a robot sensor do not integrate the abstract idea into a practical application at Step 2A or provide an inventive concept at Step 2B. Thus, even when viewed as a whole/ordered combination, nothing in the claim adds significantly more (i.e., an inventive concept) to the abstract idea. Thus, claim 22 is ineligible.
Step 2A, Prong Two
Dependent Claim 29 further narrows the previously recited abstract idea limitations. Claim 29 also recites the additional element of a database, which are recited at a high-level of generality (See Para. 62 and 84 of the Applicants Specification disclosing the database), such that, when viewed as whole/ordered combination, it amounts to no more than mere instruction to apply the judicial exception using generic computer components or “apply it” (See MPEP 2106.05(f)).
Accordingly, the additional elements, when viewed individually and as a whole/ordered combination, do not integrate the abstract idea into a practical application because they do not impose any meaningful limits on practicing the abstract idea. Thus, the claims are directed to an abstract idea.
Step 2B
As discussed above with respect to Step 2A Prong Two, the additional element amounts to no more than: “apply it” (or an equivalent), and is not a practical application of the abstract idea. The same analysis applies here in Step 2B, i.e., (i) merely invoking the generic components as a tool to perform the abstract idea or “apply it” (See MPEP 2106.05(f)), does not integrate the abstract idea into a practical application at Step 2A or provide an inventive concept at Step 2B.
Therefore, the additional element of a database does not integrate the abstract idea into a practical application at Step 2A or provide an inventive concept at Step 2B. Thus, even when viewed as a whole/ordered combination, nothing in the claim adds significantly more (i.e., an inventive concept) to the abstract idea. Thus, claim 29 is ineligible.
Step 2A, Prong Two
Dependent Claim 33 further narrows the previously recited abstract idea limitations. Claim 33 also recites the additional element of a training unit, which is recited at a high-level of generality (See Para. 34 and 83 of the Applicants Specification disclosing the training unit), such that, when viewed as whole/ordered combination, it amounts to no more than mere instruction to apply the judicial exception using generic computer components or “apply it” (See MPEP 2106.05(f)).
Accordingly, the additional elements, when viewed individually and as a whole/ordered combination, do not integrate the abstract idea into a practical application because they do not impose any meaningful limits on practicing the abstract idea. Thus, the claims are directed to an abstract idea.
Step 2B
As discussed above with respect to Step 2A Prong Two, the additional element amounts to no more than: “apply it” (or an equivalent), and is not a practical application of the abstract idea. The same analysis applies here in Step 2B, i.e., (i) merely invoking the generic components as a tool to perform the abstract idea or “apply it” (See MPEP 2106.05(f)), does not integrate the abstract idea into a practical application at Step 2A or provide an inventive concept at Step 2B.
Therefore, the additional element of a training unit does not integrate the abstract idea into a practical application at Step 2A or provide an inventive concept at Step 2B. Thus, even when viewed as a whole/ordered combination, nothing in the claim adds significantly more (i.e., an inventive concept) to the abstract idea. Thus, claim 33 is ineligible.
Dependent Claim 34 merely narrows the previously recited abstract idea limitations. For reasons described above with respect to claims 33 these judicial exceptions are not meaningfully integrated into a practical application or significantly more than the abstract idea. Thus, claim 34 is also ineligible.
Step 2A, Prong Two
Dependent Claims 35 further narrows the previously recited abstract idea limitations. Claim 35 also recites the additional element of a database, which are recited at a high-level of generality (See Para. 62 and 84 of the Applicants Specification disclosing the database), such that, when viewed as whole/ordered combination, it amounts to no more than mere instruction to apply the judicial exception using generic computer components or “apply it” (See MPEP 2106.05(f)).
Accordingly, the additional elements, when viewed individually and as a whole/ordered combination, do not integrate the abstract idea into a practical application because they do not impose any meaningful limits on practicing the abstract idea. Thus, the claims are directed to an abstract idea.
Step 2B
As discussed above with respect to Step 2A Prong Two, the additional element amounts to no more than: “apply it” (or an equivalent), and is not a practical application of the abstract idea. The same analysis applies here in Step 2B, i.e., (i) merely invoking the generic components as a tool to perform the abstract idea or “apply it” (See MPEP 2106.05(f)), does not integrate the abstract idea into a practical application at Step 2A or provide an inventive concept at Step 2B.
Therefore, the additional element of a database does not integrate the abstract idea into a practical application at Step 2A or provide an inventive concept at Step 2B. Thus, even when viewed as a whole/ordered combination, nothing in the claim adds significantly more (i.e., an inventive concept) to the abstract idea. Thus, claim 35 is ineligible.
Step 2A, Prong Two
Dependent Claims 36 further narrows the previously recited abstract idea limitations. Claim 36 also recites the additional element of a server, which are recited at a high-level of generality (See Para. 124 of the Applicants Specification disclosing the server), such that, when viewed as whole/ordered combination, it amounts to no more than mere instruction to apply the judicial exception using generic computer components or “apply it” (See MPEP 2106.05(f)).
Accordingly, the additional elements, when viewed individually and as a whole/ordered combination, do not integrate the abstract idea into a practical application because they do not impose any meaningful limits on practicing the abstract idea. Thus, the claims are directed to an abstract idea.
Step 2B
As discussed above with respect to Step 2A Prong Two, the additional element amounts to no more than: “apply it” (or an equivalent), and is not a practical application of the abstract idea. The same analysis applies here in Step 2B, i.e., (i) merely invoking the generic components as a tool to perform the abstract idea or “apply it” (See MPEP 2106.05(f)), does not integrate the abstract idea into a practical application at Step 2A or provide an inventive concept at Step 2B.
Therefore, the additional element of a server does not integrate the abstract idea into a practical application at Step 2A or provide an inventive concept at Step 2B. Thus, even when viewed as a whole/ordered combination, nothing in the claim adds significantly more (i.e., an inventive concept) to the abstract idea. Thus, claim 36 is ineligible.
Step 2A, Prong Two
Dependent Claims 37 further narrows the previously recited abstract idea limitations. Claim 37 also recites the additional element of a cloud based server, which are recited at a high-level of generality (See Para. 124 of the Applicants Specification disclosing the cloud based server), such that, when viewed as whole/ordered combination, it amounts to no more than mere instruction to apply the judicial exception using generic computer components or “apply it” (See MPEP 2106.05(f)).
Accordingly, the additional elements, when viewed individually and as a whole/ordered combination, do not integrate the abstract idea into a practical application because they do not impose any meaningful limits on practicing the abstract idea. Thus, the claims are directed to an abstract idea.
Step 2B
As discussed above with respect to Step 2A Prong Two, the additional element amounts to no more than: “apply it” (or an equivalent), and is not a practical application of the abstract idea. The same analysis applies here in Step 2B, i.e., (i) merely invoking the generic components as a tool to perform the abstract idea or “apply it” (See MPEP 2106.05(f)), does not integrate the abstract idea into a practical application at Step 2A or provide an inventive concept at Step 2B.
Therefore, the additional element of a cloud based server does not integrate the abstract idea into a practical application at Step 2A or provide an inventive concept at Step 2B. Thus, even when viewed as a whole/ordered combination, nothing in the claim adds significantly more (i.e., an inventive concept) to the abstract idea. Thus, claim 37 is ineligible.
Step 2A, Prong Two
Dependent Claim 39 further narrows the previously recited abstract idea limitations. Claim 39 also recites the additional elements of CCTV camera sensors, lidar sensors, and thermal sensors which are recited at a high-level of generality (See Para. 48 of the Applicants Specification disclosing the CCTV camera sensors, the lidar sensors, and the thermal sensors) such that when viewed as whole/ordered combination, the additional elements do no more than generally link the use of the judicial exception to a particular technological environment or field of use (i.e. data sensors) (See MPEP 2106.05(h)).
Accordingly, the additional elements, when viewed individually and as a whole/ordered combination, do not integrate the abstract idea into a practical application because they do not impose any meaningful limits on practicing the abstract idea. Thus, the claims are directed to an abstract idea.
Step 2B
As discussed above with respect to Step 2A Prong Two, the additional element amounts to no more than: generally linking the use of a judicial exception to a particular technological environment or field of use, and is not a practical application of the abstract idea. The same analysis applies here in Step 2B, i.e., (i) generally linking the use of a judicial exception to a particular technological environment or field of use (See MPEP 2106.05(h)), does not integrate the abstract idea into a practical application at Step 2A or provide an inventive concept at Step 2B.
Therefore, the additional elements of CCTV camera sensors, lidar sensors, and thermal sensors do not integrate the abstract idea into a practical application at Step 2A or provide an inventive concept at Step 2B. Thus, even when viewed as a whole/ordered combination, nothing in the claim adds significantly more (i.e., an inventive concept) to the abstract idea. Thus, claims 39 is ineligible.
Step 2A, Prong Two
Dependent Claim 40 further narrows the previously recited abstract idea limitations. Claim 40 also recites the additional element of an elevator sensor, a robot sensor, and an entry-and-exit gate sensor which are recited at a high-level of generality (See Para. 48 of the Applicants Specification disclosing the elevator sensor, the robot sensor, and the entry-and-exit gate sensor) such that when viewed as whole/ordered combination, the additional elements do no more than generally link the use of the judicial exception to a particular technological environment or field of use (i.e. data sensors) (See MPEP 2106.05(h)).
Accordingly, the additional elements, when viewed individually and as a whole/ordered combination, do not integrate the abstract idea into a practical application because they do not impose any meaningful limits on practicing the abstract idea. Thus, the claims are directed to an abstract idea.
Step 2B
As discussed above with respect to Step 2A Prong Two, the additional element amounts to no more than: generally linking the use of a judicial exception to a particular technological environment or field of use, and is not a practical application of the abstract idea. The same analysis applies here in Step 2B, i.e., (i) generally linking the use of a judicial exception to a particular technological environment or field of use (See MPEP 2106.05(h)), does not integrate the abstract idea into a practical application at Step 2A or provide an inventive concept at Step 2B.
Therefore, the additional elements of elevator sensor, a robot sensor, and an entry-and-exit gate sensor do not integrate the abstract idea into a practical application at Step 2A or provide an inventive concept at Step 2B. Thus, even when viewed as a whole/ordered combination, nothing in the claim adds significantly more (i.e., an inventive concept) to the abstract idea. Thus, claims 40 are ineligible.
Claim Rejections - 35 USC § 103
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.
The factual inquiries for establishing a background for determining obviousness under 35 U.S.C. 103 are summarized as follows:
1. Determining the scope and contents of the prior art.
2. Ascertaining the differences between the prior art and the claims at issue.
3. Resolving the level of ordinary skill in the pertinent art.
4. Considering objective evidence present in the application indicating obviousness or nonobviousness.
This application currently names joint inventors. In considering patentability of the claims the examiner presumes that the subject matter of the various claims was commonly owned as of the effective filing date of the claimed invention(s) absent any evidence to the contrary. Applicant is advised of the obligation under 37 CFR 1.56 to point out the inventor and effective filing dates of each claim that was not commonly owned as of the effective filing date of the later invention in order for the examiner to consider the applicability of 35 U.S.C. 102(b)(2)(C) for any potential 35 U.S.C. 102(a)(2) prior art against the later invention.
Claims 21-23, 25, and 26 are rejected under 35 U.S.C. 103 as being unpatentable over Mori (US 20250298419) (hereafter Mori) in view of Velten (US 20200125109) (hereafter Velten) and further in view of Chae (KR 20200075378) (hereafter Chae) and even further in view of van der Merwe (US 20190377349) (hereafter van der Merwe).
In regards to claim 21, Mori discloses a method for controlling indoor robot delivery, the method comprising: (Claim 17) (“An information processing method for controlling a plurality of automated transport bodies that transport a target object from a transport source to a transport destination in an automated transport system”)
Mori discloses collecting, by sensors including at least a camera sensor, crowd estimation information associated with the plurality of candidate delivery paths; (Para. 30) (“The congestion degree evaluator 50 evaluates the degree of congestion within the work area W on the basis of the imaging data acquired by the acquirer 32 from the stationary camera 20. Here, the “degree of congestion” is a quantity that represents a degree of congestion of objects, people, automated transport bodies, and the like that could become obstacles to the travel of the target automated transport bodies 10A to 10C at a certain position within the work area W. Moreover, the “obstacle” here refers to something that is physically present in the work area W and that may impede the travel of a target automated transport body in a case in which it moves at a certain time (i.e. collecting, by sensors including at least a camera sensor, crowd estimation information associated with the plurality of candidate delivery paths).”)
Mori discloses determining crowdedness of sections; Para. 45) (At a position P1 (i.e. determining crowdedness of sections) since there are many obstacles (any of B1 to B4), a congestion degree value is large. At a position P2 (i.e. determining crowdedness of sections), since there are relatively few obstacles (any of B1 to B4), the congestion degree value is small. The degree of congestion at a position P3 (i.e. determining crowdedness of sections) has a value approximately intermediate between the positions P1 and P2.”)
Mori discloses determining traffic information for each candidate delivery path based on: (i) information about a number of people collected from the camera sensor and a thermal imaging sensor, and (ii) the crowdedness; (Para. 30-31, 37) (“The congestion degree evaluator 50 evaluates the degree of congestion within the work area W on the basis of the imaging data acquired by the acquirer 32 from the stationary camera 20. … At a position P1, since there are many obstacles (any of B1 to B4), a congestion degree value (i.e. determining traffic information for each candidate delivery path based on: (i) information about a number of people collected from the camera sensor and a thermal imaging sensor, and (ii) the crowdedness) is large. At a position P2, since there are relatively few obstacles (any of B1 to B4), the congestion degree value (i.e. determining traffic information for each candidate delivery path based on: (i) information about a number of people collected from the camera sensor and a thermal imaging sensor, and (ii) the crowdedness) is small. The degree of congestion at a position P3 has a value (i.e. determining traffic information for each candidate delivery path based on: (i) information about a number of people collected from the camera sensor and a thermal imaging sensor, and (ii) the crowdedness) approximately intermediate between the positions P1 and P2.” “the congestion degree evaluator 50 recognizes non-stationary objects (for example, a worker B1, … that are temporarily present within the work area W from the imaging data acquired from the stationary camera 20. Here, the ‘non-stationary object’ refers to an object (which may be a person) that can change a position thereof within the work area W, is temporarily located at a certain position, and is movable from there.”)
Mori discloses predicting delivery times respectively corresponding to the candidate delivery paths based on the traffic information and latency information; and (Para. 44-45) (“the travel time calculator (i.e. a delivery time prediction unit) 54 calculates a time required for each of the automated transport bodies 10 to travel from the current position to the transport source TO along the route R0. The travel time calculator 54 also calculates a time required for each of the automated transport bodies 10 to travel from the transport source T0 to the transport destination T1 along the route R1. Hereinafter, a time required for the automated transport body 10 to travel from one position to another will be referred to as a ‘travel time.’ (i.e. predicting delivery times respectively corresponding to the candidate delivery paths based on the traffic information and latency information) … The travel time calculator 54 can calculate the travel time of the automated transport body 10 taking into consideration the congestion degree distribution calculated by the congestion degree evaluator 50 (i.e. predicting delivery times respectively corresponding to the candidate delivery paths based on the traffic information and latency information). … the travel time calculator 54 can correct the calculation so that the travel time of the automated transport body 10 is slower (i.e. predicting delivery times respectively corresponding to the candidate delivery paths based on the traffic information and latency information) in a section on the route in which the degree of congestion is high. The method of correcting the calculation is not particularly limited. For example, the travel time calculator 54 may add a stop time (i.e. predicting delivery times respectively corresponding to the candidate delivery paths based on the traffic information and latency information) according to the degree of congestion to the travel time for a section in which the degree of congestion is greater than a predetermined value, or may multiply the travel time by a coefficient (i.e. predicting delivery times respectively corresponding to the candidate delivery paths based on the traffic information and latency information)”)
Mori discloses controlling the delivery robot to travel via a selected delivery path having a shortest predicted delivery time, (Para. 43, 45, 50) (“controlling the delivery robot to travel via a selected delivery path having a shortest predicted delivery time, … the route setter 52 may select and set one of the shortest routes on the basis of any criteria (for example, so that an accumulated value of the degree of congestion at a position through which the route passes is minimized) (i.e. a selected delivery path having a shortest predicted delivery time)” “The travel time calculator 54 can calculate the travel time of the automated transport body 10 taking into consideration the congestion degree distribution calculated by the congestion degree evaluator 50 (i.e. controlling the delivery robot to travel via a selected delivery path having a shortest predicted delivery time).” “The instruction generator 58 generates a travel instruction indicating a travel route of the automated transport body 10. For example, the instruction generator 58 generates a travel instruction including information on the route R0 from the current position of the automated transport body 10 selected by the automated transport body selector 56 to the transport source TO and the route R1 from the transport source T0 to the transport destination T1. The controller 30 transmits the travel instruction to the selected automated transport body 10 via the communication unit 34. The transport body controller 14 of the automated transport body 10 controls the transport main body 12 to travel within the work area W in accordance with the received travel instruction.”)
Mori does not explicitly disclose, however Velten, in the same field of endeavor, discloses receiving, from a delivery robot, a stored movement path plan including a plurality of candidate delivery paths to a destination; (Para. 34, 37, 51, 66) (“AGV 200a also a navigation module 238, a wireless communication module 234, a monitoring module 264 operable to monitor a parameter of AGV 200a, and a controller 230” “Controller 230 communicates with orchestrator 102 and/or sorting controller 120 to transmit AGV parameter information to orchestrator 102 (i.e. receiving a stored movement path plan from robot), which is monitored by monitoring module a monitoring module 264.” “AGVs that are in transit will both did on a task. … has an existing delivery task that routes (i.e. a stored movement path plan including a plurality of candidate delivery paths to a destination) the AGV nearby the destination location of the item referenced in the incoming task , may submit the winning (lowest cost) bid. In some scenarios, an AGV that has an existing task that routes it in a direction that is in a different direction than the destination location of the incoming task (i.e. a stored movement path plan including a plurality of candidate delivery paths to a destination) may lose a bid to another AGV that is not yet docked, but has no conflicting talking already assigned. Thus, an AGVs current tasking will affect its bid” “transmit the AGV parameter to an orchestrator; and receive delivery instructions from the orchestrator.”)
Therefore, it would be obvious to one of ordinary skill in the art, before the effective filing date of the claimed invention, to have modified the automated transport navigation of Mori with routing of autonomous vehicles of Velten in order to improve operational efficiency of the system. (Velten – Para. 1)
Mori in view of Velten does not explicitly disclose, however Chae, in the same field of endeavor, discloses determining crowdedness of Mori of elevator sections and entry-and-exit gate sections based on entry and exit log data obtained from the elevator sensor and the entry-and-exit gate sensor; (Para. 17, 19) (“The plurality of measurement sensors (i.e. determining crowdedness of Mori) 20 are for detecting the presence or absence of a room, the RFID sensor 21 installed in a building entrance or a certain area to detect the presence or absence of an occupant (i.e. determining crowdedness of Mori of entry-and-exit gate sections based on entry and exit log data obtained from the entry-and-exit gate sensor), the building entrance or each of the buildings Emergency exit of the side, CCTV (22) installed in the elevator, PIR sensor (23) installed in each zone as a human body sensor to detect the presence of a room (i.e. determining crowdedness of Mori of elevator sections based on entry and exit log data obtained from the elevator sensor)” “The entrance/exit analysis unit 40 receives measurement data sensed through a plurality of measurement sensors 20 … stored in the database 70 for the received measurement data (i.e. entry and exit log data obtained from the elevator sensor and the entry-and-exit gate sensor)”)
Therefore, it would be obvious to one of ordinary skill in the art, before the effective filing date of the claimed invention, to have modified the automated transport navigation of Mori in view of Velten with occupant density sensors of Chae in order to improve speed and accuracy of monitoring occupant density. (Chae – Para. 44)
Mori in view of Velten and further in view of Chae does not explicitly disclose, however van der Merwe, in the same field of endeavor, discloses information about a number of people collected of Mori from the camera sensor and a thermal imaging sensor (Para. 32) (“Sensors located on any of the utility robots of the present teachings, the trucks, and/or the smart beacons can provide current congestion information from cameras and/or thermal imaging to form heat maps.”)
Mori in view of Velten and further in view of Chae does not explicitly disclose, however van der Merwe, in the same field of endeavor, discloses wherein the selected delivery path is dynamically updated during the delivery according to real-time updated traffic information. (Para. 30) (“The utility robot can include routing technology that can avoid congested areas based on, for example, but not limited to, current congestion information from other utility robots of the present teachings, crowd-sourced congestion information, … Dynamic navigation paths can be created based on current path data and the maps.”)
Therefore, it would be obvious to one of ordinary skill in the art, before the effective filing date of the claimed invention, to have modified the automated transport navigation of Mori in view of Velten and further in view of Chae with delivery routing of van der Merwe in order to improve route planning and execution. (van der Merwe – Para. 75)
In regards to claim 22, Mori in view of Velten and further in view of Chae and even further in view of van der Merwe discloses the limitations of claim 21. Mori discloses wherein the sensors comprise a robot sensor (Para. 60) (“transport body 10 is selected on the basis of data acquired by a transport body camera 120 and/or an optical scanner 220 mounted on the automated transport body 10 (i.e. a robot sensor).”)
Mori in view of Velten does not explicitly disclose, however Chae, in the same field of endeavor, discloses wherein the sensors of Mori comprise a CCTV camera sensor, the elevator sensor, and the entry-and- exit gate sensor. (Para. 17, 20) (“The plurality of measurement sensors 20 are for detecting the presence or absence of a room, the RFID sensor 21 installed in a building entrance (i.e. an entry-and-exit gate sensor) or a certain area to detect the presence or absence of an occupant, the building entrance or each of the buildings Emergency exit of the side, CCTV (22) installed in the elevator (i.e. a CCTV, an elevator sensor), PIR sensor (23) installed in each zone as a human body sensor to detect the presence of a room, Bluetooth capable of grasping the presence and location of occupants within a certain communication range (Bluetooth: 24) and the like.” “the entrance/exit analysis unit 40 may analyze whether or not access is made based on measurement data detected from the RFID sensor 21 and the CCTV 22 (i.e. a CCTV, an entry-and-exit gate sensor) among the plurality of measurement sensors 20.”)
Therefore, it would be obvious to one of ordinary skill in the art, before the effective filing date of the claimed invention, to have modified the automated transport navigation of Mori in view of Velten with occupant density sensors of Chae in order to improve speed and accuracy of monitoring occupant density. (Chae – Para. 44)
Mori in view of Velten and further in view of Chae does not explicitly disclose, however van der Merwe, in the same field of endeavor, discloses wherein the sensors comprise a lidar sensor, the thermal imaging sensor. (Para. 8, 32) (“The sensors can … include, for example, but not limited to… LIDAR” “Sensors located on any of the utility robots of the present teachings, the trucks, and/or the smart beacons can provide current congestion information from … thermal imaging”)
Therefore, it would be obvious to one of ordinary skill in the art, before the effective filing date of the claimed invention, to have modified the automated transport navigation of Mori in view of Velten and further in view of Chae with delivery routing of van der Merwe in order to improve route planning and execution. (van der Merwe – Para. 75)
In regards to claim 23, Mori in view of Velten and further in view of Chae and even further in view of van der Merwe discloses the limitations of claim 21. Mori disclose wherein collecting the crowd estimation information associated with the plurality of candidate delivery paths comprises collecting the information about the number of people for each of the plurality of paths through the camera sensor and (Para. 30-31, 37) (“The congestion degree evaluator 50 evaluates the degree of congestion within the work area W on the basis of the imaging data acquired by the acquirer 32 from the stationary camera 20. … At a position P1, since there are many obstacles (any of B1 to B4), a congestion degree value (i.e. collecting the information about the number of people for each of the plurality of paths through the camera sensor) is large. At a position P2, since there are relatively few obstacles (any of B1 to B4), the congestion degree value (i.e. collecting the information about the number of people for each of the plurality of paths through the camera sensor) is small. The degree of congestion at a position P3 has a value (i.e. collecting the information about the number of people for each of the plurality of paths through the camera sensor) approximately intermediate between the positions P1 and P2.” “the congestion degree evaluator 50 recognizes non-stationary objects (for example, a worker B1, … that are temporarily present within the work area W from the imaging data acquired from the stationary camera 20. Here, the ‘non-stationary object’ refers to an object (which may be a person) that can change a position thereof within the work area W, is temporarily located at a certain position, and is movable from there.”)
Mori in view of Velten and further in view of Chae does not explicitly disclose, however van der Merwe, in the same field of endeavor, discloses wherein collecting the crowd estimation information associated with the plurality of candidate delivery paths of Mori comprises collecting the information about the number of people for each of the plurality of paths of Mori through the thermal imaging sensor. (Para. 32) (“Sensors located on any of the utility robots of the present teachings, the trucks, and/or the smart beacons can provide current congestion information from cameras and/or thermal imaging (i.e. collecting the crowd estimation information associated with the plurality of candidate delivery paths of Mori comprises collecting the information about the number of people for each of the plurality of paths of Mori through the thermal imaging sensor)”)
Therefore, it would be obvious to one of ordinary skill in the art, before the effective filing date of the claimed invention, to have modified the automated transport navigation of Mori in view of Velten and further in view of Chae with delivery routing of van der Merwe in order to improve route planning and execution. (van der Merwe – Para. 75)
In regards to claim 25, Mori in view of Velten and further in view of Chae and even further in view of van der Merwe discloses the limitations of claim 21. Mori discloses calculating the latency information based on a time between a time point collecting the crowd estimation information and a time point of calculating the traffic information by using the crowd estimation information. (Para. 30) (“The congestion degree evaluator 50 evaluates the degree of congestion within the work area W (i.e. a time point collecting the crowd estimation information) on the basis of the imaging data acquired by the acquirer 32 from the stationary camera 20. Here, the ‘degree of congestion’ is a quantity that represents a degree of congestion of objects, people, automated transport bodies, and the like that could become obstacles to the travel of the target automated transport bodies 10A to 10C at a certain position within the work area W (i.e. a time point of calculating the traffic information by using the crowd estimation information). Moreover, the ‘obstacle’ here refers to something that is physically present in the work area W and that may impede the travel of a target automated transport body in a case in which it moves at a certain time (i.e. calculating the latency information based on a time between a time point collecting the crowd estimation information and a time point of calculating the traffic information by using the crowd estimation information). … The congestion degree evaluator 50 can evaluate the congestion degree distribution in which the degree of congestion is mapped for each of the positions within the work area W.”)
In regards to claim 26, Mori in view of Velten and further in view of Chae and even further in view of van der Merwe discloses the limitations of claim 21. Mori discloses wherein predicting the delivery times respectively corresponding to the candidate delivery paths based on the traffic information and the latency information comprises predicting the delivery times respectively corresponding to the candidate delivery paths, by adding an additional time calculated based on the traffic information and a delay time calculated according to the latency information. (Para. 45) (“The travel time calculator 54 can calculate the travel time of the automated transport body 10 taking into consideration the congestion degree distribution calculated by the congestion degree evaluator 50. … The method of correcting the calculation is not particularly limited. For example, the travel time calculator 54 may add a stop time according to the degree of congestion to the travel time (i.e. predicting the delivery times respectively corresponding to the candidate delivery paths based on the traffic information and the latency information comprises predicting the delivery times respectively corresponding to the candidate delivery paths, by adding an additional time calculated based on the traffic information and a delay time calculated according to the latency information) for a section in which the degree of congestion is greater than a predetermined value”)
Claims 27 and 28 are rejected under 35 U.S.C. 103 as being unpatentable over Mori in view of Velten and further in view of Chae and even further in view of van der Merwe and even further in view of Eisinga (US 20240328803) (hereafter Eisinga).
In regards to claim 27, Mori in view of Velten and further in view of Chae and even further in view of van der Merwe discloses the limitations of claim 21. Mori in view of Velten and further in view of Chae and further in view of van der Merwe does not explicitly disclose, however, Eisinga in the same field of endeavor, discloses comparing the predicted delivery time and an actual delivery time with respect to a determined delivery path. (Para. 21, 32, 37) (“for updating a model to be used by a routing module of a navigation system, the routing module being operable to determine an estimated travel time for a route extending through a navigable network from a start location in the navigable network to an end location in the navigable network” “evaluating the performance of the current version of the model by comparing an estimated travel time (i.e. the predicted delivery time of Mori) determined by a routing module using the model with the recorded travel time (i.e. an actual delivery time)” “The accuracy of these estimated travel times provided by a navigation system (e.g., compared to the actual travel time recorded by a user) (i.e. comparing the predicted delivery time and an actual delivery time with respect to the determined delivery path)”)
Therefore, it would be obvious to one of ordinary skill in the art, before the effective filing date of the claimed invention, to have modified the automated transport navigation of Mori in view of Velten and further in view of Chae and further in view of van der Merwe with data processing of Eisinga in order to improve user experience through more reliable and accurate predictions. (Eisinga – Para. 18)
In regards to claim 28, Mori in view of Velten and further in view of Chae and even further in view of van der Merwe and even further in view of Eisinga discloses the limitations of claim 27. Mori discloses a delivery is completed (Para. 18) (“the automated transport body 10 first moves to a transport source T0 to load luggage, and then moves from the transport source T0 to a transport destination T1 to unload the luggage (i.e. a delivery is completed).”)
Mori in view of Velten and further in view of Chae and further in view of van der Merwe does not explicitly disclose, however, Eisinga in the same field of endeavor, discloses after a delivery is completed of Mori, updating a delivery time prediction model based on a comparison result of the comparison when a comparison result satisfies a specific criterion. (Para. 21, 32, 37, 40, 45, 49) (“for updating a model to be used by a routing module of a navigation system, the routing module being operable to determine an estimated travel time for a route extending through a navigable network from a start location in the navigable network to an end location in the navigable network” “evaluating the performance of the current version of the model by comparing an estimated travel time (i.e. the predicted delivery time of Mori) determined by a routing module using the model with the recorded travel time (i.e. an actual delivery time)” “The accuracy of these estimated travel times provided by a navigation system (e.g., compared to the actual travel time recorded by a user) (i.e. comparing the predicted delivery time and an actual delivery time with respect to the determined delivery path, after a delivery is completed)” “since the actual recorded travel times associated with the historic positional traces are generally known, or can be determined, and can therefore be compared with estimated travel times predicted using the model. For instance, in this way it is possible to automatically validate any changes in the model by ensuring that the model does provide improved estimated travel times at least for a suitable set of test data (traces) (and if not, then it is possible to, e.g., update the training set and re-train the model appropriately until the model does provide the desired improvements) (i.e. updating a delivery time prediction model based on a comparison result of the comparing).” “alongside the gradual refinement of the model over time as new positional data is obtained, the present invention also provides a so-called ‘pattern-breaking’ detection step … such that the performance is worse than a set performance threshold, it is thereby determined that a change in the conditions associated with the navigable network (a ‘pattern-breaking event’) may have occurred. When a pattern-breaking event is detected in this way, an indication of this may be outputted (either to a user, or to the system itself))” “Accordingly, in a preferred embodiment, the ‘pattern-breaking’ detection step is performed …. for removing outliers (i.e. updating a delivery time prediction model based on a comparison result of the comparing when the comparison result satisfies a specific criterion)”)
Therefore, it would be obvious to one of ordinary skill in the art, before the effective filing date of the claimed invention, to have modified the automated transport navigation of Mori in view of Velten and further in view of Chae and further in view of van der Merwe with data processing of Eisinga in order to improve user experience through more reliable and accurate predictions. (Eisinga – Para. 18)
Claim 29 are rejected under 35 U.S.C. 103 as being unpatentable over Mori in view of Velten and further in view of Chae and even further in view of van der Merwe and even further in view of Eisinga and even further in view of Steenwinckel (“FLAGS: A methodology for adaptive anomaly detection”; October 19, 2020) (hereafter Steenwinckel).
In regards to claim 29, Mori in view of Velten and further in view of Chae and even further in view of van der Merwe and even further in view of Eisinga discloses the limitations of claim 28. Mori in view of Velten and further in view of Chae and further in view of van der Merwe does not explicitly disclose, however, Eisinga in the same field of endeavor, discloses when the comparison result does not satisfy the specific criterion. (Para. 45) (““alongside the gradual refinement of the model over time as new positional data is obtained, the present invention also provides a so-called ‘pattern-breaking’ detection step … such that the performance is worse than a set performance threshold, it is thereby determined that a change in the conditions associated with the navigable network (a ‘pattern-breaking event’) may have occurred (i.e. when the comparison result does not satisfy the specific criterion). When a pattern-breaking event is detected in this way, an indication of this may be outputted (either to a user, or to the system itself)”)
Therefore, it would be obvious to one of ordinary skill in the art, before the effective filing date of the claimed invention, to have modified the automated transport navigation of Mori in view of Velten and further in view of Chae and further in view of van der Merwe with data processing of Eisinga in order to improve user experience through more reliable and accurate predictions. (Eisinga – Para. 18)
Mori in view of Velten and further in view of Chae and further in view of van der Merwe and even further in view of Eisinga does not explicitly disclose, however, Steenwinckel in the same field of endeavor, discloses storing the comparison result in a database when the comparison result does not satisfy the specific criterion. (Pg. 35) (“These enriched anomalies (i.e. the comparison result of Eisinga does not satisfy the specific criterion of Eisinga) are also stored in the semantic database (i.e. storing the comparison result of Eisinga in a database when the comparison result of Eisinga does not satisfy the specific criterion of Eisinga).”)
Therefore, it would be obvious to one of ordinary skill in the art, before the effective filing date of the claimed invention, to have modified the automated transport navigation of 107. Mori in view of Velten and further in view of Chae and further in view of van der Merwe and even further in view of Eisinga with anomaly databasing of Steenwinckel in order to improve data monitoring. (Steenwinckel – Pg. 31)
Novel and Non-Obvious Over the Prior Art
Claim 24 and 30-40 are novel and non-obvious over the prior art; however, these claims are subject to the above rejections.
The closest prior art is U.S. Patent Application No. 2025/0012651 to Mori et al (hereafter Mori). Mori discloses a system for gathering traffic and latency data in order determine delivery paths and delivery time to the destination.
The next closest prior art is U.S. Patent Application No. 2020/0125109 to Velten et al (hereafter Velten). Velten discloses receiving stored movement path plans from delivery robots.
The next closest prior art is Korean Patent Application No. 2020/0075378 to Chae et al (hereafter Chae). Chae discloses use of CCTV camera sensors, entry/exit gate sensors, and elevator sensors in determining occupancy and path routing.
The next closest prior art is U.S. Patent Application No. 2019/0377349 to van der Merwe et al (hereafter van der Merwe). Van der Merwe discloses use of thermal imaging in determining congestion and path routing and dynamically updating paths based on real-time traffic data.
The next closest prior art is U.S. Patent Application No. 2023/0017144 to Emacha et al (hereafter Emacha). Emacha discloses system responses to a defect or error of the sensor.
The next closest prior art is U.S. Patent Application No. 2020/0225046 to Stewart et al (hereafter Stewart). Stewart discloses predicting an average delivery time based on historical traffic and congestion and average latency data, and generating a plurality of paths and priorities based on the predicted delivery time, and selecting a path based on highest priority.
The next closest prior art is Japanese Patent No. 3,849,590 to Yamane et al (hereafter Yamane). Yamane discloses determining a second path having subsequent priority based on updated traffic and latency information updated while en route.
While the closest prior art above teaches the various aspects of the claimed invention individually, the combination of these references are not obvious in such a way that they would have been obvious to one of ordinary skill in the art at the time of invention. Specifically, Mori in view of Velten and further in view of Chae and even further in view of van der Merwe and even further in view of Emacha further in view of Stewart and even further in view of Yamane fails to explicitly “when the traffic information and the latency information cannot be calculated due to a defect or an error of the sensors, predicting the delivery times respectively corresponding to the candidate delivery paths based on the traffic information and the latency information further comprises predicting an average delivery time based on recent traffic information” in combination with the other recited limitations. Therefore, the claims are rendered novel and non-obvious over the prior art.
Conclusion
Applicant's 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.
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/DAVID G. GODBOLD/Examiner, Art Unit 3628
/RUPANGINI SINGH/Primary Examiner, Art Unit 3628
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