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 .
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 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.
Status of Claims
This Office Action is in response to the application filed 03 October 2025. Claims 1-15 are presently pending and are presented for examination.
Foreign Priority
Acknowledgment is made of applicant’s claim for foreign priority under 35 U.S.C. 119 (a)-(d). The certified copy has been filed in parent Application No. KR10-2022-0069335, filed on 08 June 2022.
Information Disclosure Statement
The information disclosure statements (IDS’s) submitted on 21 November 2024 and 28 November 2025 are in compliance with the provisions of 37 CFR 1.97, 1.98. Accordingly, the IDS’s were considered.
Claim Objections
Claim 14 is objected to because of the following informalities:
Claim 14, line 5, “…a path generation apparatus configured to: generate a movement…” should read --…a path generation apparatus configured to generate a movement…--;
Appropriate correction is required.
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:
problem solving unit in claim 1, 4-6, 11-14;
path generation unit in claims 1, 2, 11, 14;
data transceiver unit in claim 7;
path identification unit in claims 7, 10;
graph completion unit in claims 7-9;
path generation apparatus in claim 14;
The structures of the “…unit” and “…apparatus” are disclosed in para 0114-0117 of the specification.
control device in claims 14-15;
The structure of the control device is disclosed in Fig. 2.
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.
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.
Claim Rejections - 35 USC § 112
The following is a quotation of 35 U.S.C. 112(b):
(b) CONCLUSION.—The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the inventor or a joint inventor regards as the invention.
The following is a quotation of 35 U.S.C. 112 (pre-AIA ), second paragraph:
The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the applicant regards as his invention.
Claims 1-15 are rejected under 35 U.S.C. 112(b) or 35 U.S.C. 112 (pre-AIA ), second paragraph, as being indefinite for failing to particularly point out and distinctly claim the subject matter which the inventor or a joint inventor, or for pre-AIA the applicant regards as the invention.
Claim 1 recites “…output a solution by solving a vehicle routing problem model by using a metaheuristic technique with respect to a graph in which a connection relationship among a plurality of checkpoints included in the object is defined as a target” which is ambiguous. It is not clear whether the “model” is “with respect to a graph…” OR the “technique” is “with respect to a graph…”. Further, it is not clear what is meant by “defined as a target”, i.e., whether the target is for the “at least one drone” OR for the “routing problem model” OR something else. Therefore, the claim is indefinite and rejected under 35 U.S.C. 112(b). The claims have been interpreted as best understood by the examiner.
Claims 11 and 14 recite similar language as claim 1 and are rejected for similar reasons above.
Claim 2 recites the limitation “the drone” in line 1. There is insufficient antecedent basis for this limitation in the claim.
Claim 3 recites the limitation “the overlapping checkpoint” in line 2. There is insufficient antecedent basis for this limitation in the claim.
Claim 5 recites the limitation “the preset number…” in line 3. There is insufficient antecedent basis for this limitation in the claim.
Claim 7 recites “a plurality of checkpoints” in lines 2-3. Claim 1, from which claim 7 is dependent, also recites “a plurality of checkpoints” in line 5. It is not clear if the “a plurality of checkpoints” in claim 7 is the same “a plurality of checkpoints” in claim 1. Therefore, the claim is indefinite and rejected under 35 U.S.C. 112(b). The “a plurality of checkpoints” in claim 7 is interpreted as “the plurality of checkpoints” by the examiner for the purpose of examination.
Claim 8 recites “…an element of 0 among elements excluding a diagonal matrix in an adjacency matrix…” which is ambiguous. It is not clear what “element of 0” means, i.e., whether “element 0” refers to an index of the element OR a value of the element. In addition, it is not clear what “…among elements excluding a diagonal matrix in an adjacency matrix” means, e.g., how a diagonal matrix is excluded. A matrix includes diagonal elements but does not include a diagonal matrix. Therefore, the claim is indefinite and rejected under 35 U.S.C. 112(b). The claims have been interpreted as best understood by the examiner.
Claim 11 recites the limitation “the number…” in the last limitation. There is insufficient antecedent basis for this limitation in the claim.
Claim 14 recites the limitation “…at least one of the corresponding drones and control devices” in line 7 and “the at least one drone” in line 12. There is insufficient antecedent basis for this limitation in the claim.
Claim 15 recites the limitation “the drone” in line 1 and “the control device” in line 2. There is insufficient antecedent basis for this limitation in the claim.
Claims 2-10, 12-13 and 15 are rejected by virtue of the dependency on previously rejected claims.
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 1-15 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more.
101 Analysis – Step 1
Claim 1 is directed to a path generation apparatus (i.e., an apparatus). Therefore, claim 1 is within at least one of the four statutory categories.
101 Analysis – Step 2A, Prong I
Regarding Prong I of the Step 2A analysis in the 2019 PEG, the claims are to be analyzed to determine whether they recite subject matter that falls within one of the follow groups of abstract ideas: a) mathematical concepts, b) certain methods of organizing human activity, and/or c) mental processes.
Independent claim 1 includes limitations that recite an abstract idea (emphasized below) and will be used as a representative claim for the remainder of the 101 rejection. Claim 1 recites:
A path generation apparatus for generating a movement path of at least one drone for inspection of an object, the path generation apparatus comprising:
- a problem solving unit configured to output a solution by solving a vehicle routing problem model by using a metaheuristic technique with respect to a graph in which a connection relationship among a plurality of checkpoints included in the object is defined as a target; and
- a path generation unit configured to generate the movement path of the at least one drone based on the outputted solution,
wherein the problem solving unit is configured to:
- search for a solution based on a weight according to the connection relationship among the plurality of checkpoints,
- evaluate fitness by performing conformity evaluation for the searched solution based on operation efficiency for the at least one drone, and
- solve the vehicle routing problem model based on whether the evaluated fitness satisfies an algorithm end condition.
The examiner submits that the foregoing bolded limitation(s) constitute a “mental process” because under its broadest reasonable interpretation, the claim covers performance of the limitation in the human mind. For example, “solving a vehicle routing problem model...”, “generate the movement path…”, “search for a solution…”, “evaluate fitness…” and “solve the vehicle routing problem…” in the context of this claim encompasses a person (e.g., a driver) looking at data collected and forming a simple judgement. In addition, the limitation “solving a vehicle routing problem model...” also recites at least one mathematical concept. Accordingly, the claim recites at least one abstract idea.
101 Analysis – Step 2A, Prong II
Regarding Prong II of the Step 2A analysis in the 2019 PEG, the claims are to be analyzed to determine whether the claim, as a whole, integrates the abstract into a practical application. As noted in the 2019 PEG, it must be determined whether any additional elements in the claim beyond the abstract idea integrate the exception into a practical application in a manner that imposes a meaningful limit on the judicial exception. The courts have indicated that additional elements merely using a computer to implement an abstract idea, adding insignificant extra solution activity, or generally linking use of a judicial exception to a particular technological environment or field of use do not integrate a judicial exception into a “practical application.”
In the present case, the additional limitations beyond the above-noted abstract idea are as follows (where the underlined portions are the “additional limitations” while the bolded portions continue to represent the “abstract idea”):
A path generation apparatus for generating a movement path of at least one drone for inspection of an object, the path generation apparatus comprising:
- a problem solving unit configured to output a solution by solving a vehicle routing problem model by using a metaheuristic technique with respect to a graph in which a connection relationship among a plurality of checkpoints included in the object is defined as a target; and
- a path generation unit configured to generate the movement path of the at least one drone based on the outputted solution,
wherein the problem solving unit is configured to:
- search for a solution based on a weight according to the connection relationship among the plurality of checkpoints,
- evaluate fitness by performing conformity evaluation for the searched solution based on operation efficiency for the at least one drone, and
- solve the vehicle routing problem model based on whether the evaluated fitness satisfies an algorithm end condition.
For the following reason(s), the examiner submits that the above identified additional limitations do not integrate the above-noted abstract idea into a practical application.
Regarding the additional limitation of “output a solution...” the examiner submits that the limitation is an insignificant extra-solution activity that merely output the results of “solving…”. In particular, the “output…” step is recited at a high level of generality (i.e. as a general means of output result from the solving step), and amounts to mere post-solution data transmission, which is a form of insignificant extra-solution activity. Lastly, the specification does not disclose the structure of “problem solving unit” and “path generation unit”. The “…unit” is interpreted as part of a generic computer system which merely describes how to generally “apply” the otherwise mental judgements in a generic or general purpose computer. The “…unit” is recited at a high level of generality and merely automates the solving…, generating…, searching…, evaluating… and solving… steps.
Thus, taken alone, the additional elements do not integrate the abstract idea into a practical application. Further, looking at the additional limitation(s) as an ordered combination or as a whole, the limitation(s) add nothing that is not already present when looking at the elements taken individually. For instance, there is no indication that the additional elements, when considered as a whole, reflect an improvement in the functioning of a computer or an improvement to another technology or technical field, apply or use the above-noted judicial exception to effect a particular treatment or prophylaxis for a disease or medical condition, implement/use the above-noted judicial exception with a particular machine or manufacture that is integral to the claim, effect a transformation or reduction of a particular article to a different state or thing, or apply or use the judicial exception in some other meaningful way beyond generally linking the use of the judicial exception to a particular technological environment, such that the claim as a whole is not more than a drafting effort designed to monopolize the exception (MPEP § 2106.05). Accordingly, the additional limitation(s) do/does not integrate the abstract idea into a practical application because it does not impose any meaningful limits on practicing the abstract idea.
101 Analysis – Step 2B
Regarding Step 2B of the 2019 PEG, representative independent claim 1 does not include additional elements (considered both individually and as an ordered combination) that are sufficient to amount to significantly more than the judicial exception for the same reasons to those discussed above with respect to determining that the claim does not integrate the abstract idea into a practical application. As discussed above with respect to integration of the abstract idea into a practical application, the additional elements of using “…unit” to perform the solving…, generating…, searching…, evaluating… and solving… steps amount to nothing more than applying the exception using a generic computer component. Generally applying an exception using a generic computer component cannot provide an inventive concept. And as discussed above, the additional limitations of “output...,” the examiner submits that these limitations are insignificant extra-solution activities.
Further, a conclusion that an additional element is insignificant extra-solution activity in Step 2A should be re-evaluated in Step 2B to determine if they are more than what is well-understood, routine, conventional activity in the field. The additional limitation of “output…” is a well-understood, routine, and conventional activity because the background recites that the output…is merely conventional outputting of results, and the specification does not provide any indication that the …unit is anything other than a conventional computer component. MPEP 2106.05(d)(II), and the cases cited therein, including Intellectual Ventures I, LLC v. Symantec Corp., 838 F.3d 1307, 1321 (Fed. Cir. 2016), TLI Communications LLC v. AV Auto. LLC, 823 F.3d 607, 610 (Fed. Cir. 2016), and OIP Techs., Inc., v. Amazon.com, Inc., 788 F.3d 1359, 1363 (Fed. Cir. 2015), indicate that mere collection or receipt of data over a network is a well‐understood, routine, and conventional function when it is claimed in a merely generic manner.
As per Claim 11.
Claim 11, an apparatus claim (a path generation apparatus), includes limitations analogous to claim 1 an apparatus claim (a path generation apparatus).
Accordingly, claim 11 is rejected under 35 U.S.C. § 101 because the claim is directed to an abstract idea without significantly more.
As per Claim 14.
Claim 14, an apparatus claim (a system), includes limitations analogous to claim 1 an apparatus claim (a path generation apparatus), but adds a plurality of drones and a plurality of control devices. The generically recited computer elements do not add significantly more to the abstract idea because, they merely amount to implementing the abstract idea on a computer. The generically recited drones being configured to inspect… merely applies the abstract idea in a specific technological environment.
Accordingly, claim 14 is rejected under 35 U.S.C. § 101 because the claim is directed to an abstract idea without significantly more.
Dependent claims 2-10, 12-13 and 15 do not recite any further limitations that cause the claims to be patent eligible. Rather, the limitations of dependent claims are directed toward additional aspects of the judicial exception and/or well-understood, routine and conventional additional elements that do not integrate the judicial exception into a practical application. Therefore, dependent claims 2-10, 12-13 and 15 are not patent eligible under the same rationale as provided for in the rejection of claims 1, 11 and 14.
Therefore, claims 1-15 are ineligible under 35 USC §101.
Claim Rejections - 35 USC § 102
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 1-4, 11-12 and 14 are rejected under 35 U.S.C. 102(a)(1) as being anticipated by Jing (“Multi-UAV Coverage Path Planning for the Inspection of Large and Complex Structures”).
As to Claim 1, Jing teaches a path generation apparatus for generating a movement path of at least one drone for inspection of an object (Jing abstract, also see 1st paragraph of section III), the path generation apparatus comprising:
a problem solving unit configured to output a solution by solving a vehicle routing problem model by using a metaheuristic technique with respect to a graph in which a connection relationship among a plurality of checkpoints included in the object is defined as a target (Jing section IV: …generates way-points and path primitives by incremental sampling to create a C-PRM graph with information on topology, coverage and path length; the MACPP is then formulated as a min-max SC-VRP problem and solved by BRKGA… Coverage Probabilistic Roadmap (C-PRM) graph, G(V;E) with coverage information for inspection is formulated for a multi-UAV system… The inspection path planning problem with multiple UAVs could be formulated as an SC-VRP by combining two NP hard problems: SCP and VRP… Path Planning and Optimization with BRKGA: Random Key Genetic Algorithm (RKGA) is a meta-heuristic frame work that uses random keys in the chromosome to encode the solution. RKGA has been applied to many combinatorial optimization problems… transfers the ILP problem with many
constraints into a sequencing problem. As shown in Algo. 2, the fitness evaluation of BRKGA decodes the chromosome into paths of UAVs; also see Fig. 2, Fig. 5, Fig. 6); and
a path generation unit configured to generate the movement path of the at least one drone based on the outputted solution (Jing section IV: …generates way-points and path primitives by incremental sampling to create a C-PRM graph with information on topology, coverage and path length…Path Planning and Optimization with BRKGA: Random Key Genetic Algorithm (RKGA) is a meta-heuristic frame work that uses random keys in the chromosome to encode the solution. RKGA has been applied to many combinatorial optimization problems… transfers the ILP problem with many constraints into a sequencing problem. As shown in Algo. 2, the fitness evaluation of BRKGA decodes the chromosome into paths of UAVs; also see Fig. 2, Fig. 5, Fig. 6),
wherein the problem solving unit is configured to:
search for a solution based on a weight according to the connection relationship among the plurality of checkpoints (Jing, Section IV. A. 2): …a Coverage Probabilistic Roadmap graph with coverage information… In addition to topological information, edge eij 2 E also encodes distance information and coverage information…a surface patch indexed by k is visible ..is invisible; also see Fig. 7),
evaluate fitness by performing conformity evaluation for the searched solution based on operation efficiency for the at least one drone (Jing Section IV. B. 2): …transfers the ILP problem with many constraints into a sequencing problem. As shown in Algo. 2, the fitness evaluation of BRKGA decodes the chromosome into paths of K UAVs. The coverage constraint will be evaluated after decoding each random-key. Once the coverage constraint is satisfied, the fitness evaluation exits and returns the fitness value, as well as the paths of the UAVs… the local improvement heuristic is used as an additional operator…; also see section VI: …the planned inspection paths are shorter than the discrete viewpoints planning method…finding efficient inspection paths is widely applicable to inspection applications for any geometries of complex 3D structure), and
solve the vehicle routing problem model based on whether the evaluated fitness satisfies an algorithm end condition (Jing Section IV. B. 2): …transfers the ILP problem with many constraints into a sequencing problem. As shown in Algo. 2, the fitness evaluation of BRKGA decodes the chromosome into paths of K UAVs. The coverage constraint will be evaluated after decoding each random-key. Once the coverage constraint is satisfied, the fitness evaluation exits and returns the fitness value, as well as the paths of the UAVs).
As to claim 2, Jing teaches the path generation apparatus of claim 1, wherein the drone
comprises a plurality of drones, and
wherein the path generation unit is configured to generate sub-movement paths that correspond to the plurality of drones, respectively, as the movement path of the drone (Jing, Fig. 5, Fig. 6 and related text).
As to claim 3, Jing teaches the path generation apparatus of claim 2, wherein the vehicle routing problem model is configured so that the overlapping checkpoint between the sub-movement paths corresponds to only a starting point (depot) in consideration of battery capacities of the plurality of drones (Jing, Fig. 5, Fig. 6 and related text, also see section I, 1st and 2nd paragraphs).
As to claim 4, Jing teaches the path generation apparatus of claim 1, wherein the problem solving unit is configured to:
end the problem solving in case that the evaluated fitness satisfies the algorithm end condition (Jing Section IV. B. 2): …transfers the ILP problem with many constraints into a sequencing problem. As shown in Algo. 2, the fitness evaluation of BRKGA decodes the chromosome into paths of K UAVs. The coverage constraint will be evaluated after decoding each random-key. Once the coverage constraint is satisfied, the fitness evaluation exits and returns the fitness value, as well as the paths of the UAVs).
solve the vehicle route problem model by repeating the problem solving by changing the weight in case that the evaluated fitness does not satisfy the algorithm end condition (Jing Section IV. B. 2): equations (2)-(7) and related text, … where xi,j,k is the binary selection of the path…).
As to claim 11, Jing teaches a path generation apparatus for generating a movement path of at least one drone for inspection of an object, the path generation apparatus comprising:
a problem solving unit configured to output a solution by solving a vehicle routing problem model with respect to a graph in which a connection relationship among a plurality of checkpoints included in the object is defined as a target (Jing section IV: …generates way-points and path primitives by incremental sampling to create a C-PRM graph with information on topology, coverage and path length; the MACPP is then formulated as a min-max SC-VRP problem and solved by BRKGA… Coverage Probabilistic Roadmap (C-PRM) graph, G(V;E) with coverage information for inspection is formulated for a multi-UAV system… The inspection path planning problem with multiple UAVs could be formulated as an SC-VRP by combining two NP hard problems: SCP and VRP… Path Planning and Optimization with BRKGA: Random Key Genetic Algorithm (RKGA) is a meta-heuristic frame work that uses random keys in the chromosome to encode the solution. RKGA has been applied to many combinatorial optimization problems… transfers the ILP problem with many constraints into a sequencing problem. As shown in Algo. 2, the fitness evaluation of BRKGA decodes the chromosome into paths of UAVs; also see Fig. 2, Fig. 5, Fig. 6); and
a path generation unit configured to generate the movement path of the at least one drone based on the outputted solution (Jing section IV: …generates way-points and path primitives by incremental sampling to create a C-PRM graph with information on topology, coverage and path length…Path Planning and Optimization with BRKGA: Random Key Genetic Algorithm (RKGA) is a meta-heuristic frame work that uses random keys in the chromosome to encode the solution. RKGA has been applied to many combinatorial optimization problems… transfers the ILP problem with many constraints into a sequencing problem. As shown in Algo. 2, the fitness evaluation of BRKGA decodes the chromosome into paths of UAVs; also see Fig. 2, Fig. 5, Fig. 6),
wherein the problem solving unit is configured to determine a technique to solve the vehicle routing problem model according to the number of the plurality of checkpoints of the object (Jing, Section IV.: …generates way-points and path primitives by incremental sampling to create a C-PRM graph with information on topology, coverage and path length; the MACPP is then formulated as a min-max SC-VRP problem and solved by BRKGA. The overall structure of the proposed problem-solving framework is shown in Fig. 2 …a Coverage Probabilistic Roadmap graph with coverage information… a surface patch indexed by k is visible …transfers the ILP problem with many constraints into a sequencing problem. As shown in Algo. 2, the fitness evaluation of BRKGA decodes the chromosome into paths of K UAVs. The coverage constraint will be evaluated after decoding each random-key. Once the coverage constraint is satisfied, the fitness evaluation exits and returns the fitness value, as well as the paths of the UAVs… the local improvement heuristic is used as an additional operator…; also see section VI: …the planned inspection paths are shorter than the discrete viewpoints planning method…finding efficient inspection paths is widely applicable to inspection applications for any geometries of complex 3D structure, also see Figs. 5 and 6).
As to claim 12, Jing teaches the path generation apparatus of claim 11, wherein the problem solving unit is configured to solve a solving technique of the vehicle routing problem model through the metaheuristic technique in case that the number of the plurality of checkpoints of the object exceeds a preset reference checkpoint threshold value (Jing section IV. B). 2).: Path Planning and Optimization with BRKGA: Random Key Genetic Algorithm (RKGA) is a meta-heuristic frame work that uses random keys in the chromosome to encode the solution [33]. RKGA has been applied to many combinatorial optimization problems; also see Fig. 5, Fig.6).
As to claim 14, Jing teaches a system for inspecting an object comprising:
a plurality of drones configured to inspect the object (Jing Section I: para 5, This paper presents a novel formulation and algorithm for the CPP problem with multiple UAVs for 3D visual inspection tasks, Fig. 2, Fig. 5);
a plurality of control devices configured to correspond to the plurality of drones, respectively (Jing Section I: para 5, This paper presents a novel formulation and algorithm for the CPP problem with multiple UAVs for 3D visual inspection tasks, Fig. 2, Fig. 5); and
a path generation apparatus configured to: generate a movement path of the plurality of drones including sub-movement paths corresponding to the plurality of drones, respectively, and provide the sub-movement paths to at least one of the corresponding drones and control devices (Jing section IV: …generates way-points and path primitives by incremental sampling to create a C-PRM graph with information on topology, coverage and path length…Path Planning and Optimization with BRKGA: Random Key Genetic Algorithm (RKGA) is a meta-heuristic frame work that uses random keys in the chromosome to encode the solution. RKGA has been applied to many combinatorial optimization problems… transfers the ILP problem with many constraints into a sequencing problem. As shown in Algo. 2, the fitness evaluation of BRKGA decodes the chromosome into paths of UAVs; also see Fig. 2, Fig. 5, Fig. 6),
wherein the path generation apparatus includes:
a problem solving unit configured to output a solution by solving a vehicle routing problem model by using a metaheuristic technique with respect to a graph in which a connection relationship among a plurality of checkpoints included in the object is defined as a target (Jing section IV: …generates way-points and path primitives by incremental sampling to create a C-PRM graph with information on topology, coverage and path length; the MACPP is then formulated as a min-max SC-VRP problem and solved by BRKGA… Coverage Probabilistic Roadmap (C-PRM) graph, G(V;E) with coverage information for inspection is formulated for a multi-UAV system… The inspection path planning problem with multiple UAVs could be formulated as an SC-VRP by combining two NP hard problems: SCP and VRP… Path Planning and Optimization with BRKGA: Random Key Genetic Algorithm (RKGA) is a meta-heuristic frame work that uses random keys in the chromosome to encode the solution. RKGA has been applied to many combinatorial optimization problems… transfers the ILP problem with many constraints into a sequencing problem. As shown in Algo. 2, the fitness evaluation of BRKGA decodes the chromosome into paths of UAVs; also see Fig. 2, Fig. 5, Fig. 6); and
a path generation unit configured to generate the movement path of the at least one drone based on the outputted solution (Jing section IV: …generates way-points and path primitives by incremental sampling to create a C-PRM graph with information on topology, coverage and path length…Path Planning and Optimization with BRKGA: Random Key Genetic Algorithm (RKGA) is a meta-heuristic frame work that uses random keys in the chromosome to encode the solution. RKGA has been applied to many combinatorial optimization problems… transfers the ILP problem with many constraints into a sequencing problem. As shown in Algo. 2, the fitness evaluation of BRKGA decodes the chromosome into paths of UAVs; also see Fig. 2, Fig. 5, Fig. 6),
wherein the problem solving unit is configured to:
search for a solution based on a weight according to the connection relationship among the plurality of checkpoints (Jing, Section IV. A. 2): …a Coverage Probabilistic Roadmap graph with coverage information… In addition to topological information, edge eij 2 E also encodes distance information and coverage information…a surface patch indexed by k is visible ..is invisible; also see Fig. 7),
evaluate fitness by performing conformity evaluation for the searched solution based on operation efficiency for the plurality of drones (Jing Section IV. B. 2): …transfers the ILP problem with many constraints into a sequencing problem. As shown in Algo. 2, the fitness evaluation of BRKGA decodes the chromosome into paths of K UAVs. The coverage constraint will be evaluated after decoding each random-key. Once the coverage constraint is satisfied, the fitness evaluation exits and returns the fitness value, as well as the paths of the UAVs… the local improvement heuristic is used as an additional operator…; also see section VI: …the planned inspection paths are shorter than the discrete viewpoints planning method…finding efficient inspection paths is widely applicable to inspection applications for any geometries of complex 3D structure), and
solve the vehicle routing problem model based on whether the evaluated fitness satisfies an algorithm end condition (Jing Section IV. B. 2): …transfers the ILP problem with many constraints into a sequencing problem. As shown in Algo. 2, the fitness evaluation of BRKGA decodes the chromosome into paths of K UAVs. The coverage constraint will be evaluated after decoding each random-key. Once the coverage constraint is satisfied, the fitness evaluation exits and returns the fitness value, as well as the paths of the UAVs).
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.
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.
The factual inquiries set forth in Graham v. John Deere Co., 383 U.S. 1, 148 USPQ 459 (1966), that are applied 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.
Claims 5-7 and 10 are rejected under 35 U.S.C. 103 as being unpatentable over Jing in view of Laporte (“What You Should Know about the Vehicle Routing Problem”).
As to claim 5, Jing teaches the path generation apparatus of claim 4.
Jing does not explicitly teach wherein the problem solving unit is configured to end the problem solving and output the searched solution in case that the problem solving is performed as many times as the preset number of repetitions of the problem solving when the problem solving is repeated by changing the weight.
However, in the same field of endeavor, Laporte teaches …the search ends with the best known solution after a stopping criterion has been satisfied, usually a preset number of iterations, or a given number of consecutive iterations without improvement in s* (see at least Laporte, Section 4.1).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified Jing so as to include the above limitation in view of Laporte et al. with a reasonable expectation of success. Those having ordinary skill in the art would understand ending the search after a set number of iterations of Laporte can used in Jing, as required by the claim. One of ordinary skill would have been motivated to combine Jing and Laporte because this would have achieved the desirable result of providing an efficient method of iterative searching that exits the iteration when a preset number of iteration has been reached so that the time spent on the searching can be controlled.
As to claim 6, Jing teaches the path generation apparatus of claim 1.
Laporte further teaches wherein the metaheuristic technique is an ant colony system (ACS) (Laporte Section 4.3: and this line of research seems to have been abandoned. Ant colony optimization heuristics attempt to mimic the behavior of ants who detect paths containing pheromone and strengthen them with their own pheromone), and
wherein the problem solving unit is configured to search for the solution by further utilizing pheromone information accumulated in an existing path as a positive feedback (Laporte Section 4.3: and this line of research seems to have been abandoned. Ant colony optimization heuristics attempt to mimic the behavior of ants who detect paths containing pheromone and strengthen them with their own pheromone).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified Jing so as to include the above limitation in view of Laporte et al. with a reasonable expectation of success. One of ordinary skill would have been motivated to combine Jing and Laporte because this is merely combining prior art elements according to known methods to yield predictable results (KSR International Co. v. Teleflex Inc., 550 U.S. 398, 82 USPQ2d 1385 (2007)).
As to claim 7, Jing teaches the path generation apparatus of claim 1, further comprising:
a data transceiver unit configured to receive object information related to the object and a plurality of checkpoints of the object (Jing section II:…3D model of the target…; section IV: …generates way-points and path primitives by incremental sampling to create a C-PRM graph with information on topology, coverage and path length…with coverage information for inspection is formulated for a multi-UAV system…; also see Fig. 2, Fig. 5, Fig. 6).
a graph completion unit configured to complete a relationship of the plurality of checkpoints by defining a virtual path between the checkpoints where the connection relationship is not defined (Jing, Fig. 3, Fig. 5-6 and related text).
Laporte further teaches a path identification unit configured to: identify a path on which the drone is movable and a path on which the drone is unmovable at the plurality of checkpoints in consideration of the object information, and define a connection relationship of the checkpoints corresponding to the path on which the drone is movable (Laporte section 2.3: …R be the set of all feasible routes…, also see section 3.1, Fig. 2); and
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified Jing so as to include the above limitation in view of Laporte et al. with a reasonable expectation of success. One of ordinary skill would have been motivated to combine Jing and Laporte because this is merely combining prior art elements according to known methods to yield predictable results (KSR International Co. v. Teleflex Inc., 550 U.S. 398, 82 USPQ2d 1385 (2007)).
As to claim 10, Jing in view of Laporte teaches the path generation apparatus of claim 7.
Jing further teaches wherein the path identification unit is configured to: generate a 3D model of the object based on the object information, and identify the path on which the drone is movable and the path on which the drone is unmovable at the plurality of checkpoints by using the 3D model of the object (Jing Fig. 3, Figs. 5-6 and related text).
Claims 8-9 are rejected under 35 U.S.C. 103 as being unpatentable over Jing in view of Laporte as applied to claim 7 above, and further in view of Shao (“A Novel Service System for Long-Distance Drone Delivery Using the “Ant Colony+A*” Algorithm”).
As to claim 8, Jing in view of Laporte teaches the path generation apparatus of claim 7.
Jing modified by Laporte does not teach wherein the graph completion unit is configured to identify a pair of checkpoints where the connection relationship is not formed by searching for a path corresponding to an element of 0 among elements excluding a diagonal matrix in an adjacency matrix representing the connection relationship of the plurality of checkpoints.
However, in the same field of endeavor, Shao teaches …a type of reachability matrix that indicates the reachability of any two depots so that the unreachable two points will not be considered in the solutions… a type of the reachability matrix is defined, where eij = 1s if ni can reach nj and eij = 0 if ni cannot reach nj … (Shao Section V, equation (3)).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified Jing so as to include the above limitation in view of Shao et al. with a reasonable expectation of success. One of ordinary skill would have been motivated to combine Jing and Shao because this is merely combining prior art elements according to known methods to yield predictable results (KSR International Co. v. Teleflex Inc., 550 U.S. 398, 82 USPQ2d 1385 (2007)).
As to claim 9, Jing in view of Laporte and Shao teaches the path generation apparatus of claim 8.
Jing further teaches wherein the graph completion unit is configured to define the virtual path as a detour path connecting the pair of checkpoints where the connection relationship is not formed through at least one checkpoint (Jing Fig. 3, Figs. 5-6 and related text).
Claim 13 is rejected under 35 U.S.C. 103 as being unpatentable over Jing in view of
Mund (US20120277993).
As to claim 13, Jing teaches the path generation apparatus of claim 11.
Jing does not explicitly teach wherein the problem solving unit is configured to solve a solving technique of the vehicle routing problem model through an exact technique in case that the number of the plurality of checkpoints of the object is equal to or smaller than a preset reference checkpoint threshold value.
However, in the same field of endeavor, Mund teaches … To match a point p, of a trace line p to a network element w, the following conditions must be observed: …There are at least n connected points which have an offset to w smaller than the predetermined maximum offset value, and where n is a fixed number greater than or equal to 2 (Mund para 0026-0028).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified Jing so as to include the above limitation in view of Mund et al. with a reasonable expectation of success. One of ordinary skill would have been motivated to combine Jing and Mund because this is merely combining prior art elements according to known methods to yield predictable results (KSR International Co. v. Teleflex Inc., 550 U.S. 398, 82 USPQ2d 1385 (2007)).
Claim 15 is rejected under 35 U.S.C. 103 as being unpatentable over Jing in view of
Natarajan (US20170147975).
As to claim 15, Jing teaches the system of claim 14.
Jing does not teach wherein the drone is configured to: fly autonomously according to the movement path, or fly according to a control signal of the control device,
wherein the drone is further configured to: generate location information, and provide the generated location information to the control device, and
wherein the control device is configured to: display the movement path and the location information together on a display to provide them to a user.
However, in the same field of endeavor, Natarajan teaches …The GPS information is transmitted by the UAV to the delivery management system 20 through a cellular service or the like on the UAV 12 or through the ground station it communicates with through radio. The GPS location data can then be transmitted to the customer 15 to track the location of the UAV 12 on a map displayed upon a display of the user's smart device 17 …Users of the system 20 can track the process from beginning to end from the GPS data. For example, the customer 15 may view a video feed from an on-board camera (not shown) on the UAV 12 (Natarajan para 0055).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified Jing so as to include the above limitation in view of Natarajan et al. with a reasonable expectation of success. One of ordinary skill would have been motivated to combine Jing and Natarajan because this is merely combining prior art elements according to known methods to yield predictable results (KSR International Co. v. Teleflex Inc., 550 U.S. 398, 82 USPQ2d 1385 (2007)).
Examiner’s Notes
Examiner has cited particular columns/paragraph and line numbers in the references applied to the claims above for the convenience of the applicant. Although the specified citations are representative of the teachings of the art and are applied to specific limitations within the individual claim, other passages and figures may apply as well. It is respectfully requested from the applicant in preparing 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.
In the case of amending the claimed invention, Applicant is respectfully requested to indicate the portion(s) of the specification which dictate(s) the structure relied on for proper interpretation and also to verify and ascertain the metes and bounds of the claimed invention. This will assist in expediting compact prosecution. MPEP 714.02 recites: “Applicant should also specifically point out the support for any amendments made to the disclosure. See MPEP §2163.06. An amendment which does not comply with the provisions of 37 CFR 1.121(b), (c), (d), and (h) may be held not fully responsive. See MPEP § 714.” Amendments not pointing to specific support in the disclosure may be deemed as not complying with provisions of 37 C.F.R. 1.131(b), (c), (d), and (h) and therefore held not fully responsive. Generic statements such as "Applicants believe no new matter has been introduced" may be deemed insufficient.
Inquiry
Any inquiry concerning this communication or earlier communications from the examiner should be directed to HONGYE LIANG whose telephone number is (571)272-5410. The examiner can normally be reached on Monday-Friday 9:00am-5:00pm.
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/HONGYE LIANG/Primary Examiner, Art Unit 3664
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