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 .
This is a Final Action on the Merits. Claims 1-25 and 27-29 are currently pending and are addressed below.
Response to Amendments
The amendment filed on November 17th, 2025 has been considered and entered. Accordingly, claims 1-4, 10-13, 17, 19-22, 25, and 28 have been amended. Claim 26 has been cancelled. Claim 29 has been newly added.
Response to Arguments
The previous claim interpretation of claim 26 has been overcome due to the applicant’s amendments.
The applicant states (Amend. 11) that amended claim 1 is directed towards statutory subject matter. The examiner respectfully disagrees. The determining frontier goals for autonomous map building can be practically performed in the human mind or with the aid of a pen and paper. The use of generic computer components (a camera and a processor) to determine the frontier goals does not make the claim limitation patent-eligible. See, MPEP 2106.04(A)(2)(III) states “The courts consider a mental process (thinking) that "can be performed in the human mind, or by a human using a pen and paper" to be an abstract idea. CyberSource Corp. v. Retail Decisions, Inc., 654 F.3d 1366, 1372, 99 USPQ2d 1690, 1695 (Fed. Cir. 2011). As the Federal Circuit explained, "methods which can be performed mentally, or which are the equivalent of human mental work, are unpatentable abstract ideas the ‘basic tools of scientific and technological work’ that are open to all.’" 654 F.3d at 1371, 99 USPQ2d at 1694 (citing Gottschalk v. Benson, 409 U.S. 63, 175 USPQ 673 (1972)). See also Mayo Collaborative Servs. v. Prometheus Labs. Inc., 566 U.S. 66, 71, 101 USPQ2d 1961, 1965 (2012) ("‘[M]ental processes[] and abstract intellectual concepts are not patentable, as they are the basic tools of scientific and technological work’" (quoting Benson, 409 U.S. at 67, 175 USPQ at 675)); Parker v. Flook, 437 U.S. 584, 589, 198 USPQ 193, 197 (1978) (same) … The courts do not distinguish between mental processes that are performed entirely in the human mind and mental processes that require a human to use a physical aid (e.g., pen and paper or a slide rule) to perform the claim limitation. See, e.g., Benson, 409 U.S. at 67, 65, 175 USPQ at 674-75, 674 (noting that the claimed "conversion of [binary-coded decimal] numerals to pure binary numerals can be done mentally," i.e., "as a person would do it by head and hand."); Synopsys, Inc. v. Mentor Graphics Corp., 839 F.3d 1138, 1139, 120 USPQ2d 1473, 1474 (Fed. Cir. 2016) (holding that claims to a mental process of "translating a functional description of a logic circuit into a hardware component description of the logic circuit" are directed to an abstract idea, because the claims "read on an individual performing the claimed steps mentally or with pencil and paper").
The applicant’s arguments with respect to claims 1-25 and 27-29 have been considered but are moot in view of the newly formulated grounds of rejections necessitated by the applicant’s amendments.
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 1-25 and 27-28 are rejected under 35 U.S.C. § 101 because the claimed invention is directed to a judicial exception (i.e., an abstract idea) without significantly more.
In sum, claims 1-25 and 27-28 are rejected under 35 U.S.C. §101 because the claimed invention is directed to a judicial exception to patentability (i.e., a law of nature, a natural phenomenon, or an abstract idea) and do not include an inventive concept that is something “significantly more” than the judicial exception under the January 2019 patentable subject matter eligibility guidance (2019 PEG) analysis which follows.
Under the 2019 PEG step 1 analysis, it must first be determined whether the claims are directed to one of the four statutory categories of invention (i.e., process, machine, manufacture, or composition of matter). Applying step 1 of the analysis for patentable subject matter to the claims, it is determined that the claims are directed to the statutory category of a process. Therefore, we proceed to step 2A, Prong 1.
Revised Guidance Step 2A – Prong 1
Under the 2019 PEG step 2A, Prong 1 analysis, it must be determined whether the claims recite an abstract idea that falls within one or more designated categories of patent ineligible subject matter (i.e., organizing human activity, mathematical concepts, and mental processes) that amount to a judicial exception to patentability.
Here, with respect to independent claims 1, 10, 19, and 28, the claims recite the abstract idea of determining frontier goals for autonomous map building, and mentally “determining a frontier cost for each of the plurality of available frontier goals based on a difference between a trajectory cost and a co-visibility cost of the respective available frontier goal; selecting one of the plurality of available frontier goals having a lowest determined frontier cost”, where these claims fall within one or more of the three enumerated 2019 PEG categories of patent ineligible subject matter, specifically, a mental process, that can be performed in the human mind since each of the above steps could alternatively be performed in the human mind or with the aid of pen and paper. This conclusion follows from CyberSource Corp. v. Retail Decisions, Inc., where our reviewing court held that section 101 did not embrace a process defined simply as using a computer to perform a series of mental steps that people, aware of each step, can and regularly do perform in their heads. 654 F.3d 1366, 1373 (Fed. Cir. 2011); see also In re Grams, 888 F.2d 835, 840–41 (Fed. Cir. 1989); In re Meyer, 688 F.2d 789, 794–95 (CCPA 1982); Elec. Power Group, LLC v. Alstom S.A., 830 F. 3d 1350, 1354–1354 (Fed. Cir. 2016) (“we have treated analyzing information by steps people go through in their minds, or by mathematical algorithms, without more, as essentially mental processes within the abstract-idea category”).
Additionally, mental processes remain unpatentable even when automated to reduce the burden on the user of what once could have been done with pen and paper. See CyberSource, 654 F.3d at 1375 (“That purely mental processes can be unpatentable, even when performed by a computer, was precisely the holding of the Supreme Court in Gottschalk v. Benson.”). These limitations, as drafted, are a simple process that under their broadest reasonable interpretation, covers the performance of the limitations of the mind. For example, the claim limitation encompasses mentally determining and selecting frontier goals for autonomous map building with a space based on frontier costs provided by the car’s sensors while traveling, or alternatively, mentally determining and selecting frontier goals for autonomous map building with a space based on frontier costs.
For example, a human could mentally and with the aid of pen and paper determine and selecting frontier goals for autonomous map building with a space based on frontier costs.
In addition, the limitation “determining trajectory costs for the robotic device traversing from an occupied area to each of a plurality of available frontier goals within the space, wherein the plurality of available frontier goals include positions within the space from which the robotic device is configured to collect information to autonomously build a map of the space; determining co-visibility costs for each of the plurality of available frontier goals based on a ratio of a number of one-glance-only frontiers traversed to reach the respective available frontier goal over a length of a trajectory route used to reach the respective available frontier goal” recites the abstract idea of a mathematical concept in addition to being a mental process since the limitation invokes a “calculation” of a trajectory and co-visibility costs. See October 2019 Update: Subject Matter eligibility p. 3-4 “Mathematical Relationships” and “Mathematical Calculations” (“A mathematical relationship may be expressed in words or using mathematical symbols . . . [t]here is no particular word or set of words that indicates a claim recites a mathematical calculation. That is, a claim does not have to recite the word “calculating” in order to be considered a mathematical calculation. For example, a step of “determining” a variable or number using mathematical methods or “performing” a mathematical operation may also be considered mathematical calculations when the broadest reasonable interpretation of the claim in light of the specification encompasses a mathematical calculation.”) citing Diamond v. Diehr, Gottschalk v. Benson, Parker v. Flook, and Burnett v. Panasonic Corp (“using a formula to convert geospatial coordinates into natural numbers”).
Revised Guidance Step 2A – Prong 2
Under the 2019 PEG step 2A, Prong 2 analysis, the identified abstract idea to which the claim is directed does not include limitations that integrate the abstract idea into a practical application, since the additional elements of a vehicle camera, processor, and memory are merely generic components used as a tool (“apply it”) to implement the abstract idea. (See, e.g., MPEP §2106.05(f)). See Alice, 573 U.S. at 223 (“[T]he mere recitation of a generic computer cannot transform a patent-ineligible abstract idea into a patent-eligible invention.”)
In addition, the limitation “determining trajectory costs for the robotic device traversing from an occupied area to each of a plurality of available frontier goals within the space, wherein the plurality of available frontier goals include positions within the space from which the robotic device is configured to collect information to autonomously build a map of the space; determining co-visibility costs for each of the plurality of available frontier goals, wherein the co-visibility costs are based on one or more effects between the plurality of available frontier goals including a ratio of a number of one-glance-only frontiers traversed to reach the respective available frontier goal over a length of a trajectory route used to reach the respective available frontier goal” constitutes insignificant presolution activity that merely gathers data and, therefore, do not integrate the exception into a practical application. See In re Bilski, 545 F.3d 943, 963 (Fed. Cir. 2008) (en banc), aff' d on other grounds, 561 U.S. 593 (2010) (characterizing data gathering steps as insignificant extra-solution activity); see also CyberSource, 654 F.3d at 1371–72 (noting that even if some physical steps are required to obtain information from a database (e.g., entering a query via a keyboard, clicking a mouse), such data-gathering steps cannot alone confer patentability); OIP Techs., Inc. v. Amazon.com, Inc., 788 F.3d 1359, 1363 (Fed. Cir. 2015) (presenting offers and gathering statistics amounted to mere data gathering). Accord Guidance, 84 Fed. Reg. at 55 (citing MPEP § 2106.05(g)).
In addition, merely “[u]sing a computer to accelerate an ineligible mental process does not make that process patent-eligible.” Bancorp Servs., L.L.C. v. Sun Life Assur. Co. of Canada (U.S.), 687 F.3d 1266, 1279 (Fed. Cir. 2012); see also CLS Bank Int’l v. Alice Corp. Pty. Ltd., 717 F.3d 1269, 1286 (Fed. Cir. 2013) (en banc) (“simply appending generic computer functionality to lend speed or efficiency to the performance of an otherwise abstract concept does not meaningfully limit claim scope for purposes of patent eligibility.”), aff’d, 573 U.S. 208 (2014). Accordingly, the additional element of a processor does not transform the abstract idea into a practical application of the abstract idea.
Revised Guidance Step 2B
Under the 2019 PEG step 2B analysis, the additional elements are evaluated to determine whether they amount to something “significantly more” than the recited abstract idea. (i.e., an innovative concept). Here, the additional elements, such as: a camera, a sensor, and a memory does not amount to an innovative concept since, as stated above in the step 2A, Prong 2 analysis, the claims are simply using the additional elements as a tool to carry out the abstract idea (i.e., “apply it”) on a computer or computing device and/or via software programming. (See, e.g., MPEP §2106.05(f)). The additional elements are specified at a high level of generality to simply implement the abstract idea and are not themselves being technologically improved. (See, e.g., MPEP §2106.05 I.A.). See Alice, 573 U.S. at 223 (“[T]he mere recitation of a generic computer cannot transform a patent-ineligible abstract idea into a patent-eligible invention.”). Thus, these elements, taken individually or together, do not amount to “significantly more” than the abstract ideas themselves.
The additional elements of the dependent claims 2-9, 11-18 19-25, and 27 merely refine and further limit the abstract idea of the independent claims and do not add any feature that is an “inventive concept” which cures the deficiencies of their respective parent claim under the 2019 PEG analysis. None of the dependent claims considered individually, including their respective limitations, include an “inventive concept” of some additional element or combination of elements sufficient to ensure that the claims in practice amount to something “significantly more” than patent-ineligible subject matter to which the claims are directed.
The elements of the instant claimed invention, when taken in combination do not offer substantially more than the sum of the functions of the elements when each is taken alone. The claims as a whole, do not amount to significantly more than the abstract idea itself because the claims do not effect an improvement to another technology or technical field; the claims do not amount to an improvement to the functioning of an electronic device itself which implements the abstract idea (e.g., the general purpose computer and/or the computer system which implements the process are not made more efficient or technologically improved); the claims do not perform a transformation or reduction of a particular article to a different state or thing (i.e., the claims do not use the abstract idea in the claimed process to bring about a physical change. See, e.g., Diamond v. Diehr, 450 U.S. 175 (1981), where a physical change, and thus patentability, was imparted by the claimed process; contrast, Parker v. Flook, 437 U.S. 584 (1978), where a physical change, and thus patentability, was not imparted by the claimed process); and the claims do not move beyond a general link of the use of the abstract idea to a particular technological environment (e.g., “for selecting a frontier goal for autonomous map building within a space …” claim 1).
Accordingly, claims 1-25 and 27-28 are rejected under 35 USC 101 as being drawn to an abstract idea without significantly more, and thus are ineligible.
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 use the word “means,” and are 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) are:
“means for determining trajectory costs” in at least claim 19
“means for determining co-visibility costs” in at least claim 19
“means for determining a frontier cost” in at least claim 19
“means for selecting one of a plurality …” in at least claim 19
“means for classifying …” in at least claim 25
“means for receiving inaccurate …” in at least claim 25
“means for generating a depth map …” in at least claim 25
“means for receiving sparse …” in at least claim 25
“means for generating a feature map …” in at least claim 25
“means for determining …” in at least claim 25
“means for determining the difference …” in at least claim 27
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.
The published specification provides corresponding structure for the claim limitations in at least paragraph 99.
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 § 103
In the event the determination of the status of the application as subject to AIA 35 U.S.C. 102 and 103 (or as subject to pre-AIA 35 U.S.C. 102 and 103) is incorrect, any correction of the statutory basis (i.e., changing from AIA to pre-AIA ) for the rejection will not be considered a new ground of rejection if the prior art relied upon, and the rationale supporting the rejection, would be the same under either status.
The following is a quotation of 35 U.S.C. 103 which forms the basis for all obviousness rejections set forth in this Office action:
A patent for a claimed invention may not be obtained, notwithstanding that the claimed invention is not identically disclosed as set forth in section 102, if the differences between the claimed invention and the prior art are such that the claimed invention as a whole would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention pertains. Patentability shall not be negated by the manner in which the invention was made.
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.
Claims 1-2, 10-11, 19-20, and 28-29 are rejected under 35 U.S.C. 103 as being unpatentable over Ren (US 20200117210 A1) (“Ren”) in view of Ito (US 20210285778 A1) (“Ito”).
With respect to claim 1, Ren teaches a method executed by a processor of a robotic device for selecting a frontier goal for autonomous map building within a space, comprising:
determining trajectory costs for the robotic device traversing from an occupied area to each of a plurality of available frontier goals within the space, wherein the plurality of available frontier goals include positions within the space from which the robotic device is configured to collect information to autonomously build a map of the space (See at least Ren Paragraph 61 “During auto-exploration, the robotic vehicle 102 a may determine a target position 520 and may engage in path planning in order to find a path from the current robot vehicle position to the target destination that minimize the likelihood that localization will fail while simultaneously minimizing the length of the path. To improve the likelihood that the robotic vehicle will not become lost or disoriented while traveling to the target position, the processor of the robotic vehicle 102 a may engage in dynamic path planning based on the environment's feature distribution, generated map data and so on. For example, the processor may modify the path throughout the period in which the robotic vehicle is travelling to the target position.” | Paragraph 69 “In various embodiments, each frontier center corresponds to a specific frontier. In the map, there may be multiple frontiers. To select a target position during frontier exploration, the processor of the robotic vehicle 102 may select a frontier to explore. The processor 102 may use the path cost function to select the frontier center as target position among the frontiers that are accessible, feature-rich, and require minimal rotation. Positions 602, 604, and 520 are exemplary frontier centers that may be selected as target positions given the frontier regions of 506 to 508, 508 to 510 and 510 to 504 are all taken as frontiers. The processor may select one of the frontier centers with the smallest path cost. For example, the processor may calculate a path cost for every accessible position from the robotic vehicle to each of frontier centers. The frontier center with the smallest calculated path cost may be selected as the target position.”);
determining a ratio of a number of one-glance-only frontiers traversed to reach the respective available frontier goal over a length of a trajectory route used to reach the respective available frontier goal (See at least Ren Paragraph 62 “In various embodiments, the robotic vehicle 102 calculate a cost function for any identified path option. The cost function may include the length of the path, the number of rotations and angle of each of those rotations needed in order to traverse the path, and whether the surrounding environment is feature-rich or feature-poor. Feature-level may be quantified along a scale or according to a number of distinguishable features in an area of the environment (e.g., within a captured image). The path distance “d”, angle of rotation “a”, and feature level “f” may be used to calculate a path cost for each identified path to the target position. For example, the path cost for a given path may be represented by the function … where i is an index of accessible paths, and γ, β, and φ are weights for d, a, and f respectively.”);
determining a frontier cost for each of the plurality of available frontier goals based on a difference between objectives of the respective available frontier goal; and selecting one of the plurality of available frontier goals having a lowest determined frontier cost (See at least Ren Paragraph 63 “In some embodiments, the robotic vehicle may calculate the path cost for each accessible path and may select the path with the smallest cost function. For example, each time the robotic vehicle stops to rotate, the (processor may recalculate the path cost of available paths to the target position, and select the path with the least rotation and highest feature level. In some embodiments, the processor may only recalculate path costs once the feature level of the area in which the robotic vehicle is presently located drops below a threshold level (i.e., because feature-poor).").
Ren, however, fails to explicitly disclose determining co-visibility costs for each of the plurality of available frontier goals, wherein the co-visibility costs are based on one or more effects between the plurality of available frontier goals including a ratio of a number of one-glance-only frontiers traversed to reach the respective available frontier goal over a length of a trajectory route used to reach the respective available frontier goal; determining a frontier cost for each of the plurality of available frontier goals based on a difference between a trajectory cost and a co-visibility cost of the respective available frontier goal.
Ito teaches determining co-visibility costs for each of the plurality of available frontier goals, wherein the co-visibility costs are based on one or more effects between the plurality of available frontier goals (See at least Ito Paragraph 74 “The third step will be described. The generation unit 152 determines the visiting order for the set of nodes to be visited. The generation unit 152 performs the determination so that the vehicle visits the nodes in the order of the shortest operation time, on the condition that the vehicle visits each of the nodes within a range of the time window of the node. The generation unit 152 uses data of the time taken for traveling between nodes when calculating the operation time.”)
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 the method of Ren to include determining co-visibility costs for each of the plurality of available frontier goals, wherein the co-visibility costs are based on one or more effects between the plurality of available frontier goals, as taught by Ito as disclosed above, such that the co-visibility cost is determined based on a ratio of a number of one-glance-only frontiers traversed to reach the respective available frontier goal over a length of a trajectory route used to reach the respective available frontier goal and that the frontier cost for each of the plurality of available frontier goals is determined based on a difference between a trajectory cost and a co-visibility cost of the respective available frontier goal, in order to ensure optimal route selection (Ito Paragraph 28 “In one aspect, an object of the present disclosure is to provide an information processing apparatus, a route generation method, and a route generation program with which the time taken by an optimization apparatus to select an optimum route may be reduced.”).
With respect to claim 2, and similarly claims 11 and 20, Ren in view of Ito teaches determining the trajectory costs for the robotic device traversing to each of the plurality of available frontier goals within the space comprises determining the trajectory costs for each of the plurality of available frontier goals based on a length, speed, and rotation associated with the respective available goal (See at least Ren Paragraph 42 “The maneuvering data module 228 may be coupled to the processor 220 and/or the navigation unit 222, and may be configured to provide travel control-related information such as orientation, attitude, speed, heading, and similar information that the navigation unit 222 may use for navigation purposes, such as dead reckoning between Global Navigation Satellite System (GNSS) position updates. ” | Paragraph 62 “In various embodiments, the robotic vehicle 102 calculate a cost function for any identified path option. The cost function may include the length of the path, the number of rotations and angle of each of those rotations needed in order to traverse the path, and whether the surrounding environment is feature-rich or feature-poor. Feature-level may be quantified along a scale or according to a number of distinguishable features in an area of the environment (e.g., within a captured image). The path distance “d”, angle of rotation “a”, and feature level “f” may be used to calculate a path cost for each identified path to the target position. For example, the path cost for a given path may be represented by the function … where i is an index of accessible paths, and γ, β, and φ are weights for d, a, and f respectively”).
With respect to claim 10, Ren teaches A robotic device, comprising: a camera; and a processor coupled to the camera and configured to:
determine trajectory costs for the robotic device traversing from an occupied area to each of a plurality of available frontier goals within a space, wherein the plurality of available frontier goals include positions within the space from which the robotic device is configured to collect information to autonomously build a map of the space (See at least Ren Paragraph 61 “During auto-exploration, the robotic vehicle 102 a may determine a target position 520 and may engage in path planning in order to find a path from the current robot vehicle position to the target destination that minimize the likelihood that localization will fail while simultaneously minimizing the length of the path. To improve the likelihood that the robotic vehicle will not become lost or disoriented while traveling to the target position, the processor of the robotic vehicle 102 a may engage in dynamic path planning based on the environment's feature distribution, generated map data and so on. For example, the processor may modify the path throughout the period in which the robotic vehicle is travelling to the target position.” | Paragraph 69 “In various embodiments, each frontier center corresponds to a specific frontier. In the map, there may be multiple frontiers. To select a target position during frontier exploration, the processor of the robotic vehicle 102 may select a frontier to explore. The processor 102 may use the path cost function to select the frontier center as target position among the frontiers that are accessible, feature-rich, and require minimal rotation. Positions 602, 604, and 520 are exemplary frontier centers that may be selected as target positions given the frontier regions of 506 to 508, 508 to 510 and 510 to 504 are all taken as frontiers. The processor may select one of the frontier centers with the smallest path cost. For example, the processor may calculate a path cost for every accessible position from the robotic vehicle to each of frontier centers. The frontier center with the smallest calculated path cost may be selected as the target position.”);
determine a ratio of a number of one-glance-only frontiers traversed to reach the respective available frontier goal over a length of a trajectory route used to reach the respective available frontier goal (See at least Ren Paragraph 62 “In various embodiments, the robotic vehicle 102 calculate a cost function for any identified path option. The cost function may include the length of the path, the number of rotations and angle of each of those rotations needed in order to traverse the path, and whether the surrounding environment is feature-rich or feature-poor. Feature-level may be quantified along a scale or according to a number of distinguishable features in an area of the environment (e.g., within a captured image). The path distance “d”, angle of rotation “a”, and feature level “f” may be used to calculate a path cost for each identified path to the target position. For example, the path cost for a given path may be represented by the function … where i is an index of accessible paths, and γ, β, and φ are weights for d, a, and f respectively.”);
determine a frontier cost for each of the plurality of available frontier goals based on a difference between objectives of the respective available frontier goal; and selecting one of the plurality of available frontier goals having a lowest determined frontier cost (See at least Ren Paragraph 63 “In some embodiments, the robotic vehicle may calculate the path cost for each accessible path and may select the path with the smallest cost function. For example, each time the robotic vehicle stops to rotate, the (processor may recalculate the path cost of available paths to the target position, and select the path with the least rotation and highest feature level. In some embodiments, the processor may only recalculate path costs once the feature level of the area in which the robotic vehicle is presently located drops below a threshold level (i.e., because feature-poor).").
Ren, however, fails to explicitly disclose determine co-visibility costs for each of the plurality of available frontier goals, wherein the co-visibility costs are based on one or more effects between the plurality of available frontier goals including a ratio of a number of one-glance-only frontiers traversed to reach the respective available frontier goal over a length of a trajectory route used to reach the respective available frontier goal; determine a frontier cost for each of the plurality of available frontier goals based on a difference between a trajectory cost and a co-visibility cost of the respective available frontier goal.
Ito teaches to determine co-visibility costs for each of the plurality of available frontier goals, wherein the co-visibility costs are based on one or more effects between the plurality of available frontier goals (See at least Ito Paragraph 74 “The third step will be described. The generation unit 152 determines the visiting order for the set of nodes to be visited. The generation unit 152 performs the determination so that the vehicle visits the nodes in the order of the shortest operation time, on the condition that the vehicle visits each of the nodes within a range of the time window of the node. The generation unit 152 uses data of the time taken for traveling between nodes when calculating the operation time.”)
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 the apparatus of Ren to determine co-visibility costs for each of the plurality of available frontier goals, wherein the co-visibility costs are based on one or more effects between the plurality of available frontier goals, as taught by Ito as disclosed above, such that the co-visibility cost is determined based on a ratio of a number of one-glance-only frontiers traversed to reach the respective available frontier goal over a length of a trajectory route used to reach the respective available frontier goal and that the frontier cost for each of the plurality of available frontier goals is determined based on a difference between a trajectory cost and a co-visibility cost of the respective available frontier goal, in order to ensure optimal route selection (Ito Paragraph 28 “In one aspect, an object of the present disclosure is to provide an information processing apparatus, a route generation method, and a route generation program with which the time taken by an optimization apparatus to select an optimum route may be reduced.”).
With respect to claim 19, Ren teaches A robotic device, comprising:
means for determining trajectory costs for the robotic device traversing from an occupied area to each of a plurality of available frontier goals within a space, wherein the plurality of available frontier goals include positions within the space from which the robotic device is configured to collect information to autonomously build a map of the space (See at least Ren Paragraph 61 “During auto-exploration, the robotic vehicle 102 a may determine a target position 520 and may engage in path planning in order to find a path from the current robot vehicle position to the target destination that minimize the likelihood that localization will fail while simultaneously minimizing the length of the path. To improve the likelihood that the robotic vehicle will not become lost or disoriented while traveling to the target position, the processor of the robotic vehicle 102 a may engage in dynamic path planning based on the environment's feature distribution, generated map data and so on. For example, the processor may modify the path throughout the period in which the robotic vehicle is travelling to the target position.” | Paragraph 69 “In various embodiments, each frontier center corresponds to a specific frontier. In the map, there may be multiple frontiers. To select a target position during frontier exploration, the processor of the robotic vehicle 102 may select a frontier to explore. The processor 102 may use the path cost function to select the frontier center as target position among the frontiers that are accessible, feature-rich, and require minimal rotation. Positions 602, 604, and 520 are exemplary frontier centers that may be selected as target positions given the frontier regions of 506 to 508, 508 to 510 and 510 to 504 are all taken as frontiers. The processor may select one of the frontier centers with the smallest path cost. For example, the processor may calculate a path cost for every accessible position from the robotic vehicle to each of frontier centers. The frontier center with the smallest calculated path cost may be selected as the target position.”);
means for determining a ratio of a number of one-glance-only frontiers traversed to reach the respective available frontier goal over a length of a trajectory route used to reach the respective available frontier goal (See at least Ren Paragraph 62 “In various embodiments, the robotic vehicle 102 calculate a cost function for any identified path option. The cost function may include the length of the path, the number of rotations and angle of each of those rotations needed in order to traverse the path, and whether the surrounding environment is feature-rich or feature-poor. Feature-level may be quantified along a scale or according to a number of distinguishable features in an area of the environment (e.g., within a captured image). The path distance “d”, angle of rotation “a”, and feature level “f” may be used to calculate a path cost for each identified path to the target position. For example, the path cost for a given path may be represented by the function … where i is an index of accessible paths, and γ, β, and φ are weights for d, a, and f respectively.”);
means for determining a frontier cost for each of the plurality of available frontier goals based on a difference between objectives of the respective available frontier goal; and selecting one of the plurality of available frontier goals having a lowest determined frontier cost (See at least Ren Paragraph 63 “In some embodiments, the robotic vehicle may calculate the path cost for each accessible path and may select the path with the smallest cost function. For example, each time the robotic vehicle stops to rotate, the (processor may recalculate the path cost of available paths to the target position, and select the path with the least rotation and highest feature level. In some embodiments, the processor may only recalculate path costs once the feature level of the area in which the robotic vehicle is presently located drops below a threshold level (i.e., because feature-poor).").
Ren, however, fails to explicitly disclose means for determining co-visibility costs for each of the plurality of available frontier goals, wherein the co-visibility costs are based on one or more effects between the plurality of available frontier goals including a ratio of a number of one-glance-only frontiers traversed to reach the respective available frontier goal over a length of a trajectory route used to reach the respective available frontier goal; means for determining a frontier cost for each of the plurality of available frontier goals based on a difference between a trajectory cost and a co-visibility cost of the respective available frontier goal.
Ito teaches means for determining co-visibility costs for each of the plurality of available frontier goals, wherein the co-visibility costs are based on one or more effects between the plurality of available frontier goals (See at least Ito Paragraph 74 “The third step will be described. The generation unit 152 determines the visiting order for the set of nodes to be visited. The generation unit 152 performs the determination so that the vehicle visits the nodes in the order of the shortest operation time, on the condition that the vehicle visits each of the nodes within a range of the time window of the node. The generation unit 152 uses data of the time taken for traveling between nodes when calculating the operation time.”)
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 the apparatus of Ren to include means for determining co-visibility costs for each of the plurality of available frontier goals, wherein the co-visibility costs are based on one or more effects between the plurality of available frontier goals, as taught by Ito as disclosed above, such that the co-visibility cost is determined based on a ratio of a number of one-glance-only frontiers traversed to reach the respective available frontier goal over a length of a trajectory route used to reach the respective available frontier goal and that the frontier cost for each of the plurality of available frontier goals is determined based on a difference between a trajectory cost and a co-visibility cost of the respective available frontier goal, in order to ensure optimal route selection (Ito Paragraph 28 “In one aspect, an object of the present disclosure is to provide an information processing apparatus, a route generation method, and a route generation program with which the time taken by an optimization apparatus to select an optimum route may be reduced.”).
With respect to claim 28, Ren teaches a non-transitory processor-readable medium having stored thereon processor-executable instructions configured to cause a processor of a robotic device to perform operations comprising:
determining trajectory costs for the robotic device traversing from an occupied area to each of a plurality of available frontier goals within the space, wherein the plurality of available frontier goals include positions within the space from which the robotic device is configured to collect information to autonomously build a map of the space (See at least Ren Paragraph 61 “During auto-exploration, the robotic vehicle 102 a may determine a target position 520 and may engage in path planning in order to find a path from the current robot vehicle position to the target destination that minimize the likelihood that localization will fail while simultaneously minimizing the length of the path. To improve the likelihood that the robotic vehicle will not become lost or disoriented while traveling to the target position, the processor of the robotic vehicle 102 a may engage in dynamic path planning based on the environment's feature distribution, generated map data and so on. For example, the processor may modify the path throughout the period in which the robotic vehicle is travelling to the target position.” | Paragraph 69 “In various embodiments, each frontier center corresponds to a specific frontier. In the map, there may be multiple frontiers. To select a target position during frontier exploration, the processor of the robotic vehicle 102 may select a frontier to explore. The processor 102 may use the path cost function to select the frontier center as target position among the frontiers that are accessible, feature-rich, and require minimal rotation. Positions 602, 604, and 520 are exemplary frontier centers that may be selected as target positions given the frontier regions of 506 to 508, 508 to 510 and 510 to 504 are all taken as frontiers. The processor may select one of the frontier centers with the smallest path cost. For example, the processor may calculate a path cost for every accessible position from the robotic vehicle to each of frontier centers. The frontier center with the smallest calculated path cost may be selected as the target position.”);
determining a ratio of a number of one-glance-only frontiers traversed to reach the respective available frontier goal over a length of a trajectory route used to reach the respective available frontier goal (See at least Ren Paragraph 62 “In various embodiments, the robotic vehicle 102 calculate a cost function for any identified path option. The cost function may include the length of the path, the number of rotations and angle of each of those rotations needed in order to traverse the path, and whether the surrounding environment is feature-rich or feature-poor. Feature-level may be quantified along a scale or according to a number of distinguishable features in an area of the environment (e.g., within a captured image). The path distance “d”, angle of rotation “a”, and feature level “f” may be used to calculate a path cost for each identified path to the target position. For example, the path cost for a given path may be represented by the function … where i is an index of accessible paths, and γ, β, and φ are weights for d, a, and f respectively.”);
determining a frontier cost for each of the plurality of available frontier goals based on a difference between objectives of the respective available frontier goal; and selecting one of the plurality of available frontier goals having a lowest determined frontier cost (See at least Ren Paragraph 63 “In some embodiments, the robotic vehicle may calculate the path cost for each accessible path and may select the path with the smallest cost function. For example, each time the robotic vehicle stops to rotate, the (processor may recalculate the path cost of available paths to the target position, and select the path with the least rotation and highest feature level. In some embodiments, the processor may only recalculate path costs once the feature level of the area in which the robotic vehicle is presently located drops below a threshold level (i.e., because feature-poor).").
Ren, however, fails to explicitly disclose determining co-visibility costs for each of the plurality of available frontier goals, wherein the co-visibility costs are based on one or more effects between the plurality of available frontier goals including a ratio of a number of one-glance-only frontiers traversed to reach the respective available frontier goal over a length of a trajectory route used to reach the respective available frontier goal; determining a frontier cost for each of the plurality of available frontier goals based on a difference between a trajectory cost and a co-visibility cost of the respective available frontier goal.
Ito teaches determining co-visibility costs for each of the plurality of available frontier goals, wherein the co-visibility costs are based on one or more effects between the plurality of available frontier goals (See at least Ito Paragraph 74 “The third step will be described. The generation unit 152 determines the visiting order for the set of nodes to be visited. The generation unit 152 performs the determination so that the vehicle visits the nodes in the order of the shortest operation time, on the condition that the vehicle visits each of the nodes within a range of the time window of the node. The generation unit 152 uses data of the time taken for traveling between nodes when calculating the operation time.”)
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 the method of Ren to include determining co-visibility costs for each of the plurality of available frontier goals, wherein the co-visibility costs are based on one or more effects between the plurality of available frontier goals, as taught by Ito as disclosed above, such that the co-visibility cost is determined based on a ratio of a number of one-glance-only frontiers traversed to reach the respective available frontier goal over a length of a trajectory route used to reach the respective available frontier goal and that the frontier cost for each of the plurality of available frontier goals is determined based on a difference between a trajectory cost and a co-visibility cost of the respective available frontier goal, in order to ensure optimal route selection (Ito Paragraph 28 “In one aspect, an object of the present disclosure is to provide an information processing apparatus, a route generation method, and a route generation program with which the time taken by an optimization apparatus to select an optimum route may be reduced.”).
With respect to claim 29, Ren in view of Ito teach applying a control signal to a vehicle based on the selected one of the plurality of available frontier goals (See at least Ren Paragraph 67 “In various embodiments, auto-exploration may be frontier-based, and as such a robotic vehicle's target position including the robotic vehicle's localization and orientation is determined based, at least in part on the frontier.”).
Claims 3, 12, and 21 are rejected under 35 U.S.C. 103 as being unpatentable over Ren (US 20200117210 A1) (“Ren”) in view of Ito (US 20210285778 A1) (“Ito”) further in view of Miller (US 20200200547 A1) (“Miller”).
With respect to claim 3, and similarly claims 12 and 21, Ren in view of Ito fails to explicitly disclose that determining the frontier cost for each of the plurality of available frontier goals based on the difference between the trajectory cost and the co-visibility cost of the respective available frontier goal comprises determining the frontier cost for each of the plurality of available goals using lower resolution mapping than a higher resolution mapping used for navigation to the selected frontier goal.
Miller teaches that determining the frontier cost for each of the plurality of available frontier goals based on the difference between the trajectory cost and the co-visibility cost of the respective available frontier goal comprises determining the frontier cost for each of the plurality of available goals using lower resolution mapping than a higher resolution mapping used for navigation to the selected frontier goal (See at least Miller FIG. 11 and Paragraphs 25-26 “Accordingly, the generated HD maps include the information necessary for an autonomous vehicle navigating safely without human intervention. Instead of collecting data for the HD maps using an expensive and time consuming mapping fleet process including vehicles outfitted with high resolution sensors, embodiments of the invention use data from the lower resolution sensors of the self-driving vehicles themselves as they drive around through their environments. The vehicles may have no prior map data for these routes or even for the region. Embodiments of the invention provide location as a service (LaaS) such that autonomous vehicles of different manufacturers can each have access to the most up-to-date map information created via these embodiments of invention. Embodiments generate and maintain high definition (HD) maps that are accurate and include the most updated road conditions for safe navigation. For example, the HD maps provide the current location of the autonomous vehicle relative to the lanes of the road precisely enough to allow the autonomous vehicle to drive safely in the lane.”).
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 the method of Ren in view of Ito to include that determining the frontier cost for each of the plurality of available frontier goals based on the difference between the trajectory cost and the co-visibility cost of the respective available frontier goal comprises determining the frontier cost for each of the plurality of available goals using lower resolution mapping than a higher resolution mapping used for navigation to the selected frontier goal, as taught by Miller as disclosed above, in order to ensure efficient resource allocation for navigation and cost determination (Miller Paragraph 5 “As a result, conventional techniques of maintaining maps are unable to provide the right data that is sufficiently accurate and up-to-date for safe navigation of autonomous vehicles”).
Claims 4-6, 13-15, and 22-24 are rejected under 35 U.S.C. 103 as being unpatentable over Ren (US 20200117210 A1) (“Ren”) in view of Ito (US 20210285778 A1) (“Ito”) further in view of Inoue (US 20190170527 A1) (“Inoue”).
With respect to claim 4, and similarly claims 13 and 22, Ren in view of Ito teaches that determining the trajectory costs for the robotic device traversing to each of the plurality of available frontier goals within the space comprises determining the determined trajectory costs for each of the plurality of available goals based on a sum of costs including a rotation cost of the respective available frontier goal (See at least Ren Paragraph 92 “In block 908, the processor may determine a path cost based, at least in part, on the classified areas, the determined distance, and the determined number of rotations and angles of the rotations. The path cost for each position may be determined or calculated according to equation 1 and as described.”).
Ren in view of Ito fails to explicitly disclose that the sum includes a friendliness cost.
Inoue teaches determining route costs using a friendliness cost (See at least Inoue Paragraph 8 “a map information acquisition unit that acquires map information including transport route information on a plurality of transport routes which are selection candidates; an electric power consumption map storage unit adapted to store a drive-time electric power consumption map used to estimate electric power consumption of the electric truck running on a predetermined route at a predetermined average vehicle speed without stopping; an average vehicle speed estimation unit for estimating an average vehicle speed during running on each of the plurality of transportation routes by counting out stoppage time; an electric power consumption estimation unit for estimating electric power consumption on each of the plurality of transportation routes based on the average vehicle speed estimated by the average vehicle speed estimation unit as well as on the electric power consumption map; and an optimal route selection unit that selects an optimal route based on fundamental information including information on the amount of electric power consumption of each of the plurality of transport routes.”).
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 the method of Ren in view of Ito to include determining route costs using a friendliness cost, as taught by Inoue as disclosed above, such that sum of costs for determining trajectory costs includes a friendliness cost, in order to ensure that the robotic device route moves at efficient speeds (Inoue Paragraph 7 “The present invention has been made to solve the above problem and has an object to provide a travel route selection system for an electric truck and a travel route selection method for an electric truck, where the travel route selection system and the travel route selection method can further improve electric mileage.”).
With respect to claim 5, and similarly claims 14 and 23, Ren in view of Ito in view of Inoue teaches that the friendliness cost for each of the plurality of available goals is based on a sum of the ratios of a length over a speed of each trajectory point along a route to the respective available frontier goal (See at least Inoue Paragraph 8 “a map information acquisition unit that acquires map information including transport route information on a plurality of transport routes which are selection candidates; an electric power consumption map storage unit adapted to store a drive-time electric power consumption map used to estimate electric power consumption of the electric truck running on a predetermined route at a predetermined average vehicle speed without stopping; an average vehicle speed estimation unit for estimating an average vehicle speed during running on each of the plurality of transportation routes by counting out stoppage time; an electric power consumption estimation unit for estimating electric power consumption on each of the plurality of transportation routes based on the average vehicle speed estimated by the average vehicle speed estimation unit as well as on the electric power consumption map; and an optimal route selection unit that selects an optimal route based on fundamental information including information on the amount of electric power consumption of each of the plurality of transport routes.”).
With respect to claim 6, and similarly claims 15 and 24, Ren in view of Ito in view of Inoue teach that the rotation cost for each of the plurality of available goals is based on a duration of rotations required while traversing to the respective available frontier goal (See at least Ren Paragraph 62 “In various embodiments, the robotic vehicle 102 calculate a cost function for any identified path option. The cost function may include the length of the path, the number of rotations and angle of each of those rotations needed in order to traverse the path, and whether the surrounding environment is feature-rich or feature-poor. Feature-level may be quantified along a scale or according to a number of distinguishable features in an area of the environment (e.g., within a captured image). The path distance “d”, angle of rotation “a”, and feature level “f” may be used to calculate a path cost for each identified path to the target position. For example, the path cost for a given path may be represented by the function … where i is an index of accessible paths, and γ, β, and φ are weights for d, a, and f respectively.”).
Allowable Subject Matter
Claims 7-9, 16-18, 25, and 27 are objected to as being dependent upon a rejected base claim, but would be allowable if rewritten in independent form including all of the limitations of the base claim and any intervening claims.
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.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to IBRAHIM ABDOALATIF ALSOMAIRY whose telephone number is (571)272-5653. The examiner can normally be reached M-F 7:30-5:30.
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/IBRAHIM ABDOALATIF ALSOMAIRY/ Examiner, Art Unit 3667 /KENNETH J MALKOWSKI/Primary Examiner, Art Unit 3667