DETAILED ACTION
Notice of Pre-AIA or AIA Status
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
Status of Claims
Pending
1, 4, 7, 10-11, 13-14, 16-17, 19-20
35 U.S.C. 101
1, 4, 7, 10-11, 13-14, 16-17, 19-20
35 U.S.C. 102
1, 4, 19, 20
35 U.S.C. 103
7, 10-11, 13-14, 16-17
Response to Amendment
This office action is in response to applicant’s arguments and amendments filed 09/18/2025, which are in response to USPTO Office Action mailed 06/18/2025. Applicant’s arguments and amendments have been considered with the results that follow: THIS ACTION IS MADE FINAL.
Claim Objections
Claims 1, 4, 7, 10-11, 13-14, 16-17, 19-20 are objected to because of the following informalities. The claims appear to be a literal translation into English from a foreign document and are replete with grammatical and idiomatic errors. For instance, claim 1 contains multiple errors. An example amendment includes:
“1. (Currently Amended) An intelligent scheduling system for a construction robot, comprising:
a construction robot for capturing [[a]] at least one current point cloud data of a construction environment; and
a control center communicatively connected to the construction robot, comprising:
means for storing a building model generated [[by]] based on machine learning of the at least one current point cloud data and at least one building information data, a simulated environment parameter provided by the at least one building information data in the building model is corrected by the at least one current point cloud data; and
means for evaluating a similarity between the at least one current point cloud data and the building model, and determining whether to use the building model or to generate another building model according to a preset similarity threshold, and generating a construction schedule corresponding to the building model or the another building model, wherein
the simulated environment parameter of the building model is corrected by the at least one current point cloud data when generating the another building model; and
the construction schedule is prioritized according to an at least one corrected building information data of the building model or the another building model.”
Claims 4, 7, 10, 11, 13, 14, 16, 17, 19, 20 include similar informalities that need correction and/or clarification. 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 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) is/are: means for storing in claims 1 and 7; and means for evaluating in claims 1 and 7.
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 specification discloses the corresponding structure for means for storing and means for evaluating in paragraphs [0012] and [0013].
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 § 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, 4, 7, 10-11, 13-14, 16-17, 19-20 are rejected under 35 U.S.C 101 because the claimed invention is directed to an abstract idea without significantly more.
Claim 1 is rejected under 35 U.S.C 101 because the claimed invention is directed to an abstract idea without significantly more. The claim recites:
“An intelligent scheduling system for construction robot, comprising:
a construction robot for capturing a current point cloud data of a construction environment; and
a control center communicatively connected to the construction robot, comprising:
means for storing a building model generated by based on machine learning of at least one point cloud data and at least one building information data, a simulated environment parameter provided by at least one building information data in the building model is corrected by at least one point cloud data; and
means for evaluating a similarity between the current point cloud data and the building models, and determining whether to use the building model or to generate another building model according to a preset similarity threshold, and generating a construction schedule corresponding to the building model or another building model, wherein
the simulated environment parameter of the building model is corrected by the current point cloud data when generate another building model; and
the construction schedule is prioritized according to a corrected building information data of the determined building model or the determined another building model.”
These limitations, as drafted, are simple processes that, under their broadest reasonable interpretation, cover performance of the mind, but for the recitation of “an intelligent scheduling system for construction robot, comprising: a construction robot for capturing a current point cloud data of a construction environment; and a control center communicatively connected to the construction robot, comprising: means for storing a building model generated by based on machine learning of at least one point cloud data and at least one building information data, a simulated environment parameter provided by at least one building information data in the building model is corrected by at least one point cloud data; and means for evaluating, the simulated environment parameter of the building model is corrected by the current point cloud data when generate another building model”. That is, other than reciting the underlined and italicized limitations above, nothing in the claim elements preclude the steps from being performed in the mind.
For example, a human can, in their mind, perform: evaluating a similarity between the current point cloud data and the building models, and determining whether to use the building model or to generate another building model according to a preset similarity threshold, and generating a construction schedule corresponding to the building model or another building model, wherein the construction schedule is prioritized according to a corrected building information data of the determined building model or the determined another building model.
This judicial exception is not integrated into a practical application. The claim recites the additional elements underlined and italicized above. The an intelligent scheduling system, a construction robot, a construction environment, a control center communicatively connected to the construction robot, means for storing, and means for evaluating is/are recited at a high level of generality and merely link(s) the use of the abstract idea to a particular technological environment (see MPEP 2106.05(h)).
The storing a building model step, a simulated environment parameter provided step, and the simulated environment parameter of the building model is corrected step is/are recited at a high level of generality and amounts to mere data gathering, manipulation, and transmission, which is a form of insignificant extra-solution activity (see MPEP 2106.05(g)). Accordingly, even in combination, the additional elements do not integrate the abstract idea into a practical application because they do not impose any meaningful limits on practicing the abstract idea.
The claim does not include additional elements that are sufficient to amount to significantly more than the judicial exception. The additional element of an intelligent scheduling system, a construction robot, a construction environment, a control center communicatively connected to the construction robot, means for storing, and means for evaluating is/are no more than mere generic linking of the abstract idea to a technological environment, which cannot provide an inventive concept.
The additional element of storing a building model step, a simulated environment parameter provided step, and the simulated environment parameter of the building model is corrected step is/are mere data gathering, manipulation, and transmission, and is a well-understood, routine, and conventional function (see MPEP 2106.05(d) and see Versata Dev. Group, Inc. v. SAP Am., Inc., 793 F.3d 1306, 1334, 115 USPQ2d 1681, 1701 (Fed. Cir. 2015); OIP Techs., 788 F.3d at 1363, 115 USPQ2d at 1092-93), and thus is/are no more than insignificant extra-solution activity (see MPEP 2106.05(g) and see OIP Techs., 788 F.3d at 1362-63, 115 USPQ2d at 1092-93). Thus, the limitations do not provide an inventive concept, and the claim contains ineligible subject matter.
Claims 4 recite(s) limitations that are no more that the abstract idea recited in claim(s) 1. The claim(s) recite(s) updating a schedule steps which can reasonably be performed in the human mind. The claim(s) recite(s) the construction robot at a high level of generality to generically link the use of the abstract idea in a particular technological environment. The claim(s) recite(s) providing a construction instruction, receiving the instruction, executing a procedure, and feeding a construction progress to a control center steps which is/are mere data gathering, manipulation, and transmission, and is/are a well-understood, routine, and conventional function, and thus is/are no more than insignificant extra-solution activity. See MPEP 2106.05(g). Thus, the claim(s) contain(s) ineligible subject matter.
Claim 7 is rejected under 35 U.S.C 101 because the claimed invention is directed to an abstract idea without significantly more. The claim recites:
“An intelligent construction robot system comprising:
two construction robots for capturing a current point cloud data of a construction environment separately; and
a control center communicatively connected to the construction robot, comprising:
means for storing multiple building models, each multiple building models generated by based on machine learning of multiple point cloud data and multiple building information data, a simulated environment parameter provided by at least one of the multiple building information data in each multiple building model is corrected by at least one of the multiple point cloud data; and
means for evaluating a highest similarity between each of the two current point cloud data and one of multiple building models, and determining whether to use one of multiple building models or to generate another building model according to a preset similarity threshold, and generating two construction schedules corresponding to the determined building model or another building model, wherein
the simulated environment parameter of the building model is corrected by the current point cloud data when generate another building model; and
two construction schedules are prioritized according to a corrected building information data of the determined building model or the determined another building model, and two construction instructions of each two construction schedules are sent to the two construction robots individually, wherein
one of two construction robots sequentially receive more than one of the construction instructions from two construction schedules after two construction schedules are updated by more than one construction progress from two construction robots of.”
These limitations, as drafted, are simple processes that, under their broadest reasonable interpretation, cover performance of the mind, but for the recitation of “an intelligent construction robot system comprising: two construction robots for capturing a current point cloud data of a construction environment separately; and a control center communicatively connected to the construction robot, comprising: means for storing multiple building models, each multiple building models generated by based on machine learning of multiple point cloud data and multiple building information data, a simulated environment parameter provided by at least one of the multiple building information data in each multiple building model is corrected by at least one of the multiple point cloud data; and means for evaluating; the simulated environment parameter of the building model is corrected by the current point cloud data when generate another building model; and two construction instructions of each two construction schedules are sent to the two construction robots individually, wherein one of two construction robots sequentially receive more than one of the construction instructions from two construction schedules after two construction schedules are updated by more than one construction progress from two construction robots of”. That is, other than reciting the underlined and italicized limitations above, nothing in the claim elements preclude the steps from being performed in the mind.
For example, a human can, in their mind, perform: evaluating a highest similarity between each of the two current point cloud data and one of multiple building models, and determining whether to use one of multiple building models or to generate another building model according to a preset similarity threshold, and generating two construction schedules corresponding to the determined building model or another building model, wherein two construction schedules are prioritized according to a corrected building information data of the determined building model or the determined another building model.
This judicial exception is not integrated into a practical application. The claim recites the additional elements underlined and italicized above. The an intelligent construction robot system, two construction robots, a construction environment, a control center, means for storing, and means for evaluating is/are recited at a high level of generality and merely link(s) the use of the abstract idea to a particular technological environment (see MPEP 2106.05(h)).
The storing multiple building models step, the simulated environment parameter of the building model is corrected step, two construction instructions of each two construction schedules are sent step, and construction robots sequentially receive instructions step is/are recited at a high level of generality and amounts to mere data gathering, manipulation, and transmission, which is a form of insignificant extra-solution activity (see MPEP 2106.05(g)). Accordingly, even in combination, the additional elements do not integrate the abstract idea into a practical application because they do not impose any meaningful limits on practicing the abstract idea.
The claim does not include additional elements that are sufficient to amount to significantly more than the judicial exception. The additional element of an intelligent construction robot system, two construction robots, a construction environment, a control center, means for storing, and means for evaluating is/are no more than mere generic linking of the abstract idea to a technological environment, which cannot provide an inventive concept.
The additional element of storing multiple building models step, the simulated environment parameter of the building model is corrected step, two construction instructions of each two construction schedules are sent step, and construction robots sequentially receive instructions step is/are mere data gathering, manipulation, and transmission, and is a well-understood, routine, and conventional function (see MPEP 2106.05(d) and see Versata Dev. Group, Inc. v. SAP Am., Inc., 793 F.3d 1306, 1334, 115 USPQ2d 1681, 1701 (Fed. Cir. 2015); OIP Techs., 788 F.3d at 1363, 115 USPQ2d at 1092-93), and thus is/are no more than insignificant extra-solution activity (see MPEP 2106.05(g) and see OIP Techs., 788 F.3d at 1362-63, 115 USPQ2d at 1092-93). Thus, the limitations do not provide an inventive concept, and the claim contains ineligible subject matter.
Claim(s) 10, 11 recite(s) limitations that are no more that the abstract idea recited in claim(s) 1 and 7. The claim(s) recite(s) obtaining a relative point of the dynamic reflector which can reasonably be performed in the human mind. The claim(s) recite(s) a positioning system, two total stations communicatively connected to the control center, the two total stations being fixedly installed in the two construction environment, at least one dynamic reflector installed on the two construction robots, and a total station, and the construction robot at a high level of generality to generically link the use of the abstract idea in a particular technological environment. The claim(s) recite(s) recording an absolute position of the total station steps which is/are mere data gathering, manipulation, and transmission, and is/are a well-understood, routine, and conventional function, and thus is/are no more than insignificant extra-solution activity. See MPEP 2106.05(g). Thus, the claim(s) contain(s) ineligible subject matter.
Claim(s) 13, 14 recite(s) limitations that are no more that the abstract idea recited in claim(s) 1 and 7. The claim(s) recite(s) obtain an absolute point of the environment reflector and obtain a relative point of the dynamic reflector which can reasonably be performed in the human mind. The claim(s) recite(s) a positioning system, total stations communicatively connected to the control center, the total stations being movably installed, at least one environmental reflector, and at least one dynamic reflector at a high level of generality to generically link the use of the abstract idea in a particular technological environment. The claim(s) recite(s) recording an absolute position of the total station steps which is/are mere data gathering, manipulation, and transmission, and is/are a well-understood, routine, and conventional function, and thus is/are no more than insignificant extra-solution activity. See MPEP 2106.05(g). Thus, the claim(s) contain(s) ineligible subject matter.
Claims 16, 17 recite(s) limitations that are no more that the abstract idea recited in claim(s) 1 and 7. The claim(s) recite(s) detecting and updating steps which can reasonably be performed in the human mind. The claim(s) recite(s) the control center and the total stations at a high level of generality to generically link the use of the abstract idea in a particular technological environment. The claim(s) recite(s) providing a detection command steps which is/are mere data gathering, manipulation, and transmission, and is/are a well-understood, routine, and conventional function, and thus is/are no more than insignificant extra-solution activity. See MPEP 2106.05(g). Thus, the claim(s) contain(s) ineligible subject matter.
Claim 19 is rejected under 35 U.S.C 101 because the claimed invention is directed to an abstract idea without significantly more. The claim recites:
“A method for generating an interpretation of an intelligent scheduling system for construction robot, comprising:
a machine learning phase, the steps include:
loading at least one building information data and capturing at least one point cloud data, each of the at least one point cloud data containing a construction environment parameter and an image data;
applying an image segmentation technique to each image data, correcting a simulated environment parameter of each of the at least one building information data by each construction environment parameters and each building information data for machine learning to form a building model; and
a machine interpretation phase, the steps include:
obtaining a current point cloud data corresponding to a construction environment containing the construction environment parameters and the image data corresponding to the construction environment;
applying the image segmentation technique to the image data of the current point cloud data;
evaluating a similarity between the current point cloud data and the building model; and
determining whether to use the building model or to generate another building model according to a preset similarity threshold; and
generating a construction schedule corresponding to the building model or another building model, wherein
the simulated environment parameter of the building model is corrected by the current point cloud data when generate another building model; and
the construction schedule is prioritized according to a corrected building information data of the determined building model or the determined another building model.”
These limitations, as drafted, are simple processes that, under their broadest reasonable interpretation, cover performance of the mind, but for the recitation of “an intelligent scheduling system for construction robot, a machine learning phase, the steps include: loading at least one building information data and capturing at least one point cloud data, each of the at least one point cloud data containing a construction environment parameter and an image data; applying an image segmentation technique to each image data, correcting a simulated environment parameter of each of the at least one building information data by each construction environment parameters and each building information data for machine learning to form a building model; and a machine interpretation phase, the steps include: obtaining a current point cloud data corresponding to a construction environment containing the construction environment parameters and the image data corresponding to the construction environment; applying the image segmentation technique to the image data of the current point cloud data; generating a construction schedule corresponding to the building model or another building model, wherein the simulated environment parameter of the building model is corrected by the current point cloud data when generate another building model”. That is, other than reciting the underlined and italicized limitations above, nothing in the claim elements preclude the steps from being performed in the mind.
For example, a human can, in their mind, perform a method for generating an interpretation of comprising: evaluating a similarity between the current point cloud data and the building model; and determining whether to use the building model or to generate another building model according to a preset similarity threshold; and the construction schedule is prioritized according to a corrected building information data of the determined building model or the determined another building model.
This judicial exception is not integrated into a practical application. The claim recites the additional elements underlined and italicized above. The an intelligent scheduling system for construction robot, a machine learning phase, and a machine interpretation phase is/are recited at a high level of generality and merely link(s) the use of the abstract idea to a particular technological environment (see MPEP 2106.05(h)).
The loading building information data and capturing point cloud data step, applying an image segmentation technique to image data step, correcting a simulated environment parameter step, obtaining a current point cloud data step, applying the image segmentation technique to image data of current point cloud data step, and generating a construction schedule step is/are recited at a high level of generality and amounts to mere data gathering, manipulation, and transmission, which is a form of insignificant extra-solution activity (see MPEP 2106.05(g)). Accordingly, even in combination, the additional elements do not integrate the abstract idea into a practical application because they do not impose any meaningful limits on practicing the abstract idea.
The claim does not include additional elements that are sufficient to amount to significantly more than the judicial exception. The additional element of an intelligent scheduling system for construction robot, a machine learning phase, and a machine interpretation phase is/are no more than mere generic linking of the abstract idea to a technological environment, which cannot provide an inventive concept.
The additional element of loading building information data and capturing point cloud data step, applying an image segmentation technique to image data step, correcting a simulated environment parameter step, obtaining a current point cloud data step, applying the image segmentation technique to image data of current point cloud data step, and generating a construction schedule step is/are mere data gathering, manipulation, and transmission, and is a well-understood, routine, and conventional function (see MPEP 2106.05(d) and see Versata Dev. Group, Inc. v. SAP Am., Inc., 793 F.3d 1306, 1334, 115 USPQ2d 1681, 1701 (Fed. Cir. 2015); OIP Techs., 788 F.3d at 1363, 115 USPQ2d at 1092-93), and thus is/are no more than insignificant extra-solution activity (see MPEP 2106.05(g) and see OIP Techs., 788 F.3d at 1362-63, 115 USPQ2d at 1092-93). Thus, the limitations do not provide an inventive concept, and the claim contains ineligible subject matter.
Claim(s) 20 recite(s) limitations that are no more that the abstract idea recited in claim(s) 19. The claim(s) recite(s) evaluating, retrieving and forming a schedule, selecting, and generating a model steps which can reasonably be performed in the human mind. The claim(s) recite(s) combining data steps which is/are mere data gathering, manipulation, and transmission, and is/are a well-understood, routine, and conventional function, and thus is/are no more than insignificant extra-solution activity. See MPEP 2106.05(g). Thus, the claim(s) contain(s) ineligible subject matter.
Claim Rejections - 35 USC § 102
In the event the determination of the status of the application as subject to AIA 35 U.S.C. 102 and 103 (or as subject to pre-AIA 35 U.S.C. 102 and 103) is incorrect, any correction of the statutory basis (i.e., changing from AIA to pre-AIA ) for the rejection will not be considered a new ground of rejection if the prior art relied upon, and the rationale supporting the rejection, would be the same under either status.
The following is a quotation of the appropriate paragraphs of 35 U.S.C. 102 that form the basis for the rejections under this section made in this Office action:
A person shall be entitled to a patent unless –
(a)(1) the claimed invention was patented, described in a printed publication, or in public use, on sale, or otherwise available to the public before the effective filing date of the claimed invention.
(a)(2) the claimed invention was described in a patent issued under section 151, or in an application for patent published or deemed published under section 122(b), in which the patent or application, as the case may be, names another inventor and was effectively filed before the effective filing date of the claimed invention.
Claim(s) 1, 4, 19, 20 is/are rejected under 35 U.S.C. 102(A)(1) as being anticipated by Ladha et al. (US 2018/0012125 A1, “Ladha”).
Regarding claim 1: Ladha teaches: An intelligent scheduling system for construction robot (see at least [0026]), comprising:
a construction robot for capturing a current point cloud data of a construction environment (see at least [0044] robot navigates building; [0045] traverses construction site); and
a control center communicatively connected to the construction robot (see at least [0080]; [0044]), comprising:
means for storing a building model generated by based on machine learning of at least one point cloud data and at least one building information data (see at least [0055] structure from planning and CAD; [0060] model of building from reference structure and sensor data from readings from building; [0056] machine learning),
a simulated environment parameter provided by at least one building information data in the building model is corrected by at least one point cloud data (see at least [0027] creates 3D representation of current state of building; detect discrepancies between design view and progress view to update design view); and
means for evaluating a similarity between the current point cloud data and the building models (see at least [0027] installation discrepancy threshold; [0029]; [0048]; [0049] threshold is accuracy tolerance), and
determining whether to use the building model or to generate another building model according to a preset similarity threshold (see at least [0027] sensor data makes 3D progress view and compares to 3D design view; when an installation discrepancy is above a predetermined threshold and is a reportable error, and sends a notification to project managers; [0049] being a 45 versus 90 degree angle joint, location error in excess of ⅛ inch; when discrepancy is greater than accuracy tolerance, reported as error; here, an error requires fixing and an updated model, whereas a non-error continues with the highest similarity model), and
generating a construction schedule corresponding to the building model or another building model (see at least [0028] catching error early means fixing before additional work is begun; [0071] adjust schedule to fix errors), wherein
the simulated environment parameter of the building model is corrected by the current point cloud data when generate another building model (see at least [0060] Fig. 19C shows two views after alignment; [0059] Figs. 20A-D, computer system map the label data to the component of the design plan data or sensor data; [0029] construction progress status based on combination of schedule data, maps, 3D design view, proper installation lists, discrepancies; here, building model based on point cloud data and model data; [0027]); and
the construction schedule is prioritized according to a corrected building information data of the determined building model or the determined another building model (see at least [0060] Fig. 19C shows two views after alignment; [0059] Figs. 20A-D, computer system map the label data to the component of the design plan data or sensor data; [0029] construction progress status based on combination of schedule data, maps, 3D design view, proper installation lists, discrepancies; here, building model based on point cloud data and model data; also [0027]; here, using updated model is prioritizing corrected building info).
Regarding claim 4: Ladha further teaches: The intelligent scheduling system for construction robot according to claim 1, wherein: the construction schedule comprises a construction instruction (see at least [0039] robot uses sensors to record physical properties of building; [0040] monitors construction progress; [0044] robot navigates building; [0045] robot traverses construction site); and
the construction robot executes a construction procedure in the construction environment after receiving the construction instruction (see at least [0039] robot uses sensors; [0040] monitors construction progress; [0044] robot navigates building; [0045] traverses construction site), wherein:
the construction robot feeds a construction progress to the control center after executing the construction procedure, and updates the construction schedule (see at least [0048], [0049]).
Regarding claim 19: Ladha teaches: A method for generating an interpretation of an intelligent scheduling system for construction robot (see at least [0026], [0056]), comprising:
a machine learning phase (see at least [0056]), the steps include:
loading at least one building information data and capturing at least one point cloud data, each of the at least one point cloud data containing a construction environment parameter and an image data (see at least [0045]; [0055] structure from planning and CAD; [0060] model of building from reference structure and sensor data from readings from building; [0056] machine learning);
applying an image segmentation technique to each image data, correcting a simulated environment parameter of each of the at least one building information data by each construction environment parameters and each building information data for machine learning to form a building model (see at least [0073] CNN processes image data; [0055] structure from planning and CAD; [0060] model of building from reference structure and sensor data from readings from building; Fig. 19C shows two views after alignment; [0056] machine learning; [0027] sensor data makes 3D progress view and compares to 3D design view; when an installation discrepancy is above a predetermined threshold and is a reportable error, and sends a notification to project managers; [0059] Figs. 20A-D, computer system map the label data to the component of the design plan data or sensor data; [0029] construction progress status based on combination of schedule data, maps, 3D design view, proper installation lists, discrepancies; here, building model based on point cloud data and model data); and
a machine interpretation phase (see at least [0057]), the steps include:
obtaining a current point cloud data corresponding to a construction environment containing the construction environment parameters and the image data corresponding to the construction environment (see at least [0045]; [0055] structure from planning and CAD; [0060] model of building from reference structure and sensor data from readings from building; [0056] machine learning);
applying the image segmentation technique to the image data of the current point cloud data (see at least [0056], [0057], [0073] CNN processes image data; [0027] sensor data makes 3D progress view and compares to 3D design view; when an installation discrepancy is above a predetermined threshold and is a reportable error, and sends a notification to project managers; [0049]);
evaluating a similarity between the current point cloud data and the building model (see at least [0056], [0057], [0073] CNN processes image data; [0027] sensor data makes 3D progress view and compares to 3D design view; when an installation discrepancy is above a predetermined threshold and is a reportable error, and sends a notification to project managers; [0049]); and
determining whether to use the building model or to generate another building model according to a preset similarity threshold (see at least [0056], [0057], [0073] CNN processes image data; [0027] sensor data makes 3D progress view and compares to 3D design view; when an installation discrepancy is above a predetermined threshold and is a reportable error, and sends a notification to project managers; [0049]); and
generating a construction schedule corresponding to the building model or another building model (see at least [0028] catching error early means fixing before additional work is begun; [0071] adjust schedule to fix errors), wherein
the simulated environment parameter of the building model is corrected by the current point cloud data when generate another building model (see at least [0060] Fig. 19C shows two views after alignment; [0059] Figs. 20A-D, computer system map the label data to the component of the design plan data or sensor data; [0029] construction progress status based on combination of schedule data, maps, 3D design view, proper installation lists, discrepancies; here, building model based on point cloud data and model data; [0027]); and
the construction schedule is prioritized according to a corrected building information data of the determined building model or the determined another building model (see at least [0060] Fig. 19C shows two views after alignment; [0059] Figs. 20A-D, computer system map the label data to the component of the design plan data or sensor data; [0029] construction progress status based on combination of schedule data, maps, 3D design view, proper installation lists, discrepancies; here, building model based on point cloud data and model data; also [0027]; here, using updated model is prioritizing corrected building info).
Regarding claim 20: Ladha further teaches: The method for generating an interpretation according to claim 19, during the machine interpretation phase, evaluating whether the similarity exceeds a preset similarity threshold (see at least [0027] installation discrepancy threshold; [0029]; [0048]; [0049] threshold is accuracy tolerance), wherein:
if the similarity exceeds the preset similarity threshold, the building model is directly retrieved and a construction schedule is formed (see at least [0049] being a 45 versus 90 degree angle joint, location error in excess of ⅛ inch; when discrepancy is greater than accuracy tolerance, reported as error; here, an error requires fixing and an updated model, whereas a non-error continues with the highest similarity model; [0071] adjust schedule to fix errors); and
if the similarity does not exceed the preset similarity threshold, selecting the building model with the highest similarity and combining the point cloud data with the building model to generate an updated building model to be stored in the model database (see at least [0060] Fig. 19C shows two views after alignment; [0059] Figs. 20A-D, computer system map the label data to the component of the design plan data or sensor data; [0029] construction progress status based on combination of schedule data, maps, 3D design view, proper installation lists, discrepancies).
Claim Rejections - 35 USC § 103
The following is a quotation of 35 U.S.C. 103 which forms the basis for all obviousness rejections set forth in this Office action:
A patent for a claimed invention may not be obtained, notwithstanding that the claimed invention is not identically disclosed as set forth in section 102, if the differences between the claimed invention and the prior art are such that the claimed invention as a whole would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention pertains. Patentability shall not be negated by the manner in which the invention was made.
The factual inquiries for establishing a background for determining obviousness under 35 U.S.C. 103 are summarized as follows:
1. Determining the scope and contents of the prior art.
2. Ascertaining the differences between the prior art and the claims at issue.
3. Resolving the level of ordinary skill in the pertinent art.
4. Considering objective evidence present in the application indicating obviousness or nonobviousness.
This application currently names joint inventors. In considering patentability of the claims the examiner presumes that the subject matter of the various claims was commonly owned as of the effective filing date of the claimed invention(s) absent any evidence to the contrary. Applicant is advised of the obligation under 37 CFR 1.56 to point out the inventor and effective filing dates of each claim that was not commonly owned as of the effective filing date of the later invention in order for the examiner to consider the applicability of 35 U.S.C. 102(b)(2)(C) for any potential 35 U.S.C. 102(a)(2) prior art against the later invention.
Claim(s) 7 is/are rejected under 35 U.S.C. 103 as being unpatentable over Ladha et al. (US 2018/0012125 A1) and further in view of Kumar et al. (US 2024/0181639 A1, “Kumar”).
Regarding claim 7: Ladha teaches: An intelligent construction robot system (see at least [0026]) comprising:
[construction robot] for capturing a current point cloud data of a construction environment […] (see at least [0044] robot navigates building; [0045] traverses construction site); and
a control center communicatively connected to the construction robot (see at least [0080]; [0044]), comprising:
means for storing multiple building models, each multiple building models generated by based on machine learning of multiple point cloud data and multiple building information data(see at least [0055] structure from planning and CAD; [0060] model of building from reference structure and sensor data from readings from building; [0056] machine learning),
a simulated environment parameter provided by at least one of the multiple building information data in each multiple building model is corrected by at least one of the multiple point cloud data(see at least [0027] creates 3D representation of current state of building; detect discrepancies between design view and progress view to update design view); and
means for evaluating a highest similarity between each of the two current point cloud data and one of multiple building models(see at least [0027] installation discrepancy threshold; [0029]; [0048]; [0049] threshold is accuracy tolerance), and
determining whether to use one of multiple building models or to generate another building model according to a preset similarity threshold (see at least [0027] sensor data makes 3D progress view and compares to 3D design view; when an installation discrepancy is above a predetermined threshold and is a reportable error, and sends a notification to project managers; [0049] being a 45 versus 90 degree angle joint, location error in excess of ⅛ inch; when discrepancy is greater than accuracy tolerance, reported as error; here, an error requires fixing and an updated model, whereas a non-error continues with the highest similarity model), and
generating two construction schedules corresponding to the determined building model or another building model (see at least [0028] catching error early means fixing before additional work is begun; [0071] adjust schedule to fix errors), wherein
the simulated environment parameter of the building model is corrected by the current point cloud data when generate another building model (see at least [0060] Fig. 19C shows two views after alignment; [0059] Figs. 20A-D, computer system map the label data to the component of the design plan data or sensor data; [0029] construction progress status based on combination of schedule data, maps, 3D design view, proper installation lists, discrepancies; here, building model based on point cloud data and model data; [0027]); and
two construction schedules are prioritized according to a corrected building information data of the determined building model or the determined another building model (see at least [0060] Fig. 19C shows two views after alignment; [0059] Figs. 20A-D, computer system map the label data to the component of the design plan data or sensor data; [0029] construction progress status based on combination of schedule data, maps, 3D design view, proper installation lists, discrepancies; here, building model based on point cloud data and model data; also [0027]; here, using updated model is prioritizing corrected building info), and
two construction instructions of each two construction schedules are sent to the [construction robot] individually, wherein (see at least [0039] robot uses sensors; [0040] monitors construction progress; [0044] robot navigates building; [0045] traverses construction site)
[construction robot] sequentially receive more than one of the construction instructions from two construction schedules after two construction schedules are updated by [construction robot] (see at least [0048], [0049]).
However, Ladha does not explicitly teach, but Kumar does teach:
two construction robots for capturing a current point cloud data . . . separately (see at least [0032], [0034]); and
two construction instructions of each two construction schedules are sent to the two construction robots individually, wherein (see at least [0032] robots collaborate with one another; [0034] controller controls plurality of mobile construction robots; [0051] robot path planning optimization (i.e. simultaneous control to individual robots)
one of two construction robots sequentially receive more than one of the construction instructions from two construction schedules after two construction schedules are updated by more than one construction progress from two construction robots of (see at least [0032] robots collaborate with one another; [0034] controller controls plurality of mobile construction robots; [0051] robot path planning optimization (i.e. simultaneous control to individual robots); [0081] output action; [0032] plurality of robots collaborate with one another).
Ladha and Kumar are analogous art to the claimed invention since they are from the similar field of construction site robot controls. It would have been obvious to one of ordinary skill in the art before the effective filing date of the invention to modify the invention of Ladha with the components of Kumar to create (with a reasonable expectation for success) an intelligent robot construction system that uses multiple robots, controls them simultaneously, and performs actions with the robots. The motivation for modification would have been to have robots working collaboratively (Kumar, [0032]) to reduce the time required to gather construction site data with an improved or optimal quality (Kumar, [0007]), thus increasing the overall effectiveness of the construction robot system.
Claim(s) 10 is/are rejected under 35 U.S.C. 103 as being unpatentable over Ladha et al. (US 2018/0012125 A1), Kumar et al. (US 2024/0181639 A1), and further in view of Stubler et al. (US 2019/0235733 A1, “Stubler”).
Regarding claim 10: Ladha-Kumar further teach: The intelligent construction robot system according to claim 7 including a positioning system (Ladha, see at least [0044]), comprising: at least one dynamic reflector is installed on each the two construction robots (Kumar, [0125] robot has locating mark in the form of a reflecting prism; used for high-precision localization of the construction robot; used with high-precision position detection device, e.g. a total station; [0032] robots collaborate with one another; [0034] controller controls plurality of mobile construction robots; [0051] robot path planning optimization (i.e. simultaneous control to individual robots), and two total stations (Kumar, [0125] total station and robots; [0032] robots collaborate with one another; [0034] controller controls plurality of mobile construction robots; [0051]).The motivation for modification would have been to have high-precision detection of robot location when traversing the worksite, increasing construction accuracy and positioning (Kumar, [0125]), thus increasing the overall effectiveness of the construction robot system.
However, Ladha-Kumar do not explicitly teach: two total stations communicatively connected to the control center, the two total stations being fixedly installed in each two construction environments, and each of the determined building model or another building model recorded an absolute position of the two total station separately, wherein, the two total stations capture an optical signal to obtain a relative point of each of the at least one dynamic reflector corresponding to the absolute position.
Stubler teaches: two total stations communicatively connected to the control center, see at least [0022], [0063]), the two total stations being fixedly installed in each two construction environments (see at least [0062]), and each of the determined building model or another building model recorded an absolute position of the two total station separately (see at least [0062], [0083], [0112]), wherein, the two total stations capture an optical signal to obtain a relative point of each of the at least one dynamic reflector corresponding to the absolute position (see at least [0063], [0112]).
Ladha-Kumar and Stubler are analogous art to the claimed invention since they are from the similar field of construction site robot controls. It would have been obvious to one of ordinary skill in the art before the effective filing date of the invention to modify the invention of Ladha-Kumar with the components of Stubler to create (with a reasonable expectation for success) an intelligent robot construction system that uses a total station to determine positions of relative points within the building model. The motivation for modification would have been to have a worksite where dealing with misalignment situations can be performed more efficiently without the need to call the site engineer in order to made a decision about the precise locations for setting out construction elements (Stubler, [0094]), thus increasing the overall effectiveness of the construction robot system.
Claim(s) 11 is/are rejected under 35 U.S.C. 103 as being unpatentable over Ladha et al. (US 2018/0012125 A1), and further in view of Kumar et al. (US 2024/0181639 A1), and Stubler et al. (US 2019/0235733 A1).
Regarding claim 11: Ladha further teaches: The intelligent construction robot system according to claim 1 including a positioning system (Ladha, see at least [0044] GPS, navigation system), comprising.
However, Ladha does not explicitly teach: a total station communicatively connected to the control center, the total station being fixedly installed in the construction environment, the building model recorded an absolute position of the total station, wherein at least one dynamic reflector is installed on the construction robot, and the total station captures an optical signal to obtain a relative point of each of the at least one dynamic reflector corresponding to the absolute position.
Kumar teaches: at least one dynamic reflector is installed on the construction robot ([0125] robot has locating mark in the form of a reflecting prism; used for high-precision localization of the construction robot; used with high-precision position detection device, e.g. a total station).
Ladha and Kumar are analogous art to the claimed invention since they are from the similar field of construction site robot controls. It would have been obvious to one of ordinary skill in the art before the effective filing date of the invention to modify the invention of Ladha with the components of Kumar to create (with a reasonable expectation for success) an intelligent robot construction system that uses robots with dynamic reflectors to perform positioning determination tasks. The motivation for modification would have been to have high-precision detection of robot location when traversing the worksite, increasing construction accuracy and positioning (Kumar, [0125]), thus increasing the overall effectiveness of the construction robot system.
However, Ladha-Kumar do not explicitly teach: a total station communicatively connected to the control center, the total station being fixedly installed in the construction environment, the building model recorded an absolute position of the total station, wherein . . . the total station captures an optical signal to obtain a relative point of each of the at least one dynamic reflector corresponding to the absolute position.
Stubler teaches: a total station communicatively connected to the control center (see at least [022], [0063]), the total station being fixedly installed in the construction environment (see at least [0062]), the building model recorded an absolute position of the total station (see at least [0062]), wherein . . . the total station captures an optical signal to obtain a relative point of each of the at least one dynamic reflector corresponding to the absolute position (see at least [0083], [0112]).
Ladha-Kumar and Stubler are analogous art to the claimed invention since they are from the similar field of construction site robot controls. It would have been obvious to one of ordinary skill in the art before the effective filing date of the invention to modify the invention of Ladha-Kumar with the components of Stubler to create (with a reasonable expectation for success) an intelligent robot construction system that uses a total station to determine positions of relative points within the building model. The motivation for modification would have been to have a worksite where dealing with misalignment situations can be performed more efficiently without the need to call the site engineer in order to made a decision about the precise locations for setting out construction elements (Stubler, [0094]), thus increasing the overall effectiveness of the construction robot system.
Claim(s) 13 and 16 is/are rejected under 35 U.S.C. 103 as being unpatentable over Ladha et al. (US 2018/0012125 A1), Kumar et al. (US 2024/0181639 A1), and further in view of Stubler et al. (US 2019/0235733 A1) and Stathis (US 201/0043515 A1, “Stathis”).
Regarding claim 13: Ladha-Kumar further teach: The intelligent construction robot system according to claim 7 including a positioning system (Ladha, see at least [0044]), comprising:
at least one dynamic reflector is installed on each the two construction robots (Kumar, [0125] robot has locating mark in the form of a reflecting prism; used for high-precision localization of the construction robot; used with high-precision position detection device, e.g. a total station; [0032] robots collaborate with one another; [0034] controller controls plurality of mobile construction robots; [0051] robot path planning optimization (i.e. simultaneous control to individual robots), and two total stations (Kumar, [0125] total station and robots; [0032] robots collaborate with one another; [0034] controller controls plurality of mobile construction robots; [0051]).The motivation for modification would have been to have high-precision detection of robot location when traversing the worksite, increasing construction accuracy and positioning (Kumar, [0125]), thus increasing the overall effectiveness of the construction robot system.
However, Ladha-Kumar do not explicitly teach: two total stations communicatively connected to the control center, the two total stations being movably installed in each of the construction environments, and each of the determined building model or another building model recorded an absolute position of the two total station separately, wherein at least one environmental reflector is installed in each two construction environments, and each the two total stations obtains an absolute point of the at least one environmental reflector corresponding to each two construction environments; and the two total stations capture an optical signal, and the absolute point to obtain a relative point of each of the at least one dynamic reflector corresponding to the absolute position.
Stubler teaches: two total stations communicatively connected to the control center (see at least [0022], [0063]),
each of the determined building model or another building model recorded an absolute position of the two total station separately, wherein (see at least [0062]);
at least one environmental reflector is installed in each two construction environments (see at least [0061]; [0062]; [0023]), and
each the two total stations obtains an absolute point of the at least one environmental reflector corresponding to each two construction environments (see at least [0083], [0112]); and
the two total stations capture an optical signal, and the absolute point to obtain a relative point of each of the at least one dynamic reflector corresponding to the absolute position (see at least [0083], [0112]).
Ladha-Kumar and Stubler are analogous art to the claimed invention since they are from the similar field of construction site robot controls. It would have been obvious to one of ordinary skill in the art before the effective filing date of the invention to modify the invention of Ladha-Kumar with the components of Stubler to create (with a reasonable expectation for success) an intelligent robot construction system that uses a total station to determine positions of relative points within the building model. The motivation for modification would have been to have a worksite where dealing with misalignment situations can be performed more efficiently without the need to call the site engineer in order to made a decision about the precise locations for setting out construction elements (Stubler, [0094]), thus increasing the overall effectiveness of the construction robot system.
However, Ladha-Kumar-Stubler do not explicitly teach, but Stathis does teach:
the two total stations being movably installed in each of the construction environments (see at least [0358] total station mounted on mobile robot, directs robot to specific locations for measurement, robot performs directed movement, total station performs measurement from various locations).
Ladha-Kumar-Stubler and Stathis are analogous art to the claimed invention since they are from the similar field of construction site robot controls. It would have been obvious to one of ordinary skill in the art before the effective filing date of the invention to modify the invention of Ladha-Kumar-Stubler with the components of Stathis to create (with a reasonable expectation for success) an intelligent robot construction system that uses a movable/mobile total station to determine positions of relative points within the building model. The motivation for modification would have been to have a mobile total station that can access more areas for measurement, since stationary total stations often have not available locations due to the fixed line-of-sight (Stathis, [0358]). Therefore, a movable total station increases the overall effectiveness of the construction robot system.
Regarding claim 16: Ladha-Kumar-Stubler-Stathis further teach: The intelligent construction robot system according to claim 13, wherein the control center provides a detection command to each the two total station to detect a current relative point of each of the dynamic reflector and updates the current relative point in the determined building model or another building model (Stathis, see at least [0358] total station mounted on mobile robot, directs robot to specific locations for measurement, robot performs directed movement, total station performs measurement from various locations; Kumar, see at least [0032], [0034], multiple robots and multiple total stations). The motivation for modification of Ladha-Kumar-Stubler with Stathis is the same as that described above in claim 13.
Claim(s) 14 and 17 is/are rejected under 35 U.S.C. 103 as being unpatentable over Ladha et al. (US 2018/0012125 A1), and further in view of Kumar et al. (US 2024/0181639 A1), Stubler et al. (US 2019/0235733 A1), and Stathis (US 201/0043515 A1).
Regarding claim 14: Ladha further teaches: The intelligent construction robot system according to claim 1 including a positioning system (Ladha, see at least [0044]), comprising.
However, Ladha does not explicitly teach: a total station communicatively connected to the control center, the total station being movably installed in the construction environment, the building model recording an absolute position of the total station, wherein at least one environmental reflector is installed in the construction environment, and the total station obtains an absolute point of the environmental reflector corresponding to the construction environment; and at least one dynamic reflector is installed on the construction robot, and the total station captures an optical signal, and the absolute point to obtain a relative point of the dynamic reflector corresponding to the absolute position.
Kumar teaches: at least one dynamic reflector is installed on the construction robot ([0125] robot has a reflecting prism; used with high-precision position detection device, e.g. a total station). The motivation for modification of Ladha with Kumar is the same as that described above in claim 8, with the addition of using a reflector on the robot to increase position data accuracy and the effectiveness of the use of the robot in a construction environment.
Ladha and Kumar are analogous art to the claimed invention since they are from the similar field of construction site robot controls. It would have been obvious to one of ordinary skill in the art before the effective filing date of the invention to modify the invention of Ladha with the components of Kumar to create (with a reasonable expectation for success) an intelligent robot construction system that uses robots with dynamic reflectors to perform positioning determination tasks. The motivation for modification would have been to have high-precision detection of robot location when traversing the worksite, increasing construction accuracy and positioning (Kumar, [0125]), thus increasing the overall effectiveness of the construction robot system.
However, Ladha-Kumar do not explicitly teach: a total station communicatively connected to the control center, the total station being movably installed in the construction environment, the building model recording an absolute position of the total station, wherein at least one environmental reflector is installed in the construction environment, and the total station obtains an absolute point of the environmental reflector corresponding to the construction environment; and . . . and the total station captures an optical signal, and the absolute point to obtain a relative point of the dynamic reflector corresponding to the absolute position.
Stubler teaches: a total station communicatively connected to the control center (see at least [0022], [0063]), . . . the building model recording an absolute position of the total station (see at least [0062]), wherein at least one environmental reflector is installed in the construction environment (see at least [0061]; [0062]; [0023]), and the total station obtains an absolute point of the environmental reflector corresponding to the construction environment (see at least [0083], [0112]); and . . . and the total station captures an optical signal, and the absolute point to obtain a relative point of the dynamic reflector corresponding to the absolute position (see at least [0083], [0112]).
Ladha-Kumar and Stubler are analogous art to the claimed invention since they are from the similar field of construction site robot controls. It would have been obvious to one of ordinary skill in the art before the effective filing date of the invention to modify the invention of Ladha-Kumar with the components of Stubler to create (with a reasonable expectation for success) an intelligent robot construction system that uses a total station to determine positions of relative points within the building model. The motivation for modification would have been to have a worksite where dealing with misalignment situations can be performed more efficiently without the need to call the site engineer in order to made a decision about the precise locations for setting out construction elements (Stubler, [0094]), thus increasing the overall effectiveness of the construction robot system.
However, Ladha-Kumar-Stubler do not explicitly teach, but Stathis does teach:
the total station being movably installed in the construction environment (see at least [0358] total station mounted on mobile robot, directs robot to specific locations for measurement, robot performs directed movement, total station performs measurement from various locations).
Ladha-Kumar-Stubler and Stathis are analogous art to the claimed invention since they are from the similar field of construction site robot controls. It would have been obvious to one of ordinary skill in the art before the effective filing date of the invention to modify the invention of Ladha-Kumar-Stubler with the components of Stathis to create (with a reasonable expectation for success) an intelligent robot construction system that uses a movable/mobile total station to determine positions of relative points within the building model. The motivation for modification would have been to have a mobile total station that can access more areas for measurement, since stationary total stations often have not available locations due to the fixed line-of-sight (Stathis, [0358]). Therefore, a movable total station increases the overall effectiveness of the construction robot system.
Regarding claim 17: Ladha-Kumar-Stubler-Stathis further teach: The intelligent construction robot system according to claim 14, wherein the control center provides a detection command to the total station to detect a current relative point of each of the dynamic reflector and updates the current relative point in the determined building model or another building model (Stathis, see at least [0358] total station mounted on mobile robot, directs robot to specific locations for measurement, robot performs directed movement, total station performs measurement from various locations). The motivation for modification of Ladha-Kumar-Stubler with Stathis is the same as that described above in claim 14.
Response to Arguments
Applicant's arguments filed 09/18/2025 have been fully considered but they are not persuasive.
Regarding the 101 Rejections:
Applicant argues:
Claim 1 has been amended to include the all limitations of Claim 2 and Claim 3, and include the limitations "a simulated environment parameter provided by at least one building information data in the building model is corrected by at least one point cloud data" and "the construction schedule is prioritized according to a corrected building information data of the determined building model or the determined another building model". The above quoted limitations are involved in the process of establishing the building model (such as correcting the simulated environment parameter by at least one point cloud data), and determining whether to use the building model or to generate another building model by the preset similarity threshold, the process of establishing another building model (such as correcting the simulated environment parameter by current point cloud data), and prioritizing the construction schedule. The claimed invention in amended Claim 1 should not be considered as the abstract idea to a particular technological environment.
Examiner response:
Examiner respectfully disagrees. Amending the elements of original claims 2 and 3 does not make claim 1 contain eligible subject matter. As shown above in the 101 rejections, the elements of claim 1 are still reciting evaluating, determining, generating a schedule, and prioritizing steps that can be performed in the human mind. The additional elements of the rest of the claim merely link the claim to a technological environment, and recite data gathering, manipulation, and transmission steps, which are not a recitation of a practical application, nor are they it significantly more than the judicial exception. As such, claim 1 still recites ineligible subject matter.
Applicant argues:
Claims 4-6 have also been amended to define the limitations of how to update the construction schedule. Claims 4-6 should be considered as containing eligible subject matter. Claim 7 has been rewritten as an independent claim, which includes the all limitations in amended Claim 1, and further includes the conditions of constructing a construction robot with more than one of the construction instructions sequentially. The claimed invention in amended Claim 7 should not be considered as the abstract idea to a particular technological environment.
Examiner response:
Updating a construction schedule can be performed in the human mind, or with the aid of pen and paper. This is still part of the mental process. Claim 7 is also still reciting ineligible subject matter. The robots are merely receiving instructions, which is data gathering and is a well-understood, routine and conventional function. The robots and other elements are recited at a high level of generality and merely link the use of the abstract idea to a particular technological environment, which does not provide a practical application or an inventive concept that can be considered significantly more than the judicial exception.
Applicant argues:
Claims 10-11 and 13-14 have also been amended to define the limitations of how to obtain a position of the construction robot by referring to the absolute position of the total station, which is recorded in the building model. Claims 10-11 should be considered as containing eligible subject matter. Claims 19-20 has been rewritten, to include the limitations involved in the process of establish the building model (such as correcting the simulated environment parameter by at least one point cloud data), and determining whether to use the building model or generate another building model by the preset similarity threshold, the process of establishing another building model (such as correcting the simulated environment parameter by current point cloud data), and the condition for prioritizing the construction schedule.
Examiner response:
Obtaining a relative point of something and determining a model can be performed in the human mind. The total stations and their environment are recited at a high level of generality to link the mental process to a technological environment. The recording of data and referring to absolute position data can be merely data gathering, which is insignificant, extra-solution activity. As such, claims 10-11 and 13-14 recite ineligible subject matter. As shown above in the 101 rejections, the elements of claims 19-20 are still reciting evaluating, determining, generating a schedule, and prioritizing steps that can be performed in the human mind. The additional elements of the rest of the claim merely link the claim to a technological environment, and recite data gathering, manipulation, and transmission steps, which are not a recitation of a practical application, nor are they it significantly more than the judicial exception. As such, claims 19-20 still recite ineligible subject matter.
Applicant argues:
Further, the method claimed in Claim 19, both image segmentation technique on image data of the point cloud data as a preprocessing step for machine learning, and the step for evaluating the similarity between the current point cloud data and the building model, must be implemented through specific software modules or deep learning algorithms, which is not merely a general method of applying abstract logic to a technical environment, nor is it a result of purely human mental reasoning. The claimed invention in amended Claim 19-20 should not be considered as the abstract idea to a particular technological environment.
Examiner response:
Claim 19 recites “applying an image segmentation technique to each image data, correcting a simulated environment parameter of each of the at least one building information data by each construction environment parameters and each building information data for machine learning to form a building model; and obtaining a current point cloud data corresponding to a construction environment containing the construction environment parameters and the image data corresponding to the construction environment; applying the image segmentation technique to the image data of the current point cloud data.” These limitations do not recite specific software modules or specific deep learning algorithms. They are merely recited as image segmentation and correcting parameters. Nothing in the claim precludes the limitations from being a general method of applying abstract logic to a technical environment, or from being a result of human mental processes. As such, the claims recite ineligible subject matter.
Regarding the 102/103 Rejections:
Applicant argues:
As mentioned above, the amended Claim 1 includes the limitations such as "a simulated environment parameter provided by at least one of the building information data in the building model is corrected by at least one of the point cloud data", "the simulated environment parameter of the building model is corrected by the current point cloud data when generate another building model", and "the construction schedule is prioritized according to a corrected building information data of the determined building model or the determined another building model", and none of these limitations were found in Ladha, either in the same or similar technical content. In the amended Claim 19, which includes limitations such as "correcting a simulated environment parameter of each of the at least one building information data by each the construction environment parameters and each the building information data for machine learning to form a building model", "generating a construction schedule corresponding to the building model or another building model", "the simulated environment parameter of the building model is corrected by the current point cloud data when generate another building model", and "the construction schedule is prioritized according to a corrected building information data of the determined building model or the determined another building model", none of these limitations were found in Ladha, either in the same or similar technical content. Ladha fails to disclose the technology regarding forming the construction schedule base on determined building model (or another building model). In view of the foregoing amendments, it is respectfully submitted that all claims particularly point out and distinctly claim the subject matter of the instant invention.
Examiner response:
Examiner respectfully disagrees. The prior art (Ladha) teaches an expected building model ([0055])that is based on the planned installation of the building or construction site ([0044-0045]). This model is simulated and has parameters associated with it. Then a robot navigates through the actual building and senses the actual state of the building during construction ([0027]). This data is used to correct the expected building model, by showing what is built already, what is built but might need adjustment, and what is built but is incorrect. These sensed details are used to correct the building model ([0027], [0049]). Then a construction schedule is adjusted based on the sense information and updated (corrected) building model ([0028], [0071]).
An example would be having to tear down and rebuild a wall that was placed in the wrong location. This “fix” would require an updated schedule that would need priority due to needing the “fix” to happen before other construction happens in the area associated with the incorrectly placed wall. This is Examiner’s interpretation of the prior art of record with respect to the recited claims. Specific paragraph citations can be found in the rejections in the office action above. The logic associated with each citation and how it is applied to the claim language follows that described herein.
Applicant argues:
Applicant submits that there is no motivation would have led one of ordinary skill to modify the disclosure in Ladha in view of Kumar, Stubler, and/or Stathis to arrive at the claimed in the present invention, even when combining the disclosures Ladha, Kumar, Stubler, and/or Stathis, it is still impossible to achieve the same effects as those features claimed in the Claim 1 (or 7 or 19).
Examiner response:
In response to applicant’s argument that there is no teaching, suggestion, or motivation to combine the references, the examiner recognizes that obviousness may be established by combining or modifying the teachings of the prior art to produce the claimed invention where there is some teaching, suggestion, or motivation to do so found either in the references themselves or in the knowledge generally available to one of ordinary skill in the art. See In re Fine, 837 F.2d 1071, 5 USPQ2d 1596 (Fed. Cir. 1988), In re Jones, 958 F.2d 347, 21 USPQ2d 1941 (Fed. Cir. 1992), and KSR International Co. v. Teleflex, Inc., 550 U.S. 398, 82 USPQ2d 1385 (2007). In this case:
Kumar modifies Ladha:
to have high-precision detection of robot location when traversing the worksite, increasing construction accuracy and positioning (Kumar, [0125]), thus increasing the overall effectiveness of the construction robot system.
to have robots working collaboratively (Kumar, [0032]) to reduce the time required to gather construction site data with an improved or optimal quality (Kumar, [0007]), thus increasing the overall effectiveness of the construction robot system.
Stubler modifies Ladha-Kumar:
to have a worksite where dealing with misalignment situations can be performed more efficiently without the need to call the site engineer in order to made a decision about the precise locations for setting out construction elements (Stubler, [0094]), thus increasing the overall effectiveness of the construction robot system.
Stathis modifies Ladha-Kumar-Stubler:
to have a mobile total station that can access more areas for measurement, since stationary total stations often have not available locations due to the fixed line-of-sight (Stathis, [0358]). Therefore, a movable total station increases the overall effectiveness of the construction robot system.
Applicant argues:
Applicant would like to explain first that the present invention claims "intelligent scheduling system for construction robot system and method for generating an interpretation" has several characteristics resulting in unexpected results of the claimed combination. [These are reasons (a) – (c) found in Applicant’s remarks, omitted for brevity.] As the explanation in (a) to (c) above demonstrate, the present invention not only demonstrates the data correction to obtain a complete and accurate building model (which incorporates both the actual construction environment parameters and the building data from the BIM model), but can also use the current point cloud data to renew the building model and create the construction schedule that aligns with the current construction environment.
Examiner response:
Examiner respectfully disagrees. The reasons provided in (a)-(c) are potential effects of the claimed system/method/apparatus, but they are not the claims themselves. Claim 1 (for example) recites:
“An intelligent scheduling system for construction robot, comprising:
a construction robot for capturing a current point cloud data of a construction environment; and
a control center communicatively connected to the construction robot, comprising:
means for storing a building model generated by based on machine learning of at least one point cloud data and at least one building information data, a simulated environment parameter provided by at least one building information data in the building model is corrected by at least one point cloud data; and
means for evaluating a similarity between the current point cloud data and the building models, and determining whether to use the building model or to generate another building model according to a preset similarity threshold, and generating a construction schedule corresponding to the building model or another building model, wherein
the simulated environment parameter of the building model is corrected by the current point cloud data when generate another building model; and
the construction schedule is prioritized according to a corrected building information data of the determined building model or the determined another building model.”
As such, in response to applicant's argument that the references fail to show certain features of the invention, it is noted that the features upon which applicant relies (i.e., reasons (a)-(c)) are not recited in the rejected claim(s). Although the claims are interpreted in light of the specification, limitations from the specification are not read into the claims. See In re Van Geuns, 988 F.2d 1181, 26 USPQ2d 1057 (Fed. Cir. 1993).
Applicant argues:
Ladha only provides a structure for monitoring construction, which uses machine learning (CNN) or data access (CAD) to monitor whether the construction meets the expected plan, and reports errors when the circumstance differs from expected plan. The system in Ladha can only compare differences but fails to correct the building model and generate the construction schedule automatically as the present application, and fails to provide the features or teach the features described in a) to c) above. Kumar only provides a method for optimizing a construction robot navigation (via depth image learning), which may be applied simultaneously to multiple construction robots. Kumar also fails to provide the features or teach the features described in a) to c) above. Even the combination of technologies Ladha and Kumar only optimizes the navigation path for one or more robots used to monitor the construction environment. Stubler provides a method for projecting a model (BIM) on the surface of the construction environment for assisting installation of elements and using the total station to visually track the user's movement path within the projection area. Stathis applies prism reflections to create multiple perspectives within the environment to make the system achieve multi-dimensional control. None of Stubler and Stathis provide any such teaching or suggestion as to the features described in a) to c) above.
Examiner response:
In response to applicant's arguments against the references individually, one cannot show nonobviousness by attacking references individually where the rejections are based on combinations of references. See In re Keller, 642 F.2d 413, 208 USPQ 871 (CCPA 1981); In re Merck & Co., 800 F.2d 1091, 231 USPQ 375 (Fed. Cir. 1986).
Applicant argues:
In addition to the features and unexpected results described as the explanation in a) to c) above, independent Claim 7 further includes the following characteristics: d) Multiple construction robots may process the construction instructions simultaneously based on different models, and each robot can receive instructions sequentially from different models as construction schedule is updated. Technology of machine learning offered by Ladha is designed to identify the component in the environment, but not to correct the BIM model via point cloud data. Furthermore, the building design data used by Ladha for comparison is a pre-established design plan. In other words, Ladha still fails to address the issue of BIM not being accurately integrated with the actual construction environment parameters. Consequently, the robotic system provided by Ladha only serves as a monitoring tool and cannot achieve generation and updates of the construction schedule based on the conditions of current construction environment. As shown in Tables 1 to 3, the purpose of establishing the building model in this present application is not merely to identify beams, columns, or combine data, but rather to enhance the construction robot's positioning within the construction environment by establishing accurate parameters of the actual construction environment, and achieve the coordination of construction robots between different construction schedules (and building models) and improving the accuracy of construction robot. As the explanation in a) to c) above, it can be obvious understand that the present invention not only demonstrate the data correction to obtain a complete and accurate building model (which incorporates both the actual construction environment parameters and the building data from the BIM model), but are also can use the current point cloud data to renew the building model and create the construction schedule that aligns with the current construction environment.
Examiner response:
Examiner respectfully disagrees. The reasons provided in (a)-(c) (and (d)) are potential effects of the claimed system/method/apparatus, but they are not the claims themselves. As such, in response to applicant's argument that the references fail to show certain features of the invention, it is noted that the features upon which applicant relies (i.e., reasons (a)-(c) and (d)) are not recited in the rejected claim(s). Although the claims are interpreted in light of the specification, limitations from the specification are not read into the claims. See In re Van Geuns, 988 F.2d 1181, 26 USPQ2d 1057 (Fed. Cir. 1993).
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure.
TÖRÖK et al. US 20230316567 A1: A method for surveying an environment by a movable surveying instrument with a progressional capturing of 2D-images by at least one camera and applying a visual simultaneous location and mapping algorithm (VSLAM) or a visual inertial simultaneous location and mapping algorithm (VISLAM) with a progressional deriving of a sparse evolving point cloud of at least part of the environment, and a progressional deriving of a trajectory of movement. The method comprises a progressional matching of the sparse evolving point cloud with a previously derived 3D-geometry, with a minimizing of a function configured to model a distance between the sparse point cloud and the previously derived 3D-geometry and deriving a spatial localization and orientation of the surveying instrument. At least one surveying measurement value of the environment by a spatial measurement unit is combined with the sparse point cloud or the previously derived 3D-geometry.
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 MADISON B EMMETT whose telephone number is (303)297-4231. The examiner can normally be reached Monday - Friday 9:00 - 5:00 ET.
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/MADISON B EMMETT/Examiner, Art Unit 3658
/THOMAS E WORDEN/Supervisory Patent Examiner, Art Unit 3658