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 .
Information Disclosure Statement
The information disclosure statement filed on 02/20/2024 fails to comply with 37 CFR 1.98(a)(2), which requires a legible copy of each cited foreign patent document; each non-patent literature publication or that portion which caused it to be listed; and all other information or that portion which caused it to be listed. It has been placed in the application file, but the information referred to therein has not been considered.
Claim Objections
Claim 10 objected to because of the following informalities: claim 10 begins by reciting “A method, performed by a controller, for scanning a object to be welded …” and appears to have a typographical error meant to read “…scanning an object…”. Claims 11 – 18 inherit this objection by virtue of their dependency. Appropriate correction is required.
Claim Interpretation
The following is a quotation of 35 U.S.C. 112(f):
(f) Element in Claim for a Combination. – An element in a claim for a combination may be expressed as a means or step for performing a specified function without the recital of structure, material, or acts in support thereof, and such claim shall be construed to cover the corresponding structure, material, or acts described in the specification and equivalents thereof.
The following is a quotation of pre-AIA 35 U.S.C. 112, sixth paragraph:
An element in a claim for a combination may be expressed as a means or step for performing a specified function without the recital of structure, material, or acts in support thereof, and such claim shall be construed to cover the corresponding structure, material, or acts described in the specification and equivalents thereof.
The claims in this application are given their broadest reasonable interpretation using the plain meaning of the claim language in light of the specification as it would be understood by one of ordinary skill in the art. The broadest reasonable interpretation of a claim element (also commonly referred to as a claim limitation) is limited by the description in the specification when 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, is invoked.
As explained in MPEP § 2181, subsection I, claim limitations that meet the following three-prong test will be interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph:
(A) the claim limitation uses the term “means” or “step” or a term used as a substitute for “means” that is a generic placeholder (also called a nonce term or a non-structural term having no specific structural meaning) for performing the claimed function;
(B) the term “means” or “step” or the generic placeholder is modified by functional language, typically, but not always linked by the transition word “for” (e.g., “means for”) or another linking word or phrase, such as “configured to” or “so that”; and
(C) the term “means” or “step” or the generic placeholder is not modified by sufficient structure, material, or acts for performing the claimed function.
Use of the word “means” (or “step”) in a claim with functional language creates a rebuttable presumption that the claim limitation is to be treated in accordance with 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph. The presumption that the claim limitation is interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, is rebutted when the claim limitation recites sufficient structure, material, or acts to entirely perform the recited function.
Absence of the word “means” (or “step”) in a claim creates a rebuttable presumption that the claim limitation is not to be treated in accordance with 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph. The presumption that the claim limitation is not interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, is rebutted when the claim limitation recites function without reciting sufficient structure, material or acts to entirely perform the recited function.
Claim limitations in this application that use the word “means” (or “step”) are being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, except as otherwise indicated in an Office action. Conversely, claim limitations in this application that do not use the word “means” (or “step”) are not being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, except as otherwise indicated in an Office action.
This application includes one or more claim limitations that do not use the word “means,” but are nonetheless being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, because the claim limitation(s) uses a generic placeholder that is coupled with functional language without reciting sufficient structure to perform the recited function and the generic placeholder is not preceded by a structural modifier. Such claim limitation(s) is/are: “a scan device” in claim 1 wherein a generic placeholder “device” is preceded by a functional word “scan” without sufficient rection of what the “scan device” structurally entails.
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.
Structural support for “a scan device” can be found in paragraphs (0066 – 0067) of the specification, wherein the scan device is defined to be any imaging device that includes one or more sensors (a visual sensor, a laser, a LIDAR sensor, an audio sensor, a, electromagnetic sensor, an ultrasonic sensor or a combination thereof) positioned on or coupled to a robotic arm. Thus, “a scan device” is interpreted to be any imaging device coupled to a robotic arm and equivalent thereof for the purpose of this examination.
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
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.
Claim(s) 1 – 5, 9 – 14 , 16 – 17 and 19 – 20 is/are rejected under 35 U.S.C. 103 as being unpatentable over NPL, Liu Yan et al., "Robot path planning with two-axis positioner for non-ideal sphere-pipe joint welding based on laser scanning", The International Journal of Advanced Manufacturing Technology, Springer, London, published August 30, 2019, (recited in the IDS), hereinafter “Yan”, in view of NPL, Monica Riccardo et al., “A 3D Robot Self Filter for Next Best View Planning", Third IEEE international conference on robotic computing (IRC), IEEE, February 25, 2019, (recited in the IDS) and hereinafter “Monica”.
Regarding claim 1, Yan discloses an assembly robotic system configured to scan an object to be welded (robotic laser scanning system configured to scan a weld seam (intersecting curve) of an object, page (1297 – 1298, sections 2.1, 3, see FIGS. 1and 3)), the assembly robotic system comprising:
a controller that includes one or more processors and one or more memories coupled to the one or more processors (a robot controller configured to download Robot job file from a host computer, page 1298, section 2.2. Thus, the robot controller naturally has one or more processor and one or more memories coupled to the one or mor processors), the controller configured to:
generate, based on one or more characteristics of a sensor of a scan device, a plurality of the plurality of poses associated with a region corresponding to a seam of the object, the seam associated with a feature of one or more features of the object (determine a number of scanning points on the seam and measurement attitude of the laser sensor, based on measurement attitude recommended by the manufacturer of the sensor, accurately describing measurement and approach poses, (page 1299 section 3.1) *Note here- “candidate poses” are interpreted to mean candidate vantage points or postures of the scan device (laser scanner), see specification ¶ 0110);
for each pose of the plurality of poses, simulate, based on the one or more characteristics of the sensor and based on one or more physical parameters associated with the object, a scan operation from the pose to generate simulated scan data indicating a simulated image of the region for the candidate pose (a simulation of a scan trajectory is performed, based on characteristics of the laser sensor and the physical parameters of the sphere-pipe seam, to validate the approach proposed, page 1306 – 1308 and sections 5.1 – 5.2);
select,scan poses that are associated with a scan trajectory of the scan device (a scanning point/posture of the laser scanning trajectory description is obtained by arranging simulation trajectory data into the robot motion program, (page 1299 – 1300 and section 3.2); and
initiate, based on the scan trajectory, the scan device to perform a first scan operation of the region through each scan pose of the multiple scan poses (perform scanning (Ascan) test on the sphere-pipe seam (intersecting curve) for the obtained scanning point/posture, (section 3.2 and see FIG.6b)).
Yan does not explicitly teach that the determined number of scanning points /poses are candidate poses, selecting from the plurality of candidate poses and based on the simulated scan data multiple scan poses, and the scan performed is through each scan pose of the selected multiple scan poses.
However, Monica, a paper that relates to the use of a real-time self-filter for a robot manipulator in selecting best view planning tasks (abstract), also teaches that generating of scanning poses that are candidate poses (candidate view poses of the robotic scanner, pointing towards spherical region of interest (ROI) is generated and sampled at regular intervals on the surface of a sphere, (page 118 – 119 , section III)), selecting from the plurality of candidate poses and based on the simulated scan data multiple scan poses (a sensor depth image is simulated for each view pose and a score is assigned to each view, proportional to the number of unknown visible pixels and motion planner is executed to find the reachable view pose with the highest possible score, (page 119, section III)), the scan performed is through each scan pose of the selected multiple scan poses (at this point the robot moves the sensor in the each selected best viewpoint, (page 119, section III)).
Monica further states that this self-filtering algorithm of robotic poses is to select at each iteration an optimal view pose for the sensor that provide optimize information gained from a region of interest minimizing inefficiency of the scan, (abstract).
Therefore, it would have been obvious for one of ordinary skill in the art, before the effective filling date of the claimed invention, to modify the robotic laser scanning system of Yan to include a candidate pose filtering and selecting feature based on simulated scan data scores and perform the scan for each selected pose in order to optimize the scan to produce usable information on the region of interest improving overall efficiency of the scan planning and scanning process as taught in Monica.
Regarding claim 10, Yan discloses a method, performed by a controller, for scanning an object to be welded processors (a robot controller configured to perform a scanning of a seam to be welded, page 1298, section 2.2.), the method comprising:
generating, based on one or more characteristics of a sensor of a scan device, a plurality of the plurality of poses associated with a region corresponding to a seam of the object, the seam associated with a feature of one or more features of the object (determining a number of scanning points on the seam and measurement attitude of the laser sensor, based on measurement attitude recommended by the manufacturer of the sensor, accurately describing measurement and approach poses, (page 1299 section 3.1) *Note here- “candidate poses” are interpreted to mean candidate vantage points or postures of the scan device (laser scanner), see specification ¶ 0110);
for each pose of the plurality of poses, simulate, based on the one or more characteristics of the sensor and based on one or more physical parameters associated with the object, a scan operation from the pose to generate simulated scan data indicating a simulated image of the region for the candidate pose (a simulation of a scan trajectory is performed, based on characteristics of the laser sensor and the physical parameters of the sphere-pipe seam, to validate the approach proposed, page 1306 – 1308 and sections 5.1 – 5.2);
selecting,scan poses that are associated with a scan trajectory of the scan device (a scanning point/posture of the laser scanning trajectory description is obtained by arranging simulation trajectory data into the robot motion program, (page 1299 – 1300 and section 3.2); and
initiating, based on the scan trajectory, the scan device to perform a first scan operation of the region through each scan pose of the multiple scan poses (perform scanning (Ascan) test on the sphere-pipe seam (intersecting curve) for the obtained scanning point/posture, (section 3.2 and see FIG.6b)).
Yan does not explicitly teach that the determined number of scanning points /poses are candidate poses, selecting from the plurality of candidate poses and based on the simulated scan data multiple scan poses, and the scan performed is through each scan pose of the selected multiple scan poses.
However, Monica, a paper that relates to the use of a real-time self-filter for a robot manipulator in selecting best view planning tasks (abstract), also teaches that generating of scanning poses that are candidate poses (candidate view poses of the robotic scanner, pointing towards spherical region of interest (ROI) is generated and sampled at regular intervals on the surface of a sphere, (page 118 – 119 , section III)), selecting from the plurality of candidate poses and based on the simulated scan data multiple scan poses (a sensor depth image is simulated for each view pose and a score is assigned to each view, proportional to the number of unknown visible pixels and motion planner is executed to find the reachable view pose with the highest possible score, (page 119, section III)), the scan performed is through each scan pose of the selected multiple scan poses (at this point the robot moves the sensor in the each selected best viewpoint, (page 119, section III)).
Monica further states that this self-filtering algorithm of robotic poses is to select at each iteration an optimal view pose for the sensor that provide optimize information gained from a region of interest minimizing inefficiency of the scan, (abstract).
Therefore, it would have been obvious for one of ordinary skill in the art, before the effective filling date of the claimed invention, to modify the controller of the robotic laser scanning system of Yan to include a candidate pose filtering and selecting feature based on simulated scan data scores and perform the scan for each selected pose in order to optimize the scan to produce usable information on the region of interest improving overall efficiency of the scan planning and scanning process as taught in Monica.
Regarding claim 19, a non-transitory computer-readable medium storing instructions that, when executed by one or more processors of a controller cause the controller to (a robot controller configured to download Robot job file from a host computer, page 1298, section 2.2. Thus, the robot controller naturally and inherently has a non-transitory computer-readable medium storing instructions and one or more processors that cause the controller to execute instruction):
generate, based on one or more characteristics of a sensor of a scan device, a plurality of the plurality of poses associated with a region corresponding to a seam of the object, the seam associated with a feature of one or more features of the object (determine a number of scanning points on the seam and measurement attitude of the laser sensor, based on measurement attitude recommended by the manufacturer of the sensor, accurately describing measurement and approach poses, (page 1299 section 3.1) *Note here- “candidate poses” are interpreted to mean candidate vantage points or postures of the scan device (laser scanner), see specification ¶ 0110);
for each pose of the plurality of poses, simulate, based on the one or more characteristics of the sensor and based on one or more physical parameters associated with the object, a scan operation from the pose to generate simulated scan data indicating a simulated image of the region for the candidate pose (a simulation of a scan trajectory is performed, based on characteristics of the laser sensor and the physical parameters of the sphere-pipe seam, to validate the approach proposed, page 1306 – 1308 and sections 5.1 – 5.2);
select,scan poses that are associated with a scan trajectory of the scan device (a scanning point/posture of the laser scanning trajectory description is obtained by arranging simulation trajectory data into the robot motion program, (page 1299 – 1300 and section 3.2); and
initiate, based on the scan trajectory, the scan device to perform a first scan operation of the region through each scan pose of the multiple scan poses (perform scanning (Ascan) test on the sphere-pipe seam (intersecting curve) for the obtained scanning point/posture, (section 3.2 and see FIG.6b)).
Yan does not explicitly teach that the determined number of scanning points /poses are candidate poses, selecting from the plurality of candidate poses and based on the simulated scan data multiple scan poses, and the scan performed is through each scan pose of the selected multiple scan poses.
However, Monica, a paper that relates to the use of a real-time self-filter for a robot manipulator in selecting best view planning tasks (abstract), also teaches that generating of scanning poses that are candidate poses (candidate view poses of the robotic scanner, pointing towards spherical region of interest (ROI) is generated and sampled at regular intervals on the surface of a sphere, (page 118 – 119 , section III)), selecting from the plurality of candidate poses and based on the simulated scan data multiple scan poses (a sensor depth image is simulated for each view pose and a score is assigned to each view, proportional to the number of unknown visible pixels and motion planner is executed to find the reachable view pose with the highest possible score, (page 119, section III)), the scan performed is through each scan pose of the selected multiple scan poses (at this point the robot moves the sensor in the each selected best viewpoint, (page 119, section III)).
Monica further states that this self-filtering algorithm of robotic poses is to select at each iteration an optimal view pose for the sensor that provide optimize information gained from a region of interest minimizing inefficiency of the scan, (abstract).
Therefore, it would have been obvious for one of ordinary skill in the art, before the effective filling date of the claimed invention, to modify the robotic laser scanning system of Yan to include a candidate pose filtering and selecting feature based on simulated scan data scores and perform the scan for each selected pose in order to optimize the scan to produce usable information on the region of interest improving overall efficiency of the scan planning and scanning process as taught in Monica.
Regarding claims 2 and 11, Yan in view of Monica teaches the assembly robotic system of claim 1 and the method of claim 10, wherein the controller is further configured to: evaluate the simulated scan data, wherein: to evaluate the simulated scan data, the controller is configured to assign one or more scores to one or more candidate poses of the plurality of candidate poses, the one or more scores calculated based on a similarity between the simulated scan data and model data associated with the region, and the model data includes scan data from a second scan operation, representation data associated with a representation of the region, or a combination thereof (a score is assigned to simulated views of the region (scan data) of each the plurality of candidate poses based on the number of unknown visible pixels, Monica (page 119, section III) thus, one of ordinary skill in the art would appreciate a comparison is executed between what the simulated scan revealed and what the model data of the region represented).
Regarding claims 3 and 12, Yan in view of Monica teaches the assembly robotic system of claim 2, the method of claim 11 wherein, to assign the one or more scores to the one or more candidate poses, the controller is configured to: assign one or more weights to one or more instances of the simulated scan data, one or more instances of the model data, or a combination thereof, and the one or more weights are assigned based on an information density of the one or more instances of the simulated scan data, the one or more instances of the model data, or a combination thereof (the simulated scan data is considered complete when the score (γf) of the next best view becomes lower than a given threshold γth, i.e., when a sufficiently low information gain is predicted for the next best view pose, Monica (page 119, section III) thus, one of ordinary skill in the art would appreciate when information gain (added information) to a simulated scan of a region is low, the simulated scan data has an a higher information density and the weight of the score is based on the information density of the simulated scan data).
Regarding claims 4 and 13, Yan in view of Monica teaches the assembly robotic system of claim 3 and the method of claim 12, wherein, to assign the one or more weights, the controller is configured to: determine the information density of the one or more instances of the simulated scan data, the one or more instances of the model data, or a combination thereof, and the information density is determined based on a topology indicated by the one or more instances of the simulated scan data, the one or more instances of the model data, or a combination thereof (information density is determined based on comparing how much additional information is gained by the next best view simulated data from the previous simulated scan data, Monica (page 119, section III) thus, the information density is determine based on topology of new simulated scan data has added value compared to a previous simulated scan data).
Regarding claims 5 and 14, Yan in view of Monica teaches the assembly robotic system of claim 1 and the method of claim 10, wherein, to initiate the first scan operation, the controller is configured to decrease a speed of the first scan operation performed from a set of the multiple scan poses, the set including one or more scan poses from which are generated first simulated scan data having higher information density than second simulated scan data generated from other scan poses of the plurality of candidate scan poses (a scanning curve with appropriate scanning speed (Vscan) is demonstrated, Yan (page 1299 section 3.1 and see FIG.5) and one of ordinary skill in the art would appreciate that decreasing the scanning speed when scanning areas represents higher information density, as. increasing the speed can compromise the quality or the capability to capture details of the region of interest).
Regarding claim 9, Yan in view of Monica teaches the assembly robotic system of claim 1, wherein, to select the multiple scan poses, the controller is configured to:
evaluate the scan trajectory from different combinations of the plurality of candidate poses based on modelling potential collisions among one or more objects of a welding robot associated with the controller and other objects of a workspace in which the welding robot is situated including the object, and select the multiple scan poses based on evaluating the scan trajectory (In this work the MoveIt, motion planner is used to plan collision free robot paths wherein, the motion planner considers both occupied and unknown voxels as obstacles, Monica (page 119 and section 3)).
Regarding claim 16, Yan in view of Monica teaches the method of claim 10, wherein selecting from among the one or more candidate poses includes: receiving, prior to initiating the first scan operation, welding parameters associated with a welding operation to be performed; and selecting from among the plurality of candidate poses based on the welding parameters (selecting the proper welding process parameters include arc voltage and current, welding speed, weld inclination, and welding torch attitude, all of which have a great influence on weld formation, Yan (page 1303 – 1304, section 4.3)) and one of ordinary skill in the art would appreciate, selecting among a plurality of candidate viewpoints/poses , to filter them according to welding parameters (e.g. speed, inclination, attitude)).
Regarding claims 17 and 20, Yan in view of Monica teaches the method of claim 10 and the non-transitory computer-readable medium of claim 19, further comprising:
initiating a second scan operation of the region, the second scan operation based on a second multiple scan poses selected from among the plurality of candidate poses, the second multiple scan poses including one or more scan poses distinct from the multiple scan poses; and generating a weld trajectory for a weld head of a robotic welding system based on the combined first scan data and the second scan data (multiple scanning experiments of the region of interest is conducted and the relevant parameters are continuously adjusted and optimized and finally, the data curve fed back from laser sensor can be obtained and a weld trajectory for a weld head of a robotic welding system is provided, Yan (page 1300 and section 3.2)); and one of ordinary skill in the art can appreciate combining the multiple scan poses generated (first scan data generated by the first scan operation and second scan data generated by the second scan operation) to generate a welding path in order to increase accuracy of the path generated.
Allowable Subject Matter
Claims 6 – 8, 15 and 18 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.
The following is a statement of reasons for the indication of allowable subject matter: The closest arts of record Yan or Monica failed to teach or reasonably suggest:
Regarding claims 6 and 15, while Monica discusses the robot self-filtering for acquired depth image by the robot joint values (forward and reverse kinematics) to a threshold depth and selecting the depth accordingly, Monica does not teach the claimed analyzing of model data associated with the object to identify the region , wherein the controller is: performing a comparison the one or more instances of the model data to a threshold value, removing (editing) the first instances of the one or more instances of the model data that fail to satisfy the threshold value, determining whether remaining instances of the model data are estimated to be visible to the scan device using the simulated the scan operation from one or more of the plurality of scan poses, and removing (further editing) second instances of the model data estimated to be obscured based on simulated the scan operation and It would be unfair to equate the robot joint value (depth) self-filtering taught by Monica to the claimed specific configuration of the controller that edits the model data by comparing the model data to a threshold data and simulated data in the claims. claims 7 – 8 are allowable by virtue of their dependency.
Regarding claim 18, neither Yan nor Monica discuss the claimed process of: comparing scan data generated from the first scan operation and the simulated scan data; and in response to identifying a number of discrepancies between the scan data and the simulated scan data that are greater than or equal to a threshold value iteratively performing the simulating, the generating, the selecting, and the initiating until a discrepancy between the scan data and the simulated scan data satisfies the threshold value.
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure:
Chang et al. (US 20200114449 A1), “System and Method for Weld Path Generation”, describes robots and robotic systems and methods used to assist in numerous welding tasks and scanning a particular area of a part and do not scan the entire possible welding area.
Geong et al. (US 20200021780 A1), “Vision Unit”, describes a vision unit that may recognize a workspace for assembling components as a virtual vision coordinate system using reference pins at one side as reference coordinates by using a camera which is operated on a frame in six axial directions by multiple linear rails and multiple motors, may create position coordinates of the components, a welder, and the like in the workspace, and may ensure accurate positions of the components and the welder in the workspace recognized by the camera by converting the accurate positions of the components and the welder into numerical values.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to DILNESSA B BELAY whose telephone number is (571)272-3136. The examiner can normally be reached M-F approx. 8:00 am - 5:30 pm EST.
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/DILNESSA B BELAY/Examiner, Art Unit 3761
/JOHN J NORTON/Primary Examiner, Art Unit 3761
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