DETAILED ACTION
Notice of Pre-AIA or AIA Status
The present application is being examined under the pre-AIA first to invent provisions.
Application Status
This non-final office action is in response to the application filed on 04/22/2025. Claims 1-11 are pending and rejected as detailed below.
Priority
Receipt is acknowledged of certified copies of papers required by 37 CFR 1.55. Applicant has claimed priority to CN202211621392.4; filed on 12/16/2022 and PCT/CN2023/135688; filed on 11/30/2023.
Information Disclosure Statement
The information disclosure statement(s) (IDS) submitted on 04/22/2025, are in compliance with the provisions of 37 CFR 1.97. Accordingly, the information disclosure statements have been considered by the examiner.
Drawings
The drawings are objected to under 37 CFR 1.83(a). The drawings must show every feature of the invention specified in the claims. Therefore, the steps S11, S12, S21, S22, S41, and S42 must be shown or the feature(s) canceled from the claim(s). No new matter should be entered.
Corrected drawing sheets in compliance with 37 CFR 1.121(d) are required in reply to the Office action to avoid abandonment of the application. Any amended replacement drawing sheet should include all of the figures appearing on the immediate prior version of the sheet, even if only one figure is being amended. The figure or figure number of an amended drawing should not be labeled as “amended.” If a drawing figure is to be canceled, the appropriate figure must be removed from the replacement sheet, and where necessary, the remaining figures must be renumbered and appropriate changes made to the brief description of the several views of the drawings for consistency. Additional replacement sheets may be necessary to show the renumbering of the remaining figures. Each drawing sheet submitted after the filing date of an application must be labeled in the top margin as either “Replacement Sheet” or “New Sheet” pursuant to 37 CFR 1.121(d). If the changes are not accepted by the examiner, the applicant will be notified and informed of any required corrective action in the next Office action. The objection to the drawings will not be held in abeyance.
The drawings are objected to as failing to comply with 37 CFR 1.84(p)(5) because they do not include the following reference sign(s) mentioned in the description:
[0023] Steps S11 and S12 not in drawings
[0025] Steps S21 and S22 not in drawings
[0028] Steps S41 and S42 not in drawings
Corrected drawing sheets in compliance with 37 CFR 1.121(d) are required in reply to the Office action to avoid abandonment of the application. Any amended replacement drawing sheet should include all of the figures appearing on the immediate prior version of the sheet, even if only one figure is being amended. Each drawing sheet submitted after the filing date of an application must be labeled in the top margin as either “Replacement Sheet” or “New Sheet” pursuant to 37 CFR 1.121(d). If the changes are not accepted by the examiner, the applicant will be notified and informed of any required corrective action in the next Office action. The objection to the drawings will not be held in abeyance.
Claim Objections
The claims are objected to because they include reference characters which are not enclosed within parentheses.
Reference characters corresponding to elements recited in the detailed description of the drawings and used in conjunction with the recitation of the same element or group of elements in the claims should be enclosed within parentheses so as to avoid confusion with other numbers or characters which may appear in the claims. See MPEP § 608.01(m).
Claim(s) 11 is objected to because of the following informalities:
A series of singular dependent claims is permissible in which a dependent claim refers to a preceding claim which, in turn, refers to another preceding claim.
A claim which depends from a dependent claim should not be separated by any claim which does not also depend from said dependent claim. It should be kept in mind that a dependent claim may refer to any preceding independent claim. In general, applicant's sequence will not be changed. See MPEP § 608.01(n). Claim 11 is a dependent of dependent claim 6, but is separated from it by a number of other dependent claims. Applicant can overcome this objection by cancelling claim 6, and all its dependents, and then adding a series of new claims at the end of the existing claims with proper dependencies with not separations.
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 point cloud height calculation module, a carpet identification module, and an obstacle avoidance module in claim 8. The examiner finds that the modules exist as elements on a “chip” i.e. computer modules, see [0033] of the current disclosure.
Because this/these claim limitation(s) is/are being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, it/they is/are being interpreted to cover the corresponding structure described in the specification as performing the claimed function, and equivalents thereof.
If applicant does not intend to have this/these limitation(s) interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, applicant may: (1) amend the claim limitation(s) to avoid it/them being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph (e.g., by reciting sufficient structure to perform the claimed function); or (2) present a sufficient showing that the claim limitation(s) recite(s) sufficient structure to perform the claimed function so as to avoid it/them being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph.
Claim Rejections - 35 USC § 112
The following is a quotation of 35 U.S.C. 112(d):
(d) REFERENCE IN DEPENDENT FORMS.—Subject to subsection (e), a claim in dependent form shall contain a reference to a claim previously set forth and then specify a further limitation of the subject matter claimed. A claim in dependent form shall be construed to incorporate by reference all the limitations of the claim to which it refers.
The following is a quotation of pre-AIA 35 U.S.C. 112, fourth paragraph:
Subject to the following paragraph [i.e., the fifth paragraph of pre-AIA 35 U.S.C. 112], a claim in dependent form shall contain a reference to a claim previously set forth and then specify a further limitation of the subject matter claimed. A claim in dependent form shall be construed to incorporate by reference all the limitations of the claim to which it refers.
Claim 7 is rejected under 35 U.S.C. 112(d) or pre-AIA 35 U.S.C. 112, 4th paragraph, as being of improper dependent form for failing to further limit the subject matter of the claim upon which it depends, or for failing to include all the limitations of the claim upon which it depends. The claim relies on claim 6 which in turn relies on claim 1. Claim 7 recites, “in a case that the obstacle with an uneven contour is detected by the robot on the carpet, performing plane scanning based on the data from the line laser sensor…in a case that an unevenness degree of the contour is within a preset range, determining that the obstacle is the carpet fiber based on data obtained after the plane scanning.” This is identical to the claim limitations of claim 1, except for the addition of the word “fiber” after carpet. The claim makes no distinction between a carpet and a carpet fiber and the examiner cannot find any meaningful way in which this would further limit the claims. Applicant may cancel the claim(s), amend the claim(s) to place the claim(s) in proper dependent form, rewrite the claim(s) in independent form, or present a sufficient showing that the dependent claim(s) complies with the statutory requirements.
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 1-11 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more. Analysis of the claim(s) regarding subject matter eligibility utilizing the 2019 Revised Patent Subject Matter Eligibility Guidance is described below.
STEP 1: STATUTORY CATEGORIES
Claim(s) 1-11 do fall into at least one of the four statutory subject matter categories. Claim 1, and its dependents, are directed to a method which is the statutory category of a process.
STEP 2A: JUDICIAL EXCEPTIONS
PRONG 1: RECITATION OF A JUDICIAL EXCEPTION
The claim(s) recite(s):
- Claim 1 recite(s) an abstract idea belonging to the grouping of mental processes. Claim 1 recites, “in a case that the robot has detected an obstacle with an uneven contour, performing plane scanning based on data from a line laser sensor;” this is a mere data gathering, and “in a case that an unevenness degree of the contour is within a preset range, determining that the obstacle is a carpet based on data obtained after the plane scanning.” The claim is a process to collect data, analyze it, and compare the results to some known value to make a determination. This would be considered a mental process, see MPEP 2106.04(a)(2)III.A.
- Claim 2 recite(s) an abstract idea belonging to the grouping of mental processes and mathematical calculation. Claim 2 recites, “generating, by the robot, a line laser, and obtaining an image using an image sensor to obtain point cloud data;” this is mere data gathering, and “calculating heights of point clouds, and in a case that the heights of the point clouds are not the same, determining that the obstacle with the uneven contour is detected by the robot.” This claim requires someone to gather data, then perform a calculation and determination based on it. This claim has two abstract ideas in it. Firstly the calculation step would fail as simply a formula to determine a height, MPEP2106.04(a)(2)I.C. Secondly the claim requires a simple comparison of data, if the height is too uneven it determines that the robot has encountered carpet. This is a simple data comparison step.
- Claim 3 recite(s) an abstract idea belonging to the grouping of mathematical formula. Claim 3 recites, “the height of the point cloud is calculated by the robot through point_r(x3, y3, z3)=ext(x1, y1, z1)*point_c(x2, y2, z2) wherein point_r(x3, y3, z3) represents coordinates of the point cloud relative to a center of the robot, ext(x1, y1, z1) represents coordinates of the line laser sensor relative to the center of the robot, point_c(x2, y2, z2) represents coordinates of the point cloud relative to the line laser sensor, and z3 represents the height of the point cloud. MPEP 2106.04(a)(2)I.B. recites “[a] claim that recites a numerical formula or equation will be considered as falling within the "mathematical concepts" grouping. In addition, there are instances where a formula or equation is written in text format that should also be considered as falling within this grouping.” This claim is directed squarely to a formula to calculate height based on some measured value and therefore fails the as a mathematical formula.
- Claim 4 recite(s) insignificant extra-solution activity. Claim 4 recites, “generating, by the robot, the line laser, and scanning a plane in a case that the robot moves forward by a preset distance relative to the obstacle, or rotates to left or right by a preset angle; and obtaining, by the image sensor, an image to obtain the point cloud data of the obstacle within the plane.” This is merely a step further directed towards how data gathering occurs.
- Claim 5 recite(s) an abstract idea belonging to the grouping of mental processes and mathematical calculation. Claim 5 recites, “calculating, by the robot, a height of each point cloud based on data obtained after the plane scanning;” this is a calculation step, and “comparing the heights of every two point clouds, and in a case that a height difference between the two point clouds is within a preset range, determining that the obstacle is the carpet.” This claim requires someone to gather data, then perform a calculation and determination based on it. This claim has two abstract ideas in it. Firstly the calculation step would fail as simply a formula to determine a height, MPEP2106.04(a)(2)I.C. Secondly the claim requires a simple comparison of data, if the height is too uneven it determines that the robot has encountered carpet. This is a simple data comparison step.
- Claim 6 recite(s) an abstract idea belonging to the grouping of mental processes and mathematical calculation. Claim 6 recites, “calculating a height of a carpet based on data from the line laser sensor, in a case that the height of the carpet is greater than or equal to a preset height, avoiding the carpet, and in a case that the height of the carpet is less than the preset height, proceeding to Step S4;” this is a calculation and comparison step. The claim further recites, “in a case that the robot is operating on the carpet, identifying a height of a carpet fiber and calculating a height of the carpet fiber, and in a case that an obstacle with a height greater than the height of the carpet fiber is detected, performing obstacle avoidance.” This step further requires the robot to identify the world around it, this would be data gathering. It then compares the height of the detected item to an expected value. This is a mental process of comparing to a known value.
- Claim 7 recite(s) an abstract idea belonging to the grouping of mental processes. Claim 7 recites, “in a case that the obstacle with an uneven contour is detected by the robot on the carpet, performing plane scanning based on the data from the line laser sensor;” this is mere data gathering, and “in a case that an unevenness degree of the contour is within a preset range, determining that the obstacle is the carpet fiber based on data obtained after the plane scanning.” The claim is a process to collect data, analyze it, and compare the results to some known value to make a determination. This would be considered a mental process, see MPEP 2106.04(a)(2)III.A.
- Claim 8 recite(s) an abstract idea belonging to the grouping of mental processes and mathematical calculation. Claim 8 recites, “a line laser sensor configured to generate a line laser to detect an object; an image sensor configured to obtain a line laser image projected by the line laser sensor onto a surface of the object.” This is merely data gathering. The claim further recites, “a point cloud height calculation module configured to calculate a height of a point cloud based on the line laser image obtained by the image sensor;” this would be seen as a mathematical calculation step and could be done in a human mind with or without a computer aid. “a carpet identification module configured to determine whether or not an obstacle is a carpet based on the height of the point cloud;” This step requires a person to compare collected data to a known value and make a determination based on it; and “an obstacle avoidance module configured to perform obstacle avoidance based on a height of the carpet and a height of a carpet fiber.” This is merely a determination to avoid an object based on the height.
- Claim 9 recite(s) insignificant extra-solution activity. Claim 9 recites, “wherein a quantity of line laser sensors is one or more, and the line laser sensor is arranged at such a position that the robot detects the obstacle in front of the robot.” This is merely a description of the sensor’s arrangement and quantity.
- Claim 10 recite(s) insignificant extra-solution activity. Claim 10 recites, “[A] chip storing therein a computer program code, wherein the computer program code is executed to implement the carpet detection method according to claim 1.” This is merely a description of the storage of a computer program to execute a method
- Claim 11 recite(s) insignificant extra-solution activity. Claim 11 recites, “[A] chip storing therein a computer program code, wherein the computer program code is executed to implement the obstacle avoidance method according to claim 6.” This is merely a description of the storage of a computer program to execute a method
PRONG 2: INTEGRATION INTO A PRACTICAL APPLICATION
The additional element(s) recited in the claim(s) beyond the judicial exception are types of sensors, data gathering activities, and storage of a computer program. The additional element(s) do not integrate the judicial exception into a practical application because the additional element(s) do not apply, rely on, or use the judicial exception in a manner that imposes a meaningful limit on the judicial exception and add insignificant extra-solution activity to the judicial exception. The computer elements are merely used as a tool to perform the abstract idea, and the use of the judicial exception is generally linked to the particular technological environment of autonomous robots without using the judicial exception in some other meaningful way (MPEP 2106.04(d)).
STEP 2B: INVENTIVE CONCEPT/SIGNIFICANTLY MORE
The additional elements recited in the claim(s) are not sufficient to amount to significantly more than the judicial exception because they do not add more than insignificant extra-solution activity to the judicial exception (MPEP 2106.05(g)), and the computer functions of receiving and transmitting data have been recognized by the courts as well-understood, routine, and conventional functions when they are claimed in a merely generic manner or as insignificant extra-solution activity (MPEP 2106.05(d)). Further, the additional elements of a “memory” and a “processor” recited in the claim(s) are well-understood, routine, and conventional activities previously known to the industry, specified at a high level of generality (MPEP2106.05 (d)).
Based on the above analysis, claim(S) 1-11 is/are not eligible subject matter and is/are rejected under 35 U.S.C 101.
The step of “performing obstacle avoidance,” in claim 6, or “configured to perform obstacle avoidance based on a height of the carpet and a height of a carpet fiber” in claim 8; could be rewritten to recite a positive control step, which if done may mean that the claim has a practical application. This practical application, if rolled up into claim 1, may remove the 101 rejection for a majority of the claims. Please request an interview for further explanation, if needed.
Claim Rejections - 35 USC § 103
The following is a quotation of pre-AIA 35 U.S.C. 103(a) which forms the basis for all obviousness rejections set forth in this Office action:
(a) A patent may not be obtained though the invention is not identically disclosed or described as set forth in section 102, if the differences between the subject matter sought to be patented and the prior art are such that the subject matter as a whole would have been obvious at the time the invention was made to a person having ordinary skill in the art to which said subject matter 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 pre-AIA 35 U.S.C. 103(a) are summarized as follows:
1. Determining the scope and contents of the prior art.
2. Ascertaining the differences between the prior art and the claims at issue.
3. Resolving the level of ordinary skill in the pertinent art.
4. Considering objective evidence present in the application indicating obviousness or nonobviousness.
Claims 1-3 and 6-11 is/are rejected under pre-AIA 35 U.S.C. 103(a) as being unpatentable over Xu (US PG Pub 2024/0197130) in view of Wang (US PG Pub 2021/0298553).
Regarding claim 1, Xu teaches a carpet detection method for a robot, comprising: Step S1, in a case that the robot has detected an obstacle with an uneven contour, performing plane scanning based on data from a line laser sensor; ([0053], [0067], [0156]-[0157], [0159], [0165], [0174], and [0219]-[0220] teaches the robot using a structured light projection system to scan the environment around the robot and then using this information to obtain the contour information of objects detected around the robot. It would be inherent that captured contours would include some kind of uneven contours.) and
Step S2, in a case that an unevenness degree of the contour ([0216]-[0220] teaches the system identifying the object the robot is approaching by using the detected contour information. It does this by identifying the contour and matching it to a known category of object)
Xu does not teach [the unevenness degree of the contour is] within a preset range.
However, Wang teaches “[the unevenness degree of the contour is] within a preset range.” ([0036]-[0037] and [0065] teach a robot system using a threshold based determination based on the detection results in order to determine the kind of operating surface that a robot is operating on)
It would have been prima facie obvious to one of ordinary skill in the art, before the effective filing date, to incorporate the teachings of Xu with Wang; and have a reasonable expectation of success. Both relate to the control of robotic carpet cleaners. As Wang teaches in [0005], there are different types of operations that the robot should perform on different types of floors. By using a threshold to determine that the operating surface is a particular type of floor, i.e. plush carpet, the robot can change the suction force, brush speed, etc. that it operates with. This allows the system to perform optimally.
Regarding claim 2, Xu teaches the carpet detection method according to claim 1, wherein in Step S1, the robot has detected an obstacle with an uneven contour comprises: Step S11, generating, by the robot, a line laser, and obtaining an image using an image sensor to obtain point cloud data; (Fig. 1a and [0050]-[0053] teaches the robot generating a line laser and using a camera to capture an image of the laser data, including a point cloud) and
Step S12, calculating heights of point clouds, ([0056] and [0156]-[0157] teach calculating a height of a point cloud) and in a case that the heights of the point clouds are not the same, determining that the obstacle with the uneven contour is detected by the robot. ([0217] teaches that the robot can use the detected point cloud information to determine the detected object’s contour information which would include determining that the contour is uneven)
Regarding claim 3, Xu teaches the carpet detection method according to claim 2, wherein the height of the point cloud is calculated by the robot through point_r(x3, y3, z3)=ext(x1, y1, z1)*point_c(x2, y2, z2), wherein point_r(x3, y3, z3) represents coordinates of the point cloud relative to a center of the robot, ext(x1, y1, z1) represents coordinates of the line laser sensor relative to the center of the robot, point_c(x2, y2, z2) represents coordinates of the point cloud relative to the line laser sensor, and z3 represents the height of the point cloud. ([0156]-[0157] teach the system determining the height of the point cloud using a determination of the various coordinate systems and a triangulation method to combine the world, robot, and sensor coordinate systems. This triangulation method allows the robot to determine the height of the detected point cloud)
Regarding claim 6, Xu teaches an obstacle avoidance method, comprising the carpet detection method according to claim 1, and further comprising: Step S3, calculating a height of a carpet based on data from the line laser sensor, in a case that the height of the carpet is greater than or equal to a preset height, avoiding the carpet, and in a case that the height of the carpet is less than the preset height, proceeding to Step S4; ([0238]-[0241] and [0254] teach the system as able to determine heights of obstacles, including carpet. The system can then determine whether or not to avoid the object or work on it, in the case of the carpet. The system can identify whether the carpet is “short-pile” or “long-pile” then adjust its working conditions accordingly. [0202]-[0206] further teach the robot operating within a type or obstacle avoidance mode based on the detected object) and
Step S4, in a case that the robot is operating on the carpet, identifying a height of a carpet fiber and calculating a height of the carpet fiber, and in a case that an obstacle with a height greater than the height of the carpet fiber is detected, performing obstacle avoidance. ([0240]-[0241] teaches the robot system having a mode where it operates “on top” of a carpet. When this occurs the robot considers the top contour of the carpet and in the event that the contour doesn’t match it can determine that the height is wrong and perform some form of obstacle avoidance.)
Regarding claim 7, Xu teaches the obstacle avoidance method according to claim 6, wherein in Step S4, the identifying the height of the carpet fiber comprises: Step S41, in a case that the obstacle with an uneven contour is detected by the robot on the carpet, performing plane scanning based on the data from the line laser sensor; ([0053], [0067], [0156]-[0157], [0159], [0165], [0174], and [0219]-[0220] teaches the robot using a structured light projection system to scan the environment around the robot and then using this information to obtain the contour information of objects detected around the robot. It would be inherent that captured contours would include some kind of uneven contours.) and
Step S42, in a case that an unevenness degree of the contour is ([0216]-[0220] teaches the system identifying the object the robot is approaching by using the detected contour information. It does this by identifying the contour and matching it to a known category of object)
Xu does not teach [the unevenness degree of the contour is] within a preset range.
However, Wang teaches, “[the unevenness degree of the contour is] within a preset range.” ([0036]-[0037] and [0065] teach a robot system using a threshold based determination based on the detection results in order to determine the kind of operating surface that a robot is operating on)
It would have been prima facie obvious to one of ordinary skill in the art, before the effective filing date, to incorporate the teachings of Xu with Wang; and have a reasonable expectation of success. Both relate to the control of robotic carpet cleaners. As Wang teaches in [0005], there are different types of operations that the robot should perform on different types of floors. By using a threshold to determine that the operating surface is a particular type of floor, i.e. plush carpet, the robot can change the suction force, brush speed, etc. that it operates with. This allows the system to perform optimally.
Regarding claim 8, Xu teaches a robot for implementing the obstacle avoidance method according to claim 6, comprising: a line laser sensor configured to generate a line laser to detect an object; (Fig. 1a and [0050]-[0051] teach the robot having a line laser sensor to generate a line laser)
an image sensor configured to obtain a line laser image projected by the line laser sensor onto a surface of the object; (Fig. 1a and [0050]-[0052] teach the robot having a camera to capture images of the line laser)
a point cloud height calculation module configured to calculate a height of a point cloud based on the line laser image obtained by the image sensor; ([0064] and [0164]-[0165] teach the robot having a CPU configured to calculate the height of detected object point clouds)
a carpet identification module configured to determine whether or not an obstacle is a carpet based on the height of the point cloud; ([0164]-[0165] and [0067] teach the CPU being able to identify the type of object detected, this would include determining that the detected object is carpet) and
an obstacle avoidance module configured to perform obstacle avoidance based on a height of the carpet and a height of a carpet fiber. ([0139] teaches a CPU controller configured to control the robot to avoid an obstacle based on the detected information)
Regarding claim 9, Xu teaches the robot according to claim 8, wherein a quantity of line laser sensors is one or more, and the line laser sensor is arranged at such a position that the robot detects the obstacle in front of the robot. (Figs. 1a and 1b; and [0050]-[0054] teach the robot having multiple line lasers installed on it and configured to project lasers/detect objects in front of the robot)
Regarding claim 10, Xu teaches a chip storing therein a computer program code, wherein the computer program code is executed to implement the carpet detection method according to claim 1. ([0150]-[0152] teach the robot having a memory used to store any computer program needed for the robot to execute the stored computer programs)
Regarding claim 11, Xu teaches a chip storing therein a computer program code, wherein the computer program code is executed to implement the obstacle avoidance method according to claim 6. ([0150]-[0152] teach the robot having a memory used to store any computer program needed for the robot to execute the stored computer programs)
Claims 4-5 is/are rejected under pre-AIA 35 U.S.C. 103(a) as being unpatentable over Xu and Wang in view of Cui (US Pat 11,042,760).
Regarding claim 4, the combination of Xu and Wang teaches the carpet detection method according to claim 3, wherein in Step S1, the performing plane scanning comprises: generating, by the robot, the line laser, (Fig. 1a and [0050]-[0053] teaches the robot generating a line laser and using a camera to capture an image of the laser data) and
obtaining, by the image sensor, an image to obtain the point cloud data of the obstacle within the plane. (Fig. 1a and [0050]-[0053] teaches the robot generating a line laser and using a camera to capture an image of the laser data)
The combination of Xu and Wang does not teach scanning a plane in a case that the robot moves forward by a preset distance relative to the obstacle, or rotates to left or right by a preset angle.
However, Cui teaches “scanning a plane in a case that the robot moves forward by a preset distance relative to the obstacle, or rotates to left or right by a preset angle.” (Col. 10, lines 4-19; teaches a robotic system that can move and/or rotate by a given amount in order to capture sensor data for an object at multiple time points. Using this movement and sensor data the robot can determine additional information about the obstacle)
It would have been prima facie obvious to one of ordinary skill in the art, before the effective filing date, to incorporate the teachings of Xu and Wang with Cui; and have a reasonable expectation of success. All relate to control systems for cleaning robots. As Cui teaches in Col. 6, lines 33-56; the world can be confusing for a robot to operate in. The robot can have trouble seeing the world around it and can be confused by the kind of obstacles detected. By ensuring that there is some kind of control mechanism that prevents the robot form operating with reckless abandon prevents safety incidents from occurring. By controlling the robot to have precise controls, i.e. go forward or rotate, in order to scan the world before fully continuing the system ensures it operates safely.
Regarding claim 5, the combination of Xu and Wang teaches the carpet detection method according to claim 4, wherein in Step S2, determining that the obstacle is a carpet comprises: Step S21, calculating, by the robot, a height of each point cloud based on data obtained after the plane scanning; ([0056] and [0156]-[0157] teach calculating a height of a point cloud) and
Step S22, comparing the heights of every two point clouds, and in a case that a height difference between the two point clouds is within a preset range, determining that the obstacle is the carpet. ([0157], [0159], [0174], and [0217] teach the robot system as calculating the heights of the point clouds and determining that the heights are within a certain range. The system can then compare the heights to obtain the contour of the object and based on the detected contour, use this information to determine the type of object detected. [0225] further teaches the system as averaging the height of multiple collected points of data to determine the height of the obstacle)
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure.
Yang (US PG Pub 2024/0212182) teaches a distance measurement method and device, a robot and a storage medium. The method comprises: acquiring a first image, where the first image at least comprises a to-be-detected object and a ground on which the to-be-detected object is located; determining an initial constraint condition of the ground based on the first image; acquiring a second image, where the second image at least comprises an intersection line of a line structured light beam with the ground and/or with the to-be-detected object; determining a position parameter of the ground based on the second image, and correcting the initial constraint condition of the ground based on the position parameter; and determining a distance to the to-be-detected object based on the corrected initial constraint condition of the ground and the first image.
Shen (US PG Pub 2022/0287533) teaches a sweeping robot includes a housing, at least one laser emitting component, at least one image acquisition component, and a processing component connected with each laser emitting component and each image acquisition component. Each laser emitting component is adapted to project laser in a travel direction. Each image acquisition component is adapted to acquire a target image in the travel direction. The processing component is adapted to acquire the target image collected by the image acquisition component. When there is a projection image of a projection point where the laser is projected onto an obstacle in the target image, a contour information of the obstacle is acquired, a type of the obstacle indicated by the contour information is determined, and the sweeping robot is controlled to clean. Besides, an automatic control method for the sweeping robot is also disclosed.
Kim (US PG Pub 2023/0091839) teaches a a moving robot and a control method according to the present disclosure, an obstacle is detected using structured light irradiated in a predetermined type of light pattern in a traveling direction while traveling, and a specified operation is performed in response to the obstacle. Moreover, a dangerous obstacle is recognized by extracting changes over time using a plurality of images for an obstacle or a low obstacle that is difficult to determine as detected data, and thus, it is possible to improve accuracy according to the determination of the obstacle, improve a corresponding operation according to the obstacle, minimize the uncleaned area while preventing restraint due to the obstacle, and improve the cleaning performance.
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/N.S./Examiner, Art Unit 3665 /CHRISTIAN CHACE/Supervisory Patent Examiner, Art Unit 3665
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