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 . Claims 11-20 remain pending.
Response to Arguments
Applicant’s amendments to claims 14 and 20 address and overcome the 112(b) rejections.
Applicant’s response to the 112(a) rejection has been considered but is not persuasive. In particular, the instant specification relies on FIG. 4 to illustrate the nature of crosstalk structures. Unfortunately, looking at FIG. 4 it is not apparent how a person having ordinary skill in the art at the time of filing would have understood how a crosstalk structure would be identified. For example,
Applicant's arguments against the 102 rejections filed 4/6/26 have been fully considered but they are not persuasive.
Applicant argues Yeruhami fails to disclose the identification of crosstalk in the detected light signals onto multiple photodetector elements as required by Claim 11.
Applicant provides no proof to support this argument and also fails to explain why paragraph [0266], cited specifically against this limitation, fails to teach this limitation. See FIGS. 10D – 10E showing detection of crosstalk (i.e. reflection off window obstructions) in multiple pixels 1034.
Applicant argues Yeruhami fails to disclose that “a degree of dirtiness is determined based on the predetermined reflectivity ascertained during classification, the distance and a magnitude of the crosstalk”.
Again, Applicant fails to address the citations to Yeruhami covering the claimed limitation (see [0267], [0277], [0280], [0282]). [0267] in particular describes how when an obstruction is detected, analyzed signal information is used to estimate ability of system 1000 to operate. [0268] also describes how the system is able to distinguish between partial and full blockages and also mentions mud as one type of identifiable obstruction. Distinguishing between a partial or full blockage by mud clearly anticipates distinguishing a degree of dirtiness.
Examiner notes that Applicants description of technical effects mentions detecting using blurring analysis (not present in claim 11) and measurement of deviation in object dimensions (not present in any of the pending claims). Examiner suggests that amendments to the claims that focused on the use of measurement deviation in expected object dimensions instead of blurriness of linear structures would not suffer from the same 112(a) issues.
Examiner believes that part of the difference of opinion here is that the Applicant may be relying on a narrower definition of crosstalk / crosstalk structure than is warranted in light of the pending claims / specification. FIG. 4 shows an image B that purportedly contains crosstalk structures. Image B is made up of a bunch of squiggly lines with labels (O1, O2…On) pointing out indistinct features. While these labels are supposed to correspond to the similarly labeled objects in FIG. 3, they aren’t even in the same locations with respect to one another. For example, O2 is shown directly beneath O1 in FIG. 3 and in FIG. 4 O2 is offset substantially to the left of O1. While the instant specification does describe crosstalk as appearing as blurred linear structures at [0012], an explanation of what constitutes a linear structure in a point cloud and how blurriness would manifest in a point cloud is not found in the instant specification. Examiner notes Applicants attempt to define linear crosstalk structures as linear artifacts in a lidar image caused by scattering across adjacent photodetector elements; however, this definition is not supported by the specification. If Applicant wants this interpretation, evidence may be submitted in the form of a 37 CFR 1.132 declaration indicating that at the time of filing this was the understanding of a person of ordinary skill in the art.
Examiner also notes Applicant’s focus on the LIDAR implementation in the arguments but none of the currently pending claims require the optical sensor array to be part of a LIDAR sensor and especially not a LIDAR sensor working in conjunction with a line scanner in the currently pending claims. According to the specification at [0006] the disclosed embodiments also pertain to cameras, making determination as to the scope of linear structures even more challenging. Examiner suggests a telephonic or video interview could be helpful in sorting some of the outstanding rejections as to the scope of the claims and prior art.
Claim Rejections - 35 USC § 112
The following is a quotation of the first paragraph of 35 U.S.C. 112(a):
(a) IN GENERAL.—The specification shall contain a written description of the invention, and of the manner and process of making and using it, in such full, clear, concise, and exact terms as to enable any person skilled in the art to which it pertains, or with which it is most nearly connected, to make and use the same, and shall set forth the best mode contemplated by the inventor or joint inventor of carrying out the invention.
Claims 15-16 are rejected under 35 U.S.C. 112(a) as failing to comply with the written description requirement. The claims contains subject matter which was not described in the specification in such a way as to reasonably convey to one skilled in the relevant art that the inventor or a joint inventor, at the time the application was filed, had possession of the claimed invention.
Regarding Claims 15-16, they both include the term linear structures (presumably linear crosstalk structures). However, there is no teaching or explanation in the claims or specification that makes clear what a linear crosstalk structure is or how a potential infringer would understand the scope of the claim as currently drafted. Claims 15 and 16 also apply the term “blurred” and “blurring increases” to the already undescribed term linear crosstalk structures as a way of ascertaining the presence of crosstalk. Searching the specification there does not appear to be any language providing a description of what a crosstalk structure is or how a linear crosstalk structure would be distinguished from an ordinary one. The only guidance outside the claim language appears to be that linear crosstalk structures would be a result of using a linear LIDAR scanner. Further, the drawings fail to identify crosstalk structures at all, let alone linear ones. The drawings also fail to show examples of blurring of a linear crosstalk structure.
For at least the aforementioned reasons, the subject matter contained in Claims 15 and 16 is not described in sufficient detail so that a person having ordinary skill in the art can reasonably conclude the inventor had possession of the claimed invention.
Claim Rejections - 35 USC § 102
(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.
Claims 11-20 are rejected under 35 U.S.C. 102(a)(2) as being anticipated by US2020/0249354 (hereinafter Yeruhami).
Regarding Claim 11, Yeruhami teaches a method for detecting dirt in the signal path of an optical sensor array, comprising:
objects are detected by using multiple photodetector elements in the sensor array to detect light signals reflected on the objects ([0266] and FIG. 10D – 10E show multiple pixels 1034 capturing an obstruction pattern),
each object is classified according to its type, and when it is classified the object is assigned to an object class ([0268] describes classifying a detected obstruction based on its obstruction pattern to identify a type of obstruction) with a predetermined reflectivity ([0280] & [0282] describe obstruction object models as including transparency levels and/or opacity parameters),
a distance to the object is determined ([0277] describes the use of timing (i.e. measured distance) for blockage detection),
crosstalk in the detected light signals onto multiple photodetector elements is identified ([0266] and FIG. 10D – 10E show multiple pixels 1034 capturing an obstruction pattern), and
a degree of dirtiness is determined ([0267] when obstruction is detected, analyzed signal information is used to estimate ability of system 1000 to operate) based on the predetermined reflectivity ascertained during classification ([0280] & [0282] describe obstruction object models as including transparency levels and/or opacity parameters), the distance ([0277] discussion of timing, i.e. distance, for obstruction identification), and a magnitude of the crosstalk ([0277] discusses the use of signal intensity for obstruction identification).
Regarding Claim 12, Yeruhami teaches the method as in claim 11, wherein the degree of dirtiness is determined using at least one look-up table ([0289] describing use of database 1104 storing reference obstruction patterns).
Regarding Claim 13, Yeruhami teaches the method as in claim 12, wherein the at least one look-up table is generated based on at least one reference measurement taken by the sensor array ([0265] describes storing an obstruction pattern associated with a detected obstruction).
Regarding Claim 14, Yeruhami teaches the method as in claim 11, wherein crosstalk is identified by testing an image detected by the sensor array for crosstalk structures (the comparison of the detected obstruction pattern to reference obstruction pattern described in [0269] amounts to a test and reference obstruction patterns probably correspond to what the Applicant meant by crosstalk structures).
Regarding Claims 15, Yeruhami teaches the method as in claim 14, wherein linear structures are used as the structures and there is then determined to be crosstalk if the linear structures are blurred (given the lack of description of what a blurred linear structure should look like, the grid shown in FIG. 10F marked Mud is deemed to shows linear structures, [0272] describes how obstructions are characterized based on temporal aspects such as a pace and/or order in which areas get obstructed, tracking of temporal movement of the obstruction would cause blurring of the linear structure and this aspect as described in [0272] is used for classifying an obstruction).
Regarding Claim 16, Yeruhami teaches the method as in claim 15, wherein as the degree of blurring increases, a higher degree of crosstalk is identified ([0268] describes how obstructions are characterized based on a pixel by pixel analysis and increased blurring of a linear structure would consequently result in more pixel blockage and greater amounts of crosstalk occurring).
Regarding Claim 17, Yeruhami teaches the method as in claim 11, wherein crosstalk is identified as follows: dimensions of the detected object are compared to expected dimensions for such an object, and an increasing degree of crosstalk is identified with increasingly positive deviation of the dimensions for the detected object from the expected dimensions ([0282] describes how the reference obstruction pattern can include a size characteristic, when the obstruction is larger than the reference obstruction a larger amount of crosstalk would result).
Regarding Claim 18, Yeruhami teaches the method as in claim 17, wherein the expected dimensions are determined from dimensions determined for an object class corresponding to the object based on at least one reference measurement taken by the sensor array ([0265] describes storing an obstruction pattern associated with a detected obstruction & [0282] describes how the reference obstruction pattern can include a size characteristic).
Regarding Claim 19, Yeruhami teaches the method as in claim 18, wherein the expected dimensions are derived from an object class corresponding to the object, wherein objects belonging to the object class have standardized dimensions ([0282] describes how the reference obstruction pattern can include a size characteristic).
Regarding Claim 20, Yeruhami teaches use of a method as in claim 11 in a vehicle and/or robot to perform a fully automated or autonomous operation ([0113] describes implementation of the invention in autonomous road-vehicles).
Conclusion
THIS ACTION IS MADE FINAL. 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 BENJAMIN WIGGER whose telephone number is (571)272-4208. The examiner can normally be reached 9:30am to 7:00pm.
Examiner interviews are available via telephone, in-person, and video conferencing using a USPTO supplied web-based collaboration tool. To schedule an interview, applicant is encouraged to use the USPTO Automated Interview Request (AIR) at http://www.uspto.gov/interviewpractice.
If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Helal Algahaim can be reached at (571)270-5227. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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/BENJAMIN DAVID WIGGER/Examiner, Art Unit 3645
/HELAL A ALGAHAIM/SPE , Art Unit 3645
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