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 .
Claim Rejections - 35 USC § 112
The following is a quotation of 35 U.S.C. 112(b):
(b) CONCLUSION.—The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the inventor or a joint inventor regards as the invention.
The following is a quotation of 35 U.S.C. 112 (pre-AIA ), second paragraph:
The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the applicant regards as his invention.
Claims 1-20 rejected under 35 U.S.C. 112(b) or 35 U.S.C. 112 (pre-AIA ), second paragraph, as being indefinite for failing to particularly point out and distinctly claim the subject matter which the inventor or a joint inventor (or for applications subject to pre-AIA 35 U.S.C. 112, the applicant), regards as the invention.
Terms “contamination rate”, “object recognition rate” , “object obstruction rate” are not terms of the art and therefore create clarity issues. Specification does not fully define the limitations and therefore it is not clear what Applicant means by those terms.
The terms will be interpreted as well as understood by the Examiner.
Claim Rejections - 35 USC § 102
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)(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, 12, 20 and claims bellow are rejected under 35 U.S.C. 102(a) (2)as anticipated by or, in the alternative, under 35 U.S.C. 103 as obvious over D1 US 12235396 B1..
Regarding claims 1, 12 20 D1 teaches
1, 12, 20. A vehicle comprising:
a sensor including a receiver, the sensor being configured to generate a sensor output;(fig. 1implicit)
isolating a frame of a sensor output;(col 22 line 19-39)
determining an object recognition rate(col 6 line 50-col 7 line 9) of the sensor output and consulting a look up table(col 11 lines 7-15 look up table) to identify a contamination rate corresponding to the object recognition rate of the sensor output;(col 11 lines 16-34)
a controller communicatively coupled with the sensor, wherein the controller includes a memory and a processor, the memory storing instructions for determining an object obstruction rate of the sensor output and (col 14 line 63- col 15 line 23)
detecting a contamination rate of the receiver based at least in part on obstruction rate of the sensor output using a method including isolating a frame of the sensor output, determining an object recognition rate of the sensor output and consulting a look up table to identify a contamination rate corresponding to the object recognition rate of the sensor output, (col 11 lines 7-34)
(also claim 4 )and identifying and implementing at least one remedial action corresponding to the contamination rate, (col 18 lines 25-58)wherein the at least one remedial action is stored in the look up table. (col 14 line 63- col 15 line 23 look up table is implicit as actions can include initiate a cleaning operation to remove the obstruction from the sensor, control the vehicle 502, adjust a parameter of the sensor, generate a request for lidar point cloud data, and so on they need to be programmed using specific predetermined functions(programming code can be considered look up table where computer looks to make decision) based on contamination level col 19 lines 45-55)
Although D1 does not explicitly say “look up table” it is clear that multiple different actions can be implemented based on contamination level (col 19 lines 45-55) and hence if not explcit then at leas obvious to use look up table in order to guide apparatus regarding proper actions at different conditions as reuqired by D1.
2. The vehicle of claim 1, wherein the sensor is an optical sensor.(fig. 1)
3. The vehicle of claim 2, wherein the sensor is one of a camera and a light dimension and ranging (LiDAR) sensor.(fig. 1)
5. The vehicle of claim 4, wherein the corresponding remedial action includes at least one of ignore contamination, engage clearing implement, notify a driver of contamination, and remove the sensor from a set of perception system sensors until the sensor is manually cleared. (col 18 lines 25-58))
6. The vehicle of claim 4, wherein the look up table is constructed by correlating contamination rates detected in a controlled environment with object recognition rates detected in an uncontrolled environment.(col 3 and col 11 compare to baseline)
7. The vehicle of claim 6, wherein the contamination rates detected in the controlled environment are determined using a set of determinators, with each determinator corresponding to a parameter impacted by contamination.(col 3 compared to baseline)
10, 17 The vehicle of claim 7, wherein the contamination rate is a statistical aggregation of contamination rates determined by the set of determinators.(col 5 lines 25-34 statistical modeling)
13. The method of claim 12, wherein the at least one remedial action is at least one of engaging a sensor cleaning implement, notifying a driver of a vehicle to clean the sensor and removing the sensor from a set of perception system sensors.(col 8 initiating cleaning)
14. The method of claim 12, wherein the look up table is generated by operating the sensor in a controlled environment with a known contamination and determining a controlled contamination rate, operating a vehicle in an uncontrolled environment with a known contamination rate and determining an uncontrolled object recognition rate, and correlating the uncontrolled object recognition rate with the controlled contamination rate.(implicit /obvious comparing to baseline col 3 and col 11)
It will be obvious to one of ordinary skills in the art to modify teachings taught by D1 with to compare with baseline which is obtained in controlled environment in order to make sure that nothing abstracts the view.
Regarding claim 15 D1 teaches size and location of abstraction (col 3 line 53-col4 line 5)
Although D1 does not explicitly say
15. The method of claim 14, wherein the uncontrolled object recognition rate is an obscured percentage of at least one detected object in a sensor output.
As size is directly correlated with percentage For one of ordinary skills in the art it will be obvious modification as two parameter indicate obvious modification of the same parameter.
16. The method of claim 15, wherein the at least one detected object is detected in the frame by using object recognition on a combination of the frame and a cotemporaneous output from at least one other sensor.(col 2 lines 36-45)
D1 teaches separately each one of the limitation
9,19. The method of claim 17, wherein the sensor is a light detection and ranging (LiDAR) sensor and the plurality of determinators includes a noise value determinator.(col 10 lines 43-55) , a point cloud density determinator(col 2 line 61-col 3 line 9), and a reflection magnitude determinator. .(col 10 lines 43-55)
But does not explicitly say all of them together. Although Does not explicitly say that it is clear that all of those parameters affect the abstraction identification according to D1 and therefore It will be obvious to one of ordinary skills in the art to modify teachings taught by D1 to use al of them in order to make sure that obstruction is detected.
Claim(s) 8, 18 is rejected under 35 U.S.C. 103 as obvious over D1.
Although D1 does not explicitly teach
8, 18 The vehicle of claim 7, wherein the sensor is a camera and the determinators include a contrast and edge profile determinator, a luma value determinator and a noise value determinator.
One of ordinary skills in the art would recognize which parameters can be affected by the debris, for example luma and noise values are detected signal parameters which are clearly affected, similarly the contrast , edge profile directly relates to the size and position determination by D1 and hence although not explicit It will be obvious to one of ordinary skills in the art to modify teachings taught by D1 to use all those parameters in order to identify the debris, size and position of it.
Claim(s) 11 is rejected under under 35 U.S.C. 103 as obvious over D1 US 12235396 B1 in view of D2 US 20190385025 A1.
Although D1 does not teach D2 teaches
11. The vehicle of claim 10, wherein the statistical aggregation of contamination rates includes a weighted averaging of the contamination rates determined by the set of determinators.[0100][0084,0089]
It will be obvious to one of ordinary skills in the art to modify teachings taught by D1 with teachings by D2 in order to identify and mitigate effect of the abstraction.
Conclusion
Additional art provided in 892 form relates to Monitoring defects and activating cleaning protocols.
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/HOVHANNES BAGHDASARYAN/Examiner, Art Unit 3645
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