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 .
DETAILED ACTION
Continued Examination Under 37 CFR 1.114
A request for continued examination under 37 CFR 1.114, including the fee set forth in 37 CFR 1.17(e), was filed in this application after final rejection. Since this application is eligible for continued examination under 37 CFR 1.114, and the fee set forth in 37 CFR 1.17(e) has been timely paid, the finality of the previous Office action has been withdrawn pursuant to 37 CFR 1.114. Applicant's submission filed on August 10th, 2026, has been entered.
Information Disclosure Statement
The Information Disclosure Statement filed on August 13th, 2026, has been considered by the examiner. The applicant is advised no translation or statement of relevance was found for the Chinese Office Action sited on the IDS.
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.
Claim 7 is rejected under 35 U.S.C. 112(a) or 35 U.S.C. 112 (pre-AIA ), first paragraph, as failing to comply with the written description requirement. The claim(s) 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, or for applications subject to pre-AIA 35 U.S.C. 112, the inventor(s), at the time the application was filed, had possession of the claimed invention. Claim 7 recites “transferring the target particular battery into a safety bin.” Claim 1 was amended to recite “transfer the at least one battery into a dunk tank.” There is no support in the specification for a dunk tank and a safety bin. The specification only outlines using one or the other (P0041, P0043).
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.
Claim 14 is 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.
Claim 14 recites “a battery sorting mechanism” in L2. It is unclear whether this is the same battery sorting mechanism recited in claim 9 or a new battery sorting mechanism. Additionally claim 14, L5, recites “the battery sorting mechanism.” There is no antecedent basis for this limitation. It is unclear which of the battery sorting mechanisms is “the battery sorting mechanism.”
Claim Rejections - 35 USC § 103
The text of those sections of Title 35, U.S. Code not included in this action can be found in a prior Office action.
Claim(s) 9-15 is/are rejected under 35 U.S.C. 103 as being unpatentable over Young et al. (US 11747290), hereafter Young further in view of Wagner et al. (US 20200151407), hereafter Wagner, Dwivedi et al. (US-11911797) hereafter Dwivedi and Klemmack (US-11548729)
With regards to claim 9, Young discloses a system (Abstract) comprising: one or more
memory devices comprising a classifier machine learning model (Col. 10, L25-28) and a plurality of battery classifications (Col. 9, L47-57); and one or more processors (compute device 120) configured to cause the system to perform operations comprising: determining one or more attributes of a target battery from a plurality of signals from a plurality of sensors (Col. 9, L60-62; Col. 10 L20-25) and determining, utilizing the classifier machine learning model, a predicted
battery classification of the target battery from a plurality of battery classifications based on the determined one or more attributes of the target battery (Col. 9, L60-62); and actuating a battery sorting mechanism (sorting mechanism 120) to transfer the target battery into a bin corresponding to the predicted battery classification of the target battery. Young also discloses another embodiment that senses weight, shape/size, and chemistry (see Figure 5) but does not directly disclose that the sensor is a 3D scanner.
However, Wagner discloses using a 3D scanner to image items (P0121). It would have been obvious to a person with ordinary skill in the art before the effective filing date of the invention to replace the physical sensing device of Young with the 3D scanner as disclosed by Wagner in order to more accurately identify the battery.
Young and Wagner do not disclose in response to determining that the first predicted battery classification fails actuating a battery sorting mechanism to transfer the target battery for additional scanning by the plurality of sensors; determining one or more additional attributes of the target battery from one or more additional signals received from the plurality of sensors; determining, utilizing the classifier machine learning model, a second predicted battery classification of the target battery from the plurality of battery classifications based on the one or more additional attributes; and actuating the battery sorting mechanism to transfer the target battery into a bin corresponding to the second predicted battery classification of the target battery.
However, Dwivedi discloses recirculating and rescanning an item if it cannot be identified and resorting the item. It would have been obvious to a person with ordinary skill in the art before the effective filing date of the invention to recirculate batteries that cannot be identified in manner disclosed by Dwivedi in the system disclosed by Young and Wagner in order to increase throughput. Young, Wagner and Dwivedi do not disclose determining that the first predicted battery classification fails a confidence threshold.
However, Klemmack discloses using a confidence threshold in order to properly identify items (Col. 8, L8-13). It would have been obvious to a person with ordinary skill in the art before the effective filing date of the invention to use a confidence threshold as disclosed by in in the system disclosed by Young, Wagner, and Dwivedi, in order to ensure an accurate sort.
With regards to claim 10, Young, Wagner, Dwivedi and Klemmack disclose all the elements of claim 9 as outlined above. Young further discloses indicating, to a battery sorting mechanism, the predicted battery classification of the target battery to cause actuation of the battery sorting mechanism to transfer the target battery into the bin corresponding to the predicted battery classification (Col.10, L25-28).
With regards to claim 11, Young, Wagner, Dwivedi and Klemmack disclose all the elements of claim 9 as outlined above. Young further discloses wherein: the operations further comprise receiving one or more label images and one or more profile images of the target battery from a RGB camera of the plurality of sensors (Col. 7, L29-38); determining the one or more attributes of the target battery comprises: determining, utilizing optical character recognition, the printed characters of the target battery from the one or more label images (Col. 7, L29-38); and determining the form factor of the target battery from the one or more profile images (Col. 7, L31-37); and determining, utilizing the classifier machine learning model, the predicted battery classification of the target battery is based on the printed characters and the form factor (Col. 7, L8-17).
With regards to claim 12, Young, Wagner, Dwivedi and Klemmack disclose all the elements of claim 9 as outlined above. Young further discloses wherein: determining the one or more attributes of the target battery comprises: the dimensions of the target battery based on the 3D scan data from the 3D scanner of the plurality of sensors; and determining a battery chemistry of the target battery based on x-ray attenuation data from an x-ray scanning array of the plurality of sensors (Col. 6, L22-34); and determining, utilizing the classifier machine learning model, the predicted battery classification of the target battery is based on the battery chemistry (Col. 5, L62-Col. 6 L2).Young does not disclose the determining dimensions of the target battery based on the 3D scan data from the 3D scanner of the plurality of sensors and determining, utilizing the classifier machine learning model, the predicted battery classification of the target battery is based on the battery chemistry and dimensions.
However, Wagner discloses determining dimensions using a 3D scanner (P0120). Therefore, the combination of Young and Wagner discloses this feature.
With regards to claim 13, Young, Wagner, Dwivedi and Klemmack disclose all the elements of claim 9 as outlined above. Young further discloses receiving, from the plurality of sensors, additional signals corresponding to additional batteries; and determining, utilizing the classifier machine learning model, additional predicted battery classifications of the additional batteries from the plurality of battery classifications based on the additional signals (Col.5 L53-57).
With regards to claim 14, Young, Wagner, Dwivedi and Klemmack disclose all the elements of claim 13 as outlined above. Young further discloses indicating, to a battery sorting mechanism, the predicted battery classification of the target battery and the additional predicted battery classifications of the additional batteries; and individually transferring each battery of the target battery and the additional batteries, utilizing the battery sorting mechanism, into a plurality of bins respectively associated with the plurality of battery classifications (Col. 6, L3-12).
Allowable Subject Matter
Claims 1-6, 8, and 16-20 are allowable.
Independent claims 1 and 16 are allowable for disclosing “actuating the battery sorting mechanism to transfer the at least one battery into a dunk tank containing a fire retardant.”
Claim 15 is 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.
Claim 15 would be allowable for disclosing “and in response, transferring the at least one
battery into a dunk tank containing a fire retardant.
Although US 20220416323 discloses sounding an alarm for a hazardous anomaly, there is no teaching or suggestion that would render it obvious to a person with ordinary kill in the art before the effective filing date of the invention to use a dunk tank as recited.
Claims 2-8 and 17-20 are allowable by virtue of their dependencies.
Response to Arguments
The applicant’s arguments with regards to claim 9 are rendered moot. New grounds of rejection are presented above.
Conclusion
Any inquiry concerning this communication or earlier communications from the examiner should be directed to JESSICA LYNN BURKMAN whose telephone number is (571)272-5824. The examiner can normally be reached M-Th 7:30am to 6:00pm EST.
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/J.L.B./Examiner, Art Unit 3653
/MICHAEL MCCULLOUGH/Supervisory Patent Examiner, Art Unit 3653
