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
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 statements (IDS’s) submitted on 5/22/2025 & 3/9/2026 are in compliance with the provisions of 37 CFR 1.97. Accordingly, the information disclosure statements are being considered by the examiner.
Election/Restrictions
Applicant’s election without traverse of Claims 9 - 16 in the reply filed on 7/30/2026 is acknowledged.
Priority
Receipt is acknowledged of certified copies of papers required by 37 CFR 1.55.
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 9 – 14 & 16 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more.
The determination of whether a claim recites patent ineligible subject matter is a 2 step inquiry.
STEP 1: the claim does not fall within one of the four statutory categories of invention (process, machine, manufacture or composition of matter), see MPEP 2106.03, or
STEP 2: the claim recites a judicial exception, e.g. an abstract idea, without reciting additional elements that amount to significantly more than the judicial exception, as determined using the following analysis: see MPEP 2106.04
STEP 2A (PRONG 1): Does the claim recite an abstract idea, law of nature, or natural phenomenon? see MPEP 2106.04(II)(A)(1)
STEP 2A (PRONG 2): Does the claim recite additional elements that integrate the judicial exception into a practical application? see MPEP 2106.04(II)(A)(2) and 2106.05(a) thru (d) for explanations.
STEP 2B: Does the claim recite additional elements that amount to significantly more than the judicial exception? see MPEP 2106.05
101 Analysis – Step 1
Claim 9 is directed to a vehicle guidance system (i.e., a machine). Therefore, claim 9 is within at least one of the four statutory categories.
101 Analysis – Step 2A, Prong I
Regarding Prong I of the Step 2A analysis, the claims are to be analyzed to determine whether they recite subject matter that falls within one of the follow groups of abstract ideas: a) mathematical concepts, b) certain methods of organizing human activity, and/or c) mental processes. see MPEP 2106(A)(II)(1) and MPEP 2106.04(a)-(c)
Independent claim 9 includes limitations that recite an abstract idea (emphasized below [with the category of abstract idea in brackets]) and will be used as a representative claim for the remainder of the 101 rejection. Claim 9 recites:
A guidance, navigation, and control system for a material handling vehicle, the system comprising:
a first sensor, the first sensor to measure odometry data;
a second sensor, the second sensor to measure inertial measurement unit data; and
a processor, the processor to:
predict a location of the material handling vehicle based on the odometry data from the first sensor; [mental process/step]
measure the location of the material handling vehicle based on the inertial measurement unit data from the second sensor; and [mental process/step]
combine the odometry data from the first sensor and the inertial measurement unit data from the second sensor within a Kalman filter to generate an updated location estimate for the material handling vehicle. [mental process/step]
The examiner submits that the foregoing bolded limitation(s) constitute a “mental process” because under its broadest reasonable interpretation, the claim covers performance of the limitation in the human mind. For example, “predict…” in the context of this claim encompasses a person looking at odometry data collected and forming a simple judgement as to a vehicle’s position, which is a mental process of evaluating data collected under the broadest reasonable interpretation of the claim. Similarly, “measure…” under the broadest reasonable interpretation of the claim encompasses a similar evaluation of data collected to determine a vehicle position, in this instance with inertial data, and therefore also recites an abstract idea under the broadest reasonable interpretation of the claim. Finally, the limitation “combine…” in the context of the claim encompasses generating an updated location estimate by combining data using a Kalman filter, which is a mathematical evaluation, and therefore amental process, under the broadest reasonable interpretation of the claim. Accordingly, the claim recites at least one abstract idea.
101 Analysis – Step 2A, Prong II
Regarding Prong II of the Step 2A analysis, the claims are to be analyzed to determine whether the claim, as a whole, integrates the abstract into a practical application. see MPEP 2106.04(II)(A)(2) and MPEP 2106.04(d)(2). It must be determined whether any additional elements in the claim beyond the abstract idea integrate the exception into a practical application in a manner that imposes a meaningful limit on the judicial exception. The courts have indicated that additional elements merely using a computer to implement an abstract idea, adding insignificant extra solution activity, or generally linking use of a judicial exception to a particular technological environment or field of use do not integrate a judicial exception into a “practical application.”
In the present case, the additional limitations beyond the above-noted abstract idea are as follows (where the underlined portions are the “additional limitations” [with a description of the additional limitations in brackets], while the bolded portions continue to represent the “abstract idea”.):
A guidance, navigation, and control system for a material handling vehicle, the system comprising: [generic linking to technical field, 2106.05(h), Apply it, 2106.05(f)]
a first sensor, the first sensor to measure odometry data; [pre-solution activity (data gathering), 2106.05(g) using generic sensors, generic link to technical field, 2106.05(h)];
a second sensor, the second sensor to measure inertial measurement unit data; and [pre-solution activity (data gathering), 2106.05(g) using generic sensors, generic link to technical field, 2106.05(h)];
a processor, the processor to: [applying the abstract idea using generic computing module, Apply it 2106.05(f)]
predict a location of the material handling vehicle based on the odometry data from the first sensor;
measure the location of the material handling vehicle based on the inertial measurement unit data from the second sensor; and
combine the odometry data from the first sensor and the inertial measurement unit data from the second sensor within a Kalman filter to generate an updated location estimate for the material handling vehicle.
For the following reason(s), the examiner submits that the above identified additional limitations do not integrate the above-noted abstract idea into a practical application.
Regarding the additional limitations of “a first sensor…,” “a second sensor…,” and “a processor…,” the examiner submits that these limitations are insignificant extra-solution activities that merely use a computer to perform the process. In particular, “a first sensor…” and “a second sensor…” are recited at a high level of generality (i.e. as a general means of gathering data for use in the determination of vehicle location), and amounts to mere data gathering, which is a form of insignificant extra-solution activity. Lastly, the “processor…” is recited at a high-level of generality (i.e., as a generic processor performing a generic computer function) such that it amounts no more than mere instructions to apply the exception using a generic computer component.
Thus, taken alone, the additional elements do not integrate the abstract idea into a practical application. Further, looking at the additional limitation(s) as an ordered combination or as a whole, the limitation(s) add nothing that is not already present when looking at the elements taken individually. For instance, there is no indication that the additional elements, when considered as a whole, reflect an improvement in the functioning of a computer or an improvement to another technology or technical field, apply or use the above-noted judicial exception to effect a particular treatment or prophylaxis for a disease or medical condition, implement/use the above-noted judicial exception with a particular machine or manufacture that is integral to the claim, effect a transformation or reduction of a particular article to a different state or thing, or apply or use the judicial exception in some other meaningful way beyond generally linking the use of the judicial exception to a particular technological environment, such that the claim as a whole is not more than a drafting effort designed to monopolize the exception. see MPEP § 2106.05. Accordingly, the additional limitation(s) do/does not integrate the abstract idea into a practical application because it does not impose any meaningful limits on practicing the abstract idea.
101 Analysis – Step 2B
Regarding Step 2B of the Revised Guidance, representative independent claim 1 does not include additional elements (considered both individually and as an ordered combination) that are sufficient to amount to significantly more than the judicial exception for the same reasons to those discussed above with respect to determining that the claim does not integrate the abstract idea into a practical application. As discussed above with respect to integration of the abstract idea into a practical application, the additional element of using a processor to perform the computations amounts to nothing more than mere instructions to apply the exception using a generic computer component. Mere instructions to apply an exception using a generic computer component cannot provide an inventive concept. And as discussed above, the additional limitations of “a first sensor…” and “a second sensor…,” the examiner submits that these limitations are insignificant extra-solution activities.
Dependent claim(s) 10 – 14 & 16 do not recite any further limitations that cause the claim(s) to be patent eligible. Rather, the limitations of dependent claims are directed toward additional aspects of the judicial exception and do not integrate the judicial exception into a practical application. Specifically:
Claim 10 recites wherein an amount of noise in both the odometry and inertial measurements are computed, which is an abstract idea of mathematical evaluation without significantly more under the broadest reasonable interpretation of the claim.
Claim 11 recites wherein the updated location estimate for the material handling vehicle is based on the odometry data from the first sensor, the inertial measurement unit data from the second sensor, and the noise in both the measured odometry data and the measured inertial measurement unit data, which is an abstract idea of mathematical evaluation without significantly more under the broadest reasonable interpretation of the claim.
Claim 12 recites wherein the locations of objects outside a sensor field of view are estimated based on the own vehicle location, which is a mental process of evaluating data collected under the broadest reasonable interpretation of the claim.
Claim 13 recites wherein the feature tracking system is configured to create a buffer zone around tracked objects to account for potential offsets in the updated location estimate, which is a mental process under the broadest reasonable interpretation of the claim.
Claim 14 recites wherein the location estimate is used to determine a position of the vehicle in a warehouse, which is a mental process under the broadest reasonable interpretation of the claim.
Claim 16 recites wherein the location computed is transmitted to a warehouse management system, which is the mere extra-solution activity of outputting data under the broadest reasonable interpretation of the claim.
Therefore, dependent claims 10 – 14 & 16 are not patent eligible under the same rationale as provided for in the rejection of Independent Claim 9.
Therefore, claim(s) 9 – 14 & 16 is/are ineligible under 35 USC §101.
Claim Rejections - 35 USC § 103
In the event the determination of the status of the application as subject to AIA 35 U.S.C. 102 and 103 (or as subject to pre-AIA 35 U.S.C. 102 and 103) is incorrect, any correction of the statutory basis (i.e., changing from AIA to pre-AIA ) for the rejection will not be considered a new ground of rejection if the prior art relied upon, and the rationale supporting the rejection, would be the same under either status.
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.
Claim(s) 9 - 11 & 14 is/are rejected under 35 U.S.C. 103 as being unpatentable over Steinhardt (US 2017/0122770 A1) in view of Wong (US 2012/0303176 A1).
Regarding Claim 9:
Steinhardt discloses: A guidance, navigation, and control system for a… vehicle, the system comprising: (Steinhardt discloses in at least Paragraphs 0027 & 0037 a system for determining the position of a motor vehicle, including a corresponding navigation system for the vehicle [i.e. a guidance, navigation, and control system for a vehicle])
a first sensor, the first sensor to measure odometry data; (Steinhardt discloses in at least Paragraphs 0027 & 0042 an odometry navigation system, including an odometry sensor system, which may measure values from wheel speed sensors and steering angle sensors [i.e. a first sensor configured to measure odometry data])
a second sensor, the second sensor to measure inertial measurement unit data; and (Steinhardt discloses in at least Paragraphs 0027 & 0038 an inertial navigation system, including a sensor system configured to detect accelerations and rotation rates along a plurality of vehicle axes through the use of an inertial measurement unit as disclosed in at least Paragraph 0063 of Steinhardt [i.e. a second sensor, the second sensor to measure inertial measurement unit data])
a processor, the processor to: (Steinhardt discloses in at least Paragraph 0030 wherein the system may include a processor and electronic storage device upon which a computer program may be stored to be executed by the processor)
predict a location of the… vehicle based on the odometry data from the first sensor; (Steinhardt discloses in at least Paragraphs 0075 & 0076 wherein detected values by the odometry navigation system may be output to a preprocessing unit, which is configured to determine the position and orientation of the vehicle based on dead reckoning methods, with an associated error being determined for the odometry navigation system’s output [i.e. predict a location of the vehicle based on the odometry data from the first sensor])
measure the location of the… vehicle based on the inertial measurement unit data from the second sensor; and (Steinhardt discloses in at least Paragraphs 0066 & 0067 wherein a position of the vehicle may be determined using the measured values from the inertial measurement unit, based on a dead reckoning algorithm [i.e. measure the location of the vehicle based on the inertial measurement unit data from the second sensor])
combine the odometry data from the first sensor and the inertial measurement unit data from the second sensor within a Kalman filter to generate an updated location estimate for the… vehicle. (Steinhardt discloses in at least Paragraphs 0044 & 0047 wherein a fusion filter may take as input a fusion data set, including input data from the odometry and inertial navigation system, from which correction values for the position of the vehicle may be determined and output as disclosed in at least Paragraphs 0068, 0078, & 0079. Steinhardt further discloses in at least Paragraphs 0048, 0078, & 0079 wherein a fusion filter may be embodied as a Kalman filter [i.e. the data is combined within a Kalman filter])
Steinhardt however appears to be silent regarding:
Wherein the vehicle is a material handling vehicle
However Wong teaches wherein a forklift vehicle may be localized in a warehouse environment through the use of a Kalman filter, based on inertial and odometry sensors.
Wherein the vehicle is a material handling vehicle (However Wong teaches in at least Paragraphs 0032, 0047, & 0063 wherein a Kalman filter may be used to produce a position prediction for a vehicle based on odometry and IMU sensor information, the vehicle including an automated forklift or lift truck as taught in at least Paragraphs 0028 & 0034 of Wong [i.e. the vehicle whose position is determined by a Kalman filter is a material handling vehicle])
It would have been obvious to one of ordinary skill in the art before the effective filing date of the present claimed invention to have modified the disclosure of Steinhardt by incorporating the determination of a position of a forklift through the use of Kalman-filtered measurements as taught by Wong.
The motivation to do so is that, as acknowledged by Wong in at least Paragraphs 0009 & 0047, a work vehicle may be better localized in a warehouse environment, allowing said vehicle to better traverse the industrial environment as it handles material, improving the operation of the vehicle in a defined environment.
Regarding Claim 10:
The system of claim 9, wherein the processor calculates an amount of noise in both the measured odometry data and the measured inertial measurement unit data.
Steinhardt discloses in at least Paragraphs 0023, 0077, & 0087 wherein error values may be computed for each of the inertial and odometry location estimates, which include measurement noise from the odometry and inertial sensors [i.e. an amount of noise in both the measured odometry data and the measured inertial measurement unit data].
Regarding Claim 11:
The system of claim 10, wherein the updated location estimate for the material handling vehicle is based on the odometry data from the first sensor, the inertial measurement unit data from the second sensor, and the noise in both the measured odometry data and the measured inertial measurement unit data.
Steinhardt discloses in at least Paragraphs 0044 & 0047 wherein a fusion filter may take as input a fusion data set, including input data from the odometry and inertial navigation system, as well as the respective errors of each, from which correction values for the position of the vehicle may be determined and output as disclosed in at least Paragraphs 0068, 0078, & 0079 of Steinhardt [i.e. the updated location estimate for the material handling vehicle is based on the odometry data from the first sensor, the inertial measurement unit data from the second sensor, and the noise in both the measured odometry data and the measured inertial measurement unit data].
Regarding Claim 14:
The system of claim 9, further comprising: an absolute position measurement system configured to determine an absolute position of the material handling vehicle within a warehouse based on the updated location estimate.
Steinhardt does not appear to specifically disclose wherein an absolute position measurement system configured to determine an absolute position of the material handling vehicle within a warehouse based on the updated location estimate.
However Wong teaches in at least Paragraphs 0032, 0047, & 0063 wherein a Kalman filter may be used to produce a position prediction for a vehicle based on odometry and IMU sensor information, the predicted position being within a physical environment such as a warehouse as taught in at least Paragraphs 0027 & 0030 [i.e. an absolute position measurement system configured to determine an absolute position of the material handling vehicle within a warehouse based on the updated location estimate].
It would have been obvious to one of ordinary skill in the art before the effective filing date of the present claimed invention to have modified the disclosure of Steinhardt by incorporating the determination of a position of a forklift within a warehouse through the use of Kalman-filtered measurements as taught by Wong.
The motivation to do so is that, as acknowledged by Wong in at least Paragraphs 0009 & 0047, a work vehicle may be better localized in an industrial environment, allowing said vehicle to better traverse the industrial environment as it handles material, improving the operation of the vehicle in a defined environment.
Claim(s) 12 is/are rejected under 35 U.S.C. 103 as being unpatentable over Steinhardt (US 2017/0122770 A1) in view of Wong (US 2012/0303176 A1) as applied to claim 9 above, and further in view of Saunders (US 2024/0100702 A1).
Regarding Claim 12:
The system of claim 9, further comprising: a feature tracking system configured to track locations of objects outside a field of view of a sensor based on the updated location estimate of the material handling vehicle.
Steinhardt does not appear to specifically disclose a feature tracking system configured to track locations of objects outside a field of view of a sensor based on the updated location estimate of the material handling vehicle.
However Saunders teaches in at least Paragraphs 0092 & 0113 wherein a plurality of sensors may be configured to track objects in an environment, such as a warehouse, including through sensor systems off-robot. In the event that the tracked entities are outside the field of view of sensor systems, the likely position of the tracked entities may continue to be tracked, along with an increasing degree of uncertainty regarding the position of the object in the environment, with the position of the robot being compared to the uncertainty position in order to determine if the robot should operate more conservatively [i.e. a feature tracking system configured to track locations of objects outside a field of view of a sensor based on the updated location estimate of the material handling vehicle].
It would have been obvious to one of ordinary skill in the art before the effective filing date of the present claimed invention to have modified the disclosure of Steinhardt by incorporating the tracking of location of objects outside the field of view of the sensors as taught by Saunders.
The motivation to do so is that, as acknowledged by Saunders in at least Paragraphs 0113, vehicles may operate more conservatively in an environment where other vehicles may be present but are not currently in sensor view, improving the safety of the vehicle.
Claim(s) 16 is/are rejected under 35 U.S.C. 103 as being unpatentable over Steinhardt (US 2017/0122770 A1) in view of Wong (US 2012/0303176 A1) as applied to claim 9 above, and further in view of Emanuel (US 2011/0093134 A1).
Regarding Claim 16:
The system of claim 9, wherein the processor is further configured to communicate the updated location estimate to a warehouse management system to facilitate tracking of the material handling vehicle throughout a warehouse.
Steinhardt does not appear to specifically disclose communicating the updated location estimate to a warehouse management system.
However Emanuel teaches in at least Paragraphs 0044 – 0046 wherein the positioning system of a vehicle may determine and communicate the precise position of each vehicle to a server which manages mapping and collision avoidance operations for a warehouse environment as disclosed in at least Paragraphs 0038 & 0039 of Emanuel.
It would have been obvious to one of ordinary skill in the art before the effective filing date of the present claimed invention to have modified the disclosure of Steinhardt by incorporating the communication of vehicle locations to a central system as taught by Emanuel.
The motivation to do so is that, as acknowledged by Emanuel in at least Paragraphs 0044 – 0046, the positions of a plurality of vehicles in the environment may be tracked, improving the alerting of when multiple vehicles in the environment approach one another, assisting in avoiding collisions.
Claim(s) 13 is/are rejected under 35 U.S.C. 103 as being unpatentable over Steinhardt (US 2017/0122770 A1) in view of Wong (US 2012/0303176 A1) and Saunders (US 2024/0100702 A1) as applied to claim 12 above, and further in view of Emanuel (US 2011/0093134 A1).
Regarding Claim 13:
The system of claim 12, wherein the feature tracking system is configured to create a buffer zone around tracked objects to account for potential offsets in the updated location estimate.
Steinhardt does not appear to specifically disclose wherein the feature tracking system is configured to create a buffer zone around tracked objects to account for potential offsets in the updated location estimate.
However Emanuel teaches in at least Paragraphs 0049 & 0056 wherein a vehicle buffer radius may be defined for each class of vehicle operating in an environment, which define a safety zone of interest around the vehicles, the buffer zones being monitored for intersection between the respective vehicles during operation [i.e. the feature tracking system is configured to create a buffer zone around tracked objects to account for potential offsets in the updated location estimate].
It would have been obvious to one of ordinary skill in the art before the effective filing date of the present claimed invention to have defined buffer zones around the position of vehicles operating in an environment as taught by Emanuel.
The motivation to do so is that, as acknowledged by Emanuel in at least Paragraphs 0049 & 0056, a safety zone may be defined around each vehicle operating in the environment, improving the safety of the vehicles by reducing the likelihood of vehicle collisions.
Claim(s) 15 is/are rejected under 35 U.S.C. 103 as being unpatentable over Steinhardt (US 2017/0122770 A1) in view of Wong (US 2012/0303176 A1) as applied to claim 9 above, and further in view of Kashyap (US 2020/0039353 A1).
Regarding Claim 15:
The system of claim 9, wherein the processor is further configured to adjust operational parameters of the material handling vehicle based on the updated location estimate, wherein the operational parameters include at least one of maximum speed, lift height, or turning radius.
Steinhardt does not appear to specifically disclose wherein the processor is further configured to adjust operational parameters of the material handling vehicle based on the updated location estimate.
However Kashyap teaches in at least Paragraphs 0046 & 0047 wherein a materials handling vehicle may be limited to operate at a maximum operation value, such as a speed cap, when the vehicle is determined to be located in a zone of specific speed limit, which may be determined based on the location of the vehicle relative to the warehouse environment as taught in at least Paragraphs 0027 & 0039 of Kashyap [i.e. adjust operational parameters of the material handling vehicle based on the updated location estimate, wherein the operational parameters include maximum speed].
It would have been obvious to one of ordinary skill in the art before the effective filing date of the present claimed invention to have modified the disclosure of Steinhardt by incorporating the limiting of maximum vehicle speed based on a determined location as taught by Kashyap.
The motivation to do so is that, as acknowledged by Kashyap in at least Paragraphs 0043 & 0047, the safety of the vehicle operating in high-traffic environments may be improved through the limiting of speed.
Conclusion
The following prior art made of record but not relied upon is considered pertinent to the Applicant’s disclosure:
Mcaree (US 8,571,762 B2): Mcaree recites a method of obtaining the pose of a mining vehicle, including through the application of a Kalman filter to collected data, the data being collected from, for example, inertial sensors and GPS sensors.
Frederic (US 8,165,795 B2): Frederic recites a system for improving navigation of a vehicle, including through the use of a Kalman filter to correct observation errors in measurements from inertial sensors.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to CHRISTOPHER RYAN CARDIMINO whose telephone number is (571)272-2759. The examiner can normally be reached M-Th 8:30-5:00.
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If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Ramya Burgess can be reached at (571)272-6011. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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/CHRISTOPHER R CARDIMINO/Examiner, Art Unit 3661
/RAMYA P BURGESS/Supervisory Patent Examiner, Art Unit 3661
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