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 .
Information Disclosure Statement
The information disclosure statement (IDS) submitted on 07/07/2025.The submission is in compliance with the provisions of 37 CFR 1.97. Accordingly, the information disclosure statement is being considered by the examiner.
Priority
Acknowledgement is made of applicants claim for foreign priority under 35 U.S.C. 119(a)-(d) and (f). The certified copy has been filed in parent application KR10-2025-0036785 filed on 03/21/2025.
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, 10, 19 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more.
On January 7, 2019, the USPTO released new examination guidelines setting forth a two-step inquiry for determining whether a claim is directed to non-statutory subject matter. According to the guidelines, a claim is directed to non-statutory subject matter if:
STEP 1: the claim does not fall within one of the four statutory categories of invention (process, machine, manufacture or composition of matter), 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:
STEP 2A (PRONG 1): Does the claim recite an abstract idea, law of nature, or natural phenomenon?
STEP 2A (PRONG 2): Does the claim recite additional elements that integrate the judicial exception into a practical application?
STEP 2B: Does the claim recite additional elements that amount to significantly more than the judicial exception?
Using the two-step inquiry, it is clear that claim is directed toward non-statutory subject matter, as shown below:
STEP 1: Do the claims fall within one of the statutory categories?
Yes claims 1, 10 and 19 are directed towards a apparatus, method and a non-transitory computer-readable medium respectively.
STEP 2A (PRONG 1): Is the claim directed to a law of nature, a natural phenomenon or an abstract idea?
Yes, the claims are directed to an abstract idea.
With regard to STEP 2A (PRONG 1), the guidelines provide three groupings of subject matter that are considered abstract ideas:
Mathematical concepts – mathematical relationships, mathematical formulas or equations, mathematical calculations;
Certain methods of organizing human activity – fundamental economic principles or practices (including hedging, insurance, mitigating risk); commercial or legal interactions (including agreements in the form of contracts; legal obligations; advertising, marketing or sales activities or behaviors; business relations); managing personal behavior or relationships or interactions between people (including social activities, teaching, and following rules or instructions); and
Mental processes – concepts that are practicably performed in the human mind (including an observation, evaluation, judgment, opinion).
The process in claims 1, 10 and 19 is a mental process that can be practicably performed in the human mind, or with the aid of pen and paper and as such is directed toward and abstract idea. The claim consists of obtaining pose using point cloud which is similar to a human calculating the pose based on the point cloud indicating a building is in front thus the robot is pointed forward, or drivable area or road surface slope that aid in determining pose. obtaining second ground information is similar to a human filtering out data that are indicative of sky from first ground information. obtaining gravity vector are similar to a human calculating the value based on sensor data indicating downward acceleration. Obtaining a constraint is similar to a human indicating a maximum height for filtering out data. Updating a pose is similar to a human correcting the pose after filtering data such as could points over a height and determining that based on updated data, the robot is pointed a different way. Notably, the claim does not positively recite any limitations regarding actual determination of the attitude of the vehicle.
STEP 2A (PRONG 2): Does the claim recite additional elements that integrate the judicial exception into a practical application?
No, the claims do not recite additional elements that integrate the judicial exception into a practical application.
With regard to STEP 2A (prong 2), whether the claim recites additional elements that integrate the judicial exception into a practical application, the guidelines provide the following exemplary considerations that are indicative that an additional element (or combination of elements) may have integrated the judicial exception into a practical application:
an additional element reflects an improvement in the functioning of a computer, or an improvement to other technology or technical field;
an additional element that applies or uses a judicial exception to effect a particular treatment or prophylaxis for a disease or medical condition;
an additional element implements a judicial exception with, or uses a judicial exception in conjunction with, a particular machine or manufacture that is integral to the claim;
an additional element effects a transformation or reduction of a particular article to a different state or thing; and
an additional element applies or uses 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 more than a drafting effort designed to monopolize the exception.
While the guidelines further state that the exemplary considerations are not an exhaustive list and that there may be other examples of integrating the exception into a practical application, the guidelines also list examples in which a judicial exception has not been integrated into a practical application:
an additional element merely recites the words “apply it” (or an equivalent) with the judicial exception, or merely includes instructions to implement an abstract idea on a computer, or merely uses a computer as a tool to perform an abstract idea;
an additional element adds insignificant extra-solution activity to the judicial exception; and
An additional element does no more than generally link the use of a judicial exception to a particular technological environment or field of use.
Claims 1, 10 and 19 do not recite any of the exemplary considerations that are indicative of an abstract idea having been integrated into a practical application. The additional limitations include the light detection and ranging, the inertial measurement, are generic linking for taking measurement. The processor is for apply it level of the abstract idea.
Thus, it is clear that the abstract idea is merely implemented on a computer at the “apply it level”, which is indicative of the abstract solution having not been integrated into a practical application.
STEP 2B: Does the claim recite additional elements that amount to significantly more than the judicial exception?
No, the claims do not recite additional elements that amount to significantly more than the judicial exception.
With regard to STEP 2B, whether the claims recite additional elements that provide significantly more than the recited judicial exception, the guidelines specify that the pre-guideline procedure is still in effect. Specifically, that examiners should continue to consider whether an additional element or combination of elements:
adds a specific limitation or combination of limitations that are not well-understood, routine, conventional activity in the field, which is indicative that an inventive concept may be present; or
simply appends well-understood, routine, conventional activities previously known to the industry, specified at a high level of generality, to the judicial exception, which is indicative that an inventive concept may not be present.
Claims 1, 10 and 19 do not recite any specific limitation or combination of limitations that are not well-understood, routine, conventional activity in the field. The additional limitations include the light detection and ranging, the inertial measurement, are generic linking for taking measurement. The processor is for apply it level of the abstract idea.
CONCLUSION
Thus, since claims 1, 10 and 19: (a) directed toward an abstract idea, (b) does not recite additional elements that integrate the judicial exception into a practical application, and (c) does not recite additional elements that amount to significantly more than the judicial exception, it is clear that the claims are directed towards non-statutory subject matter.
Claims 2 and 11: the estimation is calculation step that can be performed by a human with the aid of paper and pen and applied by a computer.
Claims 3, 12: updating a height is similar to a human determining the height based on the floor and the sensor.
Claims 4, 13: obtaining a second gravity information is similar to a human correcting the vector based on a sloped surface determined by height constraint.
Claims 5, 14: obtaining gravity is part of the abstract idea of claim 1.
Claims 6, 15: determining outlier is similar to a human comparing to threshold and removing.
Claims 7, 16: removing outlier is similar to a human comparing to threshold and then updating the pose based on the new information.
Claims 8, 17: updating pose is similar to a human reading the new points to determine new borders of ground or drivable surface and determine pose of vehicle on road.
Claims 9, 18: analyzing position is similar to a human determining the pose by matching the position with the point cloud on pose graph.
Claim 19: the updating pose is similar to a human reading a new map and updating the pose based on pose graph or point clouds showing building or drivable area or road surface slope.
Claim Rejections - 35 USC § 103
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.
Claims 1, 10, 19, 20 are rejected under 35 U.S.C. 103 as being unpatentable by Yi (US20180299557) in view of Nie (US20250306208) and Yang (US20200003869).
Regarding claim 1, Yi teaches a pose correction apparatus, comprising:
a light detection and ranging (LiDAR) (abstract disclosing laser radar);
an inertial measurement sensor ([0039] disclosing inertial measurement sensor); and
a processor ([0020] disclosing a processor),
wherein the processor is configured to: obtain pose information associated with a pose of a robot using a point cloud, based at least in part on obtaining the point cloud by at least the LiDAR ([0030]-[0047] disclosing obtaining pose information of the vehicle based on obtaining the point cloud by the Lidar);
obtain a second ground information in which at least a portion of a first ground
information indicating a ground is corrected, based at least in part on obtaining the first ground information using the pose information ([0045]-[0052] disclosing compensating cloud points based on the pose, i.e., a second ground information is generated from a first ground information);
Yi does not teach obtain a first gravity information indicating gravity acting on the robot, based at least in part on obtaining, by the inertial measurement sensor, at least one or more of: acceleration of the robot, or an angular velocity of the robot; obtain at least one or more of: a vector constraint, or an elevation constraint; and
update the pose information, based at least in part on correcting one or more of: the
second ground information, or the first gravity information with respect to one or more of: the vector constraint, or the elevation constraint.
Nie teaches obtain a first gravity information indicating gravity acting on the robot, based at least in part on obtaining, by the inertial measurement sensor, at least one or more of: acceleration of the robot, or an angular velocity of the robot ([0022], [0064]-[0068] disclosing determining gravity acting on the robot using acceleration information of the IMU);
obtain at least one or more of: a vector constraint, or an elevation constraint ([0044], [0072]-[0075] disclosing a slope constraint in the z direction, i.e., elevation constraint); and
correcting the second ground information, or the first gravity information with respect to one or more of: the vector constraint, or the elevation constraint ([0072]-[0075] disclosing updating ground information which is corrected based on the slope constraint. [0060] disclosing the ground information).
it would have been obvious to one of ordinary skill in the art to combine the teaching of Nie with the teaching Yi thus enabling the accurate determination of a pose based on an updated cloud point accounting to the pose change thus improving the accuracy of the determination.
Yi as modified by Nie does not teach Update the pose based on ground information.
Yang teaches updating the pose based on ground information (abstract, [0031]-[0032] disclosing updating a pose based on updated ground information).
Yi already teaches the obtaining of initial position and posture of vehicle based on corrected cloud point map [0022], thus It would have been obvious to one of ordinary skill in the art to have combined the teaching of yang to the teaching of Yi as modified by Nie, yielding predictable results, in order to determine the pose based on the updated point cloud as taught by Yi thus improving the accuracy of the vehicle control based on updated pose data.
Regarding claim 20, Li as modified by Nie and Yang teaches the media of claim 19, the instructions including further instructions to update a map information corresponding to a surrounding environment of the robot, based at least in part on updating pose information, and pose the robot based at least in part on updating the pose information (Yang [0030]-[0050] disclosing wherein the nodes have pose graphs and thus adjusting the poses and determining pose of the robot based on the adjusted pose graph).
Yi already teaches the obtaining of initial position and posture of vehicle based on corrected cloud point map [0022], thus It would have been obvious to one of ordinary skill in the art to have combined the teaching of yang to the teaching of Yi as modified by Nie, yielding predictable results, in order to determine the pose based on the updated point cloud as taught by Yi thus improving the accuracy of the vehicle control based on updated pose data.
Claims 10, 19 are rejected for similar reasons as claim 1.
Claims 2, 11 are rejected under 35 U.S.C. 103 as being unpatentable by Yi (US20180299557) in view of Nie (US20250306208) and Yang (US20200003869) and Liyanaarachchi, referred to as Liya (US20210343035).
Regarding claim 2, Yi as modified by Nie and Yang teaches the pose correction apparatus of claim 1, but does not teach wherein the processor is configured to: estimate a ground vector associated with the ground, based at least in part on applying a plane fitting algorithm to the first ground information; and obtain the at least one or more of the vector constraint or the elevation constraint using
the ground vector.
Liya teaches estimate a ground vector associated with the ground, based at least in part on applying a plane fitting algorithm to the first ground information ([0049]-[0050] disclosing a constraint vector as a combination of the gravity vector and angle of inclination used in a plane fitting algorithm for ground information). and
obtain the at least one or more of the vector constraint or the elevation constraint using the ground vector ([0049]-[0050] disclosing a constraint vector as a combination of the gravity vector and angle of inclination used in a plane fitting algorithm for ground information).
it would have been obvious to combine the teaching of Liya to the ground representations as taught by Yi as modified by Nie and Yang in order to allow the processor to select the candidate reference surface more accurately as taught by Liya [0050].
Claim 11 is rejected for similar reasons as claim 2.
Claims 3, 12 are rejected under 35 U.S.C. 103 as being unpatentable by Yi (US20180299557) in view of Nie (US20250306208) and Yang (US20200003869) and Liyanaarachchi, referred to as Liya (US20210343035) and Rezaeian (US20220144289).
Regarding claim 3, Li as modified by Nie and Yang and Liya teaches the pose correction apparatus of claim 2, wherein the processor is configured to:
Liya teaches update a height, using a reference plane obtained via a plane equation generated by the plane fitting algorithm, based at least in part on obtaining the plane equation ([0049]-[0055] disclosing the surface to determine the height as part of the ground fitting equation).
It would have been obvious to one of ordinary skill in the art to combine the teaching of Liya to calculate the height on the plane equation in order to enable accurate height prediction by determining a ground surface as taught by Liya.
While Li as modified by Nie and Liya does not explicitly disclose the height of the vehicle.
Rezaeian teaches height of vehicle based on ground information (at least abstract disclosing the height of the vehicle).
Li as modified by Nie and Liya already teaches “Liya” determining height based on ground, thus the combination of the teaching of Rezaeian is obvious yielding predictable results in order to determine a height of the center of gravity based on the height of the Lidar indicative of a vehicle height as shown in Figure 2, thus improving the autonomous driving as taught by Rezaeian.
Claim 12 is rejected for similar reasons as claim 3.
Claims 4, 13 are rejected under 35 U.S.C. 103 as being unpatentable by Yi (US20180299557) in view of Nie (US20250306208) and Yang (US20200003869) and Chon (US20180113204).
Regarding claim 4, Li as modified by Nie and Yang does not teach the pose correction apparatus of claim 1, wherein the processor is configured to:
obtain the first gravity information, while the robot is moving at less than predefined
acceleration or a predefined angular velocity.
Chon teaches wherein the processor is configured to: obtain the first gravity information, while the robot is moving at less than predefined acceleration or a predefined angular velocity ([0057]-[0058] disclosing the measurements are taken when the speed is less than a threshold).
It would have been obvious to one of ordinary skill in the art to combine the teaching of Chon with the teaching of Li as modified by Nie and Yang to only obtain the measurements at the low speed in order to determine the information based on stable IMU. While Chon does not explicitly state the acceleration, it would be obvious to try with the acceleration instead of the speed to solve the stability.
Claim 13 is rejected for similar reasons as claim 4.
Claims 5, 14 are rejected under 35 U.S.C. 103 as being unpatentable by Yi (US20180299557) in view of Nie (US20250306208) and Yang (US20200003869) and Huber (US20210027477).
Regarding claim 5, Li as modified by Nie and Yang teaches the pose correction apparatus of claim 1, but does not teach wherein the processor is configured to: obtain second gravity information to facilitate reducing an error value indicating an error in the first gravity information, based at least in part on applying the at least one or more of: the vector constraint, or the elevation constraint.
Huber teaches obtain second gravity information to facilitate reducing an error value indicating an error in the first gravity information, based at least in part on applying the at least one or more of: the vector constraint, or the elevation constraint ([0032] disclosing the normal vector filtering by adjusting the normal vectors based on comparison with the gravity vector, the normal vector is interpreted as gravity information since it has to be parallel to the gravity vector and it is constraint by the gravity vector).
It would have been obvious to combine the teaching of Huber to the teaching of Li as modified by Nie and Yang yielding predictable results in order to obtain an accurate representation of the ground surface thus improving the ground detection and vehicle position.
Claim 14 is rejected for similar reasons as claim 5.
Claims 6-9, 15-18 are rejected under 35 U.S.C. 103 as being unpatentable by Yi (US20180299557) in view of Nie (US20250306208) and Yang (US20200003869) and Huber (US20210027477) and Chestnutt (US20250199535).
Regarding claim 6, Li as modified by Ni and Yang teaches the pose correction apparatus of claim 5, but does not teach wherein the processor is configured to: determine whether there is an outlier in at least one or more of: the second ground
information, or the second gravity information,
Specifically, Huber teaches determine whether there is an outlier in at least one or more of: the second ground information, or the second gravity information ([0030]-[0040] disclosing the outliers based on the gravity vector constraint).
It would have been obvious to combine the teaching of Huber to the teaching of Li as modified by Nie and Yang yielding predictable results in order to obtain an accurate representation of the ground surface thus improving the ground detection and vehicle position.
Chestnutt teaches based at least in part on applying at least one or more of: graph optimization, or uncertainty estimation, to the at least one or more of: the second ground information, or the second gravity information ([0250]-[0257] disclosing the filtering based on uncertainty estimation of the sensor data).
It would have been obvious to combine/substitute the filtering method of Chestnutt using the uncertainty with the outlier detection of Huber in order to improve accuracy of the point cloud thus improving vehicle positioning.
Regarding claim 7, Li as modified by Ni and Yang and Huber and Chestnutt teaches the pose correction apparatus of claim 6, wherein the processor is configured to:
Specifically, Huber teaches remove the outlier from the at least one or more of: the second ground information, or the second gravity information, when there is the outlier in the at least one or more of: the second ground information, or the second gravity information ([0030]-[0040] disclosing filtering points from the ground points associated with outlier); and
While Li as modified by Ni and Yang and Huber and Chestnutt does not explicitly disclose update the pose information, using the at least one or more of: the second ground information, or the second gravity information, the at least one in which the outlier is removed.
Yang teaches updating the pose based on ground information (abstract, [0031]-[0032] disclosing updating a pose based on updated ground information).
Yi already teaches the obtaining of initial position and posture of vehicle based on corrected cloud point map [0022], thus It would have been obvious to one of ordinary skill in the art to have combined the teaching of yang to the teaching of Yi as modified by Nie, yielding predictable results, in order to determine the pose based on the updated point cloud including removed outliers as taught by Yi thus improving the accuracy of the vehicle control.
Regarding claim 8, Li as modified by Nie and Yang and Huber and Chestnutt teaches the pose correction apparatus of claim 6, wherein the processor is configured to:
Specifically, Chestnutt disclosing update the pose information, using the at least one or more of: the second ground information, or the second gravity information, at least when there is no outlier in the at least one or more of: the second ground information, or the second gravity information ([0146]-[0150] disclosing the pose of the robot is adjusted based on the point cloud information, at least [0163]-[0170], [0250]-[0257] disclosing the filtering of the data).
It would have been obvious to combine/substitute the filtering method of Chestnutt using the uncertainty with the outlier detection of Huber in order to improve accuracy of the point cloud thus improving vehicle positioning.
Regarding claim 9, Li as modified by Nie and Yang and Huber and Chestnutt teaches the pose correction apparatus of claim 6, wherein the processor is configured to: analyze position information about a position of the robot, update the pose information, based at least in part on analyzing the position information (Li teaches detecting the pose based on position of the robot).
Specifically, Chestnutt teaches based at least in part on applying the uncertainty estimation to the at least one or more of: the second ground information, or the second gravity information ([0146]-[0150] disclosing the pose of the robot is adjusted based on the point cloud information, at least [0163]-[0170], [0250]-[0257] disclosing the filtering of the data).
It would have been obvious to combine/substitute the filtering method of Chestnutt using the uncertainty with the outlier detection of Huber in order to improve accuracy of the point cloud thus improving vehicle positioning.
Claims 15-18 is rejected for similar reasons as claim 6-9, respectively.
Conclusion
The prior art made of record and not relied upon is considered pertinent to
applicant's disclosure. The prior art cited in PTO-892 and not mentioned above disclose related devices and methods.
US20210026361 disclosing filtering out heights over a certain height.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to MOHAMAD O EL SAYAH whose telephone number is (571)270-7734. The examiner can normally be reached on M-Th 6:30-4:30.
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, Ramon Mercado can be reached on (571) 270-5744. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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/MOHAMAD O EL SAYAH/Primary Examiner, Art Unit 3658B
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