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 .
Response to Arguments
Applicant has amended claims 1, 2 and 4-17. Claim 3 has been canceled. Claims 1, 2 and 4-17 are now currently being considered. Applicant’s arguments, filed 7/6/2026, with respect to the rejection(s) of claim(s) 1-10 under 35 U.S.C 102(a)(1) and 35 U.S.C. 112(f), sixth paragraph have been fully considered and are persuasive. Therefore, the rejection has been withdrawn. However, upon further consideration, a new ground(s) of rejection is made in view of Ogura et. al. (United States Patent Application US 2023/0024736 A1) and Miyamoto et. al. (United States Patent Application Publication US 2024/0427354 A1).
Regarding claim 3, the subject matter was incorporated into independent claim 1. Applicant argues that Suzuki does not describe evaluating the object variation characteristics based on an object arrangement characteristics database configured to hold three-dimensional positional relationships of objects in space by associating the object type information and the three-dimensional positional relationships. Examiner disagrees. Suzuki et. al. discloses in paragraph [0261] “sensor information may be any information measured by the sensor such as distance information (or three-dimensional information or depth information), image information”, which is stored and Figure 9, measurement information acquisition unit, second position/orientation estimation processing unit, map-related information management unit, first position/orientation estimation processing unit. The combination of these units serve the function of the object variation characteristics evaluation unit that includes at least one piece of information that represents the presence or absence of functions that cause an object to move, rotate, or change appearance, as stated in the specification of the instant application. One example of this is shown in Suzuki et. al. paragraph [0249] where the movement control of the mobile object is performed using the position/orientation information (the first position/orientation information) estimated from the sensor information provided by the sensor installed on the mobile object and the map-related information.
Thus, the Suzuki et. al. is still effective in maintain the grounds of rejection under 35 USC 102 for the amended claim 1.
Claim Rejections - 35 USC § 102
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 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)(1) the claimed invention was patented, described in a printed publication, or in public use, on sale, or otherwise available to the public before the effective filing date of the claimed invention.
(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) 1-2, 4-10 is/are rejected under 35 U.S.C. 102(a)(1) as being anticipated by Suzuki et. al. (United States Patent Application Publication US 2020/0333789 A1) .
Regarding claim 1, Suzuki et. al. discloses an information processing apparatus configured to perform position and orientation measurement by using sensor data from a sensor, the information processing apparatus comprising at least one processor or circuit configured to function as (Suzuki et. al. [0042]-[0043], [0045], SLAM (Simultaneous Localization and Mapping) technique is used for recognizing the surrounding environment with a sensor and at the same time accurately estimating the position and the orientation of the mobile object): a first characteristic acquisition unit configured to acquire object variation characteristics that indicate characteristics that influence the accuracy of the position and orientation measurement for each object within the measurement range of the sensor (Suzuki et. al. [0042]-[0043]); a proximity object determination unit configured to determine a proximity object that interferes with an object from which the object variation characteristics have been acquired (Suzuki et. al. [0062] objects, people, mobile objects, etc.); a second characteristic acquisition unit configured to acquire object variation factor characteristics that indicate characteristics that influence accuracy of the position and orientation measurement by interfering with other objects with respect to each of the proximity objects (Suzuki et. al. [0043], odometry information, acceleration information, distance information); and a position and orientation measurement control unit configured to control the position and orientation measurement so as to restrict the use of information in which variation is estimated among the information of objects within the measurement range of the sensor, based on the object variation characteristics and the object variation factor characteristics (Suzuki et. al. [0044], map-related information management unit, [0101] the first measurement information includes a measurement error caused by an existence of the object other than the mobile object, the error may cause a reduction in the accuracy of the first processing result. By detecting an object moving in the environment, it is possible to delete information on an object unnecessary for estimating the position or the orientation of the mobile object, which makes it possible to achieve high-reliability determination of the position of the mobile object.), wherein the at least one processor or circuit is further configured to function as: an object variation characteristics evaluation unit configured to evaluate the object variation characteristics (Suzuki et. al. Figure 9, measurement information acquisition unit, second position/orientation estimation processing unit, map-related information management unit, first position/orientation estimation processing unit. The combination of these units serve the function of the object variation characteristics evaluation unit that includes at least one piece of information that represents the presence or absence of functions that cause an object to move, rotate, or change appearance, as stated in the specification of the instant application. One example of this is shown in paragraph [0249] where the movement control of the mobile object is performed using the position/orientation information (the first position/orientation information) estimated from the sensor information provided by the sensor installed on the mobile object and the map-related information.); wherein the object variation characteristics evaluation unit evaluates the object variation characteristics based on an object arrangement characteristics database configured to hold three-dimensional positional relationships of objects in space by associating the object type information and the three-dimensional positional relationships (Suzuki et. al. [0261] sensor information may be any information measured by the sensor such as distance information (or three-dimensional information or depth information), image information).
Regarding claim 2, Suzuki et. al. discloses the information processing apparatus according to claim 1, wherein the object variation characteristics include at least one piece of information that represents the presence or absence of functions that cause movement, rotation, or change of appearance of an object, or the degree of possibility of an object to cause movement, rotation, or change of appearance; wherein the object variation factor characteristics include at least one piece of information that represents the presence or absence of functions that cause another object to move, rotate, or change appearance, or the degree of possibility of an object to cause another object to move, rotate, or change appearance (Suzuki et. al. [0101] the second position/orientation estimation processing unit recognizes objects existing around the mobile object by using an object detection method such as pattern recognition. [0232] A person may interfere with the movement of the mobile object. The movement of the person may be predicted by using a learning model learned in advance by observing movement of persons using deep learning, or may be predicted by a simulation based on the movement trajectories of persons in the past.).
Regarding claim 4, Suzuki et. al. discloses the information processing apparatus according to claim 1, wherein the at least one processor or circuit is further configured to function as: an object variation factor characteristics evaluation unit configured to evaluate the object variation factor characteristics; wherein the object variation factor characteristics evaluation unit evaluates the object variation factor characteristics based on an object arrangement characteristics database configured to hold three-dimensional positional relationships of objects in space by associating the object type information and the three-dimensional positional relationships (Suzuki et. al. [0261] sensor information may be any information measured by the sensor such as distance information (or three-dimensional information or depth information), image information, odometry (position/orientation information obtained from the rotation angle of the wheel), angular velocity, acceleration, and the like. [0201] The position/orientation information is represented by 6-degree-of-freedom position/orientation parameters given by a combination of a 3-degree-of-freedom parameters (X, Y, Z) indicating the position of the mobile object on the world coordinate system in the environment and a 3-degree-of-freedom parameters (Roll, Pitch, Yaw) indicating the orientation.).
Regarding claim 5, Suzuki et. al. discloses an information processing apparatus configured to perform position and orientation measurement by using sensor data from a sensor comprising at least one processor or circuit configured to function as: a first characteristic acquisition unit configured to acquire object variation characteristics that indicate characteristics that influence the accuracy of the position and orientation measurement for each object within the measurement range of the sensor; a region determination unit configured to determine the region in which an object that has acquired the object variation characteristics exists; a region characteristics acquisition unit configured to acquire region variation characteristics that indicate characteristics that influence the accuracy of the position and orientation measurement of the region; and a position and orientation measurement control unit configured to control the position and orientation measurement so as to restrict the use of information in which variation is estimated among the information of objects within the measurement range of the sensor, based on the object variation characteristics and the region variation characteristics (Suzuki et. al. [0042]-[0044], map-related information management unit, [0101] the first measurement information includes a measurement error caused by an existence of the object other than the mobile object, the error may cause a reduction in the accuracy of the first processing result. By detecting an object moving in the environment, it is possible to delete information on an object unnecessary for estimating the position or the orientation of the mobile object, which makes it possible to achieve high-reliability determination of the position of the mobile object.), wherein the at least one processor or circuit is further configured to function as: an object variation characteristics evaluation unit configured to evaluate the object variation characteristics; wherein the object variation characteristics evaluation unit evaluates the object variation characteristics based on an object arrangement characteristics database configured to hold three-dimensional positional relationships of objects in space by associating the object type information and the three-dimensional positional relationships (Suzuki et. al. [0261] sensor information may be any information measured by the sensor such as distance information (or three-dimensional information or depth information), image information).
Regarding claim 6, Suzuki et. al. discloses the information processing apparatus according to claim 5, wherein the region variation characteristics include at least one piece of information that represents the presence or absence of functions that cause movement, rotation, or change of appearance of an object within the region, or the degree of possibility of an object within the region to cause movement, rotation, or change of appearance (Suzuki et. al. [0101] the second position/orientation estimation processing unit recognizes objects existing around the mobile object by using an object detection method such as pattern recognition. [0232] A person may interfere with the movement of the mobile object. The movement of the person may be predicted by using a learning model learned in advance by observing movement of persons using deep learning, or may be predicted by a simulation based on the movement trajectories of persons in the past.).
Regarding claim 7, Suzuki et. al. discloses the information processing apparatus according to claim 6, wherein the at least one processor or circuit is further configured to function as a region variation characteristics evaluation unit configured to evaluate the region variation characteristics, wherein the region variation characteristics evaluation unit evaluates the region variation characteristics based on an object arrangement characteristics database configured to hold three-dimensional positional relationships of objects in space by associating the object type information and the three-dimensional positional relationships (Suzuki et. al. [0261] sensor information may be any information measured by the sensor such as distance information (or three-dimensional information or depth information), image information, odometry (position/orientation information obtained from the rotation angle of the wheel), angular velocity, acceleration, and the like. [0201] The position/orientation information is represented by 6-degree-of-freedom position/orientation parameters given by a combination of a 3-degree-of-freedom parameters (X, Y, Z) indicating the position of the mobile object on the world coordinate system in the environment and a 3-degree-of-freedom parameters (Roll, Pitch, Yaw) indicating the orientation.).
Regarding claim 8, Suzuki et. al. discloses a method of controlling an information processing apparatus, which corresponds to the apparatus claim of claim 1, which the rejection analysis is incorporated herein.
Regarding claim 9, Suzuki et. al. discloses a method of controlling an information processing apparatus, which corresponds to the apparatus claim of claim 5, which the rejection analysis is incorporated herein.
Regarding claim 10, Suzuki et. al. discloses a non-transitory computer-readable storage medium configured to store a computer program comprising instructions for executing following processes, which corresponds to the method claim of claim 1, which the rejection analysis is incorporated herein.
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.
The factual inquiries for establishing a background for determining obviousness under 35 U.S.C. 103 are summarized as follows:
1. Determining the scope and contents of the prior art.
2. Ascertaining the differences between the prior art and the claims at issue.
3. Resolving the level of ordinary skill in the pertinent art.
4. Considering objective evidence present in the application indicating obviousness or nonobviousness.
Claim(s) 11-12, 15-17 is/are rejected under 35 U.S.C. 103 as being unpatentable over Suzuki et. al. (United States Patent Application Publication US 2020/0333789 A1) in view of Ogura et. al. (United States Patent Application Publication US 2023/0024736 A1).
Regarding claim 11, Suzuki et. al. discloses the information processing apparatus according to claim 1. However, Suzuki et. al. fails to disclose wherein an object variation degree indicates a degree of influence of the object variation characteristics, and the object variation degree is determined based on, at least the presence or absence of an opening and closing function or the presence or absence of a rotary mechanism.
Ogura et. al. teaches wherein an object variation degree indicates a degree of influence of the object variation characteristics, and the object variation degree is determined based on, at least the presence or absence of an opening and closing function or the presence or absence of a rotary mechanism (Ogura et. al., Abstract, [0031]: model pattern evaluation device, an evaluation value representing the geometric distribution of a plurality of features included in the model pattern is calculated, [0131]-[0134]: When the degree of coincidence S is less than the threshold value Th, the collation unit judges that the workpiece corresponding to the model pattern is not represented in the comparison region. The collation unit then changes the comparison region by changing at least one of the relative position, orientation, and scale of the model pattern with respect to the image. [0135]-[0136]: This object detection device may be used for purposes other than controlling an automated machine.).
This is important to the claimed invention because the object variation degree can show how accurate the movable robot can measure its own position and orientation. Thus, it would have been obvious to one skilled in the art prior to the effective filing date of the claimed invention to have combined the teachings of Suzuki et. al. and Ogura et. al. so that the object variation degree is included in the solution of the claimed invention.
Regarding claim 12, Suzuki et. al. discloses the information processing apparatus according to claim 1. However, Suzuki et. al. fails to disclose wherein an object variation degree indicates a degree of influence of the object variation characteristics, and the object variation degree is determined by the degree of a moving function.
Ogura et. al. teaches wherein an object variation degree indicates a degree of influence of the object variation characteristics, and the object variation degree is determined by the degree of a moving function (Ogura et. al. [0123]-[0128]).
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This is important to the claimed invention because the object variation degree can show how accurate the movable robot can measure its own position and orientation. Thus, it would have been obvious to one skilled in the art prior to the effective filing date of the claimed invention to have combined the teachings of Suzuki et. al. and Ogura et. al. so that the object variation degree is included in the solution of the claimed invention.
Regarding claim 15, Ogura et. al further discloses the information processing apparatus according to claim 11, wherein the greater the product of the object variation degree and an object variation factor degree of a feature in an image region of an object in an image region, the smaller the weight that is assigned to the feature included in the image region of a target object in position and orientation measurement processing (Ogura et. al. [0125]-[0127]).
Regarding claim 16, Ogura et. al. further discloses the information processing apparatus according to claim 15, wherein a priority is set for the use of features in position and orientation measurement (Ogura et. al. [0121]: The collation unit then changes the comparison region by changes at least one of the relative position, orientation, and scale of the model pattern with respect to the image).
Regarding claim 17, Ogura et. al. further discloses the information processing apparatus according to claim 15, wherein the at least one processor or circuit is further configured to function as: a determination unit to determine the use/non-use, priority, or weight, in a position and orientation measurement processing, according to a position of a feature, based on one or more of the shape, position and orientation of a target object or a proximity object (Ogura et. al. [0121]-[0129]: The collation unit then changes the comparison region by changes at least one of the relative position, orientation, and scale of the model pattern with respect to the image.).
Claim(s) 13-14 is/are rejected under 35 U.S.C. 103 as being unpatentable over Suzuki et. al. (United States Patent Application Publication US 2020/0333789 A1) in view of Ogura et. al. (United States Patent Application Publication US 2023/0024736 A1) as applied to claim 12 above, and further in view of Miyamoto et. al. (United States Patent Application Publication US 2024/0427354 A1).
Regarding claim 13, Ogura et. al. further discloses the information processing apparatus according to claim 12. However, Ogura et. al. fails to disclose wherein the object variation degree is a slide friction coefficient.
Miyamoto et. al. teaches wherein the object variation degree is a slide friction coefficient (Miyamoto et. al. [0101]-[0112] movement of the mobile body moving by autonomously traveling over a traveling surface). This is important to the claimed invention because it improves the accuracy of the objection variation degree based on a moving object. Thus, it would have been obvious to one skilled in the art prior to the effective filing date of the claimed invention to have combined the teachings of Suzuki, Ogura et. al. and Miyamoto et. al.
Regarding claim 14, Ogura et. al. further discloses the information processing apparatus according to claim 12, wherein the control content is determined by the following relationship: 1/ ω x f > th where ω is the slide friction coefficient, f is an object variation factor degree, and th is a threshold value (Ogura et. al. [0125]-[0128]). However, Ogura et. al. fails to teach the slide friction coefficient. Miyamoto et. al. teaches the slide friction coefficient value of the moving object. It would have been obvious to one skilled in the art prior to the effective filing date of the claimed invention to have substituted the slide friction coefficient of Miyamoto et. al. into the equation disclosed by Ogura et. al. to arrive at the solution of the claimed invention.
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Conclusion
Response to Amendment
Examiner has carefully considered the amendments to the claims and performed an updated search. New prior arts were found to reject the amended claims.
Applicant's amendment necessitated the new ground(s) of rejection presented in this Office action. Accordingly, THIS ACTION IS MADE FINAL. See MPEP § 706.07(a). 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 JESSICA YIFANG LIN whose telephone number is (571)272-6435. The examiner can normally be reached M-F 7:00am-6:15pm, with optional day off.
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/JESSICA YIFANG LIN/Examiner, Art Unit 2668 August 20, 2026
/VU LE/Supervisory Patent Examiner, Art Unit 2668
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