DETAILED ACTION
This non-final action is in reply to the application filed 18 June 2024.
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 .
Priority
Claims 1-20 are pending, having a filing date of 18 June 2024 and claiming a National Stage entry of PCT/CP2021/087115, filed 21 December 2021.
Information Disclosure Statement
The information disclosure statement (IDSs) submitted 4 October 2024 complies with 37 C.F.R. 1.97. Accordingly, the IDS has been considered by the examiner. An initialed copy of the 1449 form is enclosed herewith.
Drawings
The drawings, filed 18 June 2024, are accepted by the examiner.
Claim Rejections - 35 USC § 112
The following is a quotation of 35 U.S.C. 112(b):
(b) CONCLUSION.—The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the inventor or a joint inventor regards as the invention.
Claims 1-20 are rejected under 35 U.S.C. 112(b) as being indefinite for failing to particularly point out and distinctly claim the subject matter which the inventor or a joint inventor regards as the invention.
Claims 1, 11, and 16, recite the following limitations:
(a) “determine, based on the motion sensor data and the lidar data, a plurality of first poses of the lidar sensor along the agent trajectory”;
(b) “determine, based on the motion sensor data and the image data, a plurality of second poses of the imaging sensor along the agent trajectory”; and
(c) “determine, based on the plurality of first poses and the plurality of second poses along the agent trajectory, a pose of the lidar sensor and a pose of the imaging sensor relative to the motion sensor”.
With regard to recitations (a), (b) and (c) the specification at [0045] repeats the claim language, without disclosing how these determinizations are being made. Further, these limitations are unclear since there is no recitation in the claims of (1) how the plurality of first poses of the lidar sensor are determined based on the motion sensor data and lidar data, (2) how the plurality of second poses of the image sensor are determined based on the image sensor data and the motion sensor data, nor (3) how the pose of lidar sensor and pose of the imaging sensor are determined relative to the motion sensor. Further with regard to (c) it is unclear how the poses of the lidar sensor and imaging sensors are determined relative to the motion sensor, based on the first pose and second pose, especially in light of the fact that respective poses of the sensors may likely be fixed relative to the motion sensor.
Since dependent claims 2-10, 12-15 and 17-20 depend upon the rejected independent claims 1, 11 and 15, they are similarly rejected under 35 U.S.C. 112(b).
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 1-20 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more.
In January, 2019 (updated October 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:
o STEP 2A (PRONG 1): Does the claim recite an abstract idea, law of nature, or natural phenomenon?
o STEP 2A (PRONG 2): Does the claim recite additional elements that integrate the judicial exception into a practical application?
o 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 claims 1, 11 and 16 are directed toward non-statutory subject matter as shown below.
STEP 1: Do claims 1, 11 and 16 fall within one of the statutory categories? Yes, because claim 1 is directed toward an apparatus, claim 11 is directed toward a vehicle, and claim 16 relates to a method, all of which fall within one of the statutory categories.
STEP 2A (PRONG 1): Are the claims directed to a law of nature, a natural phenomenon or an abstract idea? Yes, claims 1, 11 and 16 are directed to abstract ideas.
With regard to STEP 2A (PRONG 1), the guidelines provide three groupings of subject matter that are considered abstract ideas:
1. Mathematical concepts – mathematical relationships, mathematical formulas or equations, mathematical calculations;
2. 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
3. Mental processes – concepts that are practicably performed in the human mind (including an observation, evaluation, judgment, opinion).
As per claims 1, 11 and 16, the apparatus (claim 1), the vehicle (claim 11) and method (claim 16) are mental processes that can be performed in the mind and, therefore, are abstract ideas. In particular, claims 1, 11 and 16 recite the abstract ideas of:
“determining, based on the motion sensor data and the lidar data, a plurality of first poses of the lidar sensor along the agent trajectory”;
“determining, based on the motion sensor data and the image data, a plurality of second poses of the imaging sensor along the agent trajectory”; and
“determining, based on the plurality of first poses and the plurality of second poses along the agent trajectory, a pose of the lidar sensor and a pose of the imaging sensor relative to the motion sensor.”
These recitations merely consist of determining a first pose of the lidar sensor along the trajectory, determining a second pose of the image sensor along the agent trajectory and determining the pose of the lidar sensor and imaging sensors relative to the motion sensor. This is equivalent to a person determining a first pose of the lidar sensor along the trajectory, determining a second pose of the image sensor along the agent trajectory and determining the pose of the lidar sensor and imaging sensors relative to the motion sensor. The Examiner notes that under MPEP 2106.04(a)(2)(III), the courts consider a mental process (thinking) that "can be performed in the human mind, or by a human using a pen and paper" to be an abstract idea. CyberSource Corp. v. Retail Decisions, Inc., 654 F.3d 1366, 1372, 99 USPQ2d 1690, 1695 (Fed. Cir. 2011). As the Federal Circuit explained, "methods which can be performed mentally, or which are the equivalent of human mental work, are unpatentable abstract ideas the ‘basic tools of scientific and technological work’ that are open to all.’" 654 F.3d at 1371, 99 USPQ2d at 1694 (citing Gottschalk v. Benson, 409 U.S. 63, 175 USPQ 673 (1972)). See also Mayo Collaborative Servs. v. Prometheus Labs. Inc., 566 U.S. 66, 71, 101 USPQ2d 1961, 1965 ("‘[M]ental processes[] and abstract intellectual concepts are not patentable, as they are the basic tools of scientific and technological work’" (quoting Benson, 409 U.S. at 67, 175 USPQ at 675)); Parker v. Flook, 437 U.S. 584, 589, 198 USPQ 193, 197 (1978) (same). As such, a person, determines a first pose of the lidar sensor along the trajectory, determines a second pose of the image sensor along the agent trajectory and determines the pose of the lidar sensor and imaging sensors relative to the motion sensor. This may be done by an individual merely using coordinate transformations to determine the respective orientations of the sensors relative to each other along the trajectory, or merely observing the relative orientation of the motion sensor, lidar sensor and image sensor along the agent trajectory. The mere nominal recitations that the determining steps are executed by the “processing circuitry” (claims 1 and 11) does not take the limitation out of the mental process grouping.
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, 11 and 16 do not recite any of the exemplary considerations that are indicative of an abstract idea having been integrated into practical application. Claims 1, 11 and 16 further recites the additional elements of:
“a motion sensor configured to obtain motion sensor data of the agent along the agent trajectory”;
“a lidar sensor configured to obtain lidar data along the agent trajectory”;
“an imaging sensor configured to obtain image data along the agent trajectory.”
This additional element further limits the abstract idea without integrating the abstract idea into practical application or significantly more. In particular, the “obtain[ing] motion sensor data, lidar data and image data … “ steps are recited at a high level of generality (i.e., as a general means of gathering an electronic representation of an area or navigational data or planned path data) and amount to mere data gathering, a form of insignificant extra-solution activity added to the judicial exception per MPEP 2106.05(g), because the steps characterize pre solution activity, such as an individual observing the image of the barrier location.
Claims 1 and 11 still further includes the additional element “an sensor apparatus” (claim 1, 11). This elements is not sufficient to amount to significantly more than the judicial exception because it fails to integrate the exception into practical application. The mere inclusion of instructions to implement an abstract idea on a computer, or merely using a computer as a tool to perform an abstract idea is indicative that the judicial exception has not been integrated into a practical application. In the instant case, the data is obtained by “sensor apparatus” i.e. via computers. Thus, it is clear that the abstract idea is merely implemented on a computer, which is indicative of the abstract idea having not been integrated in the practical application. The “sensor apparatus,” merely describes how to generally “apply” the otherwise metal judgements in a generic or general purpose computing environment. The sensor apparatus is recited at a high level of generality and merely automate the obtaining steps.
STEP 2B: Do the claims recite additional elements that amount to significantly more than the judicial exception? No, claim 1, 11 and 16 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, 11 and 16 do not recite any specific limitation or combination of limitations that are well-understood, routine, conventional (WURC) activity in the field. Obtaining data are fundamental, i.e. WURC, activities performed by, computers operating with data as claims 1, 11 and 16. Further, applicant’s specification does not provide any indication that the obtaining activities of the system are performed using anything other than a conventional computer. MPEP 2106.05(d)(II), and the cases cited therein, including Intellectual Ventures I, LLC v. Symantec Corp., 838 F.3d 1307, 1321 (Fed. Cir. 2016), TLI Communications LLC v. AV Auto. LLC, 823 F.3d 607, 610 (Fed. Cir. 2016), and OIP Techs., Inc., v. Amazon.com, Inc., 788 F.3d 1359, 1363 (Fed. Cir. 2015), indicate that mere performance of an action is a well‐understood, routine, and conventional function when it is claimed in a merely generic manner.
Thus, since claims 1, 11 and 16 are: (a) directed toward abstract ideas; (b) do not recite additional elements that integrate the judicial exception into practical application; and (c) do not recite additional elements that amount to significantly more than the judicial exception, it is clear that claims 1, 11 and 16 are directed to non-statutory subject matter.
Dependent claims 2-10, 12-15 and 17-20 further limit the abstract idea without integrating the abstract idea into practical application or significantly more. For example, the additional elements of claims 2, 5, 6, 9, 12, 13, 16, 19 and 20 are further limitations that, under the broadest reasonable interpretations, are limitations that are abstract ideas, using similar analysis to claims 1, 11 and 16. Further, for example, the additional elements of claims 3, 4, 7, 10, 11, 14, 17 and 18 are further limitations that under their broadest reasonable interpretation further limit the abstract idea without integrating the abstract idea into practical application or adding significantly more.
Conclusion:
As such claims 1-20 are rejected as being drawn to an abstract idea without
significantly more, and thus are ineligible.
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 non-obviousness.
This application currently names joint inventors. In considering patentability of the claims the examiner presumes that the subject matter of the various claims was commonly owned as of the effective filing date of the claimed invention(s) absent any evidence to the contrary. Applicant is advised of the obligation under 37 CFR 1.56 to point out the inventor and effective filing dates of each claim that was not commonly owned as of the effective filing date of the later invention in order for the examiner to consider the applicability of 35 U.S.C. 102(b)(2)(C) for any potential 35 U.S.C. 102(a)(2) prior art against the later invention.
Claims 1- 20 are rejected under 35 U.S.C. 103 as being unpatentable over U.S. Patent Publication Number 2022/0137636 to Yang et al. (hereafter Yang) in view of U.S. Patent Publication Number 2021/0024081to Johnson-Roberson et al. (hereafter Johnson).
As per claim 1, Yang discloses [a] sensor apparatus for sensing data of an agent performing a movement along an agent trajectory (see at least Yang, Abstract),
wherein the sensor apparatus (see at least Yang, [0058] disclosing that the vehicle 205 can include a positioning system 265. The positioning system 265 can determine a current position of the vehicle 205. This can help the vehicle 205 localize itself within its environment. The positioning system 265 can be any device or circuitry for analyzing the position of the vehicle 205. For example, the positioning system 265 can determine position by using one or more of inertial sensors (e.g., inertial measurement unit(s), etc.), a satellite positioning system, based on IP address, by using triangulation or proximity to network access points or other network components (e.g., cellular towers, WiFi access points, etc.) or other suitable techniques. The position of the vehicle 205 can be used by various systems of the vehicle computing system 210 or provided to a remote computing system ) comprises:
a motion sensor configured to obtain motion sensor data of the agent along the agent trajectory (see at least Yang, [0058]; [0164] disclosing that each vehicle (e.g., vehicle 205 of FIG. 2) can be equipped with multiple sensors including image devices, wheel encoders, inertial measurement units (“IMU”), a consumer-grade global positioning system (“GPS”) receivers, and light detection and ranging systems (e.g., Velodyne HDL-64e LiDAR, etc.). LiDAR data collected by the light detection and ranging systems can be used to compute the ground-truth pose information and are not part of the training dataset 1345);
a lidar sensor configured to obtain lidar data along the agent trajectory (see at least Yang, [0055] disclosing that the sensor(s) 235 can be configured to acquire sensor data 255. The sensor(s) 235 can be external sensors configured to acquire external sensor data. This can include sensor data associated with the surrounding environment (e.g., in a real-world or simulated environment) of the vehicle 205. The surrounding environment of the vehicle 205 can include/be represented in the field of view of the sensor(s) 235. For instance, the sensor(s) 235 can acquire image or other data of the environment outside of the vehicle 205 and within a range or field of view of one or more of the sensor(s) 235. This can include different types of sensor data acquired by the sensor(s) 235 such as, for example, data from one or more Light Detection and Ranging (LIDAR) systems, one or more Radio Detection and Ranging (RADAR) systems, one or more cameras (e.g., visible spectrum cameras, infrared cameras, etc.), one or more motion sensors, one or more audio sensors (e.g., microphones, etc.), or other types of imaging capture devices or sensors; [0058]; [0079] disclosing that with regard to FIG. 3, the plurality of input image frames 335A-N can be grouped as an input multi-frame 330 based on the capture times 340A-N. For instance, the input multi-frame 330 can include a plurality of input image frames 335A-N captured within a threshold time period (e.g., within 100 ms, the time it takes for a LIDAR sweep));
an imaging sensor configured to obtain image data along the agent trajectory (see at least Yang, [0058]; [0069] disclosing that FIG. 3 is an example of a simultaneous localization and mapping technique 300, according to some implementations of the present disclosure. The simultaneous localization and mapping technique 300 may include an initialization stage 305 during which an environment is initially mapped based on synchronized camera images, an input stage 310 during which an input multi-frame 330 is collected for the simultaneous localization and mapping of a robotic platform 105, a tracking stage 315 during which a rough pose estimate 355 of the robotic platform 105 is determined based on the input multi-frame 330, a local mapping stage 320 during which the input multi-frame 330 can be used to refine a three-dimensional environment of the robotic platform 105 and/or a continuous-time motion model representative of a trajectory of the robotic platform 105 relative to the three-dimensional environment, and a loop closing stage 325 during which a previously seen environment is recognized by the robotic platform); and
a processing circuitry (see at least Yang, [0050] disclosing that the vehicle computing system 210 can include one or more computing devices located onboard the vehicle 205. For example, the computing device(s) can be located on or within the vehicle 205. The computing device(s) can include various components for performing various operations and functions. For instance, the computing device(s) can include one or more processors and one or more tangible, non-transitory, computer readable media (e.g., memory devices, etc.) ; [0147]) configured to:
determine, based on the motion sensor data and the lidar data, a plurality of first poses of the lidar sensor along the agent trajectory (see at least Yang, [0077] disclosing that the different capture times 425-435 for the plurality of asynchronous image devices 415A-E can be synchronized with one or more other sensors and/or devices of the robotic platform 105. By way of example, the robotic platform 105 can include a light detection and ranging (“LiDAR”) system. In some implementations, the plurality asynchronous image devices 415A-E can be synchronized with the LiDAR system. For instance, the capture time(s) 425-435 can be configured to trigger the image device(s) 415A-E to capture image frames based on the orientation of the LiDAR system (e.g., a 10 Hz spinning LiDAR) such that image frames for a particular region are captured concurrently with three-dimensional LiDAR data for the particular region; [0079]; [0080] );
determine, based on the motion sensor data and the image data, a plurality of second poses of the imaging sensor along the agent trajectory (see at least Yang, [0070]; [0072] disclosing that simultaneous localization and mapping technique 300 may be begin with (e.g., in response to the one or more conditions, etc.) the initialization stage 305. The initialization stage 305 can include receiving a plurality of initial image frames. The initial image frames may include a plurality of two-dimensional images (e.g., red, green, blue images, etc.) captured from one or more different image devices of the robotic platform 105. ... further disclosing that the at least two image device 405A-B can be configured to capture image frame(s) at one or more similar (e.g., synchronized) capture times. By way of example, the at least two image devices 405A-B can include a synchronous stereo camera pair that share an overlapping field of view and fire closely in time. In this manner, the initial image frames can include image frames that share an overlapping field of view and one or more matching capture time ; [0073] disclosing that a first control pose, (e.g., defined as ξ.sub.0.sup.c) for the continuous-time motion model 375 can be set to the origin of a world frame and the three-dimensional environment can be initialized with three-dimensional map points triangulated from the initial image frames (e.g., and parameters associated with the associated image devices 405A-B)); ... . But, Yang does not explicitly teach the following limitation taught in Johnson:
determine, based on the plurality of first poses and the plurality of second poses along the agent trajectory, a pose of the lidar sensor and a pose of the imaging sensor relative to the motion sensor (see at least Johnson, [0062] disclosing that the pose (e.g., absolute position and/or orientation relative to a reference frame) can be values, vectors, and/or any other suitable data element. The absolute position and/or orientation can include relative pose of each camera (or a subset thereof) to the vehicle, relative pose of each spatial sensor (or a subset thereof) to the vehicle (e.g., relative pose of each IMU to the vehicle), relative pose of spatial sensors to cameras, relative pose of each time of flight sensor (or a subset thereof) to the vehicle, relative pose of each cameras (or a subset thereof) to each other camera (or a subset thereof), relative pose of each time of flight sensor (or a subset thereof) to each other time of flight sensor (or a subset thereof) (e.g., relative pose of each LiDAR sensor to each other LiDAR sensor), relative pose of the one or more wheel odometry sensors (or a subset thereof) to the vehicle, relative pose of the one or more location sensors to the vehicle (e.g., GPS to the vehicle), and/or any other suitable relative pose of every component (or subset thereof) to every other component (or subset thereof)).
Yang and Johnson are analogous art to claim 1 because they are in the same field pertaining to a sensor apparatus with multiple sensors for a moving agent. Yang relates to systems and methods for the simultaneous localization and mapping of autonomous vehicle systems that include receiving a plurality of input image frames from the plurality of asynchronous image devices triggered at different times to capture the plurality of input image frames (see Yang, Abstract). Johnson relates to system and method for autonomous vehicle control (see Johnson, [0003]).
Therefore, it would have been prima facie obvious to one or ordinary skill in the art before the effective filing date of the claimed invention to modify the apparatus, as disclosed in Yang, to provide the benefit of determining, based on the plurality of first poses and the plurality of second poses along the agent trajectory, a pose of the lidar sensor and a pose of the imaging sensor relative to the motion sensor, as disclosed in Johnson, with a reasonable expectation of success. Doing so would provide the benefit of providing a dynamic re-calibration of the localization system (see Johnson, [0004]).
As per claim 2, the combination of Yang and Johnson discloses all of the limitations of claim 1, as shown above. Yang as modified by Johnson further disclose the following limitations:
wherein the motion sensor comprises at least one of an accelerometer or a gyroscope (see at least Johnson, [0032] disclosing that the sensors can include cameras (e.g., CCD, CMOS, multispectral, visual range, hyperspectral, stereoscopic, wide-angle, RGB-Depth, event, etc.), spatial sensors (e.g., inertial measurement units (IMU), accelerometer, gyroscope, altimeter, magnetometer, compasses, etc.), wheel odometry sensors (e.g., Hall effect sensor, conductive collar, etc.), speedometer (e.g., tachometer, odometer, etc.)), and
wherein the motion sensor data comprises data about at least one of linear accelerations or rotational motions of the motion sensor along the agent trajectory (see at least Johnson, [0034] disclosing that the system preferably includes a plurality of spatial sensors, which can function to detect sensor motion and/or vehicle motion. The spatial sensors can measure linear acceleration using one or more accelerometers, rotational rate using one or more gyroscopes, a heading reference using the magnetometer, and/or any other suitable measurement; [0047] disclosing that processing system 230 functions to perform all or portions of the method 10, control the global capture of the visual systems, control vehicle operation (e.g., vehicle localization, SLAM, path planning, vehicle actuator control, etc.), and/or perform any other functionality. The processing system can be a local processing system (e.g., GPU, CPU, TPU, etc.), a remote processing system (e.g., stream raw data, extracted features, etc.), the processing system of the inertial sensor, and/or any other suitable processing system).
Therefore, it would have been prima facie obvious to one or ordinary skill in the art before the effective filing date of the claimed invention to modify the apparatus, as disclosed in Yang, as modified by Johnson, to provide the benefit of having the motion sensor comprises at least one of an accelerometer or a gyroscope, and having the motion sensor data comprise data about at least one of linear accelerations or rotational motions of the motion sensor along the agent trajectory, as further disclosed in Johnson, with a reasonable expectation of success. Doing so would provide the benefit of providing a dynamic re-calibration of the localization system (see Johnson, [0004]).
As per claim 3, the combination of Yang and Johnson discloses all of the limitations of claim 1, as shown above. Yang as modified by Johnson further disclose the following limitations:
wherein the imaging sensor comprises a camera (see at least Yang, [0038] disclosing that the environment 110 can include one or more dynamic object(s) 130 (e.g., simulated objects, real-world objects, etc.). The dynamic object(s) 130 can include any number of moveable objects such as, for example, one or more pedestrians, animals, vehicles, etc. The dynamic object(s) 130 can move within the environment according to one or more trajectories 135. The robotic platform 105 can include one or more sensor(s) 115, 120. The first sensor(s) 115 can include a different type of sensor than the second sensor(s) 120. By way of example, the first sensor(s) 115 can include one or more imaging device(s) (e.g., cameras, etc.), whereas the second sensor(s) 120 can include one or more depth measuring device(s) (e.g., LiDAR device, etc.).; [0054] ).
Therefore, it would have been prima facie obvious to one or ordinary skill in the art before the effective filing date of the claimed invention to modify the apparatus, as disclosed in Yang, as modified by Johnson, to provide the benefit of having the imaging sensor comprises a camera, as further disclosed in Yang, with a reasonable expectation of success. Doing so would provide the benefit of providing another means of dynamically re-calibration of the localization system (see Johnson, [0004]).
As per claim 4, the combination of Yang and Johnson discloses all of the limitations of claim 1, as shown above. Yang as modified by Johnson further discloses the following limitation:
wherein the processing circuitry is configured to determine, based on the motion sensor data and the lidar data, the plurality of first poses of the lidar sensor along the agent trajectory using a continuous-time batch optimization scheme (see at least Yang, [0069] disclosing that FIG. 3 is an example of a simultaneous localization and mapping technique 300, according to some implementations of the present disclosure. The simultaneous localization and mapping technique 300 may include an initialization stage 305 during which an environment is initially mapped based on synchronized camera images, an input stage 310 during which an input multi-frame 330 is collected for the simultaneous localization and mapping of a robotic platform 105, a tracking stage 315 during which a rough pose estimate 355 of the robotic platform 105 is determined based on the input multi-frame 330, a local mapping stage 320 during which the input multi-frame 330 can be used to refine a three-dimensional environment of the robotic platform 105 and/or a continuous-time motion model representative of a trajectory of the robotic platform 105 relative to the three-dimensional environment, and a loop closing stage 325 during which a previously seen environment is recognized by the robotic platform. [0091] disclosing that the trajectory 370 of the robotic platform 105 through the environment can be updated based on the estimated pose 355 for the robotic platform 105. As described herein, the trajectory 370 of the robotic platform 105 can be represented as a continuous-time motion model 375; [0115]).
Therefore, it would have been prima facie obvious to one or ordinary skill in the art before the effective filing date of the claimed invention to modify the apparatus, as disclosed in Yang, as modified by Johnson, to provide the benefit of determining, based on the motion sensor data and the lidar data, the plurality of first poses of the lidar sensor along the agent trajectory using a continuous-time batch optimization scheme, as further disclosed in Yang, with a reasonable expectation of success. Doing so would provide the benefit of providing another means of dynamically re-calibration of the localization system (see Johnson, [0004]).
As per claim 5, the combination of Yang and Johnson discloses all of the limitations of claim 4, as shown above. Yang as modified by Johnson further discloses the following limitation:
wherein the processing circuitry is configured to represent the plurality of first poses of the lidar sensor along the agent trajectory as a continuous time function (see at least Yang, [0096] disclosing that FIG. 5 is an example of a continuous-time motion model 375, according to some implementations of the present disclosure. The continuous-time motion model 375 can be represented as one or more basis-spline(s) 505 parameterized by a plurality (e.g., four) control poses 510-525. Each control pose 510-525 can represent a spatio-temporal continuous pose of the robotic platform 105 over respective timesteps 530-545 and space 550. Each control pose 510-525 can correspond to a key multi-frame indexed at timesteps 530-545, respectively; [0098] disclosing that, the overall robot platform trajectory 375 can be formulated as a continuous-time function T.sub.wb(t):custom-character.fwdarw.custom-character(3), rather than as a sequence of discrete poses. The overall trajectory 375 can be modelled with a cumulative cubic basis-spline over asynchronous key multi-frames (e.g., multi-frames 345 of FIG. 3)).
Therefore, it would have been prima facie obvious to one or ordinary skill in the art before the effective filing date of the claimed invention to modify the apparatus, as disclosed in Yang, as modified by Johnson, to provide the benefit of representing the plurality of first poses of the lidar sensor along the agent trajectory as a continuous time function, as further disclosed in Yang, with a reasonable expectation of success. Doing so would provide the benefit of providing another means of dynamically re-calibration of the localization system (see Johnson, [0004]).
As per claim 6, the combination of Yang and Johnson discloses all of the limitations of claim 1, as shown above. Yang as modified by Johnson further discloses the following limitation:
wherein the processing circuitry is configured to determine, based on the motion sensor data and the image data, the plurality of second poses of the imaging sensor along the agent trajectory using a continuous-time batch optimization scheme (see at least Yang, [0096]; [0098]; [0113] disclosing that to perform loop closure at stage 325, the cubic basis-spline motion model 375 can be integrated to formulate an asynchronous, multi-view case of the pose graph optimization problem. With a newly-detected loop candidate 385 (e.g., KMF.sub.l) matching to multiple image devices in the current query KMF.sub.q, a pose graph can be built. Each node α can be encoded by a timestamp t.sub.α representing the underlying robotic platform pose T.sub.wb (t.sub.α) <interpreted as a continuous-time batch optimization scheme>).
Therefore, it would have been prima facie obvious to one or ordinary skill in the art before the effective filing date of the claimed invention to modify the apparatus, as disclosed in Yang, as modified by Johnson, to provide the benefit of determining, based on the motion sensor data and the image data, the plurality of second poses of the imaging sensor along the agent trajectory using a continuous-time batch optimization scheme, as further disclosed in Yang, with a reasonable expectation of success. Doing so would provide the benefit of providing another means of dynamically re-calibration of the localization system (see Johnson, [0004]).
As per claim 7, the combination of Yang and Johnson discloses all of the limitations of claim 6, as shown above. Yang as modified by Johnson further discloses the following limitation:
wherein the processing circuitry is configured to represent the plurality of second poses of the imaging sensor along the agent trajectory as a continuous time function (see at least Yang, [0038] disclosing that The sensor(s) 115, 120 can include one or more Light Detection and Ranging (LiDAR) systems, one or more Radio Detection and Ranging (RADAR) systems, one or more cameras (e.g., visible spectrum cameras or infrared cameras), one or more sonar systems, one or more motion sensors, or other types of image capture devices or sensors. The sensor(s) 115, 120 can include multiple sensors of different types. For instance, the sensor(s) 115, 120 can include one or more first sensor(s) 115 and one or more second sensor(s) 120. The first sensor(s) 115 can include a different type of sensor than the second sensor(s) 120. By way of example, the first sensor(s) 115 can include one or more imaging device(s) (e.g., cameras, etc.), whereas the second sensor(s) 120 can include one or more depth measuring device(s) (e.g., LiDAR device, etc.).; [0069] <as cited in claim 4>; [0096] <as cited in claim 5>; [0098]).
Therefore, it would have been prima facie obvious to one or ordinary skill in the art before the effective filing date of the claimed invention to modify the apparatus, as disclosed in Yang, as modified by Johnson, to provide the benefit of represent the plurality of second poses of the imaging sensor along the agent trajectory as a continuous time function, as further disclosed in Yang, with a reasonable expectation of success. Doing so would provide the benefit of providing another means of dynamically re-calibration of the localization system (see Johnson, [0004]).
As per claim 8, the combination of Yang and Johnson discloses all of the limitations of claim 1, as shown above. Yang as modified by Johnson further discloses the following limitation:
wherein the processing circuitry is further configured to determine a difference measure value between the plurality of first poses and the plurality of second poses (see at least Johnson, [0130] disclosing that the sensor pose estimates from S200 are filtered for anomalies or outliers (e.g., by comparing against each other, comparing against an expected sensor pose estimate, comparing against the prior evaluation sensor pose, etc.), wherein the anomaly-removed sensor pose estimates are used in S400. In a third variation, sensor pose estimates from S200 can be randomly selected for use in S400. However, the sensor pose estimates can be otherwise managed) and
to determine, based on the plurality of first poses and the plurality of second poses along the agent trajectory, the pose of the lidar sensor and the pose of the imaging sensor relative to the motion sensor in response to determining that the difference measure value is smaller than a threshold value (see at least Johnson, [0062]; [0065]; [0151] disclosing that determining evaluation matrix convergence over time (e.g., in relative sensor poses, in biases, etc.) functions to determine that the shifted sensor poses (represented by the evaluation matrix) are stable and not substantially changing over time (e.g., changing less than a predetermined threshold). Convergence in the relative sensor poses can be used in S600 to update the operation matrix(es), used in S200 to initialize the bundle adjustment in the next timestep, and/or otherwise used. Similar or different methods can be used to determine bias convergence over time, wherein the converged biases can be used in S200 as bias initialization variables and/or otherwise used by the system )
Therefore, it would have been prima facie obvious to one or ordinary skill in the art before the effective filing date of the claimed invention to modify the apparatus, as disclosed in Yang, as modified by Johnson, to provide the benefit of determining a difference measure value between the plurality of first poses and the plurality of second poses and determining, based on the plurality of first poses and the plurality of second poses along the agent trajectory, the pose of the lidar sensor and the pose of the imaging sensor relative to the motion sensor, in response to determining that the difference measure value is smaller than a threshold value, as further disclosed in Johnson, with a reasonable expectation of success. Doing so would provide the benefit of providing another means of dynamically re-calibration of the localization system (see Johnson, [0004]).
As per claim 9, the combination of Yang and Johnson discloses all of the limitations of claim 1, as shown above. Yang as modified by Johnson further discloses the following limitations:
wherein the sensor apparatus comprises at least one of a plurality of lidar sensors configured to obtain lidar data along the agent trajectory or a plurality of imaging sensors configured to obtain image data along the agent trajectory (see at least Yang, [0038] disclosing that The sensor(s) 115, 120 can include one or more Light Detection and Ranging (LiDAR) systems, one or more Radio Detection and Ranging (RADAR) systems, one or more cameras (e.g., visible spectrum cameras or infrared cameras), one or more sonar systems, one or more motion sensors, or other types of image capture devices or sensors. The sensor(s) 115, 120 can include multiple sensors of different types. For instance, the sensor(s) 115, 120 can include one or more first sensor(s) 115 and one or more second sensor(s) 120. The first sensor(s) 115 can include a different type of sensor than the second sensor(s) 120. By way of example, the first sensor(s) 115 can include one or more imaging device(s) (e.g., cameras, etc.), whereas the second sensor(s) 120 can include one or more depth measuring device(s) (e.g., LiDAR device, etc.); [0095] disclosing that in response to selecting the input multi-frame 330 as the new key multi-frame, the trajectory 370 of the robotic platform 105 through the environment can be updated based on the input multi-frame 330. For instance, the estimated pose 355 and previously estimated poses and map points can be refined based on the latest observations of the input multi-frame 330. To do so, a set of control poses and map points can be jointly estimated. The estimated local trajectory 370 can be refined with a basis-spline model 375 parameterized by a set of control poses. A new control pose of the set of control poses can be determined based on the input multi-frame 330 with the estimated pose 355 determined during tracking 315; [0096]).
Therefore, it would have been prima facie obvious to one or ordinary skill in the art before the effective filing date of the claimed invention to modify the apparatus, as disclosed in Yang, as modified by Johnson, to provide the benefit of having the sensor apparatus comprises at least one of a plurality of lidar sensors configured to obtain lidar data along the agent trajectory or a plurality of imaging sensors configured to obtain image data along the agent trajectory, as further disclosed in Yang, with a reasonable expectation of success. Doing so would provide the benefit of providing another means of dynamically re-calibration of the localization system (see Johnson, [0004]).
As per claim 10, the combination of Yang and Johnson discloses all of the limitations of claim 9, as shown above. Yang as modified by Johnson further discloses the following limitations:
wherein the processing circuitry is configured, for respective sensor pairs of the at least one of the plurality of lidar sensors or the plurality of imaging sensors to determine, based on a plurality of respective first poses and a plurality of respective second poses along the agent trajectory, a respective pose of a respective lidar sensor and a respective pose of a respective imaging sensor relative to the motion sensor (see at least Johnson, [0062]; [0151]; [0152] disclosing that determining convergence can include determining that a relative sensor pose has converged, determining satisfaction of a convergence condition, determining biases have converged, and/or otherwise determined; [0153]; [0173]).
As per claim 11, similar to claim 1, Yang discloses [a] vehicle (see at least Yang, Abstract) comprising
a sensor apparatus for sensing data of an agent performing a movement along an agent trajectory (see at least Yang, [0058]),
wherein the sensor apparatus comprises: a motion sensor configured to obtain motion sensor data of the agent along the agent trajectory (see at least Yang, [0058]; [0164]);
a lidar sensor configured to obtain lidar data along the agent trajectory (see at least Yang, [0055]; [0058]; [0079]);
an imaging sensor configured to obtain image data along the agent trajectory (see at least Yang, [0058]; [0069]); and
a processing circuitry (see at least Yang, [0050]; [0147]) configured to:
determine, based on the motion sensor data and the lidar data, a plurality of first poses of the lidar sensor along the agent trajectory (see at least Yang, [0077]; [0079]; [0080]);
determine, based on the motion sensor data and the image data, a plurality of second poses of the imaging sensor along the agent trajectory (see at least Yang, [0070]; [0072]; [0073]); ... .
determine, based on the plurality of first poses and the plurality of second poses along the agent trajectory, a pose of the lidar sensor and a pose of the imaging sensor relative to the motion sensor (see at least Johnson, [0062] ).
Yang and Johnson are analogous art to claim 11 because they are in the same field pertaining to a sensor apparatus with multiple sensors for a moving agent. Yang relates to systems and methods for the simultaneous localization and mapping of autonomous vehicle systems that include receiving a plurality of input image frames from the plurality of asynchronous image devices triggered at different times to capture the plurality of input image frames (see Yang, Abstract). Johnson relates to system and method for autonomous vehicle control (see Johnson, [0003]).
Therefore, it would have been prima facie obvious to one or ordinary skill in the art before the effective filing date of the claimed invention to modify the vehicle, as disclosed in Yang, to provide the benefit of determining, based on the plurality of first poses and the plurality of second poses along the agent trajectory, a pose of the lidar sensor and a pose of the imaging sensor relative to the motion sensor, as disclosed in Johnson, with a reasonable expectation of success. Doing so would provide the benefit of providing a dynamic re-calibration of the localization system (see Johnson, [0004]).
As per claim 12, similar to claim 2, the combination of Yang and Johnson discloses all of the limitations of claim 11, as shown above. Yang as modified by Johnson further disclose the following limitations:
wherein the motion sensor comprises at least one of an accelerometer or a gyroscope (see at least Johnson, [0032]), and
wherein the motion sensor data comprises data about at least one of linear accelerations or rotational motions of the motion sensor along the agent trajectory (see at least Johnson, [0034]; [0047]).
Therefore, it would have been prima facie obvious to one or ordinary skill in the art before the effective filing date of the claimed invention to modify the vehicle, as disclosed in Yang, as modified by Johnson, to provide the benefit of having the motion sensor comprises at least one of an accelerometer or a gyroscope, and having the motion sensor data comprise data about at least one of linear accelerations or rotational motions of the motion sensor along the agent trajectory, as further disclosed in Johnson, with a reasonable expectation of success. Doing so would provide the benefit of providing a dynamic re-calibration of the localization system (see Johnson, [0004]).
As per claim 13, similar to claim 3, the combination of Yang and Johnson discloses all of the limitations of claim 11, as shown above. Yang as modified by Johnson further disclose the following limitations:
wherein the imaging sensor comprises a camera (see at least Yang, [0038]; [0054]).
Therefore, it would have been prima facie obvious to one or ordinary skill in the art before the effective filing date of the claimed invention to modify the vehicle, as disclosed in Yang, as modified by Johnson, to provide the benefit of having the imaging sensor comprises a camera, as further disclosed in Yang, with a reasonable expectation of success. Doing so would provide the benefit of providing another means of dynamically re-calibration of the localization system (see Johnson, [0004]).
As per claim 14, similar to claim 4, the combination of Yang and Johnson discloses all of the limitations of claim 11, as shown above. Yang as modified by Johnson further discloses the following limitation:
wherein the processing circuitry is configured to determine, based on the motion sensor data and the lidar data, the plurality of first poses of the lidar sensor along the agent trajectory using a continuous-time batch optimization scheme (see at least Yang, [0069]; [0115]).
Therefore, it would have been prima facie obvious to one or ordinary skill in the art before the effective filing date of the claimed invention to modify the apparatus, as disclosed in Yang, as modified by Johnson, to provide the benefit of determining, based on the motion sensor data and the lidar data, the plurality of first poses of the lidar sensor along the agent trajectory using a continuous-time batch optimization scheme, as further disclosed in Yang, with a reasonable expectation of success. Doing so would provide the benefit of providing another means of dynamically re-calibration of the localization system (see Johnson, [0004]).
As per claim 15, similar to claim 5, the combination of Yang and Johnson discloses all of the limitations of claim 14, as shown above. Yang as modified by Johnson further discloses the following limitation:
wherein the processing circuitry is configured to represent the plurality of first poses of the lidar sensor along the agent trajectory as a continuous time function (see at least Yang, [0096]; [0098] ).
Therefore, it would have been prima facie obvious to one or ordinary skill in the art before the effective filing date of the claimed invention to modify the apparatus, as disclosed in Yang, as modified by Johnson, to provide the benefit of representing the plurality of first poses of the lidar sensor along the agent trajectory as a continuous time function, as further disclosed in Yang, with a reasonable expectation of success. Doing so would provide the benefit of providing another means of dynamically re-calibration of the localization system (see Johnson, [0004]).
As per claim 16, similar to claims 1 and 11, Yang discloses [a] method for sensing data of an agent performing a movement along an agent trajectory (see at least Yang, Abstract, [0058]),
wherein the method comprises: obtaining, by a motion sensor, motion sensor data along the agent trajectory (see at least Yang, [0058]; [0164] );
obtaining, by a lidar sensor, lidar data along the agent trajectory (see at least Yang, [0055]; [0058]; [0079] );
obtaining, by an imaging sensor, image data along the agent trajectory (see at least Yang, [0058]; [0069]);
determining, based on the motion sensor data and the lidar data, a plurality of first poses of the lidar sensor along the agent trajectory (see at least Yang, [0077]; [0079]; [0080);
determining, based on the motion sensor data and the image data, a plurality of second poses of the imaging sensor along the agent trajectory (see at least Yang, [0070]; [0072]; [0073] ); ... .
determining, based on the plurality of first poses and the plurality of second poses along the agent trajectory, a pose of the lidar sensor and a pose of the imaging sensor relative to the motion sensor (see at least Johnson, [0062]).
Yang and Johnson are analogous art to claim 16 because they are in the same field pertaining to a sensor apparatus with multiple sensors for a moving agent. Yang relates to systems and methods for the simultaneous localization and mapping of autonomous vehicle systems that include receiving a plurality of input image frames from the plurality of asynchronous image devices triggered at different times to capture the plurality of input image frames (see Yang, Abstract). Johnson relates to system and method for autonomous vehicle control (see Johnson, [0003]).
Therefore, it would have been prima facie obvious to one or ordinary skill in the art before the effective filing date of the claimed invention to modify the method, as disclosed in Yang, to provide the benefit of determining, based on the plurality of first poses and the plurality of second poses along the agent trajectory, a pose of the lidar sensor and a pose of the imaging sensor relative to the motion sensor, as disclosed in Johnson, with a reasonable expectation of success. Doing so would provide the benefit of providing a dynamic re-calibration of the localization system (see Johnson, [0004]).
As per claim 17, similar to claims 4 ad 14, the combination of Yang and Johnson discloses all of the limitations of claim 16, as shown above. Yang as modified by Johnson further discloses the following limitation:
wherein the plurality of first poses of the lidar sensor along the agent trajectory is determined using a continuous-time batch optimization scheme (see at least Yang, [0069]; [0115]).
Therefore, it would have been prima facie obvious to one or ordinary skill in the art before the effective filing date of the claimed invention to modify the apparatus, as disclosed in Yang, as modified by Johnson, to provide the benefit of determining, based on the motion sensor data and the lidar data, the plurality of first poses of the lidar sensor along the agent trajectory using a continuous-time batch optimization scheme, as further disclosed in Yang, with a reasonable expectation of success. Doing so would provide the benefit of providing another means of dynamically re-calibration of the localization system (see Johnson, [0004]).
As per claim 18, similar to claims 5 and 15, the combination of Yang and Johnson discloses all of the limitations of claim 17, as shown above. Yang as modified by Johnson further discloses the following limitation:
further comprising representing the plurality of first poses of the lidar sensor along the agent trajectory as a continuous time function (see at least Yang, [0096]; [0098]).
Therefore, it would have been prima facie obvious to one or ordinary skill in the art before the effective filing date of the claimed invention to modify the apparatus, as disclosed in Yang, as modified by Johnson, to provide the benefit of representing the plurality of first poses of the lidar sensor along the agent trajectory as a continuous time function, as further disclosed in Yang, with a reasonable expectation of success. Doing so would provide the benefit of providing another means of dynamically re-calibration of the localization system (see Johnson, [0004]).
As per claim 19, similar to claims 6, the combination of Yang and Johnson discloses all of the limitations of claim 16, as shown above. Yang as modified by Johnson further discloses the following limitation:
wherein the plurality of second poses of the imaging sensor along the agent trajectory is determined using a continuous-time batch optimization scheme (see at least Yang, [0096]; [0098]; [0113]).
Therefore, it would have been prima facie obvious to one or ordinary skill in the art before the effective filing date of the claimed invention to modify the apparatus, as disclosed in Yang, as modified by Johnson, to provide the benefit of determining, based on the motion sensor data and the image data, the plurality of second poses of the imaging sensor along the agent trajectory using a continuous-time batch optimization scheme, as further disclosed in Yang, with a reasonable expectation of success. Doing so would provide the benefit of providing another means of dynamically re-calibration of the localization system (see Johnson, [0004]).
As per claim 20, similar to claims 7, the combination of Yang and Johnson discloses all of the limitations of claim 19, as shown above. Yang as modified by Johnson further discloses the following limitation:
further comprising representing the plurality of second poses of the imaging sensor along the agent trajectory as a continuous time function (see at least Yang, [0038]; [0069]; [0096]; [0098]).
Therefore, it would have been prima facie obvious to one or ordinary skill in the art before the effective filing date of the claimed invention to modify the apparatus, as disclosed in Yang, as modified by Johnson, to provide the benefit of representing the plurality of second poses of the imaging sensor along the agent trajectory as a continuous time function, as further disclosed in Yang, with a reasonable expectation of success. Doing so would provide the benefit of providing another means of dynamically re-calibration of the localization system (see Johnson, [0004]).
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure: U.S. Patent Publication number 2023/0141585 to Newman et al. (hereafter Newman II), see at least, [0021]; disclosing that guidance may be provided to the operator to stop the vehicle based on global positioning system (GPS) data and/or other sensor data. For example, a computing device is programmed to determine a current pose (position and orientation) of the application tool based on location data that is derived from one or more sensors mounted at fixed known locations with respect to the vehicle; [0027] disclosing 0027] disclosing that systems and methods disclosed herein can utilize sensor fusion to integrate sensor data acquired by multiple sensor modalities. Examples of sensor modalities may include global positioning system (GPS) sensors, LIDAR sensors, camera, precision odometry sensor, speed sensors, sonar systems, steering angle sensor, ground penetrating radar sensor, a gyroscope sensor and inertial measurements (from inertial sensors), and the like. The sensor fusion can aggregate data received from the plurality of sensors to localize the spatial coordinates and orientation of the vehicle to a higher degree of precision than many existing systems.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to PATRICK M. BRADY III whose telephone number is (571)272-7458. The examiner can normally be reached Monday - Friday 7:00 am - 4;30 pm.
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PATRICK M. BRADY III
Examiner
Art Unit 3665
/PATRICK M BRADY/Examiner, Art Unit 3665
/Erin D Bishop/Supervisory Patent Examiner, Art Unit 3665
Prosecution Insights