DETAILED ACTION
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 .
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 are rejected under 35 U.S.C. 101 because the claimed invention is directed to a judicial exception (i.e., a law of nature, a natural phenomenon, or an abstract idea) without significantly more.
Specifically, representative Claim 1 recites:
A method comprising: receiving, by a processor, a collection of individual sensor data from a first sensor type deployed on a robot traversing an environment, wherein the individual sensor data type comprises a two-dimensional camera sensor data, wherein the camera sensor captures data relating to the environment, wherein the environment is the interior of a pipe; tracking, by the processor, a distance moved by the robot within the environment, wherein the tracking is performed using data received from a second sensor associated with the robot, wherein the second sensor is a motor encoder associated with a wheel attached to the robot; mapping each of the collection of individual sensor data to a position based on the tracking step; and generating, by the processor, a three-dimensional image of the environment based on the mapping step, wherein the three-dimensional image is a function of the camera's sensor position in the pipe, the camera's field of view angle in the pipe, a diameter of the pipe, and bounding box coordinates.
The claim limitations in the abstract idea have been highlighted in bold above; the remaining limitations are “additional elements”.
Under the Step 1 of the eligibility analysis, we determine whether the claims are to a statutory category by considering whether the claimed subject matter falls within the four statutory categories of patentable subject matter identified by 35 U.S.C. 101: Process, machine, manufacture, or composition of matter. The above claim is considered to be in a statutory category (process).
Under the Step 2A, Prong One, we consider whether the claim recites a judicial exception (abstract idea). In the above claim, the highlighted portion constitutes an abstract idea because, under a broadest reasonable interpretation, it recites limitations that fall into/recite an abstract idea exceptions. Specifically, under the 2019 Revised Patent Subject matter Eligibility Guidance, it falls into the grouping of subject matter when recited as such in a claim limitation, that covers mathematical concepts (mathematical relationships, mathematical formulas or equations, mathematical calculations) and mental processes – concepts performed in the human mind including an observation, evaluation, judgement, and/or opinion.
For example, steps of “tracking, by the processor, a distance moved by the robot within the environment, wherein the tracking is performed using data received from a second sensor associated with the robot, wherein the second sensor is a motor encoder associated with a wheel attached to the robot; mapping each of the collection of individual sensor data to a position based on the tracking step;” are treated by the Examiner as belonging to mental process grouping.
Next, under the Step 2A, Prong Two, we consider whether the claim that recites a judicial exception is integrated into a practical application.
In this step, we evaluate whether the claim recites additional elements that integrate the exception into a practical application of that exception.
The above claims comprise the following additional elements:
In Claim 3: Light Detection and Ranging (LIDAR) sensor
In Claim 4: infrared sensor
In Claim 6: inertia measurement unit (IMU), LIDAR sensor
In Claim 9: inertia measurement unit (IMU)
Regarding Claim 3, the LIDAR is a particular machine but is used in a manner which represents routine, conventional program instruction implementation, falling within the judicial exception and therefore constitutes extra solution activity.
Regarding Claim 4, 6 and 9 containing the additional elements of an infrared sensor and IMU, recite the functions of detect temperature gradients in the environment and determining a pose and position of the robot, respectfully, both of which, are found by the examiner to fall within a mental process MPEP 2106.04(a)(2).
With regards to the dependent claims, claim 2, 4, 7, 8 and 10 provide additional features/steps which are part of an expanded algorithm, so these limitations should be considered part of an expanded abstract idea of the independent claims.
In conclusion, the above additional elements, considered individually and in combination with the other claim elements do not reflect an improvement to other technology or technical field, and, therefore, do not integrate the judicial exception into a practical application. Therefore, the claims are directed to a judicial exception and require further analysis under the Step 2B.
However, the above claims do not include additional elements that are sufficient to amount to significantly more than the judicial exception (Step 2B analysis).
The claims, therefore, are not patent eligible.
Claim Rejections - 35 USC § 102
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.
Claim 1 is rejected under 35 U.S.C. 102(a)(1) as being anticipated by Shen et al. (WO2023159180A1, 2023-08-24) herein referred to as Shen.
Regarding Claim 1, Shen teaches a method comprising:
receiving, by a processor, a collection of individual sensor data from a first sensor type deployed on a robot traversing an environment (Abstract), wherein the individual sensor data type comprises a two-dimensional camera sensor (Abstract; [0022]), wherein the camera sensor captures data relating to the environment, wherein the environment is the interior of a pipe (Abstract; [0022]);
tracking, by the processor, a distance moved by the robot within the environment, wherein the tracking is performed using data received from a second sensor associated with the robot, wherein the second sensor is a motor encoder associated with a wheel attached to the robot [0031; 0035].
mapping each of the collection of individual sensor data to a position based on the tracking step [0047]; and
generating, by the processor, a three-dimensional image of the environment based on the mapping step, wherein the three-dimensional image is a function of the camera's sensor position in the pipe, the camera's field of view angle in the pipe, a diameter of the pipe, and bounding box coordinates [0043-0046] (Examiner interprets bounding boxes as markers).
Allowable Subject Matter
Claims 2-10 would be allowable if written to overcome the 101 rejection set forth in this office action and rewritten in independent form to incorporate all the limitations of their base claim and any intervening claims.
The following is a statement of reasons for the indication of allowable subject matter:
Regarding Claim 2, no prior either teaches or suggest, alone or in combination the method of claim 1 wherein the generating step comprises a heuristic algorithm that calculates a physical center of a cross-section of the pipe, maps the physical center to a point within the pipe based on parameters of the camera and the diameter of the pipe, and calculates the three-dimensional image based on the bounding box coordinates and a shift to the physical center of the pipe. It is for this reason, Claim 2 and all of its dependencies would be allowed.
Conclusion
The prior art made record and not relied upon is considered pertinent to applicant’s disclosure.
Kueny et al. (Image Processing Techniques For Multi-Sensor Inspection Of Pipe Interiors, 2019-09-19) teaches An embodiment provides a method, including: obtaining, from a multi-sensor pipe inspection robot that traverses through the interior of a pipe, sensor data, such as structured laser light sensor data and Light Detection and Ranging (LIDAR) sensor data, for the interior of the pipe; identifying a pipe feature using one or more of the sensor data types; selecting an image processing technique based on the pipe feature identified using a stored association between the pipe feature and an image processing technique; and forming an image of the interior of the pipe by implementing the selected image processing technique. Other embodiments are described and claimed.
Alzuhiri et al. ( “IMU-Assisted Robotic Structured Light Sensing with Featureless Registration under Uncertainties for Pipeline Inspection.” NDT & E international : independent nondestructive testing and evaluation 139 (2023): n. page. Web.) teaches Laser profilometry and structured light sensors are being increasingly deployed for pipeline inspection as they provide the operator with a precise 3D map that can enable visual detection and direct insight into the integrity of the pipe. The focus of the presented paper is the design of an integrated robotic structured
light sensing system used to improve the performance of 3D defect reconstruction for pipeline inspection while accommodating the uncertainty seen in a real-world environment. Point cloud registration of the consecutive 3D frames is a key factor in building this 3D map; therefore, a comprehensive featureless registration approach
is proposed first, which is proven more efficient than conventional feature-based registration algorithms. Wheel odometry from the developed robotic platform and inertial measurements are integrated into the registration algorithm to enhance the 3D reconstruction performance for sensor stabilization. An intensity-based threshold
searching method is further applied to retrieve the reconstructed defect size. Lastly, the uncertainties of the structured light sensing are investigated for the total reconstruction uncertainty and estimated measurement uncertainty to be quantified in order to illustrate the measurement precision. The efficacy of the proposed algorithms are supported by experimental results of pipeline inspection.
Logocki et al. ( “Atlas Fusion - Modern Framework for Autonomous Agent Sensor Data Fusion.” ELEKTRO (Žilina, Slovakia). IEEE, 2022. 1–6. Web.) teaches In this paper, we present our software sensor fusion framework for self-driving cars and other autonomous robots. We have designed our framework as a universal and scalable
platform for building up a robust 3D model of the agent’s surrounding
environment by fusing a wide range of various sensors into the data model that we can use as a basement for the decision making and planning algorithms. Our software currently covers the data fusion of the RGB and thermal cameras, 3D LiDARs, 3D
IMU, and a GNSS positioning. The framework covers a complete pipeline from data loading, filtering, preprocessing, environment model construction, visualization, and data storage. The architecture allows the community to modify the existing setup or to
extend our solution with new ideas. The entire software is fully compatible with ROS (Robotic Operation System), which allows the framework to cooperate with other ROS-based software. The source codes are fully available as an open-source under the MIT
license. See https://github.com/Robotics-BUT/Atlas-Fusion.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to MICHAEL J SINGLETARY whose telephone number is (571)272-4593. The examiner can normally be reached Monday-Friday 8:00am-5:00pm.
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If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Catherine Rastovski can be reached at 571-270-0349. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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/MICHAEL J SINGLETARY/Examiner, Art Unit 2857
/Catherine T. Rastovski/Supervisory Primary Examiner, Art Unit 2857
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