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 § 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.
Claims 1-6, 8-15, 17-20 are rejected under 35 U.S.C. 103 as being unpatentable over Prokhorov (US 20160161602 A1), in view of Wang et al. (US 20220236729 A1), herein after will be referred to as Wang.
Regarding Claim 1,
I. Disclosure by Prokhorov
Prokhorov discloses a computing system for an autonomous vehicle that automatically initiates a sensor calibration procedure in response to detected triggers.
[Claim Element 1:] A computing system
Excerpt: "a computing device 100 associated with a vehicle 200" ([0018])
Rationale: Prokhorov explicitly discloses a computing system.
[Claim Element 2:] for a vehicle,
Excerpt: "a computing device 100 associated with a vehicle 200" ([0018])
Rationale: The disclosed computing device is for a vehicle.
[Claim Element 3:] that operates autonomously or semi-autonomously,
Excerpt: "Some vehicles are configured to operate autonomously, with no or very little input required by the driver." ([0001])
Rationale: Autonomously corresponds to autonomously or semi-autonomously.
[Claim Element 4:] the computing system comprising: one or more processors;
Excerpt: "one or more processors for controlling operations of the computing device" ([0018])
Rationale: This discloses one or more processors.
[Claim Element 5:] a memory
Excerpt: "a memory for storing data and program instructions used by the one or more processors" ([0018])
Rationale: This discloses a memory.
[Claim Element 6:] storing instructions
Excerpt: "a memory for storing data and program instructions" ([0018])
Rationale: This discloses storing instructions.
[Claim Element 7:] that, when executed
Excerpt: "the one or more processors are configured to execute instructions stored in the memory" ([0018])
Rationale: This discloses instructions that, when executed.
[Claim Element 8:] by the one or more processors,
Excerpt: "the one or more processors are configured to execute instructions" ([0018])
Rationale: This discloses execution by the one or more processors.
[Claim Element 9:] cause the computing system to: when the vehicle is operating,
Excerpt: "The sensors 130 can be used to measure movement of the vehicle 200, such as direction, speed, acceleration, yaw..." ([0022]) and "based on... a defined number of miles driven" ([0031])
Rationale: The context of sensing vehicle movement and miles driven inherently and necessarily occurs when the vehicle is operating.
[Claim Element 10:] monitor the vehicle
Excerpt: "IMUs 132 in the vehicle 200 can be configured to detect a large jolt to the vehicle" ([0031])
Rationale: Monitor the vehicle is disclosed as detecting events like jolts.
[Claim Element 11:] using one or more sensors,
Excerpt: "various sensors" ([0022]) and "IMUs 132" ([0031])
Rationale: Using one or more sensors is disclosed.
[Claim Element 12:] for multiple types of sensor calibration triggers,
Excerpt: "The notifications or alerts can be issued periodically or at certain triggers, for example, based on a defined amount of time that has passed or a defined number of miles driven since the last calibration. Additionally, IMUs 132... can be configured to detect a large jolt to the vehicle..." ([0031])
Rationale: This discloses monitoring for multiple types of sensor calibration triggers.
[Claim Element 13:] each type of sensor calibration trigger
From the same excerpt, each trigger type is described.
Rationale: Each type of sensor calibration trigger is disclosed.
[Claim Element 14:] corresponding to an event or scenario
Excerpt: "based on a defined amount of time" (scenario), "defined number of miles" (scenario), "detect a large jolt" (event) ([0031])
Rationale: The triggers correspond to an event or scenario.
[Claim Element 15:] experienced by the vehicle
Excerpt: "jolt to the vehicle" ([0031])
Rationale: Experienced by the vehicle is disclosed.
[Claim Element 16:] and measured by the one or more sensors
Excerpt: "detect a large jolt" by IMUs ([0031])
Rationale: Measured by the one or more sensors is disclosed.
[Claim Element 17:] based on monitoring the vehicle,
Excerpt: "one or more sensors 130 that can capture data indicative of performance of the vehicle 200" ([0022])
Rationale: The system uses sensor data based on monitoring the vehicle to make determinations.
[Claim Element 18:] detect a sensor calibration trigger
Excerpt: "detect a large jolt" ([0031])
Rationale: Detect a sensor calibration trigger is disclosed.
[Claim Element 19:] of one of the multiple types of sensor calibration triggers;
From [0031], a jolt is one type among others (time, mileage).
Rationale: Of one of the multiple types is disclosed.
[Claim Element 20:] and in response to detecting the sensor calibration trigger,
Excerpt: "when the sensors 130 detect that the calibration object 300 occupies the footprint... the computing device 100 can be configured to begin the auto-calibration procedure automatically" ([0039])
Rationale: In response to detecting the sensor calibration trigger is disclosed. The claim's "sensor calibration trigger" is not limited to jolts/time/miles and includes object-presence detection as taught here.
[Claim Element 22:] one or more recalibration actions
Excerpt: "the auto-calibration procedure" ([0039])
Rationale: The auto-calibration procedure is a recalibration action.
[Claim Element 23:] for recalibrating one or more sensors of the vehicle
Excerpt: "Thus the calibration object 300 can be used to calibrate the sensors 130" ([0028])
Rationale: The procedure is for recalibrating one or more sensors of the vehicle.
[Claim Element 24:] that are affected by the detected sensor calibration trigger;
Excerpt: "a large jolt to the vehicle... that may have affected the alignment of the sensor 130." ([0031])
Rationale: Prokhorov explicitly links the trigger to sensors that are affected by the detected sensor calibration trigger.
[Claim Element 25:] and automatically perform at least one of the recalibration actions
Excerpt: "the computing device 100 can be configured to begin the auto-calibration procedure automatically" ([0039])
Rationale: Automatically perform at least one of the recalibration actions is disclosed.
[Claim Element 26:] to recalibrate one or more sensors of the vehicle
Excerpt: "to calibrate the sensors 130" ([0028])
Rationale: The purpose of the action is to recalibrate one or more sensors of the vehicle.
[Claim Element 27:] that are affected by the detected sensor calibration trigger.
Excerpt: "a large jolt to the vehicle... that may have affected the alignment of the sensor 130." ([0031])
Rationale: The sensors being recalibrated are those that are affected by the detected sensor calibration trigger.
II. Claim Elements Not Explicitly Disclosed by Prokhorov
Prokhorov does not explicitly disclose the following claim element:
[Claim Element 21:] identify, based on the type of the detected sensor calibration trigger, one or more recalibration actions
Prokhorov teaches a system that detects multiple types of triggers (time, mileage, jolt) and performs a single "auto-calibration procedure" in response. However, it lacks the specific logic of identifying or selecting different recalibration actions based on the type of trigger that was detected. All triggers lead to the same procedural response.
III. Disclosure by Wang
Wang provides teachings for the following missing element:
[Claim Element 21:] identify, based on the type of the detected sensor calibration trigger, one or more recalibration actions
Excerpt: "If the diagnostics service determines that sensor calibration values exceed an acceptable range... then the criticality level is classified as high." ([0063]) and "In some embodiments, the autonomous vehicle can recalibrate its sensors... Depending on how far the current calibration values deviate... a criticality... may be determined... The autonomous vehicle may then be dispatched to drive to the closest place to recalibrate its sensors... routed to a checked billboard... to recalibrate." ([0062])
Rationale: Wang discloses classifying detected issues by type ("criticality level") including specifically for sensor calibration values, and then identifying corresponding recalibration actions ("dispatched to drive to... recalibrate its sensors") based on that type. This teaches the missing logic of identify, based on the type of the detected sensor calibration trigger, one or more recalibration actions.
IV. Motivation to Combine Prokhorov and Wang
Therefore, given the teachings as a whole, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention, having Prokhorov and Wang before them, to modify Prokhorov's single-path auto-calibration flow by incorporating Wang's issue-type classification with automated action selection/dispatch so that recalibration actions are chosen based on the trigger type. Both references are in autonomous vehicle maintenance/operations; Prokhorov provides the foundation of calibration triggers and automatic calibration procedures ([0031], [0039]), while Wang provides the intelligent triage system that classifies issues by type and selects corresponding actions ([0062], [0063]). Wang's controller-level triage is a drop-in supervisory layer for Prokhorov's calibration routine, and yields predictable improvements in safety and uptime (e.g., treating an urgent "jolt" trigger as a high-criticality issue requiring immediate recalibration, while treating routine "mileage" or "time" triggers as lower-criticality issues suitable for deferred scheduling), a straightforward software configuration for a PHOSITA.
Regarding Claim 2,
The combination of Prokhorov and Wang establishes the computing system of Claim 1, which is the basis for Claim 2.
I. Disclosure by Prokhorov
Prokhorov discloses multiple types of sensor calibration triggers that form the basis for the claimed elements.
[Claim Element 2:] wherein each type of sensor calibration trigger
Excerpt: "The notifications or alerts can be issued periodically or at certain triggers, for example, based on a defined amount of time that has passed or a defined number of miles driven since the last calibration. Additionally, IMUs 132 in the vehicle 200 can be configured to detect a large jolt to the vehicle..." ([0031])
Rationale: Prokhorov expressly teaches each type of sensor calibration trigger through its explicit disclosure of time-based, mileage-based, and jolt-based triggers in a single, comprehensive description.
[Claim Element 3:] of multiple types of the set of sensor calibration triggers
Excerpt: "The notifications or alerts can be issued periodically or at certain triggers, for example, based on a defined amount of time that has passed or a defined number of miles driven since the last calibration. Additionally, IMUs 132 in the vehicle 200 can be configured to detect a large jolt to the vehicle..." ([0031])
Rationale: This discloses multiple types of the set of sensor calibration triggers by explicitly identifying and grouping time-based, mileage-based, and jolt-based triggers as members of the set of possible calibration triggers.
II. Claim Elements Not Explicitly Disclosed by Prokhorov
Prokhorov does not explicitly disclose the following claim element:
[Claim Element 4:] is associated with a corresponding severity level.
III. Disclosure by Wang
Wang provides teachings for the following missing element:
[Claim Element 4:] is associated with a corresponding severity level.
Excerpt: "In some embodiments, the system can determine the criticality of any detected issues (step 308)." ([0057])
Excerpt: "If the analysis of the diagnostics data determines that an issue is within a high criticality level (step 310), then the autonomous vehicle can come to a safe stop..." ([0058])
Excerpt: "If the analysis of the diagnostics data determines that an issue is within a medium criticality level (step 322), then the autonomous vehicle can finish its current operations..." ([0060])
Excerpt: "If the analysis of the diagnostics data determines that an issue is within a low criticality level (step 328), then a work order can be scheduled for the future..." ([0061])
Excerpt: "if the diagnostics service determines that sensor calibration values exceed an acceptable range... then the criticality level is also classified as high..." ([0063])
Rationale: Wang explicitly teaches that detected issues, including specific sensor calibration triggers, are associated with a corresponding severity level through its comprehensive criticality classification system (high, medium, low), where calibration value deviations and other issues are systematically mapped to specific criticality levels that correspond to severity levels.
IV. Motivation to Combine Prokhorov and Wang
Therefore, given the teachings as a whole, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention, having Prokhorov and Wang before them, to augment Prokhorov's multi-trigger calibration framework with Wang's comprehensive severity/criticality classification system so that each trigger type is mapped to a corresponding severity level. Both references address autonomous vehicle health/maintenance; Prokhorov supplies the specific trigger types (time/miles/jolt) while Wang supplies the severity mapping framework (criticality levels) for detected calibration issues. Wang's triage layer is a complementary, controller-level policy that yields predictable benefits (prioritized handling of urgent jolt-induced misalignment versus routine time/mileage triggers) without changing Prokhorov's calibration mechanics.
Regarding Claim 3,
The combination of Prokhorov and Wang establishes the computing system of Claim 1, which is the basis for Claim 3.
I. Disclosure by Prokhorov
Prokhorov discloses that the sensors for monitoring the vehicle include inertial measurement units (IMUs).
[Claim Element 2:] wherein the one or more sensors for monitoring the vehicle
Excerpt: "The sensors 130 can be used to measure movement of the vehicle 200, such as direction, speed, acceleration, yaw, etc." ([0022])
Rationale: This discloses that one or more sensors are used for monitoring the vehicle by measuring vehicle movement.
[Claim Element 3:] comprise one or more inertial measurement units (IMUs).
Excerpt: "Example sensors 130 can include accelerometers, gyroscopes, and/or magnetometers, one or more of which can be combined in an inertial measurement unit (IMU) 132." ([0022])
Rationale: This explicitly discloses that the sensors comprise one or more inertial measurement units (IMUs).
Regarding Claim 4,
The combination of Prokhorov and Wang establishes the computing system of Claim 1, which is the basis for Claim 4.
I. Disclosure by Prokhorov
Prokhorov discloses that the sensors of the vehicle include the specific sensor types recited in the claim.
[Claim Element 2:] wherein the one or more sensors of the vehicle
Excerpt: "The sensor signals are provided to an internal computing system in communication with the plurality of sensor systems" ([0015])
Rationale: This discloses one or more sensors of the vehicle that provide data to the computing system.
[Claim Element 3:] include any combination of one or more LIDAR sensors, one or more image sensors, one or more radar sensors, or one or more ultrasonic sensors.
Excerpt: "For example, the first sensor system 104 may be a camera sensor system and the Nth sensor system 106 may be a lidar sensor system. Other exemplary sensor systems include radar sensor systems, global positioning system (GPS) sensor systems, inertial measurement units (IMU), infrared sensor systems, laser sensor systems, sonar sensor systems, and the like." ([0022])
Excerpt: "Optical sensors 136 such as cameras can capture image data... Radar sensors 138 and/or lidar sensors 139... can help identify objects in the vicinity of the vehicle 200..." ([0022])
Rationale: This explicitly discloses that the vehicle's sensors include the specific types listed in the claim: LIDAR sensors ("lidar sensor system," "lidar sensors 139"), image sensors ("camera sensor system," "optical sensors 136 such as cameras"), radar sensors ("radar sensor systems," "radar sensors 138"), and ultrasonic sensors (included in "sonar sensor systems"). The disclosure of "any combination" of these sensors is inherent in teaching that autonomous vehicles utilize multiple different sensor types working together.
Regarding Claim 5,
The combination of Prokhorov and Wang establishes the computing system of Claim 4, which is the basis for Claim 5.
I. Disclosure by Prokhorov
Prokhorov discloses the one or more sensors for monitoring the vehicle.
[Claim Element 2:] wherein the one or more sensors for monitoring the vehicle
Excerpt: "The computing device 100 can also be in direct or indirect communication with one or more sensors 130 that can capture data indicative of performance of the vehicle 200... The sensors 130 can be used to measure movement of the vehicle 200, such as direction, speed, acceleration, yaw, etc." ([0022])
Rationale: This explicitly discloses one or more sensors for monitoring the vehicle by capturing data indicative of vehicle performance and movement.
II. Claim Elements Not Explicitly Disclosed by Prokhorov
Prokhorov does not explicitly disclose the following claim element:
[Claim Element 3:] are included in a sensor suite of the vehicle.
III. Disclosure by Wang
Wang provides teachings for the following missing element:
[Claim Element 3:] are included in a sensor suite of the vehicle.
Excerpt: "The autonomous vehicle 102 includes a plurality of sensor systems 104-106... The sensor systems 104-106 are of different types and are arranged about the autonomous vehicle 102." ([0022])
Excerpt: "Autonomous vehicle 202 can include a plurality of sensors 204 within multiple sensor systems including, but not limited to, a camera sensor system, a lidar sensor system, a radar sensor system, amongst others." ([0039])
Rationale: Wang discloses that sensors are organized into a sensor suite through its description of a "plurality of sensor systems" and "multiple sensor systems" arranged about the vehicle, which collectively constitute a sensor suite. Thus, the sensors are included in a sensor suite of the vehicle.
IV. Motivation to Combine Prokhorov and Wang
Therefore, given the teachings as a whole, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention, having Prokhorov and Wang before them, to incorporate Wang's explicit sensor suite architecture into Prokhorov's sensor monitoring system so that the one or more sensors for monitoring the vehicle are included in a sensor suite of the vehicle. Both references address autonomous vehicle sensing systems; Wang's teaching of multiple sensor systems arranged as a suite complements Prokhorov's sensor monitoring function, and integrating these teachings would yield predictable benefits in organizing and managing vehicle sensors for efficient operation.
Regarding Claim 6,
The combination of Prokhorov and Wang establishes the computing system of Claim 1, which is the basis for Claim 6.
I. Disclosure by Prokhorov
Prokhorov discloses that the multiple types of sensor calibration triggers comprise at least one of the specifically enumerated types, including a shock or vibration experienced by the vehicle.
[Claim Element 2:] wherein the multiple types of sensor calibration triggers
Excerpt: "The notifications or alerts can be issued periodically or at certain triggers, for example, based on a defined amount of time that has passed or a defined number of miles driven since the last calibration. Additionally, IMUs 132 in the vehicle 200 can be configured to detect a large jolt to the vehicle..." ([0031])
Rationale: This discloses multiple types of sensor calibration triggers, including time-based, mileage-based, and jolt-based triggers.
[Claim Element 3:] comprise at least one of: windshield breakage, windshield replacement, a shock or vibration experienced by the vehicle, an over-the-air update to software, a hardware upgrade, a hardware downgrade, a component adjustment, or a component replacement.
Excerpt: "IMUs 132 in the vehicle 200 can be configured to detect a large jolt to the vehicle (which may arise if the vehicle hits a severe bump or pothole)..." ([0031])
Rationale: A "large jolt to the vehicle" from a bump or pothole corresponds directly to a shock or vibration experienced by the vehicle, which is one of the enumerated types. Thus, the multiple types comprise at least one of the specified triggers.
Regarding Claim 8,
The combination of Prokhorov and Wang establishes the computing system of Claim 1, which is the basis for Claim 8.
I. Disclosure by Prokhorov
Prokhorov discloses that automatically performing recalibration actions includes performing intrinsic calibration to recalibrate sensors affected by the detected trigger.
[Claim Element 2:] wherein automatically performing at least one of the recalibration actions
Excerpt: "when the sensors 130 detect that the calibration object 300 occupies the footprint... the computing device 100 can be configured to begin the auto-calibration procedure automatically" ([0039])
Rationale: This explicitly teaches automatically performing at least one of the recalibration actions through automatic initiation of the calibration procedure.
[Claim Element 3:] to recalibrate one or more sensors of the vehicle
Excerpt: "Thus the calibration object 300 can be used to calibrate the sensors 130 such as the optical sensors 136..." ([0028])
Rationale: This discloses that the action is to recalibrate one or more sensors of the vehicle.
[Claim Element 4:] includes performing an intrinsic calibration
Excerpt: "The calibration object 300 can be an object of a known (a priori) geometry... Commonly, calibration objects may include a calibration pattern 310, such as a checkerboard pattern... One method... is described in Z. Zhang... which is hereby incorporated by reference." ([0028])
Rationale: The checkerboard/known-geometry calibration method described in Zhang is recognized by a person of ordinary skill in the art as canonical intrinsic calibration for estimating internal sensor parameters such as lens distortion and focal length, thus disclosing performing an intrinsic calibration.
[Claim Element 5:] to recalibrate the one or more sensors
Excerpt: "used to calibrate the sensors 130... the computing device 100 can be able to calibrate that sensor 130." ([0028])
Rationale: This confirms the purpose is to recalibrate the one or more sensors.
[Claim Element 6:] that are affected by the detected sensor calibration trigger
Excerpt: "IMUs 132... can be configured to detect a large jolt... (e.g., bump or pothole) that may have affected the alignment of the sensor 130." ([0031])
Rationale: This explicitly links the detected trigger (jolt) to sensors that are affected by the detected sensor calibration trigger.
Regarding Claim 9,
I. Disclosure by Prokhorov
Prokhorov discloses that the executed instructions cause the computing system to output a calibration alert on a display screen of the vehicle.
[Claim Element 2:] wherein the executed instructions
Excerpt: "the one or more processors are configured to execute instructions stored in the memory" ([0018])
Rationale: This discloses that the system operates through executed instructions.
[Claim Element 3:] cause the computing system to output a calibration alert,
Excerpt: "Users can be reminded to calibrate the sensors 130 using a notification or alert..." ([0031])
Rationale: This explicitly discloses that the system outputs a calibration alert in the form of a notification or alert.
[Claim Element 4:] either on a display screen of the vehicle or wirelessly transmitting the calibration alert to a display screen of a computing device of a user.
Excerpt: "The vehicle interfaces 118 can include, for example, one or more interactive displays, audio systems, voice recognition systems, buttons and/or dials..." ([0020])
Rationale: The interactive displays are part of the vehicle interfaces, allowing the calibration alert to be output on a display screen of the vehicle. Since the claim requires only one of the two options, this satisfies claim element 4.
Regarding Claim 10,
I. Disclosure by Prokhorov
Prokhorov discloses a non-transitory computer readable medium storing instruction for autonomous vehicle sensor calibration that covers most claim elements.
[Claim Element 1:] A non-transitory computer readable medium
Excerpt: "A memory 104 in the computing device 100 can be a random access memory device (RAM) or any other suitable type of storage device." ([0018])
Rationale: This discloses a non-transitory computer readable medium as memory is a storage device.
[Claim Element 2:] storing instructions
Excerpt: "a memory for storing data and program instructions" ([0018])
Rationale: This discloses storing instructions.
[Claim Element 3:] that, when executed
Excerpt: "the one or more processors are configured to execute instructions stored in the memory" ([0018])
Rationale: This discloses instructions that, when executed.
[Claim Element 4:] by one or more processors
Excerpt: "the one or more processors are configured to execute instructions" ([0018])
Rationale: This discloses execution by one or more processors.
[Claim Element 5:] of a computing system
Excerpt: "a computing device 100" ([0018])
Rationale: The computing device is a computing system.
[Claim Element 6:] of a vehicle,
Excerpt: "associated with a vehicle 200" ([0018])
Rationale: This discloses the computing system is of a vehicle.
[Claim Element 7:] cause the computing system to: when the vehicle is operating, monitor the vehicle
Excerpt: "The sensors 130 can be used to measure movement of the vehicle 200, such as direction, speed, acceleration, yaw, etc." ([0022]) and "based on... a defined number of miles driven" ([0031])
Rationale: This discloses causing the system to monitor the vehicle when the vehicle is operating.
[Claim Element 8:] using one or more sensors,
Excerpt: "various sensors" ([0022]) and "IMUs 132" ([0031])
Rationale: This discloses using one or more sensors.
[Claim Element 9:] for multiple types of sensor calibration triggers,
Excerpt: "The notifications or alerts can be issued periodically or at certain triggers, for example, based on a defined amount of time that has passed or a defined number of miles driven since the last calibration. Additionally, IMUs 132 in the vehicle 200 can be configured to detect a large jolt to the vehicle..." ([0031])
Rationale: This discloses monitoring for multiple types of sensor calibration triggers.
[Claim Element 10:] each type of sensor calibration trigger corresponding to an event or scenario experienced by the vehicle
Excerpt: "based on a defined amount of time" (scenario), "defined number of miles" (scenario), "detect a large jolt" (event) ([0031])
Rationale: Each trigger type corresponds to an event or scenario experienced by the vehicle.
[Claim Element 11:] and measured by the one or more sensors;
Excerpt: "detect a large jolt" by IMUs ([0031])
Rationale: The triggers are measured by the one or more sensors.
[Claim Element 12:] based on monitoring the vehicle,
This is inherent in the process of using sensor data to detect triggers.
Rationale: Actions are based on monitoring the vehicle.
[Claim Element 13:] detect a sensor calibration trigger
Excerpt: "detect a large jolt" ([0031])
Rationale: This discloses detect a sensor calibration trigger.
[Claim Element 14:] of one of the multiple types of calibration triggers;
From [0031], a jolt is one type among others (time, mileage).
Rationale: The detected trigger is of one of the multiple types of calibration triggers.
[Claim Element 17:] one or more recalibration actions
Excerpt: "the auto-calibration procedure" ([0039])
Rationale: This discloses one or more recalibration actions.
[Claim Element 18:] for recalibrating one or more sensors of the vehicle
Excerpt: "to calibrate the sensors 130" ([0028])
Rationale: This discloses that the action is for recalibrating one or more sensors of the vehicle.
[Claim Element 19:] that are affected by the detected sensor calibration trigger;
Excerpt: "a large jolt to the vehicle... that may have affected the alignment of the sensor 130." ([0031])
Rationale: This discloses that the sensors being recalibrated are that are affected by the detected sensor calibration trigger.
[Claim Element 20:] and automatically perform at least one of the recalibration actions
Excerpt: "the computing device 100 can be configured to begin the auto-calibration procedure automatically" ([0039])
Rationale: This discloses automatically perform at least one of the recalibration actions.
[Claim Element 21:] to recalibrate one or more sensors of the vehicle
Excerpt: "to calibrate the sensors 130" ([0028])
Rationale: This discloses to recalibrate one or more sensors of the vehicle.
[Claim Element 22:] that are affected by the detected sensor calibration trigger.
Excerpt: "a large jolt to the vehicle... that may have affected the alignment of the sensor 130." ([0031])
Rationale: This discloses that sensors are affected by the detected sensor calibration trigger.
II. Claim Elements Not Explicitly Disclosed by Prokhorov
Prokhorov does not explicitly disclose the following claim elements:
[Claim Element 15:] in response to detecting the sensor calibration trigger, identify,
[Claim Element 16:] based on the type of the detected sensor calibration trigger,
Prokhorov teaches performing an automatic calibration procedure in response to detecting triggers, but does not teach the specific logic of identifying recalibration actions based on the type of the detected trigger.
III. Disclosure by Wang
Wang provides teachings for the following missing elements:
[Claim Element 15:] in response to detecting the sensor calibration trigger, identify,
Excerpt: "analyze diagnostic data captured by one or more of its sensors. Based on the analysis of the diagnostic data, the autonomous vehicle can determine... if it needs, or will need, preventative or maintenance actions, and, based on that determination, send the analysis of the diagnostic data to a routing service." ([0019])
Rationale: This discloses analyzing data and in response to that analysis, identifying needed actions, which corresponds to in response to detecting the sensor calibration trigger, identify.
[Claim Element 16:] based on the type of the detected sensor calibration trigger,
Excerpt: "Diagnostics service 206 can also classify issues flagged by models into different criticality levels." ([0046]) and "if the diagnostics service determines that sensor calibration values exceed an acceptable range... then the criticality level is classified as high" ([0063])
Rationale: This discloses classifying detected issues based on their type (e.g., criticality levels), and explicitly applies this to sensor calibration scenarios, thus teaching based on the type of the detected sensor calibration trigger.
IV. Motivation to Combine Prokhorov and Wang
Therefore, given the teachings as a whole, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention, having Prokhorov and Wang before them, to incorporate Wang's diagnostic classification and action identification logic into Prokhorov's computer-readable medium-based calibration system to enable identification of recalibration actions based on the type of sensor calibration trigger. Both references address autonomous vehicle maintenance and sensor calibration; Prokhorov provides the foundation of multiple trigger types and automatic calibration procedures, while Wang provides the intelligent triage system that classifies issues by type and selects corresponding actions. It would be predictable that combining these teachings would result in a more efficient calibration system that responds appropriately to different trigger types based on their characteristics.
Regarding Claim 11,
The combination of Prokhorov and Wang establishes the non-transitory computer readable medium of Claim 10, which is the basis for Claim 11.
I. Disclosure by Prokhorov
Prokhorov discloses the multiple types of sensor calibration triggers but does not associate them with severity levels.
[Claim Element 2:] wherein each type of sensor calibration trigger
Excerpt: "IMUs 132 in the vehicle 200 can be configured to detect a large jolt to the vehicle..." ([0031])
Rationale: This discloses a specific type of sensor calibration trigger (jolt-based), supporting each type of sensor calibration trigger.
[Claim Element 3:] of the multiple types of sensor calibration triggers
Excerpt: "The notifications or alerts can be issued periodically or at certain triggers, for example, based on a defined amount of time that has passed or a defined number of miles driven since the last calibration. Additionally, IMUs 132 in the vehicle 200 can be configured to detect a large jolt to the vehicle..." ([0031])
Rationale: This explicitly lists multiple types of sensor calibration triggers (time-based, mileage-based, and jolt-based), satisfying of the multiple types of sensor calibration triggers.
II. Claim Elements Not Explicitly Disclosed by Prokhorov
Prokhorov does not explicitly disclose the following claim element:
[Claim Element 4:] is associated with a corresponding severity level.
III. Disclosure by Wang
Wang provides teachings for the following missing element:
[Claim Element 4:] is associated with a corresponding severity level.
Excerpt: "Diagnostics service 206 can also classify issues flagged by models into different criticality levels." ([0046])
Excerpt: "if the diagnostics service determines that sensor calibration values exceed an acceptable range... then the criticality level is classified as high..." ([0063])
Rationale: Wang discloses that detected issues are classified into criticality levels, which correspond to severity levels. A person of ordinary skill in the art would implement a policy mapping Prokhorov's trigger types (e.g., jolt, time, mileage) to Wang's criticality levels (e.g., jolt → high, time/mileage → lower), so that each type of sensor calibration trigger is associated with a corresponding severity level.
IV. Motivation to Combine Prokhorov and Wang
Therefore, given the teachings as a whole, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention, having Prokhorov and Wang before them, to augment Prokhorov's multi-trigger calibration framework with Wang's severity/criticality classification system so that each trigger type is associated with a corresponding severity level. Both references address autonomous vehicle health/maintenance; mapping trigger types to severity policies is a routine control configuration that yields predictable benefits in prioritizing and scheduling calibration actions based on trigger severity.
Regarding Claim 12,
The combination of Prokhorov and Wang establishes the non-transitory computer readable medium of Claim 10, which is the basis for Claim 12.
I. Disclosure by Prokhorov
Prokhorov discloses that the one or more sensors for monitoring the vehicle comprise one or more inertial measurement units (IMUs).
[Claim Element 2:] wherein the one or more sensors
Excerpt: "The computing device 100 can also be in direct or indirect communication with one or more sensors 130 that can capture data indicative of performance of the vehicle 200..." ([0022])
Rationale: This discloses one or more sensors that are used in the vehicle.
[Claim Element 3:] for monitoring the vehicle
Excerpt: "The sensors 130 can be used to measure movement of the vehicle 200, such as direction, speed, acceleration, yaw, etc." ([0022])
Rationale: This discloses that the sensors are for monitoring the vehicle by measuring vehicle movement and performance.
[Claim Element 4:] comprise one or more inertial measurement units (IMUs).
Excerpt: "Example sensors 130 can include accelerometers, gyroscopes, and/or magnetometers, one or more of which can be combined in an inertial measurement unit (IMU) 132." ([0022])
Rationale: This explicitly discloses that the sensors comprise one or more inertial measurement units (IMUs).
Regarding Claim 13,
The combination of Prokhorov and Wang establishes the non-transitory computer readable medium of Claim 10, which is the basis for Claim 13.
I. Disclosure by Prokhorov
Prokhorov discloses that the one or more sensors of the vehicle include several of the specific sensor types recited in the claim.
[Claim Element 2:] wherein the one or more sensors of the vehicle
Excerpt: "The computing device 100 can also be in direct or indirect communication with one or more sensors 130 that can capture data indicative of performance of the vehicle 200..." ([0022])
Rationale: This discloses one or more sensors of the vehicle that are in communication with the computing system.
[Claim Element 3:] include any combination of one or more LIDAR sensors, one or more image sensors, one or more radar sensors...
Excerpt: "Optical sensors 136 such as cameras can capture image data... Radar sensors 138 and/or lidar sensors 139 (using radio or light detection, respectively) can help identify objects in the vicinity of the vehicle 200..." ([0022])
Rationale: Prokhorov explicitly discloses that the vehicle's sensors include LIDAR sensors ("lidar sensors 139"), image sensors ("optical sensors 136 such as cameras"), and radar sensors ("radar sensors 138"). The disclosure of these multiple sensor types working together in an autonomous vehicle context supports any combination of these sensors.
II. Claim Elements Not Explicitly Disclosed by Prokhorov
Prokhorov does not explicitly disclose the following portion of claim element 3:
[Claim Element 3 (partial):] or one or more ultrasonic sensors
III. Disclosure by Wang
Wang provides teachings for the following missing element:
[Claim Element 3 (partial):] or one or more ultrasonic sensors
Excerpt: "Diagnostic data can include data received from (or about) various camera, lidar, radar and/or sonar sensors." ([0040])
Excerpt: "Autonomous vehicle 202 can include a plurality of sensors 204 within multiple sensor systems including, but not limited to, a camera sensor system, a lidar sensor system, a radar sensor system, amongst others." ([0039])
Rationale: Wang explicitly discloses "sonar sensors" as part of the vehicle's sensor systems. A person of ordinary skill in the art would recognize that sonar sensors utilize ultrasonic technology for object detection and ranging, thus teaching the inclusion of ultrasonic sensors. Wang's teaching of a "plurality of sensors" within "multiple sensor systems" further supports that these sensor types can be used in any combination.
IV. Motivation to Combine Prokhorov and Wang
Therefore, given the teachings as a whole, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention, having Prokhorov and Wang before them, to incorporate Wang's teaching of sonar/ultrasonic sensors into Prokhorov's multi-sensor autonomous vehicle framework to create a comprehensive sensor suite that includes ultrasonic sensors alongside LIDAR, image, and radar sensors. Both references address autonomous vehicle sensing systems; Wang's disclosure of sonar systems complements Prokhorov's sensor types, and it would be predictable that including ultrasonic sensing capabilities would enhance the vehicle's object detection and environmental awareness, particularly for close-range applications and in various environmental conditions.
Regarding Claim 14,
The combination of Prokhorov and Wang establishes the non-transitory computer readable medium of Claim 13, which is the basis for Claim 14.
I. Disclosure by Prokhorov
Prokhorov discloses that the one or more sensors for monitoring the vehicle are included in a sensor suite of the vehicle.
[Claim Element 2:] wherein the one or more sensors for monitoring the vehicle are included in a sensor suite of the vehicle.
Excerpt: "The computing device 100 can also be in direct or indirect communication with one or more sensors 130 that can capture data indicative of performance of the vehicle 200... Example sensors 130 can include accelerometers, gyroscopes, and/or magnetometers, one or more of which can be combined in an inertial measurement unit (IMU) 132. Location sensors 134... Optical sensors 136 such as cameras... Radar sensors 138 and/or lidar sensors 139..." ([0022])
Rationale: Prokhorov explicitly discloses a plurality of different sensor types (IMU, location sensors, optical sensors, radar sensors, lidar sensors) that collectively constitute a sensor suite. The one or more sensors for monitoring the vehicle are therefore included in a sensor suite of the vehicle.
Regarding Claim 15,
The combination of Prokhorov and Wang establishes the non-transitory computer readable medium of Claim 10, which is the basis for Claim 15.
I. Disclosure by Prokhorov
Prokhorov discloses that the multiple types of sensor calibration triggers comprise at least one of the specifically enumerated types, including a shock or vibration experienced by the vehicle.
[Claim Element 2:] wherein the multiple types of sensors calibration triggers
Excerpt: "The notifications or alerts can be issued periodically or at certain triggers, for example, based on a defined amount of time that has passed or a defined number of miles driven since the last calibration. Additionally, IMUs 132 in the vehicle 200 can be configured to detect a large jolt to the vehicle..." ([0031])
Rationale: This discloses multiple types of sensors calibration triggers, including time-based, mileage-based, and jolt-based triggers.
[Claim Element 3:] comprise: at least one of: windshield breakage, windshield replacement, a shock or vibration experienced by the vehicle, an over-the-air update to software, a hardware upgrade, a hardware downgrade, a component adjustment, or a component replacement.
Excerpt: "IMUs 132 in the vehicle 200 can be configured to detect a large jolt to the vehicle (which may arise if the vehicle hits a severe bump or pothole)..." ([0031])
Rationale: A "large jolt to the vehicle" from a bump or pothole corresponds directly to a shock or vibration experienced by the vehicle, which is one of the enumerated types. Thus, the multiple types comprise at least one of the specified triggers.
Regarding Claim 17,
The combination of Prokhorov and Wang establishes the non-transitory computer readable medium of Claim 10, which is the basis for Claim 17.
I. Disclosure by Prokhorov
Prokhorov discloses that automatically performing recalibration actions includes performing intrinsic calibration to recalibrate sensors affected by the detected trigger.
[Claim Element 2:] wherein automatically performing at least one of the recalibration actions
Excerpt: "when the sensors 130 detect that the calibration object 300 occupies the footprint... the computing device 100 can be configured to begin the auto-calibration procedure automatically" ([0039])
Rationale: This explicitly teaches automatically performing at least one of the recalibration actions through automatic initiation of the calibration procedure.
[Claim Element 3:] to recalibrate one or more sensors of the vehicle
Excerpt: "Thus the calibration object 300 can be used to calibrate the sensors 130 such as the optical sensors 136..." ([0028])
Rationale: This discloses that the action is to recalibrate one or more sensors of the vehicle.
[Claim Element 4:] includes performing an intrinsic calibration
Excerpt: "The calibration object 300 can be an object of a known (a priori) geometry... Commonly, calibration objects may include a calibration pattern 310, such as a checkerboard pattern... One method... is described in Z. Zhang... which is hereby incorporated by reference." ([0028])
Rationale: The checkerboard/known-geometry calibration method described in Zhang is recognized by a person of ordinary skill in the art as canonical intrinsic calibration for estimating internal sensor parameters such as lens distortion and focal length, thus disclosing performing an intrinsic calibration.
[Claim Element 5:] to recalibrate the one or more sensors
Excerpt: "used to calibrate the sensors 130... the computing device 100 can be able to calibrate that sensor 130." ([0028])
Rationale: This confirms the purpose is to recalibrate the one or more sensors.
[Claim Element 6:] that are affected by the detected sensor calibration trigger
Excerpt: "IMUs 132... can be configured to detect a large jolt... (e.g., bump or pothole) that may have affected the alignment of the sensor 130." ([0031])
Rationale: This explicitly links the detected trigger (jolt) to sensors that are affected by the detected sensor calibration trigger.
Regarding Claim 18,
The combination of Prokhorov and Wang establishes the non-transitory computer readable medium of Claim 10, which is the basis for Claim 18.
I. Disclosure by Prokhorov
Prokhorov discloses that the executed instructions cause the computing system to output a calibration alert on a display screen of the vehicle.
[Claim Element 2:] wherein the executed instructions
Excerpt: "the one or more processors are configured to execute instructions stored in the memory" ([0018])
Rationale: This discloses that the system operates through executed instructions.
[Claim Element 3:] cause the computing system to output a calibration alert,
Excerpt: "Users can be reminded to calibrate the sensors 130 using a notification or alert..." ([0031])
Rationale: This explicitly discloses that the system outputs a calibration alert in the form of a notification or alert.
[Claim Element 4:] either on a display screen of the vehicle or wirelessly transmitting the calibration alert to a display screen of a computing device of a user.
Excerpt: "The vehicle interfaces 118 can include, for example, one or more interactive displays, audio systems, voice recognition systems, buttons and/or dials..." ([0020])
Rationale: The interactive displays are part of the vehicle interfaces, allowing the calibration alert to be output on a display screen of the vehicle. Since the claim requires only one of the two options, this satisfies claim element 4.
Regarding Claim 19,
I. Disclosure by Prokhorov
Prokhorov discloses a computer-implemented method for monitoring a vehicle for sensor recalibration that covers most claim elements.
[Claim Element 1:] A computer-implemented method
Excerpt: "Disclosed herein are systems and methods for calibrating sensors for an autonomous vehicle." ([0004])
Rationale: Prokhorov explicitly discloses a computer-implemented method for sensor calibration.
[Claim Element 2:] for monitoring a vehicle
Excerpt: "The sensors 130 can be used to measure movement of the vehicle 200, such as direction, speed, acceleration, yaw, etc." ([0022])
Rationale: This discloses that the method is for monitoring a vehicle by measuring its movement and performance.
[Claim Element 3:] for sensor recalibration,
Excerpt: "Thus the calibration object 300 can be used to calibrate the sensors 130" ([0028])
Rationale: This discloses that the method is for sensor recalibration, as calibration involves recalibration.
[Claim Element 4:] the method being performed by one or more processors of the vehicle
Excerpt: "a computing device 100 associated with a vehicle 200... comprising: one or more processors for controlling operations of the computing device" ([0018])
Rationale: This discloses that the method is performed by one or more processors of the vehicle, as the computing device with processors is associated with the vehicle.
[Claim Element 5:] and comprising: when the vehicle is operating,
Excerpt: "The sensors 130 can be used to measure movement of the vehicle 200, such as direction, speed, acceleration, yaw, etc." ([0022]) and "based on... a defined number of miles driven since the last calibration" ([0031])
Rationale: Measuring vehicle movement and miles driven inherently occurs when the vehicle is operating.
[Claim Element 6:] monitoring the vehicle using one or more sensors,
Excerpt: "The computing device 100 can also be in direct or indirect communication with one or more sensors 130 that can capture data indicative of performance of the vehicle 200" ([0022])
Rationale: This discloses monitoring the vehicle using one or more sensors.
[Claim Element 7:] for multiple types of sensor calibration triggers,
Excerpt: "The notifications or alerts can be issued periodically or at certain triggers, for example, based on a defined amount of time that has passed or a defined number of miles driven since the last calibration. Additionally, IMUs 132 in the vehicle 200 can be configured to detect a large jolt to the vehicle..." ([0031])
Rationale: This discloses monitoring for multiple types of sensor calibration triggers (time-based, mileage-based, and jolt-based).
[Claim Element 8:] each type of sensor calibration trigger corresponding to an event or scenario experienced by the vehicle
Excerpt: "based on a defined amount of time" (scenario), "defined number of miles" (scenario), "detect a large jolt" (event) ([0031])
Rationale: Each trigger type corresponds to an event or scenario experienced by the vehicle.
[Claim Element 9:] and measured by the one or more sensors;
Excerpt: "detect a large jolt" by IMUs ([0031])
Rationale: The triggers are measured by the one or more sensors.
[Claim Element 10:] based on monitoring the vehicle,
Excerpt: "The computing device 100 can also be in direct or indirect communication with one or more sensors 130 that can capture data indicative of performance of the vehicle 200" ([0022]) leading to "detect a large jolt" ([0031]) and subsequent automatic calibration ([0039])
Rationale: The detection and response are based on monitoring the vehicle through the continuous sensor data capture described.
[Claim Element 11:] detecting a sensor calibration trigger
Excerpt: "detect a large jolt" ([0031])
Rationale: This discloses detecting a sensor calibration trigger.
[Claim Element 12:] of one of the multiple types of sensor calibration triggers;
From [0031], a jolt is one type among others (time, mileage).
Rationale: The detected trigger is of one of the multiple types of sensor calibration triggers.
[Claim Element 13:] in response to detecting the sensor calibration trigger,
Excerpt: "when the sensors 130 detect that the calibration object 300 occupies the footprint... the computing device 100 can be configured to begin the auto-calibration procedure automatically" ([0039])
Rationale: This discloses taking action in response to detecting the sensor calibration trigger.
[Claim Element 15:] for recalibrating one or more sensors of the vehicle
Excerpt: "to calibrate the sensors 130" ([0028])
Rationale: This discloses that the actions are for recalibrating one or more sensors of the vehicle.
[Claim Element 16:] that are affected by the detected sensor calibration trigger;
Excerpt: "a large jolt to the vehicle... that may have affected the alignment of the sensor 130." ([0031])
Rationale: This discloses that the sensors are affected by the detected sensor calibration trigger.
[Claim Element 17:] and automatically perform at least one of the recalibration actions
Excerpt: "the computing device 100 can be configured to begin the auto-calibration procedure automatically" ([0039])
Rationale: This discloses automatically perform at least one of the recalibration actions.
[Claim Element 18:] to recalibrate one or more sensors of the vehicle
Excerpt: "to calibrate the sensors 130" ([0028])
Rationale: This discloses to recalibrate one or more sensors of the vehicle.
[Claim Element 19:] that are affected by the detected sensor calibration trigger.
Excerpt: "a large jolt to the vehicle... that may have affected the alignment of the sensor 130." ([0031])
Rationale: This discloses that the sensors are affected by the detected sensor calibration trigger.
[Claim Element 20:] automatically perform a recalibration action
Excerpt: "the computing device 100 can be configured to begin the auto-calibration procedure automatically" ([0039])
Rationale: This discloses automatically perform a recalibration action.
[Claim Element 21:] to recalibrate one or more sensors of the vehicle
Excerpt: "to calibrate the sensors 130" ([0028])
Rationale: This discloses to recalibrate one or more sensors of the vehicle.
[Claim Element 22:] that are affected by the detected sensor calibration trigger.
Excerpt: "a large jolt to the vehicle... that may have affected the alignment of the sensor 130." ([0031])
Rationale: This discloses that the sensors are affected by the detected sensor calibration trigger.
II. Claim Elements Not Explicitly Disclosed by Prokhorov
Prokhorov does not explicitly disclose the following claim element:
[Claim Element 14:] identifying, based on the type of the detected sensor calibration trigger, one or more recalibration actions
Prokhorov teaches automatic calibration in response to triggers but does not teach identifying recalibration actions based on the type of trigger detected; it uses a single calibration procedure for all triggers.
III. Disclosure by Wang
Wang provides teachings for the following missing element:
[Claim Element 14:] identifying, based on the type of the detected sensor calibration trigger, one or more recalibration actions
Excerpt: "Diagnostics service 206 can also classify issues flagged by models into different criticality levels." ([0046])
Excerpt: "if the diagnostics service determines that sensor calibration values exceed an acceptable range... then the criticality level is classified as high..." ([0063])
Excerpt: "The autonomous vehicle may then be dispatched to drive to the closest place to recalibrate its sensors." ([0062])
Rationale: Wang discloses classifying detected issues by type (e.g., criticality levels) and explicitly applies this to sensor calibration scenarios, then identifies specific recalibration actions (e.g., "dispatched to recalibrate") based on that type. This teaches identifying, based on the type of the detected sensor calibration trigger, one or more recalibration actions.
IV. Motivation to Combine Prokhorov and Wang
Therefore, given the teachings as a whole, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention, having Prokhorov and Wang before them, to incorporate Wang's diagnostic classification and action identification logic into Prokhorov's method for sensor recalibration to enable identifying recalibration actions based on the type of sensor calibration trigger detected. Both references address autonomous vehicle maintenance and sensor calibration; Prokhorov provides the foundation of multiple trigger types and automatic calibration procedures, while Wang provides the intelligent triage system that classifies issues by type and selects corresponding actions. It would be predictable that combining these teachings would result in a more efficient method that responds appropriately to different trigger types based on their characteristics, improving vehicle safety and maintenance efficiency.
Regarding Claim 20,
The combination of Prokhorov and Wang establishes the method of Claim 19, which is the basis for Claim 20.
I. Disclosure by Prokhorov
Prokhorov discloses the multiple types of sensor calibration triggers but does not associate them with severity levels.
[Claim Element 2:] wherein each type of sensor calibration trigger
Excerpt: "The notifications or alerts can be issued periodically or at certain triggers, for example, based on a defined amount of time that has passed or a defined number of miles driven since the last calibration. Additionally, IMUs 132 in the vehicle 200 can be configured to detect a large jolt to the vehicle..." ([0031])
Rationale: Prokhorov discloses each type of sensor calibration trigger through its explicit description of time-based, mileage-based, and jolt-based triggers.
[Claim Element 3:] of the multiple types of sensor calibration triggers
Excerpt: "The notifications or alerts can be issued periodically or at certain triggers, for example, based on a defined amount of time that has passed or a defined number of miles driven since the last calibration. Additionally, IMUs 132 in the vehicle 200 can be configured to detect a large jolt to the vehicle..." ([0031])
Rationale: This discloses multiple types of sensor calibration triggers by identifying time-based, mileage-based, and jolt-based triggers as part of the set.
II. Claim Elements Not Explicitly Disclosed by Prokhorov
Prokhorov does not explicitly disclose the following claim element:
[Claim Element 4:] is associated with a corresponding severity level.
III. Disclosure by Wang
Wang provides teachings for the following missing element:
[Claim Element 4:] is associated with a corresponding severity level.
Excerpt: "Diagnostics service 206 can also classify issues flagged by models into different criticality levels." ([0046])
Excerpt: "if the diagnostics service determines that sensor calibration values exceed an acceptable range... then the criticality level is classified as high..." ([0063])
Rationale: Wang discloses that detected issues, including sensor calibration triggers, are associated with a corresponding severity level through its criticality classification system (e.g., high, medium, low), where criticality levels directly correspond to severity levels.
IV. Motivation to Combine Prokhorov and Wang
Therefore, given the teachings as a whole, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention, having Prokhorov and Wang before them, to augment Prokhorov's multi-trigger calibration framework with Wang's severity/criticality classification system so that each trigger type is associated with a corresponding severity level. Both references address autonomous vehicle maintenance and sensor calibration; Wang's teaching of classifying issues by severity (criticality) provides a predictable way to prioritize and handle different types of calibration triggers based on their potential impact on vehicle safety and operation, enhancing the efficiency of the method described in Prokhorov.
Response to Arguments
Applicant's arguments filed 09/05/2025 have been fully considered.
§112(b) – Disposition (Claims 5 and 14)
Applicant’s position: Applicant asserts that the prior §112(b) indefiniteness rejections are moot in view of amendments to Claims 5 and 14.
Examiner’s determination:Upon review of the amended claims of record, both claims now particularly point out and distinctly claim the subject matter.
Claim 5 — §112(b) WITHDRAWN. The amendment clarifies the sensors’ inclusion in a sensor suite of the vehicle, resolving the prior clarity concern.
Claim 14 — §112(b) WITHDRAWN. The claim likewise recites that the sensors are included in a sensor suite of the vehicle, which cures the previously identified grammatical/antecedent issues.
Conclusion: The §112(b) rejections of Claims 5 and 14 are withdrawn.
§101 – Examiner Analysis and Disposition
As amended, the claims are not directed to a judicial exception under the 2019 PEG because any data-monitoring aspects are integrated into a practical application: the system identifies trigger-type-specific recalibration actions and automatically performs them to recalibrate physical vehicle sensors during operation. See independent Claim 1 (system) , Claim 10 (CRM) , and Claim 19 (method) . Accordingly, the §101 rejection of claims 1–20 is withdrawn.
Detailed Alice/PEG Analysis
Step 1 — Statutory Category
Claim 1: machine/system (“A computing system for a vehicle… processors; memory…”)
Claim 10: manufacture (non-transitory computer-readable medium)
Claim 19: process (computer-implemented method) All fall within statutory categories.
Step 2A, Prong One — Judicial Exception?
The claims include monitoring and detecting events (data observation), which alone can resemble abstract ideas. But each independent claim proceeds beyond observation to (i) identify recalibration actions based on the type of detected trigger and (ii) automatically perform at least one such action to recalibrate sensors affected by that trigger (changing the state of physical hardware).
Claim 1: identify and automatically perform recalibration actions to recalibrate affected sensors.
Claim 10: same operations recited on the medium.
Claim 19: same operations in method form.
Step 2A, Prong Two — Integration into a Practical Application
The amended claims are tied to a particular technological environment—a vehicle with a sensor suite (e.g., IMU, LiDAR, image, radar, ultrasonic) —and recite concrete control over hardware: automatic performance of trigger-type-specific recalibration actions that recalibrate physical sensors during vehicle operation.
“When the vehicle is operating, monitor … detect … identify (based on trigger type) … automatically perform recalibration actions … to recalibrate sensors affected by the trigger.” (Claim 1)
Same for CRM (Claim 10) and Method (Claim 19) .
Dependents reinforce concrete vehicle scenarios (windshield replacement; shocks/vibration; OTA update; hardware changes) and intrinsic calibration as an example of the recalibration action itself (Claims 8/17).
Finding: The claims are integrated into a practical application that improves sensor calibration/maintenance in vehicles by automating the recalibration of affected physical sensors in response to concrete, trigger-type-specific events detected during operation. Under the 2019 PEG, they are not “directed to” an abstract idea.
Step 2B — “Significantly More” (Alternative)
Because Prong Two is satisfied, Step 2B need not be reached. If reached, the ordered combination (monitor during operation → detect trigger → identify type-specific actions → automatically perform recalibration to change sensor state) as claimed would amount to more than well-understood, routine, conventional post-solution activity on this record—especially with intrinsic calibration recited (e.g., Claims 8/17).
Response to Applicant’s Authorities
Enfish (improvement to computer functionality): The claims here likewise recite a technology-focused solution—automatic, trigger-type-specific recalibration of vehicle sensors—that improves operation of a technical system (the vehicle’s perception stack), not a result confined to data display. The amendments transformed prior “alert-only” claim outcomes into hardware-affecting control. Compare pre-amendment (alert to user) with amended (automatic recalibration).
BASCOM (inventive concept in ordered combination): Even if Step 2B were necessary, the claimed sequence and constraint (trigger-type-specific automatic recalibration of affected sensors) would be considered as a whole. On this record, applicant’s position is consistent with allowance: the claims do not merely collect/evaluate information, but actuate recalibration of physical sensors in a specific technological context.
Disposition
§101: In view of the amendments and analysis above, the §101 rejection of claims 1–20 is withdrawn. The amended claims are §101-eligible under the 2019 PEG.
§112(b) – Disposition (Claims 5 and 14)
Applicant’s position: Applicant asserts that the prior §112(b) indefiniteness rejections are moot in view of amendments to Claims 5 and 14.
Examiner’s determination:Upon review of the amended claims of record, both claims now particularly point out and distinctly claim the subject matter.
Claim 5 — §112(b) WITHDRAWN. The amendment clarifies the sensors’ inclusion in a sensor suite of the vehicle, resolving the prior clarity concern.
Claim 14 — §112(b) WITHDRAWN. The claim likewise recites that the sensors are included in a sensor suite of the vehicle, which cures the previously identified grammatical/antecedent issues.
Result: The §112(b) rejections of Claims 5 and 14 are withdrawn. No further §112(b) issues are noted for these claims on the present record.
Status of Prior Rejections
Withdrawal of §102:
The §102(a)(1) anticipation rejection previously applied to certain claims is withdrawn. In view of applicant’s amendments (e.g., reciting type-based identification of recalibration actions and automatic performance), the Office no longer relies on Prokhorov alone for anticipation.
New Ground of Rejection – §103 (Art on Record)
Claims at issue: All pending claims as identified in the Final Rejection.Ground: 35 U.S.C. §103 as obvious over Prokhorov in view of Wang.
Core Finding for the Independent Claims (System/CRM/Method)
What Prokhorov teaches: (i) monitoring via on-vehicle sensors and multiple calibration-related triggers (e.g., time, mileage, IMU-detected jolt); (ii) detecting such triggers based on sensor monitoring; and (iii) automatically beginning an auto-calibration procedure when conditions are met.
What Prokhorov does not expressly teach: The amended limitation to “identify, based on the type of the detected sensor-calibration trigger, one or more recalibration actions.”
What Wang supplies (the missing piece): Wang discloses a diagnostics service that classifies issues into criticality/severity levels and selects/dispatches corresponding actions, expressly including sensor-calibration deviations. This supplies the type/criticality-based action selection absent from Prokhorov alone.
KSR rationale (of record): A PHOSITA would have been motivated to incorporate Wang’s classification and action-selection logic into Prokhorov’s auto-calibration flow so that recalibration actions are chosen based on the trigger type/criticality, yielding predictable safety/uptime benefits for autonomous/semi-autonomous vehicles. See articulated motivation.
Result: In view of the amendments (monitor → detect → identify action based on type → automatically perform), the claims are now obvious over Prokhorov × Wang rather than anticipated.
Representative Mapping Pointers (by claim category)
Claim 1 (system) / Claim 10 (CRM) / Claim 19 (method): Prokhorov: multiple triggers + detection + auto-calibration. Wang: type/criticality-based selection of remedial/recalibration actions. Combination meets “identify, based on the type, one or more recalibration actions” and “automatically perform” as amended.
Severity/criticality (e.g., Claim 2 / 11 / 20): Prokhorov: multiple trigger types. Wang: criticality levels (high/medium/low) mapped to actions/dispatch → obvious to associate each type with a corresponding severity level and handle accordingly.
Intrinsic calibration (e.g., Claim 8 / 17): Prokhorov’s auto-calibration; Wang’s diagnostics signals when calibration values are out of range and triggers actions → obvious to perform intrinsic calibration for such triggers.
Sensor suite / sensor modalities (e.g., Claim 5 / 14):Prokhorov discloses a plurality of sensor types (IMU, cameras, radar, lidar) constituting a sensor suite.
Response to Applicant’s Position
“Prokhorov only guides a user; no automatic performance.”The record cites automatic initiation (“begin the auto-calibration procedure automatically”), which maps to “automatically perform at least one recalibration action.”
“No monitoring for multiple types / no detection based on monitoring.”Prokhorov expressly discloses time, mileage, and IMU-jolt triggers detected from sensor monitoring—i.e., multiple types and detection based on monitoring.
“No identification based on trigger type; Wang does not cure it.”Wang does cure it: diagnostics classify issue type/criticality and select/dispatch the corresponding action, supplying the amended type-based action-selection requirement. The KSR motivation to combine is explicitly of record.
Conclusion
The Office withdraws §102 in light of applicant’s amendments.
The claims are now rejected under §103 as obvious over Prokhorov in view of Wang, per the element-by-element mappings and KSR rationale already of record.
Conclusion
THIS ACTION IS MADE FINAL. 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.
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/OLUWABUSAYO ADEBANJO AWORUNSE/Examiner, Art Unit 3662
/JELANI A SMITH/Supervisory Patent Examiner, Art Unit 3662
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