DETAILED ACTION
This action is in response to the submission filed on 7/14/2026. Claims 18-35 are presented for examination.
Notice of Pre-AIA or AIA Status
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
Response to Arguments- 35 USC § 112
Applicant's arguments filed 7/14/2026 have been fully considered but they are not persuasive.
Applicant argues on pages 11-13 that structure is described in the specification for performing the claimed functions of “a sensor detection unit”, “a state determining unit”, “a data communications unit”, and a “motion control unit” in claim 25 and “a 3D rendering unit” in claim 31. Applicant then quotes from the disclosure that the units are "implemented by software, hardware (e.g., an integrated circuit, a FPGA, or the like) OR a combination of software and hardware" which is confirmation that the claimed units can be performed by software only.
At best, pages 25-26 of the instant application discloses a generic environment in which the invention can be carried out (“In general, various exemplary embodiments of the present disclosure can be implemented in hardware or a dedicated circuit, software, firmware, logic, or any combination thereof. Some aspects can be implemented in hardware, while other aspects can be implemented in firmware or software executable by a controller, a microprocessor, or other computing devices”). However, there is no recitation on which actual elements or structure perform the sensor detection, state determining, data communications, motion control or the 3D rendering.
The rejection is maintained.
Response to Arguments- 35 USC § 102/103
Applicant's arguments filed 7/14/2026 have been fully considered but they are not persuasive.
Argument 1:
Applicant argues from pages 14-18 that Laws does not teach “obtaining sensor data of a virtual AGV in an emulation environment”.
Applicant is directed towards paragraph [0013] of Laws, “FIG. 4 is a functional block diagram of a system for virtualizing a forklift to emulate hardware component operations” and paragraph [0034] which recites “ the sensor array 108 may combine multiple laser scans into a single virtual laser scan, which may be used by various software modules to control the forklift 200”, paragraph [0025] recites “the vehicle 102 may be an automated guided vehicle (AGV), such as an automated forklift” and paragraph [0038], “FIG. 3 is a block diagram of a system 300 for virtualizing industrial vehicles to automate task execution in a physical environment according to one or more embodiments. As explained further below, the industrial vehicles are virtualized or modeled as a logical configuration of various vehicle capabilities and vehicle characteristics. In some embodiments, the system 300 includes the mobile computer 104, the central computer 106, the sensor array 108 and vehicle hardware components 334 in which each is coupled to each other through a network 302”. Clearly, the virtual laser scan is a part of the sensor array 108, which obtains sensor data of the virtual industrial vehicle in an emulated environment. The rejection is maintained.
Argument 2:
Applicant argues from pages 18-21 that Laws does not teach “determining a device state of a virtual device interacting with the virtual AGV in the emulation environment”.
As shown above in at least paragraphs [0013] and [0038], the virtual AGV interacts in an emulated environment. Figure 1 of Laws depicts the environment that is to be emulated, in which the AGV interacts with various devices. Paragraph [0066] recites that sensors “detect obstructions and generate a map illustrating each and every obstruction in an industrial environment. The obstruction map may be used by any vehicles for path planning”. Paragraph [0032] recites “the sensor array 108 includes various devices, such as a laser scanner and a camera, for capturing the sensor array data associated with objects within a physical environment, such as the position of actuators, obstructions, pallets and/or the like”. Therefore, the sensory array 108 (which is combined in a single virtual scan as shown in paragraph [0034] above) determines the state of virtual devices such as obstructions and pallets that interact with the virtual AGV in the emulated environment. The rejection is maintained.
All other arguments depend upon previous arguments. The rejections are maintained.
Claim Interpretation
The following is a quotation of 35 U.S.C. 112(f):
(f) Element in Claim for a Combination. – An element in a claim for a combination may be expressed as a means or step for performing a specified function without the recital of structure, material, or acts in support thereof, and such claim shall be construed to cover the corresponding structure, material, or acts described in the specification and equivalents thereof.
The following is a quotation of pre-AIA 35 U.S.C. 112, sixth paragraph:
An element in a claim for a combination may be expressed as a means or step for performing a specified function without the recital of structure, material, or acts in support thereof, and such claim shall be construed to cover the corresponding structure, material, or acts described in the specification and equivalents thereof.
The claims in this application are given their broadest reasonable interpretation using the plain meaning of the claim language in light of the specification as it would be understood by one of ordinary skill in the art. The broadest reasonable interpretation of a claim element (also commonly referred to as a claim limitation) is limited by the description in the specification when 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, is invoked.
As explained in MPEP § 2181, subsection I, claim limitations that meet the following three-prong test will be interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph:
(A) the claim limitation uses the term “means” or “step” or a term used as a substitute for “means” that is a generic placeholder (also called a nonce term or a non-structural term having no specific structural meaning) for performing the claimed function;
(B) the term “means” or “step” or the generic placeholder is modified by functional language, typically, but not always linked by the transition word “for” (e.g., “means for”) or another linking word or phrase, such as “configured to” or “so that”; and
(C) the term “means” or “step” or the generic placeholder is not modified by sufficient structure, material, or acts for performing the claimed function.
Use of the word “means” (or “step”) in a claim with functional language creates a rebuttable presumption that the claim limitation is to be treated in accordance with 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph. The presumption that the claim limitation is interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, is rebutted when the claim limitation recites sufficient structure, material, or acts to entirely perform the recited function.
Absence of the word “means” (or “step”) in a claim creates a rebuttable presumption that the claim limitation is not to be treated in accordance with 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph. The presumption that the claim limitation is not interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, is rebutted when the claim limitation recites function without reciting sufficient structure, material or acts to entirely perform the recited function.
Claim limitations in this application that use the word “means” (or “step”) are being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, except as otherwise indicated in an Office action. Conversely, claim limitations in this application that do not use the word “means” (or “step”) are not being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, except as otherwise indicated in an Office action.
This application includes one or more claim limitations that do not use the word “means,” but are nonetheless being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, because the claim limitation(s) uses a generic placeholder that is coupled with functional language without reciting sufficient structure to perform the recited function and the generic placeholder is not preceded by a structural modifier. Such claim limitations) is/are: “a sensor detection unit”, “a state determining unit”, “a data communications unit”, and a “motion control unit” in claim 25 and “a 3D rendering unit” in claim 31.
Because this/these claim limitation(s) is/are being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, it/they is/are being interpreted to cover the corresponding structure described in the specification as performing the claimed function, and equivalents thereof; however there is no corresponding structure for performing the claimed functions.
If applicant does not intend to have this/these limitation(s) interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, applicant may: (1) amend the claim limitation(s) to avoid it/them being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph (e.g., by reciting sufficient structure to perform the claimed function); or (2) present a sufficient showing that the claim limitation(s) recite(s) sufficient structure to perform the claimed function so as to avoid it/them being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph.
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.
The following is a quotation of 35 U.S.C. 112 (pre-AIA ), second paragraph:
The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the applicant regards as his invention.
Claims 25-31 are rejected under 35 U.S.C. 112(b) or 35 U.S.C. 112 (pre-AIA ), second paragraph, as being indefinite for failing to particularly point out and distinctly claim the subject matter which the inventor or a joint inventor (or for applications subject to pre-AIA 35 U.S.C. 112, the applicant), regards as the invention.
This application includes one or more claim limitations that do not use the word “means,” but are nonetheless being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, because the claim limitations uses a generic placeholder that is coupled with functional language without reciting sufficient structure to perform the recited function and the generic placeholder is not preceded by a structural modifier. Such claim limitations are: “a sensor detection unit”, “a state determining unit”, “a data communications unit”, and a “motion control unit” in claim 25 and “a 3D rendering unit” in claim 31.
Because these claim limitations are being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, they are being interpreted to cover the corresponding structure described in the specification as performing the claimed function, and equivalents thereof.
However, there is no corresponding structure for performing the claimed functions. Therefore, claims 25 and 31 are indefinite. Dependent claims 26-30 are rejected due to their dependency on the rejected claim 25. Correction is required.
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.
Claims 18-20, 25-27 and 32-34 are rejected under 35 U.S.C. 102(a)(1) as being anticipated by US 2012/0123614 A1 (“Laws”).
Regarding claims 18, 25, and 35 Laws teaches:
A method for emulating an automated guided vehicle (AGV) system (Laws: para [0025] “the vehicle 102 may be an automated guided vehicle (AGV), such as an automated forklift, which is configured to handle and/or move the plurality of units 114 about the floor 110”; para [0013], “FIG. 4 is a functional block diagram of a system for virtualizing a forklift to emulate hardware component operations and enhance safety within an industrial environment”), comprising:
obtaining sensor data of a virtual AGV in an emulation environment (Laws: para [0040], “an emulation module 314 for generating the configuration information 310 and the abstraction information 312 as explained further below. The automated vehicle software 316 also invokes the emulation module 314 in order to execute vehicle commands 348”; para [0034], “a single virtual laser scan, which may be used by various software modules to control the forklift 200”; para [0013], “FIG. 4 is a functional block diagram of a system for virtualizing a forklift to emulate hardware component operations”; para [0025] “the vehicle 102 may be an automated guided vehicle (AGV), such as an automated forklift”; para[0038], “FIG. 3 is a block diagram of a system 300 for virtualizing industrial vehicles to automate task execution in a physical environment according to one or more embodiments. As explained further below, the industrial vehicles are virtualized or modeled as a logical configuration of various vehicle capabilities and vehicle characteristics. In some embodiments, the system 300 includes the mobile computer 104, the central computer 106, the sensor array 108 and vehicle hardware components 334 in which each is coupled to each other through a network 302”);
determining a device state of a virtual device interacting with the virtual AGV in the emulation environment (Laws: para [0034], “a single virtual laser scan, which may be used by various software modules to control the forklift 200”; para [0032], “[The forklift 200 is also coupled with the sensor array 108, which transmits data (e.g., image data, video data, range map data and/or three-dimensional graph data) to the mobile computer 104, which stores the sensor array data according to some embodiments. As described in detail further below, the sensor array 108 includes various devices, such as a laser scanner and a camera, for capturing the sensor array data associated with objects within a physical environment, such as the position of actuators, obstructions, pallets and/or the like.”; para [0066], “the vehicle capabilities model 402 enables fleet management and task coordination without requiring every forklift 200 to be equipped with numerous sensors, such as laser scanners and/or cameras. Instead, the facility manager 332 uses a limited number of sensor-equipped vehicles to detect obstructions and generate a map illustrating each and every obstruction in an industrial environment. The obstruction map may be used by any vehicles for path planning”; para [0066] recites that sensors “detect obstructions and generate a map illustrating each and every obstruction in an industrial environment. The obstruction map may be used by any vehicles for path planning”; paragraph [0032] “the sensor array 108 includes various devices, such as a laser scanner and a camera, for capturing the sensor array data associated with objects within a physical environment, such as the position of actuators, obstructions, pallets and/or the like”);
transmitting the sensor data and the device state to the AGV system, and receiving AGV motion control information and device operation information from the AGV system, wherein the AGV motion control information and the device operation information are generated by the AGV system based on the sensor data and the device state (Laws: para [0066], “the vehicle capabilities model 402 enables fleet management and task coordination without requiring every forklift 200 to be equipped with numerous sensors, such as laser scanners and/or cameras. Instead, the facility manager 332 uses a limited number of sensor-equipped vehicles to detect obstructions and generate a map illustrating each and every obstruction in an industrial environment. The obstruction map may be used by any vehicles for path planning”; para [0068], “The emulation module 314 isolates the automated vehicle software 316 and/or the task manager 332 from details associated with the vehicle hardware components 334 being operated. The emulation module 314 generates the abstraction information 312 to include objects (e.g., primitive data models) for storing such details and enabling manipulation of the industrial vehicle being automated, for a forklift, by the automated vehicle software 316. In some embodiments, the emulation module 314 creates controller objects for the vehicle hardware components 334, such as steering components (e.g., a steering wheel or a joystick), engine control components (e.g., a throttle), braking components, lifting components (e.g., forks), tilt components, side-shift components and/or the like”; para [0072], “As shown in FIG. 5, the task manager 332 includes various software modules for executing the task 346 using an industrial vehicle, such an automated forklift (e.g., the forklift 200 of FIG. 2). The task manager 332 includes a path planning module 506 for creating a path 518 based the vehicle planning model 502. The task manager 332 also includes a motion control module 508, which uses the vehicle behavior model 504 to determine vehicle commands (e.g., the vehicle commands 348 of FIG. 3) for moving the industrial vehicle along the path 518. The task manager 332 also includes a positioning module 510 that communicates positional data 512 to the motion control module 508. The task manager 332 also optimizes motion control by updating the vehicle behavior model 504 with recent vehicle performance as explained further below”);
and controlling a motion of the virtual AGV and the virtual device in the emulation environment based on the AGV motion control information and the device operation information respectively (Laws: para [0066], “the vehicle capabilities model 402 enables fleet management and task coordination without requiring every forklift 200 to be equipped with numerous sensors, such as laser scanners and/or cameras. Instead, the facility manager 332 uses a limited number of sensor-equipped vehicles to detect obstructions and generate a map illustrating each and every obstruction in an industrial environment. The obstruction map may be used by any vehicles for path planning”; para [0072], “As shown in FIG. 5, the task manager 332 includes various software modules for executing the task 346 using an industrial vehicle, such an automated forklift (e.g., the forklift 200 of FIG. 2). The task manager 332 includes a path planning module 506 for creating a path 518 based the vehicle planning model 502. The task manager 332 also includes a motion control module 508, which uses the vehicle behavior model 504 to determine vehicle commands (e.g., the vehicle commands 348 of FIG. 3) for moving the industrial vehicle along the path 518. The task manager 332 also includes a positioning module 510 that communicates positional data 512 to the motion control module 508. The task manager 332 also optimizes motion control by updating the vehicle behavior model 504 with recent vehicle performance as explained further below” ).
Regarding claims 19 and 26, Laws teaches:
The method according to claim 18, wherein the step of obtaining the sensor data of the virtual AGV in the emulation environment further comprises:
obtaining the sensor data based on a sensor model of the virtual AGV, the sensor model of the virtual AGV including a position and parameters of a virtual sensor of the virtual AGV (Laws: para [0044], “ The sensor array 108 is communicable coupled to the mobile computer 104, which is attached to an automated forklift (e.g., the forklift 200 of FIG. 2). The sensor array 108 includes a plurality of devices 318 for monitoring a physical environment and capturing data associated with various objects, which is stored by the mobile computer 104 as the sensor array data 338. In some embodiments, the sensor array 108 may include any combination of one or more laser scanners and/or one or more cameras. In some embodiments, the plurality of devices 318 may be mounted to the automated vehicle. For example, a laser scanner and a camera may be attached to a lift carriage at a position above the forks. Alternatively, the laser scanner and the camera may be located below the forks. Furthermore, the laser scanner and the camera may be articulated and moved up and down the automated forklift”; para0054], “The emulation module 314 examines the sensor array data 338 to identify measurements related to vehicle responses to the input parameters 340. These vehicle responses include vehicle movement and/or hardware component operation, such as lifting element movement. Various sensing devices of the sensor array 108 capture and store various measurements as the sensor array data 338. Based on these measurements, the actuator data 342 indicates position, velocity or acceleration information associated with the vehicle movement during command execution according to some embodiments. The actuator data 342 may further include positional and velocity information associated with the lifting element movement. After the emulation module 314, for example, applies a certain voltage emulating a voltage that a human operator would normally apply and causing the industrial vehicle to move to a new position, the emulation module 314 records the new position as well as velocity and acceleration information in the actuator data 342 along with a time value”).
Regarding claims 20 and 27, Laws teaches:
The method according to claim 18, wherein the step of determining the device state of the virtual device interacting with the virtual AGV in the emulation environment further comprises:
obtaining state data of the virtual device based on a sensor model of the virtual device, the state data representing a relative motion between moving components of the virtual device (Laws: para [0060], “Similarly, a vehicle characteristics model 404 may represent another level of abstraction for the particular vehicle. The vehicle characteristics model 404 indicates vehicle attachment control attributes to enable object (i.e., product) handling, kinematic models
associated with motion control attributes for the industrial vehicle, outline models required for path planning, sensor geometry models required for processing sensor array data (e.g., the sensor array data 338 of FIG. 3)”), and the sensor model of the virtual device comprising a position and parameters of a virtual sensor of the virtual device (Laws: para [0044], “ The sensor array 108 is communicable coupled to the mobile computer 104, which is attached to an automated forklift (e.g., the forklift 200 of FIG. 2). The sensor array 108 includes a plurality of devices 318 for monitoring a physical environment and capturing data associated with various objects, which is stored by the mobile computer 104 as the sensor array data 338. In some embodiments, the sensor array 108 may include any combination of one or more laser scanners and/or one or more cameras. In some embodiments, the plurality of devices 318 may be mounted to the automated vehicle. For example, a laser scanner and a camera may be attached to a lift carriage at a position above the forks. Alternatively, the laser scanner and the camera may be located below the forks. Furthermore, the laser scanner and the camera may be articulated and moved up and down the automated forklift”; para0054], “The emulation module 314 examines the sensor array data 338 to identify measurements related to vehicle responses to the input parameters 340. These vehicle responses include vehicle movement and/or hardware component operation, such as lifting element movement. Various sensing devices of the sensor array 108 capture and store various measurements as the sensor array data 338. Based on these measurements, the actuator data 342 indicates position, velocity or acceleration information associated with the vehicle movement during command execution according to some embodiments. The actuator data 342 may further include positional and velocity information associated with the lifting element movement. After the emulation module 314, for example, applies a certain voltage emulating a voltage that a human operator would normally apply and causing the industrial vehicle to move to a new position, the emulation module 314 records the new position as well as velocity and acceleration information in the actuator data 342 along with a time value”); and
determining the device state of the virtual device according to the state data (Laws: para [0080], “As shown in FIG. 6, the emulation module 314 is completely disconnected from the industrial vehicle during manual control by, for example, a relay, such as an auto/manual changeover 612. The auto/manual changeover 612 is configured such that a power loss disconnects the emulation module 314, which improves overall safety. During the automatic mode, the emulation module 314 provides complementary voltages to the vehicle control unit 604 through the digital potentiometers 608, which mimic the manual operation of manual joysticks. Finally, a fault interlock 610 configures the joystick operation emulation circuit 600 to indicate a state that will be detected by the vehicle control unit 604 as a fault, such as a power failure. In response, the vehicle control unit 604 freezes industrial vehicle movement as a safety measure”).
Regarding claim 32, Laws teaches:
A computing device, comprising: a processor; and a memory connected to said processor and configured to store a computer- executable instruction, the computer-executable instruction, when executed, causing the processor to perform the method according to claim 18 (Laws: Fig. 3).
Regarding claim 33, Laws teaches:
A non-transitory computer-readable storage medium, comprising computer-executable instructions stored thereon, that when executed on a processor, perform the method according to claim 18 (Laws: Fig. 3).
Regarding claim 34, Laws teaches:
A computer program product, stored in a computer-readable storage medium in non-transitory form and comprising a computer-executable instruction, when executed, causing at least one processor to perform the method according to claim 18 (Laws: Fig. 3).
Claim Rejections - 35 USC § 103
The following is a quotation of 35 U.S.C. 103 which forms the basis for all obviousness rejections set forth in this Office action:
A patent for a claimed invention may not be obtained, notwithstanding that the claimed invention is not identically disclosed as set forth in section 102, if the differences between the claimed invention and the prior art are such that the claimed invention as a whole would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention pertains. Patentability shall not be negated by the manner in which the invention was made.
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 24 and 31 are rejected under 35 U.S.C. 103 as being unpatentable over US 20120123614 A1 (“Laws”) in view of “ARENA – Augmented Reality to enhanced Experimentation in Smart Warehouses” (“Piardi”).
Regarding claims 24 and 31, Laws does not explicitly teach but Piardi does teach:
The method according to claim 18, which further comprises displaying, according to 3D models of all virtual AGVs, virtual devices, and environmental objects in the emulation environment, 3D images of all the virtual AGVs, virtual devices, and environmental objects via a display interface (Piardi: page 11, last paragraph, “An example of complete experimentation in the ARENA is illustrated in Figure 12, containing WsBots (as real forklifts) and virtual forklifts, both with LRF. These agents are handling pallet boxes, through the sequence specified in the warehouse logistics state machine (Figure 3). The virtual perception allows the tiny robot to perceive the industrial environment, understanding obstacles, and allowing intelligent and autonomous behaviors”; Figure 12, page 12).
Accordingly, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have combined Laws (directed to emulating an AGV) and Piardi (directed to displaying the emulation environment) and arrived at displaying the emulation environment of the AGV. One of ordinary skill in the art would have been motivated to make such a combination for the purpose of “providing an environment for experimentation of advanced behaviors in smart factories, allowing experimentation with multi-robot systems (MRS), interconnected, cooperative, and interacting with virtual elements” (Piardi: Abstract).
Claims 21 and 28 are rejected under 35 U.S.C. 103 as being unpatentable over US 20120123614 A1 (“Laws”) in view of US 20170120804 A1 (“Kentley”).
Regarding claims 21 and 28, Laws does not teach but Kentley teaches:
The method according to claim 18, wherein the step of controlling the motion of the virtual AGV and the virtual device in the emulation environment based on the AGV motion control information and the device operation information respectively further comprises:
determining next positions of moving components of the virtual AGV based on the AGV motion control information, a kinematic model of the virtual AGV, and current positions of the moving components of the virtual AGV; and determining next positions of moving components of the virtual device based on the device operation information, a kinematic model of the virtual device, and current positions of the moving components of the virtual device, wherein the kinematic models of the virtual AGV and the virtual device include motion relationships and motion parameters of the moving components of the virtual AGV and the virtual device respectively (Kentley: para [0057], “A kinematics calculator 115 may be configured to compute data representing one or more scalar and/or vector quantities associated with motion of the object 180 in the environment 190, including but not limited to velocity, speed, acceleration, deceleration, momentum, local pose and force, for example. Data from kinematics calculator 115 may be used to compute other data including but not limited to data representing an estimated time to impact between the object 180 and the autonomous vehicle 100 and data representing a distance between the object 180 and the autonomous vehicle 100, for example. In some examples the kinematics calculator 115 may be configured to predict a likelihood that other objects in the environment 190 (e.g. cars, pedestrians, bicycles, motorcycles, etc.) are in an alert or in-control state, versus an un-alert, out-of-control, or drunk state, etc. As one example, the kinematics calculator 115 may be configured estimate a probability that other agents (e.g., drivers or riders of other vehicles) are behaving rationally (e.g., based on motion of the object they are driving or riding), which may dictate behavior of the autonomous vehicle 100, versus behaving irrationally (e.g. based on erratic motion of the object they are riding or driving). Rational or irrational behavior may be inferred based on sensor data received over time that may be used to estimate or predict a future location of the object relative to a current or future trajectory of the autonomous
vehicle 100. Consequently, a planner system of the autonomous vehicle 100 may be configured
to implement vehicle maneuvers that are extra cautious and/or activate a safety system of the autonomous vehicle 100, for example”; para [0073] , “At a stage 276 a predicted next
location of the object in the environment may be calculated based on the predicted rate
of motion 281. The stage 276 may generate data representing the predicted next location
283”; para [0074], “At a stage 278, probabilities of impact between the object and the autonomous vehicle may be predicted based on the predicted next location 283 and
the autonomous vehicle trajectory 273. The stage 278 may generate data representing the probabilities of impact 285”).
Accordingly, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have combined Laws (directed to emulating an AGV) and Kentley (directed to predicting positions of moving components) and arrived at emulating an AGV including predicting positions of moving components. One of ordinary skill in the art would have been motivated to make such a combination to “to avert a potential collision or an approach of the vehicle within an unsafe distance of an external object, such as a pedestrian or other vehicles, for example” (Kentley: para [0003]).
Claims 22-23 and 29-30 are rejected under 35 U.S.C. 103 as being unpatentable over US 20120123614 A1 (“Laws”) in view of US 20210300679 A1 (“Meurer”).
Regarding claims 22 and 29, Laws does not teach but Meurer does teach:
The method according to claim 18, which further comprises determining whether the virtual AGV collides with or is excessively close to at least one of a virtual device or an environmental object around the virtual AGV (Meurer: para [0012], “a vision and emulation
model, it is possible to recognize areas as being safe or free and/or to assess possible
collisions or other dangers for persons by means of a virtual model of the entire warehouse including the installed conveyor equipment, extended by persons and automated machines located in the building”; para [0068], “since the movement paths 600 of the autonomous vehicles 504 and the persons 201 overlap, there is a risk of collisions”; para [0075], “The movement data are used for determining potential dangers and, if a danger to persons is established, control commands are generated for the AGV 504 which eliminate the danger. These can be simple standstill commands to stop immediately or even evasion commands to bypass the danger area”; para [0017], “The virtual movement of the warehouse, including the conveyor equipment, comprises inter alia dimensions and position of the individual components and their movement parameters (speed, acceleration etc.). Therefore, situations which endanger persons in the warehouse can be predicted, recognized and prevented by means of appropriate control”).
Accordingly, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have combined Laws (directed to emulating an AGV) and Meurer (directed to determining closeness or collisions) and arrived at emulating and AGV including determining closeness and collisions. One of ordinary skill in the art would have been motivated to make such a combination that “provides a possibility which allows staff to be safe in spite of a simplified installation design, and to minimize the effect of the safety systems on the performance of the installation and at the same time to reduce the outlay for the corresponding devices” (Meurer: para [0011]).
Regarding claims 23 and 30, Laws teaches:
3D model of the virtual AGV; 3D model of the virtual AGV (Laws: para [0046], “three-dimensional object models”; para [0060], “outline models required for path planning”);
Laws does not teach but Meurer does teach:
The method according to claim 22, wherein the step of determining whether the virtual AGV collides with or is excessively close to a virtual device and/or an environmental object around the virtual AGV comprises:
determining a distance between the virtual AGV and the virtual device and/or the environmental object around the virtual AGV based on a model of the virtual AGV and a model of the virtual AGV and/or the environmental object around the virtual AGV; and determining, according to the distance so determined, whether the virtual AGV collides with or is excessively close to the virtual device and/or the environmental object around the virtual AGV (Meurer: para [0012], “a vision and emulation model, it is possible to recognize areas as being safe or free and/or to assess possible collisions or other dangers for persons by means of a virtual model of the entire warehouse including the installed conveyor equipment, extended by persons and automated machines located in the building”; para [0068], “since the movement paths 600 of the autonomous vehicles 504 and the persons 201 overlap, there is a risk of collisions”; para [0075], “The movement data are used for determining potential dangers and, if a danger to persons is established, control commands are generated for the AGV
504 which eliminate the danger. These can be simple standstill commands to stop immediately or even evasion commands to bypass the danger area”; para [0017], “The virtual movement of the warehouse, including the conveyor equipment, comprises inter alia dimensions and position of the individual components and their movement parameters (speed, acceleration etc.). Therefore, situations which endanger persons in the warehouse can be predicted, recognized and prevented by means of appropriate control”); wherein the model of the virtual AGV and the model of the virtual device and/or the environmental object around the virtual AGV include contour data of the virtual AGV and the virtual device and/or the environmental object around the virtual AGV respectively (Meurer: para [0071], “For this purpose, dimensions
and movement parameters, including the actuator properties of the persons 501 and AGV 504, are stored in the computer in the real-time model of the warehouse 1000”; claim 1, “whereby a virtual model of the warehouse, including the real conveyor installation, the automated machines and the persons with their dimensions and movement parameters, including the actuator properties, is stored”).
Accordingly, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have combined Laws (directed to emulating an AGV) and Meurer (directed to determining closeness or collisions) and arrived at emulating and AGV including determining closeness and collisions. One of ordinary skill in the art would have been motivated to make such a combination that “provides a possibility which allows staff to be safe in spite of a simplified installation design, and to minimize the effect of the safety systems on the performance of the installation and at the same time to reduce the outlay for the corresponding devices” (Meurer: para [0011]).
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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/NITHYA J. MOLL/Primary Examiner, Art Unit 2189
