DETAILED ACTION
Notice of Pre-AIA or AIA Status
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
In the event the determination of the status of the application as subject to AIA 35 U.S.C. 102 and 103 is incorrect, any correction of the statutory basis 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.
Status of Claims
This Office Action is in response to the Applicant’s Response dated 4/9/2026. Claims 1 and 4-22 are presently pending and are presented for examination.
Information Disclosure Statement
The information disclosure statement (IDS) was submitted on 4/29/2026. The submission is in compliance with the provisions of 37 CFR 1.97. Accordingly, the information disclosure statement is being considered by the examiner.
Response to Amendment
Applicant’s amendments, see pages 9-11 of 19, filed 4/9/2026, with respect to specification objections and claim objections have been fully considered and are mostly persuasive. The specification objections and claim objections of record have been withdrawn, with the exception of one objection still applicable to claim 15, detailed again below.
Response to Arguments
Applicant's arguments, see pages 12-13 of 19, filed 4/9/2026, have been fully considered but they are not persuasive. The Applicant has argued that the “location 110” as disclosed by Samaraweera does not apply to the limitation of claim 1 which states “…location of the material container…” however the Examiner respectfully disagrees. Samaraweera describes a loading spot location 30/32 as being on a left and/or right side of the loading machine (see Samaraweera at least [0020] and [0030]). While the claim recites both a “rough location” as well as a “precise location”, there is no additional detail as to the accuracy level differentiating these locations. Rather, the Examiner has relied upon the disclosure of Samaraweera which describes a “general location of the loading machine” as being applicable to the “rough location”, and a “loading spot location 110” (shown as being adjacent to the loading machine in Figure 3) as being applicable to the “precise location”.
Applicant's arguments, see pages 14-15 of 19, filed 4/9/2026, have been fully considered but they are not persuasive. The Applicant has argued that the teachings of Venkatraman do not apply to a “confidence level” as claimed, however the Examiner respectfully disagrees. Venkatraman teaches generalized confidence scores associated with detected positions, as well as the concept of updating previously less accurate data with higher accurate data, according to a specific confidence data.
Applicant's arguments, see page 16 of 19, filed 4/9/2026, have been fully considered but they are not persuasive. The Applicant has argued that the teachings of Venkatraman are non-analogous because Venkatraman is “not in the field of truck loading and does not provide a motivation or rationale to incorporate the cited features” however the Examiner respectfully disagrees. In response to applicant's argument that the sensors and confidence scores of Venkatraman is nonanalogous art, it has been held that a prior art reference must either be in the field of the inventor’s endeavor or, if not, then be reasonably pertinent to the particular problem with which the inventor was concerned, in order to be relied upon as a basis for rejection of the claimed invention. See In re Oetiker, 977 F.2d 1443, 24 USPQ2d 1443 (Fed. Cir. 1992). In this case, one of ordinary skill in the art would seek prior art pertaining to location sensing specifics, since primary reference Samaraweera discloses a vehicle navigating in an environment without explicit mention of sensors. Venkatraman details navigation by way of dead reckoning as well as using GPS, and applying a confidence value or weight to the different navigation techniques.
A detailed rejection follows below.
Claim Objections
Claim 15 is objected to because of the following informalities:
Claim 15 as currently presented states “…the haulage vehicle is detected with the second sensor wherein the precise approach location is configured to detect the precise approach location based on the location signal…” which the Examiner recommends updating to properly convey what is performing the detection, such as the second sensor, if that is in fact what the Applicant intends. Such an amendment may resemble the following: “…the haulage vehicle is detected with the second sensor wherein the precise approach location is detected based on the location signal…” or the like.
Appropriate correction is required.
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 set forth in Graham v. John Deere Co., 383 U.S. 1, 148 USPQ 459 (1966), that are applied 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.
This application currently names joint inventors. In considering patentability of the claims the examiner presumes that the subject matter of the various claims was commonly owned as of the effective filing date of the claimed invention(s) absent any evidence to the contrary. Applicant is advised of the obligation under 37 CFR 1.56 to point out the inventor and effective filing dates of each claim that was not commonly owned as of the effective filing date of the later invention in order for the examiner to consider the applicability of 35 U.S.C. 102(b)(2)(C) for any potential 35 U.S.C. 102(a)(2) prior art against the later invention.
Claims 1, 4, 8-10, and 12-21 are rejected under 35 U.S.C. 103 as being unpatentable over Samaraweera (US-2018/0173221; already of record) in view of Venkatraman et al. (US-2018/0091946; hereinafter Venkatraman; already of record).
Regarding claim 1, Samaraweera discloses a computer implemented method of controlling a material transfer vehicle in an approach operation relative to a material container (see Samaraweera at least Abs), comprising:
receiving a rough location signal (see Samaraweera at least Fig 1 and [0020]-[0021] “During operation at worksite 10, some trucks will be in the process of transporting a load that has been received, while other trucks will be returning to worksite 10 and queuing up to maneuver into position to receive a load from loading machine 12. As a truck 26 approaches the general location of loading machine 12, for example along one or more haul roads such as haul road 28, truck 26 may not yet know the precise location at which a load will be deposited by loading machine 12. For example, loading machine 12 may deposit a load at a loading spot location 30 at left side 22, or at loading spot location 32 at right side 24. Currently, as truck 26 moves to a cusp location 34, a cusp location 36, or a cusp location 38, for example, in anticipation of shifting to reverse and backing to a loading spot location 30 or 32 to receive a load, the truck operator may then know which side of loading machine 12 he or she may need to be on. This may have been communicated to the truck operator via the “hanging bucket” technique or by direct communication between the truck operator and the loading machine operator. Where there is no communication indicating the side of loading machine 12 for truck 26 to be on, the truck operator may simply make a guess which side to position on.”) …
identifying a rough approach location based on the rough location signal (see Samaraweera at least Fig 1 and [0020] “During operation at worksite 10, some trucks will be in the process of transporting a load that has been received, while other trucks will be returning to worksite 10 and queuing up to maneuver into position to receive a load from loading machine 12. As a truck 26 approaches the general location of loading machine 12, for example along one or more haul roads such as haul road 28, truck 26 may not yet know the precise location at which a load will be deposited by loading machine 12. For example, loading machine 12 may deposit a load at a loading spot location 30 at left side 22, or at loading spot location 32 at right side 24.”);
generating a navigation path based on the rough approach location (see Samaraweera at least Fig 1 and [0020] “During operation at worksite 10, some trucks will be in the process of transporting a load that has been received, while other trucks will be returning to worksite 10 and queuing up to maneuver into position to receive a load from loading machine 12. As a truck 26 approaches the general location of loading machine 12, for example along one or more haul roads such as haul road 28, truck 26 may not yet know the precise location at which a load will be deposited by loading machine 12. For example, loading machine 12 may deposit a load at a loading spot location 30 at left side 22, or at loading spot location 32 at right side 24.”);
controlling the material transfer vehicle to travel along the navigation path toward the rough approach location (see Samaraweera at least Fig 1 and [0019]-[0021] “Typically, one or more haulage machines, for example trucks 26, may be employed at worksite 10 for receiving material excavated or removed by loading machine 12 and transporting the material to another location. For example, in a surface mining or quarrying operation, trucks 26 may transport loads received from loading machine 12 to one or more crushers... During operation at worksite 10, some trucks will be in the process of transporting a load that has been received, while other trucks will be returning to worksite 10 and queuing up to maneuver into position to receive a load from loading machine 12. As a truck 26 approaches the general location of loading machine 12, for example along one or more haul roads such as haul road 28, truck 26 may not yet know the precise location at which a load will be deposited by loading machine 12. For example, loading machine 12 may deposit a load at a loading spot location 30 at left side 22, or at loading spot location 32 at right side 24. Currently, as truck 26 moves to a cusp location 34, a cusp location 36, or a cusp location 38, for example, in anticipation of shifting to reverse and backing to a loading spot location 30 or 32 to receive a load, the truck operator may then know which side of loading machine 12 he or she may need to be on. This may have been communicated to the truck operator via the “hanging bucket” technique or by direct communication between the truck operator and the loading machine operator. Where there is no communication indicating the side of loading machine 12 for truck 26 to be on, the truck operator may simply make a guess which side to position on.”);
detecting a precise approach location based on a location signal … the location signal … being indicative of a sensed location of the material container (see Samaraweera at least Fig 3, [0021]-[0022] “Currently, as truck 26 moves to a cusp location 34, a cusp location 36, or a cusp location 38, for example, in anticipation of shifting to reverse and backing to a loading spot location 30 or 32 to receive a load, the truck operator may then know which side of loading machine 12 he or she may need to be on. This may have been communicated to the truck operator via the “hanging bucket” technique or by direct communication between the truck operator and the loading machine operator. Where there is no communication indicating the side of loading machine 12 for truck 26 to be on, the truck operator may simply make a guess which side to position on... Loading machine 12, in accordance with disclosed embodiments to be further described subsequently, may broadcast information regarding potential loading spot locations via any conventional broadcasting technology within a broadcast range 44, and trucks 26 within broadcast range 44 may receive that information.”, and [0027]-[0028] “Loading machine 102 may retrieve a load of material in the normal course of operation and make a decision, e.g. via the loading machine operator and controller 106, to deposit the load at a loading spot location, e.g., loading spot location 110. Controller 106 may, via transmitting device 112, broadcast signals indicative of the position of the selected loading spot location 110. The broadcast frequency may vary, but may be selected so as to broadcast the signals over a broadcast range that may cover an area in which several trucks 104 are currently located, either returning to the worksite for a load, maneuvering into position to receive a load, or leaving the worksite with a load. For example only, the broadcast range may have a radius on the order of 100 meters, more or less. The signals indicative of the position of the selected loading spot location 110 may be received by all trucks within the broadcast range, for example by truck 104 via receiving device 114, and processed by controller 108. Truck 104 also may include a display device 116 configured to display to an operator of truck 104 visual information including, among other things, the loading spot location 110 indicated by signals received by receiving device 114. However, although the signals may be received, the loading spot location 110 will not necessarily be displayed to all trucks that receive the signals.”);
…
…
However, Samaraweera does not explicitly disclose the following:
…[receive data] from a first sensor…
…[receive data] from a second sensor…
…identifying a confidence level corresponding to the precise approach location…
…correcting the navigation path based on the precise approach location and based on the confidence level corresponding to the precise approach location…
Venkatraman, in the same field of endeavor, teaches the following:
…[receive data] from a first sensor (see Venkatraman at least [0020] "...In such circumstances, sensor equipped mobile devices can perform pedestrian dead reckoning (PDR) to estimate the mobile device's position. However, accuracy is limited by magnetic disturbances inside structures, sensor precision, and other unknown variables such as device position, bias, and differences in stride. Additionally, PDR error from use of mobile device sensor data is typically magnified over time as every new positioning error is compounded with previous errors.")…
…[receive data] from a second sensor (see Venkatraman at least [0020] "Mobile devices may be equipped with satellite based navigation systems for determining position and providing navigation assistance. A global navigation satellite system (GNSS) such as, for example, the Global Positioning System (GPS) may send timing signals used by mobile devices to estimate the position of the mobile device...")…
…identifying a confidence level corresponding to the precise approach location (see Venkatraman at least [0022] "...However, typical PDR can be relatively inaccurate over anything but short distances due to drift and other sensor errors that multiply over time. Therefore, measurement batching will take PDR and AP measurements collected while the mobile is within an indoor environment, and “batch” process the currently collected PDR and AP measurement data together with an updated mobile device position having a higher accuracy. For example, one or more low confidence positions (for example, from PDR) may be adjusted or corrected when a high confidence position (for example from GNSS) is determined..." and [0026] "...In one embodiment, when a GNSS and/or other position fix may be detected with high confidence, the mobile device may align the prior trajectory to the high confidence position fix and to update previously computed positions via backfiltering the PDR positioning data.")…
…correcting the navigation path based on the precise approach location and based on the confidence level corresponding to the precise approach location (see Venkatraman at least [0022] "...In one embodiment, a mobile device may use a GNSS position fix to correct potentially less accurate historical mobile sensor based positioning (for example, PDR). A mobile device may traverse an indoor environment and measure AP signals while also tracking current position using the best available positioning methods. In some embodiments, the best available positioning methods may be determined from mobile device motion sensors, such as what may be used as input for determining PDR, which may be used instead of the GNSS due to the building blocking GNSS signals. However, typical PDR can be relatively inaccurate over anything but short distances due to drift and other sensor errors that multiply over time. Therefore, measurement batching will take PDR and AP measurements collected while the mobile is within an indoor environment, and “batch” process the currently collected PDR and AP measurement data together with an updated mobile device position having a higher accuracy. For example, one or more low confidence positions (for example, from PDR) may be adjusted or corrected when a high confidence position (for example from GNSS) is determined. In one embodiment, PDR only positioning data may be adjusted or corrected (for example through a backfilter using a Kalman filter of prior data) according to one or more subsequent more accurate positioning fix(es) (for example, an acquired GNSS fix). Batching may be performed by a server in response to receiving a bundle of positioning and AP measurement data, or batching may be performed directly by the mobile device." and [0026] "...In one embodiment, when a GNSS and/or other position fix may be detected with high confidence, the mobile device may align the prior trajectory to the high confidence position fix and to update previously computed positions via backfiltering the PDR positioning data.")…
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the location detection accuracies as disclosed by Samaraweera with an update based on the higher precision sensor detection such as taught by Venkatraman with a reasonable expectation of success so as to improve measurement data to achieve more accurate results (see Venkatraman at least [0022]).
Regarding claim 4, Samaraweera in view of Venkatraman teach the computer implemented method of claim 1 wherein correcting the navigation path comprises:
comparing the confidence level to a first threshold confidence level to generate a first comparison result (see Venkatraman at least [0062] "...In some embodiments, the confidence measure associated with the new position of the mobile device meets or exceeds a threshold confidence. When the confidence measure associated with the new position of the mobile device meets or exceeds a threshold confidence, such data can be useful in crowdsourcing AP location information and hence the measurement data batch is useful and can be sent to the server immediately or at a later time relative to detection of the data batch trigger..."); and
based on a determination that the navigation path is to be corrected based on the first comparison result, correcting the navigation path based on the precise approach location (see Venkatraman at least [0026] "...In one embodiment, when a GNSS and/or other position fix may be detected with high confidence, the mobile device may align the prior trajectory to the high confidence position fix and to update previously computed positions via backfiltering the PDR positioning data." and [0062] "...In some embodiments, the confidence measure associated with the new position of the mobile device meets or exceeds a threshold confidence. When the confidence measure associated with the new position of the mobile device meets or exceeds a threshold confidence, such data can be useful in crowdsourcing AP location information and hence the measurement data batch is useful and can be sent to the server immediately or at a later time relative to detection of the data batch trigger...").
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to further modify the location detection accuracies as disclosed by Samaraweera with a threshold confidence and comparison such as further taught by Venkatraman with a reasonable expectation of success so that the higher accuracy measurement can be evaluated not just in comparison to the lower accuracy measurement, thus continuing to improve measurement data and achieve more accurate results (see Venkatraman at least [0022]).
Regarding claim 8, Samaraweera in view of Venkatraman teach the computer implemented method of claim 1 wherein the material container comprises a haulage vehicle (see Samaraweera at least [0017] "...Worksite 10 may include a loading machine 12 capable of excavating or otherwise removing material from a surface, for example the surface on which loading machine 12 is supported or a face of an excavation, and then depositing a load of that material. Typically, loading machine 12 may be an electric rope shovel (ERS) or a hydraulic excavator (HEX). Loading machine 12 also may be a wheel-type loader, a tracked loader, a backhoe, or any other machine capable of removing material and then depositing a load of the removed material.") and wherein detecting the precise approach location comprises:
controlling the material transfer vehicle to travel along the navigation path to reach the rough approach location (see Samaraweera at least [0020] "During operation at worksite 10, some trucks will be in the process of transporting a load that has been received, while other trucks will be returning to worksite 10 and queuing up to maneuver into position to receive a load from loading machine 12. As a truck 26 approaches the general location of loading machine 12, for example along one or more haul roads such as haul road 28, truck 26 may not yet know the precise location at which a load will be deposited by loading machine 12. For example, loading machine 12 may deposit a load at a loading spot location 30 at left side 22, or at loading spot location 32 at right side 24.");
after reaching the rough approach location, waiting until the haulage vehicle is detected (see Samaraweera at least [0020] "During operation at worksite 10, some trucks will be in the process of transporting a load that has been received, while other trucks will be returning to worksite 10 and queuing up to maneuver into position to receive a load from loading machine 12. As a truck 26 approaches the general location of loading machine 12, for example along one or more haul roads such as haul road 28, truck 26 may not yet know the precise location at which a load will be deposited by loading machine 12. For example, loading machine 12 may deposit a load at a loading spot location 30 at left side 22, or at loading spot location 32 at right side 24.") with the second sensor (see Venkatraman at least [0020]); and
detecting the precise approach location based on the location signal from the second sensor (see Venkatraman at least [0020] "Mobile devices may be equipped with satellite based navigation systems for determining position and providing navigation assistance. A global navigation satellite system (GNSS) such as, for example, the Global Positioning System (GPS) may send timing signals used by mobile devices to estimate the position of the mobile device...").
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to further modify the location detection accuracies as disclosed by Samaraweera with sensors such as taught by Venkatraman with a reasonable expectation of success for reasons similar to those provided above in claim 1.
Regarding claim 9, Samaraweera in view of Venkatraman teach the computer implemented method of claim 1 wherein the first sensor comprises a location sensor (see Venkatraman at least [0020]) on a haulage vehicle and wherein identifying the rough approach location (see Samaraweera at least [0021]-[0022]) comprises:
receiving the rough location signal from the location sensor on the haulage vehicle ((see Samaraweera at least Fig 1 and [0020]-[0021]) and (see Venkatraman at least [0020])).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to further modify the location detection accuracies as disclosed by Samaraweera with sensors such as taught by Venkatraman with a reasonable expectation of success for reasons similar to those provided above in claim 1.
Regarding claim 10, Samaraweera in view of Venkatraman teach the computer implemented method of claim 1 wherein obtaining the rough approach location comprises:
accessing map information from a map (see Venkatraman at least [0038]-[0039] “Location assistance data can include: a map of the location (for example, including building or floor layout and points of interest), number of known access points, historical data traffic, device activity associated with the position or location, or other known location features. In one embodiment, the location data stored at the server (for example, within the location database) may be determined by a baseline data collection sequence from one or more mobile devices or a pre-seeded database. During one or more initial position data collection sessions by one or more mobile devices, measurement batching at the server may obtain location data as described above...” and [0042] “The server may request AP measurements responsive to different situations, or the mobile may determine that better AP measurements are recommended for a given location. For example, in response to detecting a change in positioning performance of the mobile device, the mobile device may begin collecting positioning and AP measurement data to send as a data batch to a server. In other embodiments, a server can detect the change in positioning performance and request AP measurements and/or send request to mobile devices indicating that more data is requested for a given location. Positioning performance may relate to the ability of the mobile device to determine or infer a position or location of the mobile device, for example, relative to a landmark, map coordinates, or other physical space...”); and
identifying, as the rough approach location, an unloading area based on the map information (see Venkatraman at least [0038]-[0039] “Location assistance data can include: a map of the location (for example, including building or floor layout and points of interest), number of known access points, historical data traffic, device activity associated with the position or location, or other known location features. In one embodiment, the location data stored at the server (for example, within the location database) may be determined by a baseline data collection sequence from one or more mobile devices or a pre-seeded database. During one or more initial position data collection sessions by one or more mobile devices, measurement batching at the server may obtain location data as described above...” and [0042] “The server may request AP measurements responsive to different situations, or the mobile may determine that better AP measurements are recommended for a given location. For example, in response to detecting a change in positioning performance of the mobile device, the mobile device may begin collecting positioning and AP measurement data to send as a data batch to a server. In other embodiments, a server can detect the change in positioning performance and request AP measurements and/or send request to mobile devices indicating that more data is requested for a given location. Positioning performance may relate to the ability of the mobile device to determine or infer a position or location of the mobile device, for example, relative to a landmark, map coordinates, or other physical space...”).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the location detection as disclosed by Samaraweera with map information such as taught by Venkatraman with a reasonable expectation of success since crowdsourced data such as a map can be easily accessed from a server (see Venkatraman at least [0036]).
Regarding claim 12, Samaraweera in view of Venkatraman teach the analogous material of that in claim 1 as recited in the instant claim and is rejected for similar reasons.
Regarding claim 13, Samaraweera in view of Venkatraman teach the analogous material of that in claim 4 as recited in the instant claim and is rejected for similar reasons.
Regarding claim 14, Samaraweera in view of Venkatraman teach the analogous material of that in claim 4 as recited in the instant claim and is rejected for similar reasons.
Regarding claim 15, Samaraweera in view of Venkatraman teach the analogous material of that in claim 8 as recited in the instant claim and is rejected for similar reasons.
Regarding claim 16, Samaraweera in view of Venkatraman teach the analogous material of that in claim 9 as recited in the instant claim and is rejected for similar reasons.
Regarding claim 17, Samaraweera in view of Venkatraman teach the analogous material of that in claim 10 as recited in the instant claim and is rejected for similar reasons.
Regarding claim 18, Samaraweera in view of Venkatraman teach the analogous material of that in claim 1 as recited in the instant claim and is rejected for similar reasons. Additionally, Samaraweera discloses the following:
…at least one processor (see Samaraweera at least [0026])…
…a data store storing computer executable instructions which, when executed by the at least one processor, cause the at least one processor to perform steps (see Samaraweera at least [0026])…
Regarding claim 19, Samaraweera in view of Venkatraman teach the analogous material of that in claim 4 as recited in the instant claim and is rejected for similar reasons.
Regarding claim 20, Samaraweera in view of Venkatraman teach the analogous material of that in claim 8 as recited in the instant claim and is rejected for similar reasons.
Regarding claim 21, Samaraweera in view of Venkatraman teach the computer implemented method of claim 1 wherein the second sensor (see Venkatraman at least [0020]) is disposed on the material transfer vehicle (see Samaraweera at least [0019] and [0024]).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the material transfer vehicle as disclosed by Samaraweera with a sensor such as further taught by Venkatraman with a reasonable expectation of success since adding a known technique, such as a sensor, to a known device ready for improvement, such as the material transfer vehicle, would yield predictable results. Additionally, the implementation of a sensor on the machine would improve measurement data to achieve more accurate results (see Venkatraman at least [0022]).
Claims 5-7 are rejected under 35 U.S.C. 103 as being unpatentable over Samaraweera in view of Venkatraman, and further in view of Robinson et al. (US-2019/0113624; hereinafter Robinson; already of record).
Regarding claim 5, Samaraweera in view of Venkatraman teach the computer implemented method of claim 4. However, while Venkatraman teaches the determination of a high confidence position and the update of a trajectory according to a high confidence position rather than a low confidence position, neither Samaraweera nor Venkatraman explicitly disclose or teach the following:
…comparing the confidence level to a second threshold confidence level to generate a second comparison result.
Robinson, in the same field of endeavor, teaches the following:
…comparing the confidence level to a second threshold confidence level to generate a second comparison result (see Robinson at least [0002] "A tracking sensor such as a radar system or an electro-optical sensor may, in operation, produce a sensor output signal that contains a combination of signals from targets of interest, clutter (e.g., signals from terrain features that are not of interest), and noise. A threshold may be set, in a processing circuit receiving data from the sensor. When the sensor output signal exceeds the threshold, the signal may be classified as a detection of a target; otherwise, the signal may be discarded, and not processed further. Each new frame (e.g., of an electro-optical sensor) or dwell (e.g., of a radar sensor) may result in a new set of detections..." and [0033] "Accordingly, in some embodiments, as discussed in further detail below, the system may use two thresholds, including a first threshold, and a second, higher threshold. The first threshold may be applied to each sensor observation, resulting in the identification of a larger number of low-confidence target detections referred to herein as “pre-detections”, which are stored for later use. The confidence in the pre-detections is low because the low first threshold results in a relatively high probability of false alarm. A second, higher threshold is used to identify high-confidence target detections that are referred to herein as “robust detections.” Only robust detections trigger the tracker to form candidate tracks; accordingly, a sensor observation containing a robust detection is referred to herein as a “triggering” sensor observation.").
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the determination of a high confidence position such as taught by Samaraweera in view of Venkatraman with a comparison to a threshold such as taught by Robinson with a reasonable expectation of success so as to ensure proper classification of locational detections (see at least Robinson at least [0002]).
Regarding claim 6, Samaraweera in view of Venkatraman and Robinson teach the computer implemented method of claim 5 wherein correcting the navigation path comprises:
determining whether to continue correcting the navigation path (see Venkatraman at least [0022] and [0026]) based on the second comparison result (see Robinson at least [0033]).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to further modify the location detection accuracies as disclosed by Samaraweera with an update based on the higher precision sensor detection such as further taught by Venkatraman with a reasonable expectation of success for reasons similar to those provided above in claim 1.
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to further modify the method as taught by Samaraweera in view of Venkatraman with a second comparison such as taught by Robinson with a reasonable expectation of success for reasons similar to those provided above in claim 1.
Regarding claim 7, Samaraweera in view of Venkatraman and Robinson teach the computer implemented method of claim 6 wherein correcting the navigation path comprises:
based on a determination that the navigation path is to continue to be corrected, repeating the detecting the precise approach location, and correcting the navigation path based on the precise approach location (see Venkatraman at least [0022], [0026], and [0062]).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to further modify the location detection accuracies as disclosed by Samaraweera with comparison information such as further taught by Venkatraman with a reasonable expectation of success for reasons similar to those provided above in claim 2.
Claims 11 and 22 are rejected under 35 U.S.C. 103 as being unpatentable over Samaraweera in view of Venkatraman, and further in view of Engle et al. (US-2020/0064826; hereinafter Engle; already of record).
Regarding claim 11, Samaraweera in view of Venkatraman teach the computer implemented method of claim 1 wherein obtaining the rough approach location comprises:
navigating the material transfer vehicle to the rough approach location (see Samaraweera at least [0020] "During operation at worksite 10, some trucks will be in the process of transporting a load that has been received, while other trucks will be returning to worksite 10 and queuing up to maneuver into position to receive a load from loading machine 12. As a truck 26 approaches the general location of loading machine 12, for example along one or more haul roads such as haul road 28, truck 26 may not yet know the precise location at which a load will be deposited by loading machine 12. For example, loading machine 12 may deposit a load at a loading spot location 30 at left side 22, or at loading spot location 32 at right side 24."); and
after the material transfer vehicle reaches the rough approach location … the rough approach location (see Samaraweera at least [0020]).
However, neither Samaraweera nor Venkatraman explicitly disclose or teach the following:
…detecting an operator input saving a current location of the material transfer vehicle…
Engle, in the same field of endeavor, teaches the following:
…detecting an operator input saving a current location of the material transfer vehicle (see Engle at least [0064] "...The mobile computing device 200 can then receive input to select the graphical overlay 506 and further receive input to save the venue into a profile of the user 302. It is noted that multiple locations and venues can be saved into the profile of the user 302...")…
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the material transfer vehicle navigation as taught by Samaraweera in view of Venkatraman with location saving such as taught by Engle with a reasonable expectation of success so as to have access to important locational data for vehicle maneuvering controls (see Engle at least [0002]).
Regarding claim 22, Samaraweera in view of Venkatraman teach the computer implemented method of claim 21. While Samaraweera discloses a vehicle that receives data, but does not specify the means of detections, and Venkatraman teaches sensors capable of providing navigational assistance, neither reference explicitly discloses or teaches the following:
wherein the second sensor comprises at least one of:
an optical sensor,
a radar sensor,
a LIDAR sensor,
an ultrasonic sensor, or
an ultra-wide band sensor.
Engle, in the same field of endeavor, teaches the following:
wherein the second sensor comprises at least one of:
an optical sensor (see Engle at least [0035] "With reference now to FIG. 1, an exemplary autonomous vehicle 100 is illustrated. The autonomous vehicle 100 can navigate about roadways without human conduction based upon sensor signals output by sensor systems of the autonomous vehicle 100. The autonomous vehicle 100 includes a plurality of sensor systems 102-104 (a first sensor system 102 through an Nth sensor system 104). The sensor systems 102-104 are of different types and are arranged about the autonomous vehicle 100. For example, the first sensor system 102 may be a lidar sensor system and the Nth sensor system 104 may be a camera (image) system. Other exemplary sensor systems include radar sensor systems, GPS sensor systems, sonar sensor systems, infrared sensor systems, and the like."),
a radar sensor (see Engle at least [0035] "With reference now to FIG. 1, an exemplary autonomous vehicle 100 is illustrated. The autonomous vehicle 100 can navigate about roadways without human conduction based upon sensor signals output by sensor systems of the autonomous vehicle 100. The autonomous vehicle 100 includes a plurality of sensor systems 102-104 (a first sensor system 102 through an Nth sensor system 104). The sensor systems 102-104 are of different types and are arranged about the autonomous vehicle 100. For example, the first sensor system 102 may be a lidar sensor system and the Nth sensor system 104 may be a camera (image) system. Other exemplary sensor systems include radar sensor systems, GPS sensor systems, sonar sensor systems, infrared sensor systems, and the like."),
a LIDAR sensor (see Engle at least [0035] "With reference now to FIG. 1, an exemplary autonomous vehicle 100 is illustrated. The autonomous vehicle 100 can navigate about roadways without human conduction based upon sensor signals output by sensor systems of the autonomous vehicle 100. The autonomous vehicle 100 includes a plurality of sensor systems 102-104 (a first sensor system 102 through an Nth sensor system 104). The sensor systems 102-104 are of different types and are arranged about the autonomous vehicle 100. For example, the first sensor system 102 may be a lidar sensor system and the Nth sensor system 104 may be a camera (image) system. Other exemplary sensor systems include radar sensor systems, GPS sensor systems, sonar sensor systems, infrared sensor systems, and the like."),
an ultrasonic sensor, or
an ultra-wide band sensor.
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the vehicle including sensors as taught by Samaraweera in view of Venkatraman by substituting the generically recited sensor with a specific type of sensor such as taught by Engle with a reasonable expectation of success since one of ordinary skill in the art would recognize that the simple substitution of one known element for another produces a predictable result (object detection).
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure. Bojarski et al. (US-2020/0324795) teaches the use of different types of sensors to achieve approximate locational information versus other types of sensors to achieve accurate locational information.
Applicant's amendment necessitated the new ground(s) of rejection presented in this Office action. Accordingly, THIS ACTION IS MADE FINAL. See MPEP § 706.07(a). Applicant is reminded of the extension of time policy as set forth in 37 CFR 1.136(a).
A shortened statutory period for reply to this final action is set to expire THREE MONTHS from the mailing date of this action. In the event a first reply is filed within TWO MONTHS of the mailing date of this final action and the advisory action is not mailed until after the end of the THREE-MONTH shortened statutory period, then the shortened statutory period will expire on the date the advisory action is mailed, and any extension fee 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 date of this final action.
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/S.P.R./Examiner, Art Unit 3663
/KYLE J KINGSLAND/Primary Examiner, Art Unit 3663
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