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 .
Response to Arguments
With respect to the previous 35 U.S.C. 112a&b rejections. Applicant's remarks filed on 05/20/2026 with respect to previous claim rejections under 35 U.S.C. 112a&b have been fully considered and persuasive and thus withdraw the 112a&b rejections.
With respect to the previous 35 U.S.C. 101 rejections. Applicant's remarks filed on 05/20/2026 with respect to previous claim rejections under 35 U.S.C. 101 have been fully considered and persuasive and thus withdraw of 101 rejections.
With respect to the previous 35 U.S.C. 103 rejections. Applicant's remarks filed on 05/20/2026 with respect to previous claim rejections under 35 U.S.C. 103 have been fully considered and unpersuasive.
With respect to the previous 35 U.S.C. 103 rejections of claim 1 Applicant argue the cited art of record, Dawson-Townsend (US 2021/0295722 A1) in view of Williams et al (US 2022/0365545 A1), fails to explicitly disclose all of the recited features of the amended claim 1 (see response pages 12-14), specifically “wherein the control unit is configured to: in a case that the control unit determines that a weight of a detection result outputted by one or more of the sensors in the obstacle detecting unit under a condition of the determined sensor perception model is below a predetermined threshold, control the one or more sensors to operate in an enhanced mode".
However, Examiner respectfully disagrees. As Williams teaches, evaluating the performance of sensors 940 relative to predetermined performance thresholds, including a minimum performance threshold and an optimal performance threshold (Williams ¶77). Williams further teaches that the applicable performance threshold may vary based on operating conditions and expressly provides that, when increased sensor performance is required, “the sensors 940 may be required to operate at a higher capacity” (Williams ¶77). Williams additionally teaches monitoring the output of sensor 940 and determining that the sensor output is unreliable and in need of adjustment based on a figure of merit representing sensor performance (Williams ¶79). Further, when the monitored data does not meet at least one performance threshold, an adjustment is performed (Williams ¶80), and additional or different processing algorithms may be employed in response to detected characteristics so as to improve performance (Williams ¶81). Thus, Williams is not limited to merely ignoring the input of a temporarily unreliable sensor, as argued by Applicant, but teaches adjusting sensor/system operation in response to monitored sensor performance and expressly teaches operating sensors 940 at a higher capacity when increased sensor performance is required. Accordingly, Williams teaches or suggests controlling the one or more sensors to operate in an enhanced mode when the applicable performance requirement is not satisfied, as claimed.
With respect to the newly amended subject matter and applicant’s arguments, the Examiner relies upon newly cited reference Zheng et al (US 2020/0394924 A1).
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 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 1-5, 10, 12-14, 18 and 20 are rejected under 35 U.S.C. 103 as being unpatentable in view of Dawson-Townsend (US 2021/0295722 A1) in view of Williams et al (US 2022/0365545 A1).
Regarding claim 1, Dawson-Townsend discloses an aircraft ground anti-collision system, comprising: (see Dawson-Townsend paras “0003-0004” “The commercial aviation industry has, however, adopted a traffic collision avoidance system (“TCAS”) as a standard to avoid collisions, which allows cooperative aircraft to locate and avoid each other”),
an obstacle detecting unit, comprising a plurality of sensors configured to detect position information of an obstacle around an aircraft (see Dawson-Townsend para “0007” “a plurality of sensors coupled to the aerial vehicle, each of the plurality of sensors configured to generate sensor data reflecting a position of an obstacle in the environment; an obstacle detection circuit operatively coupled to the processor and the plurality of sensors, the obstacle detection circuit configured to blend the sensor data from each of the plurality of sensors to identify obstacles in the environment and to generate obstacle information that reflects a best estimate of a position of the obstacle in the environment”),
a weather monitoring unit comprising a receiver communicatively coupled to an information source and configured to receive weather information from the information source (see Dawson-Townsend paras “0057-0058”, “0063-0065” and “0079” “For example, in addition to altitude, geographic area, and/or airspace, the ASA system 200 may further adapt the fusion of sensors as a function of the time of day, current weather, and season of the year” and “The ASA system 200 may also take into account weather conditions when calculating obstacle avoidance maneuvers. For example, the ASA system 200 may account for ambient winds or density altitude when determining optimal trajectories, and avoiding weather hazards in the immediate vicinity”, “the obstacle detection circuit 202 can use environmental data from the environmental database 224 b refine the detection algorithms based on environmental factors such as time of year, day of week, time of day, climate and weather conditions, etc. Based on the various input from sensors and databases” regarding receiving weather information from the information source, the environmental database 224b stores environmental data including current and pending weather data and the obstacle detection circuit 202 uses environmental data from the environmental database 224b, including weather conditions (e.g., receiver communicatively coupled to the information source and configured to receive weather information from the information source)),
and a control unit, comprising a processor communicatively coupled to the obstacle detecting unit and the weather monitoring unit and configured to: receive the position information from the obstacle detecting unit and the weather information from the weather monitoring unit (see Dawson-Townsend paras “0007” and “0057-0058” “a plurality of sensors coupled to the aerial vehicle, each of the plurality of sensors configured to generate sensor data reflecting a position of an obstacle in the environment” and “For example, in addition to altitude, geographic area, and/or airspace, the ASA system 200 may further adapt the fusion of sensors as a function of the time of day, current weather, and season of the year” and “The ASA system 200 may also take into account weather conditions when calculating obstacle avoidance maneuvers. For example, the ASA system 200 may account for ambient winds or density altitude when determining optimal trajectories, and avoiding weather hazards in the immediate vicinity”),
determine, based on the weather information, a sensor perception model suitable for the weather information (see Dawson-Townsend paras “0057”, “0070-0071” and “0079-0080” “the ASA system 200 may further adapt the fusion of sensors as a function of the time of day, current weather, and season of the year… such as weighting of the different sensors”, “The one or more sensors may also be used to determine the current weather” and “Based on the state of the aircraft 100 and the surrounding environment… At step 308, the obstacle detection circuit 202 may assign weights to the various sensors 110 (e.g., obstacle sensors 226). For example, if the weather is clear (e.g., high visibility), the ASA system 200 may set obstacle detection weights that favor the sensor data from vision-based obstacle sensors” regarding determining current weather conditions and adapts the sensor fusion and weighting strategy as a function of those weather conditions (i.e., sensor perception model))
and set, based on the sensor perception model, a weight of a detection result outputted by each of the sensors in the obstacle detecting unit and output an obstacle detection result (see Dawson-Townsend paras “0070-0071” and “0081” “The obstacle detection circuit 202 can also set obstacle detection weights 210 based on current state and environment, as well as currently-active sensors… if current weather conditions include poor visibility, data from a radar sensor may be given a greater weight than data from a vision-based sensor”, “Using weighted sensor data, the obstacle detection circuit 202 can evaluate incoming obstacle data… can use the obstacle detection weights to cross-check and refine the relative position of the obstacle” and “the obstacle detection circuit 202 generates threat information and reports the data reflecting the detected obstacles”).
wherein the control unit is configured to control an operating mode and/or an operating parameter of at least one of the sensors in the obstacle detecting unit based on the determined sensor perception model (see Dawson-Townsend paras “0069-0071” “obstacle detection circuit 202 may also set any sensor modes 208 as necessary… as a function of the current aircraft state and environment” and “obstacle detection weights 210 based on current state and environment, as well as currently-active sensors 226. Based on the environmental factors described above, the obstacle detection circuit 202 sets weighting factors for evaluating the obstacle data coming from the sensors”).
Dawson-Townsend fails to explicitly teach wherein the control unit is configured to: in a case that the control unit determines that a weight of a detection result outputted by one or more of the sensors in the obstacle detecting unit under a condition of the determined sensor perception model is below a predetermined threshold, control the one or more sensors to operate in an enhanced mode.
However, Williams teaches wherein the control unit is configured to: in a case that the control unit determines that a weight of a detection result outputted by one or more of the sensors in the obstacle detecting unit under a condition of the determined sensor perception model is below a predetermined threshold, control the one or more sensors to operate in an enhanced mode (see Williams paras “0076-0083” “each of the sensors 940 are expected to operate at a minimum performance threshold. The aircraft 1000 monitors the data by comparing the outputs to the minimum performance threshold”, “When the outputs do not meet the minimum performance threshold”, “first threshold measures the minimum performance threshold of the sensors 940 and a second threshold measures an optimal performance threshold of the sensors 940” and “based on the monitored data not meeting at least one performance threshold, the aircraft 1000 adjusts the DAA outputs”).
It would have been obvious to a person having ordinary skill in the art before the effective filing date of the claimed invention to modify the invention of Dawson-Townsend for adaptive sense and avoid system to monitor sensor performance against predefined detection thresholds as taught by Williams (paras. [0076-0082]) in order to ensure reliable obstacle detection and system integrity and also adjusting the sensor operation to maintain safe aircraft operation.
Regarding claim 2, Dawson-Townsend discloses wherein a preset plurality of sensor perception models is stored in the control unit, and the control unit is configured to select, based on the weather information, a sensor perception model from the preset plurality of sensor perception models by means of a look-up table; or an algorithm for building or determining a sensor perception model based on the weather information is stored in the control unit (see Dawson-Townsend paras “0049”, “0064-0065” and “0079” “one or more aircraft processors 124 communicatively coupled with at least one memory device 128, a flight controller 126, a wireless transceiver 130, and a navigation system 142. The aircraft processor 124 may be configured to perform one or more operations based at least in part on instructions (e.g., software) and one or more databases stored to the memory device 128 (e.g., hard drive, flash memory, or the like)”, “Obstacle detection circuit 202 may be used to correlate data (e.g., using internal algorithms) from multiple sensors to refine obstacle location, and to determine the threat level of detected obstacles… one or more machine learning techniques may be employed”, “the obstacle detection circuit 202 can use airspace data from the airspace database 224 a to refine the detection algorithms based on the location of the aircraft 100 in relation to different types of regulated airspace. In another example, the obstacle detection circuit 202 can use environmental data from the environmental database 224 b refine the detection algorithms based on environmental factors such as time of year, day of week, time of day, climate and weather conditions, etc” and “The one or more sensors may also be used to determine the current weather”).
Regarding claim 3, Dawson-Townsend teaches wherein the aircraft ground anti-collision system further comprises a human-machine interface configured to input a pilot instruction to the control unit by a pilot (see Dawson-Townsend paras “0051”, “0056”, “0069-0070” and “0081” “The remote device 138 serves as a primary channel of communication between the pilot and the ASA system 200, enabling the user to, where desired, command tasks to and receive feedback or instructions from the ASA system 200… The remote device 138 serves as a primary channel of communication between the pilot and the ASA system 200”, “an adaptive sense and avoid (ASA) system 200 for the automatic detection and avoidance of obstacles”, “The obstacle detection circuit 202 may also set any sensor modes 208 as necessary”, “the obstacle detection circuit 202 sets weighting factors for evaluating the obstacle data coming from the sensors” and “the obstacle detection circuit 202 generates threat information and reports the data reflecting the detected obstacles”),
the control unit is configured to determine a sensor perception model based on the pilot instruction (see Kunes para “0051” “The remote device 138 serves as a primary channel of communication between the pilot and the ASA system 200, enabling the user to, where desired, command tasks to and receive feedback or instructions from the ASA system 200. The remote device 138 may give visual and auditory alerts to direct the pilot's attention to a particular alert”),
and the control unit is further configured to output the obstacle detection result to the pilot via the human-machine interface (see Dawson-Townsend para “0051” “The remote device 138 may give visual and auditory alerts to direct the pilot's attention to a particular alert”).
Regarding claim 4, Dawson-Townsend discloses wherein the human-machine interface comprises an aircraft instrument and/or a head-up display (see Dawson-Townsend paras “0069-0071” “The remote device 138 provides a control and communication interface for the user. The remote device 138 may be configurable to operate as a manager that enables the user to monitor, direct, and control the ASA system 200. The remote device 138 can be used to enable a user to input tasks, constraints, revise task assignment lists, update software/firmware, etc. The remote device 138 may include a touch screen graphical user interface (“GUI”) and/or speech-recognition systems. The remote device 138 may employ, for example, a tablet computer, a laptop computer, a smart phone”).
Regarding claim 5, Dawson-Townsend discloses wherein the aircraft ground anti-collision system is configured to operate in a cooperative mode and/or a non-cooperative mode, wherein in the cooperative mode, an aircraft equipped with the aircraft ground anti-collision system and a cooperatively communicable obstacle communicate with each other, and the human-machine interface is configured to provide a global view in which a position of the cooperatively communicable obstacle is displayed; wherein in the non-cooperative mode, the aircraft equipped with the aircraft ground anti-collision system autonomously senses an obstacle around the aircraft, and the human-machine interface is configured to provide a local view in which the obstacle autonomously sensed is displayed (see Dawson-Townsend paras “0004”, “0047”, “0051”, “0061” and “0072” “a cooperative target sends out its location and heading (e.g., GPS location and velocity vector) to other aircraft via radio (e.g., using ADS-B or other methods)”, “Accordingly, the plurality of sensors 110 would enable the aerial vehicle 100 to detect a threat of collision on any side of the aerial vehicle 100, effectively providing a 360 degree field of view around the aerial vehicle 100.”, “The remote device 138 provides a control and communication interface for the user… The remote device 138 may include a touch screen graphical user interface (“GUI”)”, “The plurality of obstacle sensors 226 may comprise, for example, cooperative obstacle sensors 226 a to detect cooperative obstacle (e.g., another aircraft having a cooperative transmitter or transceiver) and/or non-cooperative obstacle sensors 226 b to detect non-cooperative obstacle. The cooperative obstacle sensors 226 a may be used to detect obstacles (e.g., other air traffic) using, for example, a radio-frequency transceiver configured to communicated using one or more of various protocols, including ADS-B, TCAS, TAS, etc”).
Regarding claim 9, Dawson-Townsend discloses wherein, the control unit is configured to: after controlling the one or more sensors to operate in the enhanced mode, redetermine the weight of the detection result outputted by the one or more sensors under the condition of the determined sensor perception model (see Dawson-Townsend paras “0069-0071” and “0080-0081” “set obstacle detection weights 210 based on current state and environment”, “Using weighted sensor data, the obstacle detection circuit 202 can evaluate incoming obstacle data”, “the obstacle detection circuit 202 may assign weights to the various sensors 110 (e.g., obstacle sensors 226). For example, if the weather is clear (e.g., high visibility), the ASA system 200 may set obstacle detection weights that favor the sensor data from vision-based obstacle sensors” and “Although it is possible to detect an obstacle using multiple sensors (e.g., both the vision and radar sensors), where the weighting factor favors the vision-based system, the vision-based system is given preference (or priority) when evaluating the sensor data from both sensors. At step 312, the obstacle detection circuit 202 generates threat information and reports the data reflecting the detected obstacles to the avoidance maneuver trajectory circuit 204… where the process repeats.” Regarding the obstacle detection circuit assigns weighting factors to sensor data based on aircraft state and environment and evaluates obstacle data using those weights and any change in sensor operating mode results in reassignment of weighting factors (i.e., redetermine the weight)).
Regarding claim 10, Dawson-Townsend discloses wherein the aircraft ground anti-collision system further comprises a risk evaluating unit comprising a processor communicatively coupled to the control unit and configured to perform risk evaluation based on the obstacle detection result outputted by the control unit and issue warning information to a pilot based on an evaluated risk level (see Dawson-Townsend paras “0056”, “0060-0064” “The ASA system 200 can also pass warning alerts and status information to any ground operator or supervisor via, for example, a remote device 138 at a ground control station (GCS) 230 through an existing datalink on the aircraft 100, such as network 136. More specifically, the obstacle detection circuit 202 may send obstacle alerts to the GCS 230, while the avoidance maneuver trajectory circuit 204 may send avoidance maneuver information to the GCS 230”, “the obstacle sensors 226 may assign a threat level (priority level) to one or more (or all) of possible obstacle threats” and “Obstacle detection circuit 202 may be used to correlate data (e.g., using internal algorithms) from multiple sensors to refine obstacle location, and to determine the threat level of detected obstacles”).
Regarding claim 12, Dawson-Townsend discloses wherein the plurality of sensors in the obstacle detecting unit comprises at least two of: millimeter wave radar, LiDAR, a conventional camera, an infrared camera, a position sensor, or an ultrasound sensor, and/or wherein the information source comprises one or more aviation weather information broadcast of: a global forecast system, an automatic terminal information service, a meteorological terminal aviation routine weather report, a special weather report, a terminal aerodrome forecast (see Dawson-Townsend paras “0046” and “0061” “The non-cooperative obstacle sensors 226 b may detect obstacles (e.g., other air traffic) using, for example, radar-based systems, electro-optical systems (e.g., LIDAR), infrared systems, acoustic systems, vision-based systems, etc”).
Regarding claim 13, Dawson-Townsend discloses an aircraft ground anti-collision method, comprising (see Dawson-Townsend paras “0003-0004” “The commercial aviation industry has, however, adopted a traffic collision avoidance system (“TCAS”) as a standard to avoid collisions, which allows cooperative aircraft to locate and avoid each other”),
obtaining weather information (see Dawson-Townsend paras “0057-0058” “For example, in addition to altitude, geographic area, and/or airspace, the ASA system 200 may further adapt the fusion of sensors as a function of the time of day, current weather, and season of the year” and “The ASA system 200 may also take into account weather conditions when calculating obstacle avoidance maneuvers. For example, the ASA system 200 may account for ambient winds or density altitude when determining optimal trajectories, and avoiding weather hazards in the immediate vicinity”),
determining a sensor perception model based on the weather information (see Dawson-Townsend paras “0057”, “0070-0071” and “0079-0080” “the ASA system 200 may further adapt the fusion of sensors as a function of the time of day, current weather, and season of the year… such as weighting of the different sensors”, “The one or more sensors may also be used to determine the current weather” and “Based on the state of the aircraft 100 and the surrounding environment… At step 308, the obstacle detection circuit 202 may assign weights to the various sensors 110 (e.g., obstacle sensors 226). For example, if the weather is clear (e.g., high visibility), the ASA system 200 may set obstacle detection weights that favor the sensor data from vision-based obstacle sensors” regarding determining current weather conditions and adapts the sensor fusion and weighting strategy as a function of those weather conditions (i.e., sensor perception model)),
and setting, based on the sensor perception model, a weight of a detection result outputted by each of sensors in an obstacle detecting unit of an aircraft and outputting an obstacle detection result (see Dawson-Townsend paras “0070-0071” and “0081” “The obstacle detection circuit 202 can also set obstacle detection weights 210 based on current state and environment, as well as currently-active sensors… if current weather conditions include poor visibility, data from a radar sensor may be given a greater weight than data from a vision-based sensor”, “Using weighted sensor data, the obstacle detection circuit 202 can evaluate incoming obstacle data… can use the obstacle detection weights to cross-check and refine the relative position of the obstacle” and “the obstacle detection circuit 202 generates threat information and reports the data reflecting the detected obstacles”)
wherein the obstacle detecting unit comprises a plurality of sensors configured to detect position information of an obstacle around the aircraft (see Dawson-Townsend para “0007” “a plurality of sensors coupled to the aerial vehicle, each of the plurality of sensors configured to generate sensor data reflecting a position of an obstacle in the environment; an obstacle detection circuit operatively coupled to the processor and the plurality of sensors, the obstacle detection circuit configured to blend the sensor data from each of the plurality of sensors to identify obstacles in the environment and to generate obstacle information that reflects a best estimate of a position of the obstacle in the environment”),
controlling an operating mode and/or an operating parameter of at least one of the sensors in the obstacle detecting unit based on the sensor perception model (see Dawson-Townsend paras “0069-0071” “obstacle detection circuit 202 may also set any sensor modes 208 as necessary… as a function of the current aircraft state and environment” and “obstacle detection weights 210 based on current state and environment, as well as currently-active sensors 226. Based on the environmental factors described above, the obstacle detection circuit 202 sets weighting factors for evaluating the obstacle data coming from the sensors”).
Dawson-Townsend fails to explicitly teach wherein in a case that it is determined that a weight of a detection result outputted by one or more of the sensors in the obstacle detecting unit under a condition of the sensor perception model is below a predetermined threshold, the one or more sensors are controlled to operate in an enhanced mode.
However, Williams teaches wherein in a case that it is determined that a weight of a detection result outputted by one or more of the sensors in the obstacle detecting unit under a condition of the sensor perception model is below a predetermined threshold, the one or more sensors are controlled to operate in an enhanced mode (see Williams paras “0076-0083” “each of the sensors 940 are expected to operate at a minimum performance threshold. The aircraft 1000 monitors the data by comparing the outputs to the minimum performance threshold”, “When the outputs do not meet the minimum performance threshold”, “first threshold measures the minimum performance threshold of the sensors 940 and a second threshold measures an optimal performance threshold of the sensors 940” and “based on the monitored data not meeting at least one performance threshold, the aircraft 1000 adjusts the DAA outputs”).
It would have been obvious to a person having ordinary skill in the art before the effective filing date of the claimed invention to modify the invention of Dawson-Townsend for adaptive sense and avoid system to monitor sensor performance against predefined detection thresholds as taught by Williams (paras. [0076-0082]) in order to ensure reliable obstacle detection and system integrity and also adjusting the sensor operation to maintain safe aircraft operation.
Regarding claim 14, Dawson-Townsend teaches obtaining a pilot instruction (see Dawson-Townsend paras “0051”, “0056”, “0069-0070” and “0081” “The remote device 138 serves as a primary channel of communication between the pilot and the ASA system 200, enabling the user to, where desired, command tasks to and receive feedback or instructions from the ASA system 200… The remote device 138 serves as a primary channel of communication between the pilot and the ASA system 200”, “an adaptive sense and avoid (ASA) system 200 for the automatic detection and avoidance of obstacles”, “The obstacle detection circuit 202 may also set any sensor modes 208 as necessary”, “the obstacle detection circuit 202 sets weighting factors for evaluating the obstacle data coming from the sensors” and “the obstacle detection circuit 202 generates threat information and reports the data reflecting the detected obstacles”),
and determining a sensor perception model based on the pilot instruction (see Kunes para “0051” “The remote device 138 serves as a primary channel of communication between the pilot and the ASA system 200, enabling the user to, where desired, command tasks to and receive feedback or instructions from the ASA system 200. The remote device 138 may give visual and auditory alerts to direct the pilot's attention to a particular alert”).
Regarding claim 17, Dawson-Townsend discloses wherein, after the one or more sensors are controlled to operate in the enhanced mode, the weight of the detection result outputted by the one or more sensors under the condition of the sensor perception model is redetermined (see Dawson-Townsend paras “0069-0071” and “0080-0081” “set obstacle detection weights 210 based on current state and environment”, “Using weighted sensor data, the obstacle detection circuit 202 can evaluate incoming obstacle data”, “the obstacle detection circuit 202 may assign weights to the various sensors 110 (e.g., obstacle sensors 226). For example, if the weather is clear (e.g., high visibility), the ASA system 200 may set obstacle detection weights that favor the sensor data from vision-based obstacle sensors” and “Although it is possible to detect an obstacle using multiple sensors (e.g., both the vision and radar sensors), where the weighting factor favors the vision-based system, the vision-based system is given preference (or priority) when evaluating the sensor data from both sensors. At step 312, the obstacle detection circuit 202 generates threat information and reports the data reflecting the detected obstacles to the avoidance maneuver trajectory circuit 204… where the process repeats.” Regarding the obstacle detection circuit assigns weighting factors to sensor data based on aircraft state and environment and evaluates obstacle data using those weights and any change in sensor operating mode results in reassignment of weighting factors (i.e., redetermine the weight)).
Regarding claim 18, Dawson-Townsend discloses displaying, via a human-machine interface, a global view and/or a local view, wherein a position of a cooperatively communicable obstacle, obtained by the aircraft and the cooperatively communicable obstacle communicating with each other, is displayed in the global view; and an obstacle autonomously sensed by the sensors of the aircraft is displayed in the local view, and automatically displaying the local view in a case that an obstacle is sensed within a predetermined distance around the aircraft (see Dawson-Townsend paras “0004”, “0047”, “0051”, “0061” and “0072” “a cooperative target sends out its location and heading (e.g., GPS location and velocity vector) to other aircraft via radio (e.g., using ADS-B or other methods)”, “Accordingly, the plurality of sensors 110 would enable the aerial vehicle 100 to detect a threat of collision on any side of the aerial vehicle 100, effectively providing a 360 degree field of view around the aerial vehicle 100.”, “The remote device 138 provides a control and communication interface for the user… The remote device 138 may include a touch screen graphical user interface (“GUI”)”, “The plurality of obstacle sensors 226 may comprise, for example, cooperative obstacle sensors 226 a to detect cooperative obstacle (e.g., another aircraft having a cooperative transmitter or transceiver) and/or non-cooperative obstacle sensors 226 b to detect non-cooperative obstacle. The cooperative obstacle sensors 226 a may be used to detect obstacles (e.g., other air traffic) using, for example, a radio-frequency transceiver configured to communicated using one or more of various protocols, including ADS-B, TCAS, TAS, etc”).
Regarding claim 20, Dawson-Townsend discloses wherein the sensors in the obstacle detecting unit comprise at least two of: millimeter wave radar, LiDAR, a conventional camera, an infrared camera, a position sensor, or an ultrasound sensor, and/or wherein an information source for obtaining the weather information comprises one or more aviation weather information broadcast of: a global forecast system, an automatic terminal information service, a meteorological terminal aviation routine weather report, a special weather report, a terminal aerodrome forecast (see Dawson-Townsend paras “0046” and “0061” “The non-cooperative obstacle sensors 226 b may detect obstacles (e.g., other air traffic) using, for example, radar-based systems, electro-optical systems (e.g., LIDAR), infrared systems, acoustic systems, vision-based systems, etc”).
Claim 6 is rejected under 35 U.S.C. 103 as being unpatentable in view of Dawson-Townsend (US 2021/0295722 A1) in view of Williams et al (US 2022/0365545 A1) in view of Khatwa (US 2006/0238376 A1).
Regarding claim 6, Dawson-Townsend fails to explicitly disclose wherein the human-machine interface is configured to automatically display the local view in a case that an obstacle is sensed within a predetermined distance around the aircraft.
However, Khatwa teaches wherein the human-machine interface is configured to automatically display the local view in a case that an obstacle is sensed within a predetermined distance around the aircraft (see Khatwa figure 2 and paras “0015”, “0017-0019” and “0021” “The TAD 44 is generally configured to display a symbolic representation 46 of the aircraft, and a viewing sector 48 that extends radially outwardly from the symbolic representation 46 of the aircraft. The TAD 44 is also configured to display terrain obstructions, aircraft traffic, navigational information and/or weather obstructions within a predetermined range and bearing relative to the aircraft.”, “the viewing sector 48 also includes at least one first ground obstruction symbol 54 that represents a ground obstacle” and “the first display mode (wherein the ground obstruction symbols are excluded from view) is automatically overridden when one or more ground obstruction symbols 72 are within a predetermined range and bearing relative to the aircraft”).
It would have been obvious to a person having ordinary skill in the art before the effective filing date of the claimed invention to modify the invention of Dawson-Townsend for adaptive sense and avoid system to automatically present obstacles within a defined proximity relative to the aircraft as taught by Khatwa (paras. [0017-0019]) in order to reduce display clutter and improve pilot situational awareness and safety.
Claims 11 and 19 are rejected under 35 U.S.C. 103 as being unpatentable in view of Dawson-Townsend (US 2021/0295722 A1) in view of Williams et al (US 2022/0365545 A1) in view of Rangan (US 11,661,195 B2).
Regarding claim 11, Dawson-Townsend fails to explicitly disclose wherein the risk evaluating unit is configured to: in a case that the risk evaluating unit determines that an automatic driving mode of the aircraft is not suitable for a current weather condition, confirm to the pilot whether to disable the automatic driving mode.
However, Rangan teaches wherein the risk evaluating unit is configured to: in a case that the risk evaluating unit determines that an automatic driving mode of the aircraft is not suitable for a current weather condition, confirm to the pilot whether to disable the automatic driving mode (see Rangan col 37, lines 36-46 “Similarly, based on the updated predicted fatigue profile 450 for the pilot and co-pilot, the co-pilot is predicted to experience fatigue levels 444 above the threshold level 404 during the hazardous weather event 406 b and the pilot is predicted to experience fatigue levels 414 below the threshold level 404 during the hazardous weather event 406 b. In response, if the aircraft is being controlled by the co-pilot prior to the expected hazardous weather event 406 b, the control of the aircraft will be automatically switched to the pilot during the times correlating to the hazardous weather event 406 b.”).
It would have been obvious to a person having ordinary skill in the art before the effective filing date of the claimed invention to modify the invention of Dawson-Townsend for adaptive sense and avoid system to confirm or disable automatic driving in response to adverse weather or risk conditions as taught by Rangan (col 37, lines 36-46) in order to improve flight safety and prevent operation under unsuitable control modes.
Regarding claim 19, Dawson-Townsend discloses performing risk evaluation based on the obstacle detection result and issue warning information to a pilot based on an evaluated risk level (see Dawson-Townsend paras “0056”, “0060-0064” “The ASA system 200 can also pass warning alerts and status information to any ground operator or supervisor via, for example, a remote device 138 at a ground control station (GCS) 230 through an existing datalink on the aircraft 100, such as network 136. More specifically, the obstacle detection circuit 202 may send obstacle alerts to the GCS 230, while the avoidance maneuver trajectory circuit 204 may send avoidance maneuver information to the GCS 230”, “the obstacle sensors 226 may assign a threat level (priority level) to one or more (or all) of possible obstacle threats” and “Obstacle detection circuit 202 may be used to correlate data (e.g., using internal algorithms) from multiple sensors to refine obstacle location, and to determine the threat level of detected obstacles”).
But Dawson-Townsend fails to explicitly disclose in a process of the risk evaluation, in a case that it is determined that an automatic driving mode of the aircraft is not suitable for a current weather condition, confirming to the pilot whether to disable the automatic driving mode.
However, Rangan teaches in a process of the risk evaluation, in a case that it is determined that an automatic driving mode of the aircraft is not suitable for a current weather condition, confirming to the pilot whether to disable the automatic driving mode (see Rangan col 37, lines 36-46 “Similarly, based on the updated predicted fatigue profile 450 for the pilot and co-pilot, the co-pilot is predicted to experience fatigue levels 444 above the threshold level 404 during the hazardous weather event 406 b and the pilot is predicted to experience fatigue levels 414 below the threshold level 404 during the hazardous weather event 406 b. In response, if the aircraft is being controlled by the co-pilot prior to the expected hazardous weather event 406 b, the control of the aircraft will be automatically switched to the pilot during the times correlating to the hazardous weather event 406 b.”).
It would have been obvious to a person having ordinary skill in the art before the effective filing date of the claimed invention to modify the invention of Dawson-Townsend for adaptive sense and avoid system to confirm or disable automatic driving in response to adverse weather or risk conditions as taught by Rangan (col 37, lines 36-46) in order to improve flight safety and prevent operation under unsuitable control modes.
Claims 21 are rejected under 35 U.S.C. 103 as being unpatentable in view of Dawson-Townsend (US 2021/0295722 A1) in view of Williams et al (US 2022/0365545 A1) in view of Zheng et al (US 2020/0394924 6 A1).
Regarding claim 21, Dawson-Townsend fails to explicitly disclose wherein the control unit is configured to apply noise reduction to the detection results directly outputted by the obstacle detecting unit.
However, Zheng teaches wherein the control unit is configured to apply noise reduction to the detection results directly outputted by the obstacle detecting unit (see Zheng paras “0026-0027”, “0030”, “”0062-0065 and “0092-0093” “influence of the noise to judgment of the obstacle may be reduced, and accuracy of judgment of the obstacle area may be improved”).
It would have been obvious to a person having ordinary skill in the art before the effective filing date of the claimed invention to modify the invention of Dawson-Townsend for adaptive sense and avoid system to reduce the influence of noise in the detection results as taught by Zheng (paras. [0092-0093]) in order to improve the accuracy of obstacle detection.
Regarding claim 22, Dawson-Townsend fails to explicitly disclose wherein after noise reduction, the detection result of a sensor originally operating in a normal mode under the current weather information is judged by the control unit to be too inaccurate to be adopted.
However, Williams teaches wherein after noise reduction, the detection result of a sensor originally operating in a normal mode under the current weather information is judged by the control unit to be too inaccurate to be adopted (see Williams paras “0076-0083” “Sensor performance meeting the minimum performance threshold without also meeting the optimal performance threshold can indicate degradation of or a potential problem with the sensor 940, but that the sensor 940 remains at least party serviceable. For example, outputs that meet the minimum performance threshold without also meeting the optimal performance threshold can be due to environmental conditions, such as weather, electrical or mechanical issues, or in some instances, operator error”, “In implementations where the probability of detection and the false alarm rate are monitored, the monitored outputs can include, but are not limited to, ambient RF noise, image texture noise, and ambient audio noise” and “For example, based on cloud coverage surrounding the aircraft 1000 or the location of the sun on the horizon, one of the sensors 940 can be temporarily unreliable. Accordingly, the inputs from the particular sensor 940 can be ignored for a period of time to provide more reliable calculations and the DAA outputs are adjusted accordingly”).
It would have been obvious to a person having ordinary skill in the art before the effective filing date of the claimed invention to modify the invention of Dawson-Townsend for adaptive sense and avoid system to monitor sensor performance against predefined detection thresholds as taught by Williams (paras. [0076-0082]) in order to ensure reliable obstacle detection and system integrity and also adjusting the sensor operation to maintain safe aircraft operation.
Conclusion
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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/HOSSAM M ABD EL LATIF/Primary Examiner, Art Unit 3664
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