阅读说明：本技术 用于感测外部对象的交通工具监控系统和方法 (vehicle monitoring system and method for sensing external objects ) 是由 A·斯托赫克 于 2017-03-31 设计创作，主要内容包括：用于交通工具(10)的监控系统(5)具有传感器(20、30),其用于感测交通工具周围对象(15)的存在用于避免碰撞、导航或其他目的。传感器(20)(称为“主传感器”)中的至少一个可以被配置成感测其视场(25)内的对象并提供指示被感测对象的数据。监控系统可以使用这种数据,以追踪被感测对象。验证传感器(30)(例如雷达传感器)可以被不时地使用以验证来自主传感器的数据,而不以来自验证传感器的数据追踪交通工具周围的对象。(A monitoring system (5) for a vehicle (10) has sensors (20, 30) for sensing the presence of objects (15) surrounding the vehicle for collision avoidance, navigation or other purposes. At least one of the sensors (20) (referred to as a "primary sensor") may be configured to sense an object within its field of view (25) and provide data indicative of the sensed object. The monitoring system may use this data to track the sensed object. Verification sensors (30), such as radar sensors, may be used from time to verify data from the master sensors without tracking objects around the vehicle with data from the verification sensors.)

1. A vehicle monitoring system (5), comprising:

A plurality of sensors (20) positioned on an aircraft (10) and configured to sense an object (15) outside the aircraft within a field of view (25) of the plurality of sensors, wherein the field of view completely surrounds the aircraft, and wherein the plurality of sensors are configured to provide first data indicative of the object;

At least one radar sensor (30) positioned on the aircraft and configured to sense the object, wherein the at least one radar sensor is configured to provide second data indicative of the object; and

At least one processor (310) configured to track the object sensed by the plurality of sensors based on the first data, the at least one processor configured to perform a comparison between the first data and the second data and determine whether to validate the accuracy of the first data based on the comparison without tracking the object with the second data, wherein the at least one processor is configured to provide an alert based on the comparison if the first data fails to accurately indicate the location of the object sensed by the radar sensor.

2. a vehicle monitoring system (5), comprising:

a first sensor (20) positioned on a vehicle (10), the first sensor configured to sense an object (15) within a field of view (25) of the first sensor and provide first data indicative of a location of the object, wherein the object is external to the vehicle;

a radar sensor (30) positioned on the vehicle, the radar sensor configured to sense the object within the field of view and provide second data indicative of a position of the object; and

At least one processor (310) configured to track the object using the first data from the first sensor, the at least one processor configured to compare a sample of the first data and a sample of the second data to determine whether to validate the accuracy of the first data from the first sensor without tracking the object using the second data, wherein the at least one processor is configured to provide an alert in response to a difference between the first data and the second data.

3. the system of claim 2, wherein the first sensor is an optical sensor.

4. the system of claim 2, wherein the vehicle is an aircraft.

5. The system of claim 2, wherein the vehicle is an automobile.

6. the system of claim 2, further comprising a vehicle controller (220), the vehicle controller (220) configured to control a speed or direction of the vehicle based on the first data.

7. The system of claim 2, wherein the at least one processor is configured to determine whether the object poses a collision threat to the vehicle based on the first data.

8. The system of claim 2, wherein the at least one processor is configured to compare the location indicated by the first data with the location indicated by the second data.

9. The system of claim 2, further comprising a third sensor (20) coupled to the vehicle, the third sensor configured to sense a second object (15) within a field of view (25) of the third sensor and provide third data indicative of a location of the second object, wherein the second object is external to the vehicle, wherein the radar sensor is configured to sense the second object within the field of view of the third sensor, wherein the second data is indicative of a location of the second object, wherein the at least one processor is configured to track the second object using the third data from the third sensor, wherein the at least one processor is configured to compare samples of the third data and samples of the second data to confirm accuracy of the third data from the third sensor, without tracking the second object using the second data, and wherein the at least one processor is configured to provide an alert in response to a difference between the third data and the second data.

10. A vehicle monitoring method, comprising:

Sensing an object (15) within a field of view (25) of a first sensor (20) positioned on a vehicle (10), wherein the object is external to the vehicle;

Providing first data indicative of a location of the object based on the sensing with the first sensor;

Sensing the object within the field of view with a radar sensor positioned on the vehicle;

providing second data indicative of a location of the object based on the sensing with the radar sensor;

Tracking, with at least one processor (310), the object using the first data from the first sensor;

Comparing, with the at least one processor, a sample of the first data and a sample of the second data;

Determining a difference between the first data and the second data based on the comparison;

Determining, with the at least one processor, whether to validate the accuracy of the first data based on the difference without tracking the object with the second data; and

Providing a warning based on the determined difference.

11. The method of claim 10, wherein the first sensor is an optical sensor.

12. The method of claim 10, wherein the vehicle is an aircraft.

13. The method of claim 10, wherein the vehicle is an automobile.

14. The method of claim 10, further comprising controlling a speed or direction of the vehicle based on the first data.

15. The method of claim 10, further comprising determining, with the at least one processor, whether the object poses a collision threat to the vehicle based on the first data.

16. The method of claim 10, further comprising:

Sensing a second object (15) within a field of view (25) of a third sensor (20) positioned on the vehicle, wherein the second object is external to the vehicle;

Providing third data indicative of a location of the second object based on the sensing with the third sensor;

Sensing the second object within the field of view of the third sensor with the radar sensor, wherein the second data is indicative of a location of the second object;

Comparing, with the at least one processor, the sample of the third data and the sample of the second data;

determining a second difference between the third data and the second data based on comparing the sample of the third data and the sample of the second data;

Determining, with the at least one processor, whether to validate the accuracy of the third data based on the second difference without tracking the second object with the second data; and

providing an alert based on the determined second difference.

Background

Many vehicles have sensors for sensing external objects for various purposes. For example, a driver or pilot of a vehicle (e.g., an automobile, a watercraft, or an aircraft) may encounter a wide variety of collision risks, such as debris, other vehicles, equipment, buildings, birds, terrain, and other objects. Collisions with any such object may cause significant damage to the vehicle and, in some cases, injury to personnel on the vehicle. Sensors can be used to detect objects that pose a risk of collision and alert the driver or pilot of the detected risk of collision. If the vehicle is self-driving or self-flying, sensor data indicative of objects around the vehicle may be used by the controller to avoid collisions with detected objects. In other examples, objects may be sensed and identified for use in assisting in navigation and control of the vehicle in other ways.

to ensure safe and efficient operation of the vehicle, it is desirable that the sensors used to detect external objects be accurate and reliable. However, ensuring reliable operation of such sensors in all situations can be difficult. Taking an aircraft as an example, there may be a large number of objects in its vicinity, and such objects may be positioned in any direction of the aircraft. Further, such objects may be moving rapidly relative to the aircraft, and any failure to accurately detect an object or its position may be a disaster. Sensors that can reliably detect objects under such conditions can be expensive or subject to burdensome regulatory restrictions.

Improved techniques for reliably detecting objects in the vicinity of a vehicle are generally desired.

Drawings

the present disclosure can be better understood with reference to the following drawings. The elements of the drawings are not necessarily to scale relative to each other, emphasis instead being placed upon illustrating the principles of the disclosure.

Fig. 1 depicts a top perspective view of a vehicle having a vehicle monitoring system according to some embodiments of the present disclosure.

Fig. 2 depicts a three-dimensional perspective view of the vehicle depicted in fig. 1.

Fig. 3 depicts a top perspective view of the vehicle depicted in fig. 1.

FIG. 4 is a block diagram illustrating various components of a vehicle monitoring system according to some embodiments of the present disclosure;

FIG. 5 is a block diagram illustrating data processing elements for processing sensor data according to some embodiments of the present disclosure; and

fig. 6 is a flow chart illustrating a method for validating sensor data in accordance with some embodiments of the present disclosure.

Detailed Description

The present disclosure relates generally to vehicle monitoring systems and methods for sensing external objects. In some embodiments, a vehicle includes a vehicle monitoring system having sensors for sensing the presence of objects around the vehicle for collision avoidance, navigation, or other purposes. At least one of the sensors is configured to sense an object within a field of view of the sensor and provide sensor data indicative of the sensed object. The vehicle may then be controlled based on the sensor data. As one example, the speed or direction of the vehicle may be controlled to avoid collisions with the sensed object, to navigate the vehicle to a desired position relative to the sensed object, or to control the vehicle for other purposes.

To help ensure safe and efficient operation of a vehicle, it is generally desirable for a vehicle monitoring system to reliably and accurately detect and track objects around the vehicle, particularly objects that may be close enough to the vehicle to pose a significant collision threat. In some embodiments, the space around the vehicle is monitored by different types of sensors to provide sensor redundancy, thereby reducing the likelihood of missing an object within the monitored space. As one example, objects around a vehicle may be detected and tracked with a first type of sensor (hereinafter "primary sensor"), such as a LIDAR sensor or an optical camera, and a second type of sensor (hereinafter "verification sensor"), such as a radar sensor, may be used to verify the accuracy of the sensor data from the primary sensor. That is, data from the verification sensor may be compared to data from the primary sensor to confirm that the primary sensor accurately detected all objects within a given field of view. If there is a difference between the sensor data of the primary sensor and the data of the verification sensor (e.g., if the primary sensor fails to detect an object detected by the verification sensor, or if the location of the object detected by the primary sensor fails to match the location of the same object detected by the verification sensor), then at least one action can be taken in response to the difference. As one example, the vehicle can be controlled to steer away from the zone corresponding to the discrepancy, or the confidence in the sensor data from the primary sensor can be changed (e.g., decreased) in the control algorithm used to control the vehicle.

In some embodiments, a radar sensor is used as a verification sensor to verify the data of the primary sensor. Such radar sensors can be used to detect and track objects similar to the primary sensor, if desired. However, the use of radar sensors in aircraft to track objects may be regulated, thereby increasing the cost or burden associated with using radar sensors in such applications. In some embodiments, radar sensors are used to verify sensor data from the primary sensor from time to time without actually tracking the detected object over time with the radar sensors. That is, the primary sensor is used to track objects around the vehicle, and the radar sensor is used from time to provide data samples indicative of the objects currently around the aircraft. This sample is then compared to data from the primary sensor to confirm that the primary sensor accurately sensed the presence and location of each object within the field of view of the primary sensor. Thus, the radar sensor may be used to verify sensor data from the primary sensor from time to time without utilizing the radar sensor to track objects around the vehicle, thereby potentially avoiding at least some of the regulatory limitations associated with using the radar sensor. Moreover, using radar sensors in this manner (to verify sensor data from the primary sensor from time to time, rather than using data from the radar sensors for tracking) helps reduce the amount of data that needs to be processed or stored by the vehicle monitoring system.

fig. 1 depicts a top perspective view of a vehicle 10 having a vehicle monitoring system 5, the vehicle monitoring system 5 for sensing objects around the vehicle 10, according to some embodiments of the present disclosure. The system 5 has a plurality of sensors 20, 30 to detect objects 15 within a certain range in the vicinity of the vehicle 10, such as objects 15 approaching the path of the vehicle 10. The system 5 may determine that the object 15 poses a threat to the vehicle 10, for example, when the object 15 has a position or velocity that will cause it to approach the path of the vehicle 10 or to be within its path as the object 15 travels. In such a case, the vehicle 10 may provide a warning to the pilot or driver, or autonomously take evasive action to avoid the object 15. In other examples, the system 5 may use detection of the object 15 for other purposes. As one example, the system 5 may use the detected object 15 as a reference point to navigate the vehicle 10 or to control the vehicle during takeoff or landing when the vehicle 10 is an aircraft.

In some embodiments, the vehicle 10 may be an aircraft as depicted in fig. 1, but other types of vehicles 10 are possible in other embodiments. The vehicle 10 may be manned or unmanned and may be configured to operate under control from a variety of sources. For example, the vehicle 10 may be an aircraft (e.g., an airplane or helicopter) controlled by a human pilot (which may be located on the vehicle 10). In other embodiments, the vehicle 10 may be configured to operate under remote control, such as by communicating with a remote pilot or driver by wireless (e.g., radio) communication. In some embodiments, the vehicle 10 may be self-flying or self-propelled (e.g., a drone). In the embodiment shown in fig. 1, the vehicle 10 is a Self-flying vertical takeoff and landing (VTOL) Aircraft, such as the Aircraft described in PCT application number PCT/US17/18182 entitled "Self-flying Aircraft for passenger or Cargo transport (Self-Piloted Aircraft for passenger or Cargo transport)" filed on day 16, 2 months 2017, which is incorporated herein by reference. Various other types of vehicles may be used in other embodiments, such as automobiles or watercraft.

The object 15 of fig. 1 is depicted as a single object having a particular size and shape, but it should be understood that the object 15 may have various characteristics. Furthermore, although fig. 1 depicts a single object 15, the airspace surrounding the vehicle 10 may include any number of objects 15. The object 15 may be stationary, for example when the object 15 is a building, but in some embodiments the object 15 is capable of moving. For example, the object 15 may be another vehicle moving along a path that may constitute a risk of collision with the vehicle 10. The object 15 may be other obstacles that pose a risk to the safe operation of the vehicle 10 in other embodiments, or the object 15 may be used for navigation or other purposes during operation of the vehicle 10.

In some embodiments, the object 15 may be one of tens, hundreds, or even thousands of other aircraft that the vehicle 10 may encounter at different times while it is traveling. For example, when the vehicle 10 is a self-flying VTOL aerial vehicle, it may be common for other similar self-flying VTOL aerial vehicles to operate nearby. In some areas (e.g., urban or industrial sites), the use of smaller unmanned aircraft may be common. In this regard, the vehicle monitoring system 5 needs to monitor the position and velocity of each of a large number of objects 15 within a certain range of the vicinity around the aircraft, determine if any of the objects present a collision threat, and if so, take action.

Fig. 1 also depicts a sensor 20 (hereinafter "primary sensor") having a field of view 25 in which the sensor 20 can detect the presence of an object 15, and the system 5 can use data from the sensor 20 to track the object 15 for various purposes, such as collision avoidance, navigation, or other purposes. Fig. 1 also depicts a sensor 30 (hereinafter referred to as a "verification sensor") having a field of view 35 in which the sensor 30 can sense the object 15. The fields of view 25 and 35 are depicted in fig. 1 as substantially overlapping, but the field of view 35 extends to a greater extent from the vehicle 10. In some embodiments, the field of view 35 of the verification sensor 30 may be larger than the field of view 25 of the primary sensor 20 (e.g., extend completely around the vehicle 10, as will be described in more detail below). In this regard, the data sensed by the verification sensor 30 may be used by the vehicle monitoring system 5 to validate the data sensed by the sensor 20 (e.g., to confirm detection of the one or more objects 15). It should be noted that, unless explicitly stated otherwise herein, the term "field of view" as used herein does not imply that the sensor is optical, but rather generally means that the sensor is capable of sensing an object over the area, regardless of the type of sensor employed.

The sensors 20 may be various types of sensors or combinations of various types of sensors to monitor the space around the vehicle 10. In some embodiments, the sensor 20 may sense the presence of the object 15 within the field of view 25 and provide sensor data indicative of the location of the object 15. Such sensor data may then be processed for various purposes, such as navigating the vehicle 10 or determining whether the object 15 poses a collision threat to the vehicle 10, as will be described in more detail below.

In some embodiments, the sensor 20 may include at least one camera to capture images of a scene and provide data defining the captured scene. Such data may define a plurality of pixels, where each pixel represents a portion of a captured scene and includes a color value and a set of coordinates indicating a location of the pixel within an image. This data may be analyzed by the system 5 to identify the object 15. In some embodiments, the system 5 has a plurality of primary sensors 20 (e.g., cameras), where each primary sensor 20 is configured to sense (e.g., focus on) an object (e.g., a lens with each camera having a different focal length) at different distances (e.g., 200m, 600m, 800m, 1km, etc.) within the field of view 25 relative to the other sensors 20. In other embodiments, a single sensor 20 may have one or more lenses configured to sense the different distances. In some embodiments, other types of sensors are possible. As one example, the sensor 20 may include any optical or non-optical sensor to detect the presence of an object, such as an electronic optical or infrared (EO/IR) sensor, a light detection and ranging (LIDAR) sensor, or other type of sensor.

As described above, the sensor 20 may have a field of view 25 that defines a space in which the sensor 20 may sense the object 15. The field of view 25 may cover various areas (including two-dimensional and three-dimensional spaces) and may have various shapes or contours. In some embodiments, the field of view 25 may be a three-dimensional space having dimensions that depend on the characteristics of the sensor 20. For example, where the sensor 20 includes one or more optical cameras, the field of view 25 may be related to an attribute of the camera (e.g., lens focal length, etc.). It should be noted, however, that in the embodiment of FIG. 1, the field of view 25 may not have a shape or profile that allows the sensor 20 to monitor the entire space surrounding the vehicle 10. In this regard, additional sensors may be used to extend the area in which the system 5 is able to detect objects, thereby enabling a sensing range that will enable safe self-flying operation of the vehicle 10.

It should be noted that the data from the sensor 20 may be used to perform a primary tracking operation of an object within the field of view 25 regardless of whether any additional sensors (e.g., the verification sensor 30) may sense all or a portion of the field of view 25. In this regard, the vehicle monitoring system 5 may rely primarily on sensor data from the sensors 20 to identify and track the object 15. As described herein, the system 5 may use data from other sensors in various ways (e.g., for verification, redundancy, or sensing enhancement purposes).

FIG. 1 shows an authentication sensor 30 having a field of view 35, the field of view 35 generally coinciding with the extent of the field of view 25 of the sensor 20. In some embodiments, verification sensor 30 comprises a radar sensor to provide data different from that provided by sensor 20, but which allows verification of data provided by sensor 20. In other words, the verification sensor 30 may be configured such that its field of view 35 allows the vehicle monitoring system 5 to perform validation (e.g., redundant sensing) of the object 15 within the field of view 25 of the sensor 20. For purposes of illustration, unless otherwise indicated, it shall be assumed hereinafter that each primary sensor 20 is implemented as a camera that captures images of a scene within its corresponding field of view, while the verification sensor 30 is implemented as a radar sensor having a field of view 35, the field of view 35 covering the field of view 25 of the primary sensor 20, although it should be emphasized that other types of sensors 20, 30 may be used as desired to achieve the functionality described herein.

When the verification sensor 30 is implemented as a radar sensor, the sensor 30 may have a transmitter for transmitting pulses into the space monitored by the sensor 30 and a receiver for receiving echoes reflected from objects 15 within the monitored space. Based on the echoes from the subject, the verification sensor 30 can estimate the size, shape, and location of the subject. In some embodiments, the verification sensor may be mounted at a fixed location on the vehicle 10, and if desired, multiple verification sensors 30 can be used to monitor different fields of view around the vehicle 10. When the vehicle 10 is an aircraft, the sensors 20, 30 may be configured to monitor in all directions surrounding the aircraft (including above and below the aircraft and all sides surrounding the aircraft). Thereby, an object approaching from an arbitrary angle can be detected by the main sensor 20 and the verification sensor 30. As one example, there may be multiple sensors 20, 30 oriented in various directions such that the composite field of view of all primary sensors 20 and the composite field of view of all verification sensors 30 completely surround the vehicle 10.

In some embodiments, the primary sensor 20 or the verification sensor 30 may be movable, enabling the sensors 20, 30 to monitor different fields of view at different times as the sensors 20, 30 move. As one example, the verification sensor 30 may be configured to be rotatable, thereby enabling a 360 degree field of view to be obtained. As the sensor 30 rotates, it takes measurements from different sectors. Further, after performing a 360 degree scan (or other angular scan) of the space surrounding the vehicle 10, the verification sensor 30 may change its height and perform another scan. By repeating this process, the verification sensor 30 may perform multiple scans at different heights to monitor the space surrounding the vehicle 10 in all directions. In some embodiments, multiple verification sensors 30 may be used to perform scans in different directions. As one example, the validation sensor 30 on the top surface of the vehicle 30 may perform a scan of a hemispherical region above the vehicle 10, and the validation sensor 30 on the bottom surface of the vehicle 30 may perform a scan of a hemispherical region below the vehicle 30. In such an example, the verification data from the two verification sensors 30 may be used to monitor the space within the complete sphere surrounding the vehicle 10, thereby enabling the object to be sensed regardless of its angle relative to the vehicle 10.

During operation of the vehicle 10, sensor data from the primary sensors 20 is analyzed to detect the presence of one or more objects 15 within the field of view 25 of the sensors. As one example, for each detected object, the sensor data may define a set of coordinates that indicate the location of the object relative to the vehicle 10 or some other reference point. The sensor data may also indicate other properties about the detected object, such as the size and/or shape of the object. Over time, sensor data is used to track the location of the object. As one example, for each sample of sensor data, the location and/or other attributes of the object may be stored, and multiple stored samples of this data showing the change in location of the object over time may be used to determine the velocity of the object. Based on the speed and position of the object, the vehicle 10 may be controlled according to a desired control algorithm. As one example, the speed or direction of the vehicle 10 may be controlled (automatically or manually) to avoid collisions with detected objects or to navigate the vehicle 10 to a desired location based on the location of the detected objects. For example, the detected objects may be used as reference points to guide the vehicle 10 to a desired destination or other location.

as described above, the verification data from the at least one verification sensor 30 may be used from time to verify the accuracy of the sensor data from the at least one primary sensor 20 by comparing samples captured simultaneously by the sensors 20, 30, as will be described in more detail below. In this regard, when verification of the sensor data is to occur, the verification sensor 30 may capture a sample of the verification data, wherein at least a portion of the verification data corresponds to the field of view 35 of the primary sensor 20. That is, the field of view 35 of the verification sensor 25 overlaps the field of view 25 of the primary sensor 20 to provide sensor redundancy such that a sample of verification data indicates whether the verification sensor 30 senses any object 15 located within the field of view 25 of the primary sensor 20.

Thus, when the object 15 is within the field of view 25 of the primary sensor 20, it should be sensed by both the primary sensor 20 and the verification sensor 30. The monitoring system 5 is configured to identify the object 15 in the sensor data sample from the primary sensor 20 and the verification data sample from the verification sensor 30 to confirm that both sensors 20, 30 detect the object 15. In addition, the monitoring system 5 also determines whether the location of the object 15 indicated by the sensor data sample from the primary sensor 20 matches (within a predefined tolerance) the location of the object 15 indicated by the verification data sample from the verification sensor 30. If each object detected by verification sensor 30 within field of view 25 of primary sensor 20 is also detected by primary sensor 20, and if the location of each object is the same in both samples (within a predefined tolerance), then monitoring system 5 validates the accuracy of the sensor data from primary sensor 20, thereby, as desired, making it possible to rely on primary sensor 20 to make control decisions. However, if an object detected by the verification sensor 30 within the field of view 25 of the primary sensor 20 is not detected by the primary sensor 20, or if the location of the detected object 15 in a sample of sensor data from the primary sensor 20 is different than the location of the same object 15 in a sample of verification data from the verification sensor 30, then the monitoring system 5 does not verify the accuracy of the sensor data from the primary sensor 20. In this case, the monitoring system 5 may provide a warning indicating that a discrepancy between the primary sensor 20 and the verification sensor 30 has been detected. Various actions may be taken in response to such alerts.

As one example, a warning notification (e.g., a message) may be displayed or otherwise provided to a user (e.g., a pilot or driver of the vehicle 10). In the case of self-flying or self-propelled vehicles, the speed or direction of the vehicle 10 may be automatically controlled in response to the warning notification. For example, the vehicle 10 may be steered away from the area corresponding to the sensed difference to avoid collision with an object that the primary sensor 20 fails to accurately detect. In some embodiments, the sensor data from the primary sensor 20 may be associated with a confidence value that indicates the confidence of the system in the sensor data. In response to detecting a discrepancy between the sensor data from primary sensor 20 and the verification data from verification sensor 30, such confidence value may be lowered or otherwise adjusted to indicate that there is a lower confidence in the sensor data. The control algorithm for controlling the vehicle 10 may use the confidence value in making the control decision, as desired. Various other actions may be taken in response to an alert provided when a difference is detected between the sensor data and the verification data.

When comparing the validation data sample with the sample data, there may be several objects 15 within the field of view 25 of the primary sensor 20, and the monitoring system 5 may be configured to identify the same object in both sets of data, so that its position in both sets of data can be compared, as described above. As one example, the monitoring system 5 may be configured to analyze the sensor data samples to measure the size and/or shape of each object sensed by the primary sensors 20, and the monitoring system 5 may be further configured to analyze the verification data samples to measure the size and/or shape of each object sensed by the verification sensors 30. When the object size and/or shape in the sensor data matches (within a predefined tolerance) its size and/or shape in the validation data, then the same object is identified in both samples. Once the same object has been identified, its position indicated by the sensor data may be compared to its position indicated by the verification data to verify the accuracy of the sensor data, as described above.

As discussed briefly above, it should be noted that the fields of view of the primary sensor 20 and the verification sensor 30 may be three-dimensional to help monitor the three-dimensional airspace surrounding the vehicle 10. Indeed, it is possible to have the field of view completely surrounding the vehicle 10, thereby enabling the object 15 to be sensed regardless of which direction it is in the vehicle 10. Such coverage may be particularly beneficial for aircraft for which objects may approach it from any direction.

in this regard, the field of view 25 of the sensor 20 shown in FIG. 2 is three-dimensional. Additional sensors (not shown in fig. 2) may be at other locations on the vehicle 10 such that the fields of view 25 of all of the sensors 20 completely surround the vehicle 10 in all directions, as shown in fig. 3. It should be noted that when aggregated together, such a field of view may form a bulbous region of airspace that completely surrounds the vehicle 10, such that objects within a certain range of the approaching vehicle 10, regardless of their direction in the vehicle 10, should be within the field of view of the at least one primary sensor 20 and therefore sensed by the at least one primary sensor 20. In some embodiments, a single primary sensor 20 having a field of view 25 (similar to the field of view shown in fig. 3) may be used, thereby eliminating the need for multiple primary sensors to observe the airspace that completely surrounds the vehicle 20.

Similarly, the field of view 35 of the verification sensor 30 may also be three-dimensional. As one example, a radar sensor performing scanning at multiple elevations may have a field of view 35, the field of view 35 completely surrounding the vehicle 10 in all directions, as shown in fig. 3. It should be noted that such a field of view may form a airspace sphere completely surrounding the vehicle 10, such that objects 15 approaching within a certain range of the vehicle 10, regardless of which direction of the vehicle 10 they are in, should be sensed by the verification sensor 30. In particular, in such embodiments, the field of view 35 of the verification sensor 30 may overlap with the multiple fields of view 25 of the multiple primary sensors 20, such that the same verification sensor 30 may be used to verify sensor data from the multiple primary sensors 20. If desired, multiple verification sensors 30 may be used to form an aggregate field of view similar to the field of view shown in FIG. 3.

it should also be noted that the monitoring system 5 does not necessarily use the verification data from the verification sensor 30 to track the object 15 sensed by the verification sensor 30. As one example, between verifications of sensor data, the verification sensor 30 does not necessarily sense an object. If the verification sensor 30 provides any samples between verifications, the monitoring system 5 may discard such samples without analyzing them or using them to track or determine the location of the object 15. Further, after using the validation data sample from the validation sensor 30 to validate the sensor data sample from the primary sensor 20, the monitoring system 5 may discard the validation data sample. Thus, from time to time (e.g., periodically), the verification data is used to verify the accuracy of the sensor data from the one or more primary sensors 20, rather than the verification data tracking the object 15. That is, the monitoring system 5 may use sensor data from the primary sensors 20 to track the object 15 in the airspace surrounding the vehicle 10 and use the verification data for the sole purpose of verifying the sensor data, rather than independently tracking the object using the verification data. By not tracking objects with authentication data from authentication sensor 30, it may be possible to be immune to at least some regulatory limitations associated with the use of authentication sensor 30. Furthermore, the amount of authentication data to be processed and stored by the monitoring system 5 may be reduced.

Fig. 4 depicts an exemplary embodiment of a vehicle monitoring system 205 according to some embodiments of the present disclosure. In some embodiments, the vehicle monitoring system 205 is configured to monitor and control operation of a self-flying VTOL aerial vehicle, although the system 205 may be configured for use with other types of vehicles in other embodiments. The vehicle monitoring system 205 of fig. 4 may include a data processing element 210, one or more primary sensors 20, one or more verification sensors 30, a vehicle controller 220, a vehicle control system 225, and a drive system 230. While certain functions may be attributed to various components of the vehicle monitoring system 205, it should be understood that such functions may be performed by one or more components of the system 205 in some embodiments. Further, in some embodiments, components of the system 205 can reside on the vehicle 10 or elsewhere, and can communicate with other components of the system 205 via various techniques, including wired (e.g., electrically conductive) or wireless communication (e.g., using a wireless network or short-range wireless protocol, such as Bluetooth). Further, the system 205 may include various components not depicted in fig. 4 to implement the functions described herein and perform collision threat sensing operations and vehicle control.

in some embodiments, as shown in fig. 4, a data processing element 210 may be coupled with each sensor 20, 30, may process sensor data from the master sensor 20 and the verification sensor 30, and may provide signals to a vehicle controller 220 for controlling the vehicle 10. The data processing element 210 may be various types of devices capable of receiving and processing sensor data from the sensors 20 and the verification sensors 30, and may be implemented in hardware or a combination of hardware and software. An exemplary configuration of data processing element 210 is described in more detail below with reference to fig. 5.

The vehicle controller 220 may include various components for controlling the operation of the vehicle 10 and may be implemented in hardware or a combination of hardware and software. As one example, the vehicle controller 220 may include one or more processors (not specifically shown) programmed with respective instructions for performing the functions described herein for the vehicle controller 220. In some embodiments, the vehicle controller 220 may be communicatively coupled to other components of the system 205, including the data processing element 210 (e.g., as described above), the vehicle control system 225, and the drive system 230.

The vehicle control system 225 may include various components for controlling the vehicle 10 as the vehicle 10 travels. As one example, for a self-flying VTOL aerial vehicle, vehicle control system 225 may include a flight control interface, such as one or more rudders, ailerons, elevators, flaps, spoilers, brakes, or other types of aerodynamic devices typically used to control an aerial vehicle. Further, the drive system 230 may include various components (e.g., an engine and a propeller) to provide drive or thrust to the vehicle 10. As will be described in greater detail hereinafter, when the data processing element 210 identifies a collision threat, the vehicle controller 220 may be configured to take action in response to the threat (e.g., provide a warning to a user (e.g., a pilot or driver)), or itself control the vehicle control system 225 and the drive system 230 to alter the path of the vehicle 10 in an attempt to avoid the sensed threat.

Fig. 5 depicts an exemplary data processing element 210 according to some embodiments of the present disclosure. Data processing element 210 may include one or more processors 310, memory 320, data interface 330, and local interface 340. Processor 310, such as a Central Processing Unit (CPU) or Digital Signal Processor (DSP), may be configured to execute instructions stored in memory to perform various functions, such as processing sensor data from each of master sensor 20 and verification sensor 30 (fig. 4). The processor 310 may communicate with and drive other elements within the data processing element 305 via a local interface 340, the local interface 340 comprising at least one bus. Further, a data interface 330 (e.g., a port or pin) may enable the components of the data processing unit 210 to communicate with other components of the system 5 (e.g., the sensors 20 and the verification sensors 30 and the vehicle controller 220).

As shown in fig. 5, the data processing element 210 may include a sensor processing logic unit 350, which may be implemented in hardware, software, or any combination thereof. In fig. 5, the sensor processing logic 350 is implemented in software and stored in memory 320. However, other configurations of the sensor processing logic 350 are possible in other embodiments.

It should be noted that when implemented in software, the sensor processing logic 350 can be stored on and transmitted over any computer-readable medium for use by or in connection with an instruction execution device that can fetch and execute the instructions. In the context of this document, a "computer-readable medium" can be any means that can contain or store the code for use by or in connection with the instruction execution means.

Sensor processing logic 350 is configured to verify the accuracy of sensor data 343 from sensor 20 by processing sensor data 343 and verification data 345 from verification sensor 30 in accordance with the techniques described herein. As one example, the sensor processing logic 350 may be configured to identify objects 15 sensed by the sensors 20, 30 and evaluate whether each sensed object 15 constitutes a collision threat to the vehicle 10 based on the position and speed of the object relative to the vehicle 10, the speed of the vehicle, or the expected travel path. Once the sensor processing logic 350 determines that an object 15 is a collision threat, the sensor processing logic 350 may notify the vehicle controller 220 of the threat and the vehicle controller 220 may take additional action in response to the threat. As one example, the vehicle controller 220 may control the vehicle 10 to avoid threats, such as by adjusting the route of the vehicle 10 based on an assessment by the sensor processing logic 350 that the object 15 is a collision threat. For each object 15 identified by the logic 350 as a collision threat, the controller 220 may perform similar adjustments to the route of the vehicle 10, thereby causing the vehicle 10 to complete safe self-flying operations. As a further example, the vehicle controller 220 may provide a warning to the user or automatically control the travel path of the vehicle to avoid the sensed object 15. An exemplary alert may include a message, such as a human-readable text message sent to an operator of the vehicle. Other exemplary alerts may include audible alerts (e.g., whistling), visual alerts (e.g., lights), physical alerts (e.g., tactile feedback), or other means.

in other examples, the evaluations made by the sensor processing logic 350 may be used for other purposes. As one example, the detected objects may be used for navigation purposes to determine or confirm the location of the vehicle if the sensor data 343 is verified to be accurate. In this regard, the detected object may be used as a reference point to confirm the position of the vehicle relative to the reference point and then control the vehicle 10 to guide it to a desired position relative to the reference point. The information about the sensed object 15 may be used for other purposes in other examples.

An exemplary use and operation of the system 5 to validate data from the sensor 20 using validation data from the validation sensor 30 will be described in more detail below with reference to fig. 6. For purposes of illustration, it will be assumed that the object 15 is within the field of view 25 of the primary sensor 20 and the field of view 35 of the verification sensor 30.

First, as shown in block 402 of FIG. 6, samples are taken from each of the primary sensor 20 and the verification sensor 30 substantially simultaneously while the object 15 is within the fields of view 25 and 35. As shown in block 404 of fig. 6, such samples are provided to the sensor processing logic unit 350, which detects the objects 15 in the samples from the primary sensor 20. As shown in block 408 of fig. 6, the sensor processing logic 350 then determines the location of the object 15 from the sample provided by the primary sensor 20.

as shown in block 410, the sensor processing logic 350 detects the same object 15 in the sample from the verification sensor 30. As shown in block 412 of fig. 6, the sensor processing logic 350 then determines the location of the object 15 indicated by the sample provided by the verification sensor 30. After determining such a location, the sensor processing logic 350 compares the location of the object 15 indicated by the sample from the verification sensor 30 with the location of the object 15 indicated by the sample from the primary sensor 20, as shown in block 414, and based on this comparison, the sensor processing logic 350 verifies the location of the object 15 in the sensor data from the sensor 30 and determines whether to take action, as shown in block 416 of fig. 4. In this regard, based on the difference in compared positions, sensor processing logic 350 may verify that sensor data 343 from sensor 30 accurately indicates the coordinates of object 15. In this case, the sensor processing logic 350 can reliably use the sensor data 343 to track the object. If sensor processing logic 350 determines that sensor data 343 does not accurately reflect the position of object 15, sensor processing logic 350 takes action to mitigate the discrepancy. As one example, the sensor processing logic 350 may report the discrepancy to the vehicle controller 220, and the vehicle controller 220 then makes one or more control decisions, such as changing the direction or speed of the vehicle 10, based on the notification. As shown in fig. 6, processing may end after block 416 for the sample collected at step 402. Thereafter, a new sample may be collected from each of the sensor 20 and the verification sensor 30, and the process may return to step 402 to repeat the verification.

Various embodiments are described above as using a camera to implement sensor 20 and a radar sensor to implement verification sensor 30. However, it should be emphasized that other types of primary sensors 20 and verification sensors 30 may be used to perform tracking of the object and to perform verification of the location of the object, according to the same or similar techniques described herein.

The foregoing merely illustrates the principles of the disclosure and various modifications can be made by those skilled in the art without departing from the scope of the disclosure. The above-described embodiments are presented for purposes of illustration and not limitation. The present disclosure can take many forms other than those explicitly described herein. It is therefore emphasized that this disclosure is not limited to the explicitly disclosed methods, systems and devices, but is intended to include variations and modifications thereof within the spirit and scope of the following claims.

as a further example, variations in apparatus or process parameters (e.g., size, configuration, components, order of process steps, etc.) may be employed to further optimize the provided structures, devices, and methods, as shown and described herein. In any event, the structures and devices described herein, and the associated methods, have many applications. Thus, the disclosed subject matter should not be limited to any single embodiment described herein, but rather construed in breadth and scope in accordance with the appended claims.