HK1239851B - Method and apparatus for controlling aircraft - Google Patents

Description

Aircraft control method and device

Technical Field

The present invention relates to the field of aircraft control technology, and in particular to an aircraft control method and device.

Background Art

A drone, also known as an unmanned aerial vehicle, is an unmanned aircraft controlled by radio remote control and telemetry equipment and a self-contained programmable controller. While lacking a cockpit, a drone is equipped with a navigation and flight control system, programmable controllers, and power and electrical equipment. Ground-based remote control and telemetry stations use data links and other equipment to track, locate, remotely control, measure, and transmit digital data. Compared to manned aircraft, drones are smaller, less expensive, easier to use, and adaptable to a variety of flight environments. Consequently, they are widely used in aerial remote sensing, meteorological research, agricultural aerial seeding, pest control, and even warfare.

During flight, drones and other aircraft can crash due to mechanical failures, collisions with other objects, and other factors. These crashes can potentially hit pedestrians or vehicles, causing personal and property damage. Therefore, with the widespread use of drones and other aircraft, controlling them, particularly during crashes, has become a pressing issue.

In the prior art, the loss caused by the aircraft crash is reduced by controlling the occurrence of the aircraft crash, but this method cannot control the aircraft after the crash occurs.

Summary of the Invention

In order to solve the problem of controlling an aircraft after a crash occurs, embodiments of the present invention provide a method and apparatus for controlling an aircraft.

In one aspect, an embodiment of the present invention provides a method for controlling an aircraft, the method comprising:

Determining the horizontal velocity _vhorizontal and vertical velocity _vvertical of the aircraft;

Acquire an object whose distance from the aircraft is not greater than a preset distance L in the falling direction of the aircraft;

Predicting a positional relationship between the aircraft and the object after flying L based on the _horizontal v, the _vertical v, and the L;

If the position relationship satisfies a preset relationship, a preset control measure is taken to control the aircraft.

Optionally, before determining the v _horizontal and v _vertical of the aircraft, the method further includes:

Confirmed that the aircraft crashed.

Optionally, predicting the positional relationship between the aircraft and the object after flight L based on the v _horizontal , the v _vertical , and the L includes:

Determining a first projection position of the aircraft in a detection plane and determining a scanning position of the object in the detection plane, where the detection plane is at a distance L from the UAV and the detection plane is perpendicular to a direction of motion of the UAV;

Predicting a second projection position of the aircraft in the detection plane after flying L based on the first projection position, v _horizontal , v _vertical , and L;

The positional relationship between the second projection position and the scanning position is determined as the positional relationship between the aircraft and the object after flight L.

Optionally, the aircraft is equipped with a depth of field sensor, and the detection direction of the depth of field sensor is consistent with the movement direction of the aircraft;

Acquiring an object whose distance from the aircraft is not greater than a preset distance L in the direction of movement of the aircraft includes:

Obtain an object detected by the depth of field sensor with a depth of field L.

Optionally, determining a first projection position of the aircraft in the detection plane includes:

Obtaining the three-dimensional size of the aircraft;

determining an angle between the depth sensor and an initial direction of the aircraft;

Projecting the aircraft onto a detection plane according to the three-dimensional size and the angle;

The projection position of the aircraft in the detection plane is determined as a first projection position.

Optionally, predicting a second projection position of the aircraft in the detection plane after flight L based on the first projection position, the _horizontal v, the _vertical v, and the L includes:

According to the _horizontal v, the _vertical v, and the L, predict the longitudinal distance s of the aircraft in the detection plane after flying L;

The position after the first projection position is longitudinally moved by the distance s is determined as the second projection position.

Optionally, the predicting, based on the v _horizontal , the v _vertical , and the L, a distance s that the aircraft moves longitudinally in the detection plane after flying L includes:

Predict s according to the following formula:

Where g is the acceleration due to gravity and a is the preset reduction ratio constant.

Optionally, the preset control measure is: deploying an airbag, or disintegrating the aircraft.

In another aspect, an embodiment of the present invention provides a control device for an aircraft, the device comprising:

A first determination module is used to determine the horizontal velocity _vhorizontal and the vertical velocity _vvertical of the aircraft;

An acquisition module, configured to acquire an object whose distance from the aircraft is not greater than a preset distance L in the falling direction of the aircraft;

a prediction module, configured to predict a positional relationship between the aircraft and the object acquired by the acquisition module after flight L based on v _horizontal determined by the first determination module, v _vertical determined by the first determination module, and L;

The control module is configured to take preset control measures to control the aircraft when the position relationship predicted by the prediction module satisfies a preset relationship.

Optionally, the device further includes:

The second determination module is used to determine that the aircraft has crashed.

Optionally, the prediction module includes:

a first determining unit, configured to determine a first projection position of the aircraft in a detection plane, where a distance L between the detection plane and the UAV is equal to or greater than 0.05, and the detection plane is perpendicular to a moving direction of the UAV;

a second determining unit, configured to determine a scanning position of the object in the detection plane;

a prediction unit, configured to predict a second projection position of the aircraft in the detection plane after flight L based on the first projection position determined by the first determination unit, the v _horizontal , the v _vertical , and the L;

The third determining unit is configured to determine the positional relationship between the second projection position predicted by the predicting unit and the scanning position determined by the second determining unit as the positional relationship between the aircraft and the object after flight L.

Optionally, the aircraft is equipped with a depth of field sensor, and the detection direction of the depth of field sensor is consistent with the movement direction of the aircraft;

The acquisition module is used to acquire the object detected by the depth of field sensor with a depth of field L.

Optionally, the first determining unit includes:

an acquisition subunit, configured to acquire the three-dimensional dimensions of the aircraft;

a first determining subunit, configured to determine an angle between the depth sensor and an initial direction of the aircraft;

a projection subunit, configured to project the aircraft into a detection plane according to the three-dimensional size acquired by the acquisition subunit and the angle determined by the first determination subunit;

The second determining subunit is configured to determine the projection position of the aircraft in the detection plane by the projection subunit as a first projection position.

Optionally, the prediction unit includes:

A prediction subunit, configured to predict, based on the v _horizontal , the v _vertical , and the L, a distance s that the aircraft will move longitudinally in the detection plane after flying L;

The determination subunit is configured to determine a position after the first projection position is longitudinally moved by a distance s obtained by the prediction subunit as a second projection position.

Optionally, the prediction subunit is configured to predict s according to the following formula:

Where g is the acceleration due to gravity and a is the preset reduction ratio constant.

Optionally, the preset control measure is: deploying an airbag, or disintegrating the aircraft.

The beneficial effects are as follows:

Determine the aircraft's v _horizontal and v _vertical ; obtain an object with a distance no greater than L from the aircraft in the aircraft's falling direction; predict the positional relationship between the aircraft and the object after flying L based on v _horizontal , v _vertical , and L; if the positional relationship meets the preset relationship, take the preset control measures to control the aircraft and achieve control of the aircraft after the fall occurs.

BRIEF DESCRIPTION OF THE DRAWINGS

Specific embodiments of the present invention will be described below with reference to the accompanying drawings, in which:

FIG1 shows a flow chart of a method for controlling an aircraft provided in one embodiment of the present invention;

FIG2 shows a schematic diagram of a drone provided in another embodiment of the present invention;

FIG3 shows a flow chart of another method for controlling an aircraft provided in another embodiment of the present invention;

FIG4 shows a schematic diagram of the speed of a drone provided in another embodiment of the present invention;

FIG5 shows an obstacle information diagram provided in another embodiment of the present invention;

FIG6 shows a three-dimensional obstacle information map provided in another embodiment of the present invention;

FIG7 shows a top view of a drone provided in another embodiment of the present invention;

FIG8 shows a schematic diagram of a drone projected on a three-dimensional obstacle information map provided in another embodiment of the present invention;

FIG9 is a schematic diagram showing the position of a drone projected in a three-dimensional obstacle information map provided in another embodiment of the present invention;

FIG10 shows a schematic diagram of the displacement of a drone projected on a three-dimensional obstacle information map provided in another embodiment of the present invention;

FIG11 is a schematic diagram showing another drone projected on a three-dimensional obstacle information map provided in another embodiment of the present invention;

FIG12 shows a flow chart of another method for controlling an aircraft provided in another embodiment of the present invention;

FIG13 shows another obstacle information diagram provided in another embodiment of the present invention;

FIG14 shows another three-dimensional obstacle information diagram provided in another embodiment of the present invention;

FIG15 is a schematic structural diagram of a control device for an aircraft provided in another embodiment of the present invention;

FIG16 is a schematic structural diagram of another aircraft control device provided in another embodiment of the present invention;

FIG17 shows a schematic structural diagram of a prediction module provided in another embodiment of the present invention;

FIG18 shows a schematic structural diagram of a first determining unit provided in another embodiment of the present invention;

FIG19 shows a schematic structural diagram of a prediction unit provided in another embodiment of the present invention.

DETAILED DESCRIPTION

Currently, when an aircraft falls, it is difficult to avoid colliding with objects in front of it due to the lack of control, and it is also difficult to avoid the loss of life and property caused by hitting pedestrians or vehicles. In order to reduce the losses caused by the aircraft falling, the present application proposes a control method for an aircraft, which is applied to an aircraft control device, such as the aircraft control device described in the embodiments shown in any of Figures 15 to 19. The aircraft control device is located on the aircraft. At the same time, the aircraft can be equipped with a depth of field sensor. The detection direction of the depth of field sensor can be consistent with the movement direction of the aircraft. When the aircraft falls, the aircraft control device can determine the aircraft's v _horizontal and v _vertical ; in the direction of the aircraft's fall, the depth of field sensor is used to detect an object that is no more than a preset distance L from the aircraft; based on v _horizontal , v _vertical , and L, the positional relationship between the aircraft and the object after flying L is predicted; if the positional relationship meets the preset relationship, the preset control measures are taken to control the aircraft, thereby achieving control of the aircraft after the fall occurs.

In combination with the above implementation environment, this embodiment provides a method for controlling an aircraft. Referring to FIG1 , the method flow provided in this embodiment is as follows:

101: Determine the horizontal velocity _vhorizontal and vertical velocity _vvertical of the aircraft;

Optionally, before determining the v _horizontal and v _vertical of the aircraft, the method further includes:

Confirmed that the aircraft crashed.

102: Acquire an object whose distance from the aircraft is not greater than a preset distance L in the falling direction of the aircraft;

Optionally, the aircraft is equipped with a depth sensor, and the detection direction of the depth sensor is consistent with the movement direction of the aircraft;

Acquiring an object within a predetermined distance L from the aircraft in the direction of the aircraft's motion includes:

Get the object detected by the depth sensor at a depth of L.

103: Based on v _horizontal , v _vertical , and L, predict the positional relationship between the aircraft and the object after flying L;

Optionally, based on v _horizontal , v _vertical , and L, predicting the positional relationship between the aircraft and the object after flying L includes:

Determine the first projection position of the aircraft in the detection plane and determine the scanning position of the object in the detection plane. The distance L between the detection plane and the UAV is perpendicular to the direction of motion of the UAV.

Predict the second projection position of the aircraft in the detection plane after flying L based on the first projection position, v _horizontal , v _vertical , and L;

The positional relationship between the second projection position and the scanning position is determined as the positional relationship between the aircraft and the object after flight L.

Optionally, determining a first projection position of the aircraft in the detection plane includes:

Get the three-dimensional size of the aircraft;

Determine the angle between the depth sensor and the initial orientation of the aircraft;

Project the aircraft onto the detection plane according to the three-dimensional size and angle;

The projection position of the aircraft in the detection plane is determined as the first projection position.

Optionally, predicting a second projection position of the aircraft in the detection plane after flying L based on the first projection position, v _horizontal , v _vertical , and L includes:

Based on _vhorizontal , _vvertical , and L, predict the distance s that the aircraft will move longitudinally in the detection plane after flying L;

The position after the first projection position is longitudinally moved by a distance s is determined as the second projection position.

Optionally, based on v _horizontal , v _vertical , and L , predicting the longitudinal distance s that the aircraft moves in the detection plane after flying L includes:

Predict s according to the following formula:

Where g is the acceleration due to gravity and a is the preset reduction ratio constant.

104: If the position relationship satisfies the preset relationship, a preset control measure is taken to control the aircraft.

Optionally, the preset control measures are: deploying airbags, or disintegrating the aircraft.

Beneficial effects:

Determine the aircraft's v _horizontal and v _vertical ; obtain an object with a distance no greater than L from the aircraft in the aircraft's falling direction; predict the positional relationship between the aircraft and the object after flying L based on v _horizontal , v _vertical , and L; if the positional relationship meets the preset relationship, take the preset control measures to control the aircraft and achieve control of the aircraft after the fall occurs.

In combination with the above implementation environment, this embodiment provides a method for controlling an aircraft. Since there are many types of aircraft, for the sake of convenience, this embodiment only takes a drone and an object A whose distance from the drone is not greater than L as an example for explanation.

The UAV is shown in FIG2 . The UAV is equipped with an infrared laser depth-of-field sensor that can rotate freely 360 degrees. The detection direction of the 360-degree freely rotating infrared laser depth-of-field sensor is always consistent with the movement direction of the UAV.

Referring to FIG3 , the method flow provided in this embodiment is specifically as follows:

301: Confirmed that the drone has crashed;

During the flight, the drone will monitor its own status, the operation status of the equipment, etc., and judge whether the drone has crashed based on the monitoring results. If it is judged that the drone has crashed, it is determined that the drone has crashed.

There are many possible reasons for a drone to fall, such as a mechanical failure, a collision, or other reasons. There are also many ways a drone can fall, such as free fall, partial propeller stall, or other causes.

In addition, in actual applications, the acceleration of different drones when falling may be different. This embodiment does not limit the specific acceleration of the drone falling.

302: Determine the v _horizontal and v _vertical of the drone;

Since all drones are equipped with GPS (Global Positioning System), altitude sensors and other equipment and systems, in this step, the drone's _vhorizontal can be obtained by GPS, and the vertical speed _vvertical can be obtained by the altitude sensor.

It should be noted that, unless otherwise specified in this embodiment and subsequent embodiments, the speeds mentioned (v, v _horizontal , v _vertical , etc.) are all vectors, including both magnitude and direction.

In addition, in order to determine the position of the drone itself in the subsequent steps, after obtaining v _horizontal and v _vertical , the flight speed v of the drone can also be calculated based on v _horizontal and v _vertical to determine the speed of the drone in three-dimensional space.

For example, if the _horizontal direction of v is α degrees east of north, the flight speed v is the current actual speed of the UAV, and the direction of v is β degrees downward rotation of the horizontal plane, as shown in Figure 4.

Where β = arctan ( _vvertical / _vhorizontal )

Of course, since the drone can calculate the current flight speed in real time, v can also be directly obtained from the relevant measurement equipment of the drone.

303: Acquire an object whose distance from the drone is not greater than L in the falling direction of the drone;

Since the detection direction of the 360-degree freely rotating infrared laser depth of field sensor equipped on the drone shown in Figure 2 is always consistent with the movement direction of the drone, this step can be achieved by obtaining the objects detected by the 360-degree freely rotating infrared laser depth of field sensor with a depth of field L.

For example, a 360-degree rotating infrared laser depth sensor performs real-time depth scanning within a range of L, assuming L is the maximum scanning distance, resulting in an obstacle information map as shown in Figure 5. A 360-degree rotating infrared laser depth sensor can also measure distances within its visible area. Pixels without detected objects have a value of d equal to ∞, while pixels that detect object A record the distance information d(0-L) to that point. By plotting the distance information for each point, a three-dimensional obstacle information map is generated, as shown in Figure 6.

In addition, the specific implementation method of ensuring that the detection direction of the 360-degree freely rotating infrared laser depth of field sensor is always consistent with the movement direction of the drone can be: the 360-degree freely rotating infrared laser depth of field sensor can adjust itself horizontally to α degrees east of north in the example according to its own geomagnetic sensor, and then rotate β degrees toward the center of the earth. At this time, even if the drone rotates or rolls during the fall, the 360-degree freely rotating infrared laser depth of field sensor can still keep its absolute direction of facing speed unchanged according to the two absolute angle values α and β.

Of course, this embodiment only uses the detection of an infrared laser depth of field sensor that can rotate freely 360 degrees as an example. In actual applications, the drone can also be equipped with other forms of depth of field sensors, as long as the sensor can detect objects with a depth of field of L and can rotate freely 360 degrees to ensure that the detection direction of the sensor is always consistent with the movement direction of the drone.

304: Based on v _horizontal , v _vertical , and L, predict the positional relationship between the drone and the object after flying L;

The specific implementation includes but is not limited to the following four steps:

Step 1: Determine the first projection position of the UAV in the detection plane;

The distance between the detection plane and the UAV is L, and the detection plane is perpendicular to the movement direction of the UAV.

Step 1 can be implemented through the following three sub-steps:

Sub-step 1.1: Obtain the three-dimensional dimensions of the drone;

The drone has precise three-dimensional dimensions when it is manufactured, and these dimensions are stored as its three-dimensional model information in the drone-related program. In this step, the three-dimensional dimensions can be directly obtained from the related program.

Sub-step 1.2: Determine the angle between the depth sensor and the initial orientation of the drone.

The 360-degree freely rotating infrared laser depth sensor in Figure 2 is connected to the drone host via two or more axes. The current angle of each axis of the 360-degree freely rotating infrared laser depth sensor can be determined at any time. The current angle of each axis of the 360-degree freely rotating infrared laser depth sensor is determined as the angle between the depth sensor and the initial orientation of the drone.

Sub-step 1.3: Project the drone onto the detection plane based on its three-dimensional size and angle;

The 360-degree rotatable infrared laser depth sensor can rotate along the X and Y axes, with the forward direction as shown in Figure 2. Looking at the Y axis from a top view, as shown in Figure 7, the Y axis is now perpendicular to the device and pointing upward.

If the infrared laser depth sensor, which is currently rotating 360 degrees, rotates clockwise along the Y axis by an angle y, then at the moment of the drone's descent, the projection component of the rotation along the Y axis should be y+180°. Similarly, for rotation along the X axis, when the X axis rotates by an angle x, the projection component of the rotation along the X axis should be x+180°.

Using (x+180°, y+180°) as the projection angle of the drone's 3D model, its shape in the depth sensor can be obtained. The size of the drone is known in step 1, and the size of the photosensitive device and the focal length of the lens of the 360-degree freely rotating infrared laser depth sensor are also known. The drone itself knows the actual size of this projection at position L in the detection image, as shown in Figure 8.

Sub-step 1.4: Determine the projection position of the UAV in the detection plane as the first projection position.

Step 2: Determine the scanning position of object A in the detection plane;

Since the distance between the 3D obstacle information map in step 303 and the UAV is L, and the detection plane is perpendicular to the movement direction of the UAV, the 3D obstacle information map in step 303 is a part of the detection plane. In step 2, the 3D obstacle information map in step 303 can be directly obtained and used as the projection result of object A onto the detection plane. The projection position of object A in the map is determined as the scanning position.

Regarding the implementation order of step 1 and step 2, this embodiment is described by first executing step 1 and then executing step 2. In actual application, step 2 can also be executed first and then step 1, or step 1 and step 2 can be executed at the same time. This embodiment does not limit the specific implementation order of step 1 and step 2.

Step 3: Based on the first projection position, v _horizontal , v _vertical , and L, predict the second projection position of the UAV in the detection plane after flying L;

Step 3 can be implemented through the following two sub-steps:

Sub-step 3.1: Based on v _horizontal , v _vertical , and L, predict the longitudinal distance s that the UAV will move in the detection plane after flying L. s can be predicted using the following formula:

Where g is the acceleration due to gravity, a is the preset reduction constant, and the s prediction formula can be derived as follows:

In step 302, the drone's v, v _horizontal , and v _vertical are known, with v's direction being a downward rotation of β degrees from the horizontal plane. In sub-step 1.3 of step 304, the X and Y angular velocities of the 360-degree rotating infrared laser depth sensor and the drone's body are also known, assuming them to be ω _X and ω _Y , respectively.

If the influence of wind speed is not considered, then in free fall, v _horizontal will not change theoretically, while v _vertical will gradually increase under the action of gravitational acceleration.

In non-free fall, both v _horizontal and v _vertical will change, but the drone can still obtain v _horizontal and v _vertical at any time and predict the movement based on the falling trajectory.

Next, this embodiment uses free fall as an example for further analysis. When the detection distance is L, it can be seen that the time it takes for the drone to fly to the detection plane at a distance of L is approximately L/v, as shown in FIG9 .

Assume that after L/v time, v _vertical becomes v _vertical ',

Then _v'vertical = _vvertical + g × L/v;

At this time, β'＝arctan(v' _vertical /v _horizontal )

Assume that after the L/v time, the longitudinal movement distance of the drone projection image in the detection image before the L/v time is b (because the horizontal speed and direction of the drone do not change during free fall, there will be no lateral movement in the detection image), as shown in Figure 10.

We know that b = L × tan(β'-β), and substituting it into the equation yields:

b is the actual longitudinal movement distance. On the actual area of the 360-degree freely rotating infrared laser depth of field sensor, the movement distance is proportionally reduced to the actual distance. The reduction ratio is a known parameter after the 360-degree freely rotating infrared laser depth of field sensor and the lens group are manufactured. Assuming that the reduction ratio outside the L distance is a constant a, the longitudinal movement distance on the 360-degree freely rotating infrared laser depth of field sensor is

Sub-step 3.2: Determine the position after the first projection position is longitudinally moved by a distance s as the second projection position.

After obtaining s, we know that the angular velocities of the 360-degree freely rotating infrared laser depth of field sensor and the fuselage about the X and Y axes are ω _X and ω _Y respectively. These angular velocities do not change during free fall. Therefore, after the L/v time, the rotation angles of the drone around the X and Y axes are ω _X × L/v and ω _Y × L/v respectively. Assuming that the position of the drone after moving s longitudinally from the first projection position after the L/v time is shown in Figure 11 in the detection image before the L/v time, this position is determined as the second projection position.

Step 4: The positional relationship between the second projection position and the scanned position is determined as the positional relationship between the UAV and object A after flight L.

If there is an overlap between the second projection position and the scanned position, it is determined that the drone will collide with object A after flight L;

If there is no overlap between the second projected position and the scanned position, and the distance between the second projected position and the scanned position on the scanned image is c, then it is determined that the positions of the drone and object A will not collide after flight L, and the actual distance between the drone and object A is c×a;

305: If the position relationship satisfies the preset relationship, a preset control measure is taken to control the UAV.

Among them, the preset control measures include but are not limited to: deploying airbags, or disintegrating the drone.

If the preset relationship is that there is an overlap between the positions of the drone and object A, the preset control measures are taken to control the drone only after it is determined in step 304 that there is an overlap between the positions of the drone and object A after flight L.

If the preset relationship is that the actual distance between the UAV and object A is not greater than e, then not only when it is determined in step 304 that there is an overlap between the positions of the UAV and object A after flight L, the preset control measures are taken to control the UAV, but also when it is determined in step 304 that there is no overlap between the positions of the UAV and object A after flight L, the actual distance between the UAV and object A is c×a, and c×a is not greater than e, the preset control measures are taken to control the UAV.

It can be seen that by predicting the current motion state, it can be known whether the drone will collide with object A after the distance L.

For example, if the drone predicts that it will collide with an object (pedestrians, ground, buildings, etc.) at a distance of L, the drone should activate emergency protection devices, such as deploying airbags or disintegrating, to protect the drone itself from damage and to protect pedestrians or property from being injured or damaged.

The anti-collision method for falling drones provided in this embodiment uses an infrared laser depth-of-field sensor on the drone that can rotate 360 degrees freely to point to the current speed direction in real time. By using ultra-high-frequency scanning laser ranging at L or pattern-based full-frame depth-of-field analysis and other technologies, combined with the projection image of its own contour at that moment and angle, it predicts whether a collision will occur based on the two-directional components of the current speed in the projection plane and the rotation speed. If a collision is about to occur, the emergency mechanism is activated (such as popping out the airbag, decomposing the self-structure, etc.) to minimize damage to the drone itself and people or property on the ground. As drones are increasingly used, the method provided in this embodiment will greatly improve the safety of equipment, ground objects, and pedestrians.

In addition, this embodiment is explained using only one 360-degree rotatable infrared laser depth of field sensor equipped on the drone shown in FIG2 as an example. In actual applications, depending on whether the 360-degree rotatable infrared laser depth of field sensor may have line of sight obstruction or other issues, two or more 360-degree rotatable infrared laser depth of field sensors may be equipped as appropriate. The specific number is not limited in this embodiment. When a drone is equipped with multiple 360-degree rotatable infrared laser depth of field sensors, the data obtained by each 360-degree rotatable infrared laser depth of field sensor can be integrated into a single data set and used as the final data obtained by the 360-degree rotatable infrared laser depth of field sensor for subsequent processing.

The anti-collision method for a falling drone provided in this embodiment starts to execute when the drone starts to fall, and is continuously and repeatedly executed, that is, the horizontal speed and vertical speed of the drone are obtained in real time through the anti-collision method for a falling drone provided in this embodiment, and the distance in the direction of its movement is not greater than L from the object. When it is determined that it can collide with the object, the preset anti-collision measures are taken to prevent it from colliding with the object during the entire falling process.

Beneficial effects:

Determine the drone's v _horizontal and v _vertical ; obtain an object with a distance no greater than L from the drone in the direction of the drone's fall; predict the positional relationship between the drone and the object after flying L based on v _horizontal , v _vertical , and L; if the positional relationship meets the preset relationship, take the preset control measures to control the drone and achieve control of the drone after the fall occurs.

The above embodiment is described with the object A being at a distance no greater than L from the drone. Next, in conjunction with the above implementation environment, a method for controlling an aircraft provided by this application is described for a scenario where there are multiple objects at a distance no greater than L between the drones.

In this embodiment, the drone shown in FIG2 is still taken as an example, and the drone is equipped with an infrared laser depth of field sensor that can rotate freely 360 degrees, and the detection direction of the 360-degree freely rotating infrared laser depth of field sensor is always consistent with the movement direction of the drone.

Referring to FIG12 , the method flow provided in this embodiment is as follows:

1201: Confirmed that the drone has crashed;

The implementation method of this step is the same as step 301. For details, please refer to step 301 and will not be repeated here.

1202: Determine the v _horizontal and v _vertical of the drone;

The implementation method of this step is the same as step 302. For details, please refer to step 302 and will not be repeated here.

1203: Acquire all objects in the falling direction of the drone whose distance to the drone is not greater than L;

Since there are multiple objects whose distances from the drone are not greater than L in the falling direction of the drone, this step obtains all objects whose distances from the drone are not greater than L.

For each object, the implementation method is the same as step 303. For details, please refer to step 303 and will not be described in detail here.

For example, a 360-degree rotating infrared laser depth sensor performs real-time depth scanning within L, generating an obstacle information map as shown in Figure 13. If the 360-degree rotating infrared laser depth sensor can also measure the distance within its visible area, a three-dimensional obstacle information map as shown in Figure 14 can be generated.

1204: Based on v _horizontal , v _vertical , and L, predict the positional relationship between the UAV and each object after flying L;

For each object, _the method for predicting the positional relationship between _the drone and the object after flying L is the same as step 304. For details, please refer to step 304 and will not be described in detail here.

1205: If there is an object whose positional relationship with the drone satisfies a preset relationship, a preset control measure is taken to control the drone.

Determine whether the positional relationship between the drone and each object after flight L meets the preset relationship. If there is an object whose positional relationship with the drone meets the preset relationship, take the preset control measures to control the drone.

The method for determining whether the positional relationship between the drone and each object after flight L satisfies the preset relationship is the same as that in step 305. For details, please refer to step 305 and will not be described in detail here.

Beneficial effects:

Determine the v _horizontal and v _vertical of the drone; obtain all objects whose distance from the drone is no greater than L in the direction of the drone's fall; predict the positional relationship between the drone and the object after flying L based on v _horizontal , v _vertical , and L; if there is an object whose positional relationship with the drone meets the preset relationship, take the preset control measures to control the drone and achieve control of the drone after the fall occurs.

Based on the same inventive concept, referring to the embodiment shown in FIG15 , this embodiment provides a control device for an aircraft. Since the principle of solving the problem by the control device for an aircraft is similar to that of a control method for an aircraft, the implementation of the control device for the aircraft can refer to the implementation of the method, and the repeated parts will not be repeated.

Referring to FIG15 , the control device of the aircraft includes:

The first determination module 1501 is used to determine the horizontal velocity _vhorizontal and the vertical velocity _vvertical of the aircraft;

An acquisition module 1502 is configured to acquire an object whose distance from the aircraft is not greater than a preset distance L in the falling direction of the aircraft;

The prediction module 1503 is configured to predict the positional relationship between the aircraft and the object acquired by the acquisition module 1502 after flight L based on v _horizontal determined by the first determination module 1501 , v _vertical determined by the first determination module 1501 , and L;

The control module 1504 is configured to take preset control measures to control the aircraft when the prediction module 1503 predicts that the position relationship satisfies a preset relationship.

Referring to FIG16 , the device further comprises:

The second determining module 1505 is used to determine whether the aircraft has crashed.

Referring to FIG. 17 , the prediction module 1503 includes:

The first determining unit 15031 is configured to determine a first projection position of the aircraft in a detection plane, where the distance L between the detection plane and the UAV is perpendicular to the direction of motion of the UAV.

A second determining unit 15032 is configured to determine a scanning position of the object in the detection plane;

The prediction unit 15033 is configured to predict a second projection position of the aircraft in the detection plane after flight L based on the first projection position, v _horizontal , v _vertical , and L determined by the first determination unit 15031;

The third determining unit 15034 is configured to determine the positional relationship between the second projection position predicted by the predicting unit 15033 and the scanning position determined by the second determining unit 15032 as the positional relationship between the aircraft and the object after flight L.

The aircraft is equipped with a depth sensor, and the detection direction of the depth sensor is consistent with the movement direction of the aircraft;

The acquisition module 1502 is configured to acquire an object detected by the depth sensor with a depth of field L.

Referring to FIG. 18 , the first determining unit 15031 includes:

Acquisition subunit 150311 is used to obtain the three-dimensional size of the aircraft;

The first determining subunit 150312 is used to determine the angle between the depth sensor and the initial direction of the aircraft;

The projection subunit 150313 is configured to project the aircraft onto the detection plane according to the three-dimensional size obtained by the acquisition subunit 150311 and the angle determined by the first determination subunit 150312;

The second determining subunit 150314 is configured to determine the projection position of the aircraft in the detection plane by the projection subunit 150313 as the first projection position.

Referring to FIG. 19 , the prediction unit 15033 includes:

The prediction subunit 150331 is used to predict the longitudinal distance s of the aircraft in the detection plane after flying L based on v _horizontal , v _vertical , and L;

The determination subunit 150332 is configured to determine the position of the first projection position after longitudinally moving the first projection position by the distance s obtained by the prediction subunit 150331 as the second projection position.

The prediction subunit 150331 is used to predict s according to the following formula:

Where g is the acceleration due to gravity and a is the preset reduction ratio constant.

Among them, the preset control measures are: popping out the airbag, or disintegrating the aircraft.

The beneficial effects are as follows:

Determine the aircraft's v _horizontal and v _vertical ; obtain all objects whose distance from the aircraft is no greater than L in the aircraft's falling direction; predict the positional relationship between the aircraft and the object after flying L based on v _horizontal , v _vertical , and L; if there is an object whose positional relationship with the aircraft satisfies the preset relationship, take the preset control measures to control the aircraft and achieve control of the aircraft after the fall occurs.

The above embodiments can all be implemented using existing functional components and modules. For example, the processing module can utilize existing data processing components. At least, positioning servers used in existing positioning technologies already have components that implement this function. As for the receiving module, it is a component that any device with signal transmission capabilities has. Furthermore, the calculation of the A and n parameters and the intensity adjustment performed by the processing module all utilize existing technical means and can be implemented by those skilled in the art through appropriate design and development.

For the convenience of description, the various parts of the above-mentioned device are divided into various modules or units according to their functions and described separately. Of course, when implementing the present invention, the functions of each module or unit can be realized in the same or multiple software or hardware.

It will be understood by those skilled in the art that embodiments of the present invention may be provided as methods, systems, or computer program products. Thus, the present invention may take the form of an entirely hardware embodiment, an entirely software embodiment, or an embodiment combining software and hardware. Furthermore, the present invention may take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to magnetic disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

The present invention is described with reference to the flowcharts and/or block diagrams of the methods, devices (systems), and computer program products according to embodiments of the present invention. It should be understood that each process and/or box in the flowchart and/or block diagram, as well as the combination of processes and/or boxes in the flowchart and/or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to produce a machine, so that the instructions executed by the processor of the computer or other programmable data processing device produce a device for implementing the functions specified in one or more processes in the flowchart and/or one or more boxes in the block diagram.

These computer program instructions may also be stored in a computer-readable memory that can direct a computer or other programmable data processing device to operate in a specific manner, so that the instructions stored in the computer-readable memory produce a product including an instruction device that implements the functions specified in one or more processes in the flowchart and/or one or more boxes in the block diagram.

These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operating steps are executed on the computer or other programmable device to produce a computer-implemented process, so that the instructions executed on the computer or other programmable device provide steps for implementing the functions specified in one or more processes in the flowchart and/or one or more boxes in the block diagram.

Although the preferred embodiments of the present invention have been described, those skilled in the art may make additional changes and modifications to these embodiments once they have learned the basic creative concept. Therefore, the appended claims are intended to be interpreted as including the preferred embodiments and all changes and modifications that fall within the scope of the present invention.

Claims (12)

1. A control method for an aircraft, characterized in that the method comprises: Determine the horizontal velocity _{v_horizontal} and the vertical velocity _{v_vertical} of the aircraft; In the direction of the aircraft's descent, identify an object whose distance from the aircraft is no greater than a preset distance L. The first projected position of the aircraft in the detection plane is determined, and the scanning position of the object in the detection plane is determined. The distance between the detection plane and the aircraft is L, and the detection plane is perpendicular to the direction of motion of the aircraft. Based on the first projection position, the _horizontal v, the _vertical v, and L, predict the second projection position of the aircraft in the detection plane after flying L; The positional relationship between the second projection position and the scanning position is determined as the positional relationship between the aircraft and the object after flight L; If the positional relationship satisfies a preset relationship, then preset control measures are taken to control the aircraft; Before determining _{the horizontal} and _vertical v of the aircraft, the process also includes: The aircraft crash has been confirmed. 2. The method according to claim 1, wherein the aircraft is equipped with a depth sensor, and the detection direction of the depth sensor is consistent with the motion direction of the aircraft; The step of acquiring an object at a distance not greater than a preset distance L from the aircraft along the direction of the aircraft's movement includes: The depth sensor detects objects with a depth of L. 3. The method according to claim 2, wherein determining the first projected position of the aircraft in the detection plane comprises: Obtain the three-dimensional dimensions of the aircraft; Determine the angle between the depth sensor and the initial orientation of the aircraft; The spacecraft is projected onto the detection plane based on the three-dimensional dimensions and the angle. The projection position of the aircraft in the detection plane is determined as the first projection position. 4. The method according to claim 2, characterized in that, predicting the second projection position of the spacecraft in the detection plane after flight L based on the first projection position, the _horizontal v, the _vertical v, and L, comprises: Based on the _horizontal v, the _vertical v, and L, predict the distance s that the aircraft will move longitudinally in the detection plane after flying L; The position after the first projection position is moved longitudinally by the distance s is determined as the second projection position. 5. The method according to claim 4, characterized in that, predicting the distance s that the aircraft moves longitudinally in the detection plane after flying L based on the _horizontal v, the _vertical v, and L, comprises: Predict s using the following formula: Where g is the acceleration due to gravity, and a is a preset scaling constant. 6. The method according to claim 1, wherein the preset control measure is: deploying the airbag, or disassembling the aircraft. 7. A control device for an aircraft, characterized in that the device comprises: The first determining module is used to determine the horizontal velocity _{v_horizontal} and the vertical velocity _{v_vertical} of the aircraft. The acquisition module is used to acquire objects that are no more than a preset distance L from the aircraft in the direction of the aircraft's fall. The prediction module is used to predict the positional relationship between the aircraft and the object acquired by the acquisition module after flight L, based on _{the horizontal} v determined by the first determining module, _{the vertical} v determined by the first determining module, and L. The control module is used to control the aircraft by taking preset control measures when the prediction module predicts that the positional relationship meets the preset relationship. The device further includes: The second determining module is used to determine the aircraft crash location; The prediction module includes: The first determining unit is used to determine the first projected position of the aircraft in the detection plane, wherein the distance between the detection plane and the aircraft is L, and the detection plane is perpendicular to the direction of motion of the aircraft; The second determining unit is used to determine the scanning position of the object in the detection plane; The prediction unit is used to predict the second projection position of the aircraft in the detection plane after flying L, based on the first projection position determined by the first determining unit, the _horizontal v, the _vertical v, and L. The third determining unit is used to determine the positional relationship between the second projection position predicted by the prediction unit and the scanning position determined by the second determining unit as the positional relationship between the aircraft and the object after flight L. 8. The apparatus according to claim 7, wherein the aircraft is equipped with a depth sensor, and the detection direction of the depth sensor is consistent with the motion direction of the aircraft; The acquisition module is used to acquire objects detected by the depth sensor with a depth of L. 9. The apparatus according to claim 8, wherein the first determining unit comprises: A sub-unit is used to acquire the three-dimensional dimensions of the aircraft. The first determining subunit is used to determine the angle between the depth sensor and the initial orientation of the aircraft; The projection subunit is used to project the aircraft onto the detection plane based on the three-dimensional dimensions obtained by the acquisition subunit and the angle determined by the first determination subunit. The second determining subunit is used to determine the projection position of the aircraft in the detection plane by the projection subunit as the first projection position. 10. The apparatus according to claim 8, wherein the prediction unit comprises: The prediction subunit is used to predict the distance s that the aircraft will move longitudinally in the detection plane after flying L, based on the _horizontal v, the _vertical v, and L. A sub-unit is defined as the position obtained by longitudinally moving the first projection position by the prediction sub-unit and determining it as the second projection position. 11. The apparatus according to claim 10, wherein the prediction subunit is configured to predict s according to the following formula: Where g is the acceleration due to gravity, and a is a preset scaling constant. 12. The device according to claim 7, wherein the preset control measure is: deploying the airbag, or disassembling the aircraft.