CN113448337A

CN113448337A - Speed control method and device of unmanned equipment

Info

Publication number: CN113448337A
Application number: CN202111013574.9A
Authority: CN
Inventors: 陆瑶敏; 樊明宇; 魏桐雨; 任冬淳; 夏华夏
Original assignee: Beijing Sankuai Online Technology Co Ltd
Current assignee: Beijing Sankuai Online Technology Co Ltd
Priority date: 2021-08-31
Filing date: 2021-08-31
Publication date: 2021-09-28

Abstract

The specification discloses a speed control method and a device of unmanned equipment, which can be applied to the unmanned equipment in the field of unmanned driving, such as an unmanned vehicle, the stable passing speed corresponding to an uneven road surface is determined according to the integrity of goods loaded by a test device after passing through the uneven road surface, when the running path of the unmanned equipment has the uneven road surface, the nursing between the unmanned equipment and the uneven road surface is determined, the motion strategy of the unmanned equipment is determined according to the current speed, the stable passing speed and the distance between the unmanned equipment and the uneven road surface, and the unmanned equipment is controlled to pass through the uneven road surface at the stable passing speed according to the motion strategy. The movement strategy of the unmanned equipment determined by the method considers the influence of an uneven road surface area on the integrity of objects loaded on the unmanned equipment in the driving process, and ensures the completion degree of the distribution task.

Description

Speed control method and device of unmanned equipment

Technical Field

The present disclosure relates to the field of unmanned technologies, and in particular, to a method and an apparatus for controlling a speed of an unmanned device.

Background

Currently, with the development of unmanned technology, the use of unmanned equipment is more and more extensive. In order to ensure the driving safety of the unmanned equipment, after the driving route of the unmanned equipment is determined, the unmanned equipment is generally required to be subjected to speed planning and control.

In the prior art, a commonly used speed control method of the unmanned device is realized based on a driving route of the unmanned device. Specifically, the unmanned device can sense the surrounding environment through a plurality of sensors, determine the position of an obstacle around the unmanned device, and then determine the motion strategy of the unmanned device at the next moment according to the position of the obstacle around the unmanned device and the driving route of the unmanned device.

However, in the prior art, when determining the motion strategy of the unmanned device, the obstacle avoidance and lane keeping of the vehicle are generally realized by using multiple sensors, but the influence of an uneven road surface area (such as a deceleration strip) on the object loaded on the unmanned device during driving is ignored.

Therefore, how to plan the speed of the unmanned equipment so as to ensure the integrity of the object loaded on the unmanned equipment is an urgent problem to be solved.

Disclosure of Invention

The present specification provides a method and an apparatus for controlling a speed of an unmanned aerial vehicle, which partially solve the above problems in the prior art.

The technical scheme adopted by the specification is as follows:

the present specification provides a speed control method of an unmanned aerial vehicle, including:

determining the smooth passing speed corresponding to the uneven road surface according to the integrity of the goods loaded by the testing equipment after passing through the uneven road surface;

according to a driving path of the unmanned equipment, determining road surface data corresponding to the driving path;

when it is determined that an uneven road surface exists according to the road surface data, determining the distance between the unmanned equipment and the uneven road surface;

determining a motion strategy of the unmanned equipment according to the current speed of the unmanned equipment, the stable passing speed and the distance between the unmanned equipment and the uneven road surface, and controlling the unmanned equipment to pass through the uneven road surface at the stable passing speed according to the motion strategy.

Optionally, determining road surface data corresponding to the driving path according to the driving path of the unmanned device specifically includes:

determining a driving path of an unmanned device and environmental data around the unmanned device;

projecting the driving path to the environment data, and determining regional environment data corresponding to the driving path in the environment data;

determining road surface data in the area environment data as road surface data corresponding to the driving path;

wherein the environmental data includes at least one of high-precision map data, point cloud data, and image data.

Optionally, determining that an uneven road surface exists according to the road surface data specifically includes:

and identifying the target object in the road surface data, and determining that the target object is an uneven road surface when the target object exists in the road surface data.

Optionally, determining a smooth passing speed corresponding to the uneven road surface according to the integrity of the goods loaded by the testing equipment after passing through the uneven road surface, specifically comprising:

determining unmanned equipment for placing a standard container filled with standard volume of liquid as test equipment;

controlling the testing equipment to pass through an uneven road surface at a constant speed according to preset speeds, and determining the residual amount of the liquid in the standard container corresponding to each speed;

and determining the smooth passing speed corresponding to the uneven road surface according to the liquid residual amount corresponding to each speed.

Optionally, determining a motion strategy of the unmanned aerial vehicle according to the current speed of the unmanned aerial vehicle, the smooth passing speed, and the distance between the unmanned aerial vehicle and the uneven road surface, and controlling the unmanned aerial vehicle to pass through the uneven road surface at the smooth passing speed according to the motion strategy specifically includes:

determining a target distance decelerated to the stable passing speed according to the maximum braking acceleration, the stable passing speed and the current speed of the unmanned equipment, and determining a motion strategy of the unmanned equipment according to the maximum braking acceleration and the target distance;

and controlling the unmanned equipment to run according to the current speed according to the motion strategy, and controlling the unmanned equipment to decelerate according to the maximum braking acceleration when the distance between the unmanned equipment and the uneven road surface is the target distance, so that the unmanned equipment passes through the uneven road surface according to the smooth passing speed.

when the current speed of the unmanned equipment is lower than the stable passing speed, determining a target acceleration according to the current speed of the unmanned equipment, the stable passing speed and the distance between the unmanned equipment and the uneven road surface, and determining a motion strategy of the unmanned equipment according to the target acceleration;

and controlling the unmanned equipment to accelerate according to the target acceleration according to the motion strategy, so that the unmanned equipment passes through the uneven road surface according to the stable passing speed.

Optionally, before determining the target distance to decelerate to the smooth pass speed, the method further comprises:

determining a driving path of the unmanned device;

determining the maximum braking acceleration of the unmanned equipment when the unmanned equipment runs along the running path according to the running path, wherein the maximum braking acceleration is used as the braking acceleration to be selected;

and determining the minimum acceleration from the maximum braking acceleration of the unmanned equipment and the candidate braking acceleration as the maximum braking acceleration of the unmanned equipment.

aiming at uneven road surfaces of different road surface types, according to the completeness of the test equipment for loading cargoes after the cargoes loaded by the test equipment pass through the uneven road surfaces of different road surface types, determining the smooth passing speed corresponding to the uneven road surfaces of different road surface types.

Optionally, prior to determining the motion strategy of the unmanned device, the method further comprises:

when the existence of uneven road surfaces is determined according to the road surface types, determining the road surface types of the uneven road surfaces;

and selecting the smooth passing speed corresponding to the road surface type of the uneven road surface from the determined smooth passing speeds corresponding to the road surface types according to the road surface types.

This specification provides a path planning device of unmanned equipment, includes:

the first determining module is used for determining the smooth passing speed corresponding to the uneven road surface according to the cargo integrity after the test equipment loads the cargo to pass through the uneven road surface;

the second determination module is used for determining road surface data corresponding to a driving path according to the driving path of the unmanned equipment;

the third determination module is used for determining the distance between the unmanned equipment and the uneven road surface when the uneven road surface exists according to the road surface data;

and the control module is used for determining a motion strategy of the unmanned equipment according to the current speed of the unmanned equipment, the stable passing speed and the distance between the unmanned equipment and the uneven road surface, and controlling the unmanned equipment to pass through the uneven road surface at the stable passing speed according to the motion strategy.

The present specification provides a computer-readable storage medium storing a computer program which, when executed by a processor, implements a method of speed control of an unmanned aerial device as described above.

The present specification provides an electronic device comprising a memory, a processor and a computer program stored on the memory and executable on the processor, the processor implementing the above method of controlling the speed of an unmanned device when executing the program.

The technical scheme adopted by the specification can achieve the following beneficial effects:

in the speed control method of the unmanned aerial vehicle provided by the specification, a smooth passing speed corresponding to an uneven road surface is determined according to the integrity of a cargo loaded by a test device after passing through the uneven road surface, when the uneven road surface exists in a running path of the unmanned aerial vehicle, nursing between the unmanned aerial vehicle and the uneven road surface is determined, a motion strategy of the unmanned aerial vehicle is determined according to the current speed, the smooth passing speed and the distance between the unmanned aerial vehicle and the uneven road surface, and the unmanned aerial vehicle is controlled to pass through the uneven road surface at the smooth passing speed according to the motion strategy.

According to the method, the motion strategy of the unmanned equipment determined by the method considers the influence of the uneven road surface area on the integrity of the object loaded by the unmanned equipment in the driving process, and the distribution task is guaranteed to be completed.

Drawings

The accompanying drawings, which are included to provide a further understanding of the specification and are incorporated in and constitute a part of this specification, illustrate embodiments of the specification and together with the description serve to explain the specification and not to limit the specification in a non-limiting sense. In the drawings:

FIG. 1 is a schematic flow diagram of a method for controlling the speed of an unmanned vehicle provided herein;

FIG. 2 is a schematic illustration of determining a speed corresponding to an uneven road surface provided herein;

FIG. 3A is a schematic diagram of a velocity plan for an unmanned aerial device provided herein;

FIG. 3B is a schematic diagram of the change in speed of the drone device provided by the present description;

FIG. 4 is a schematic representation of a velocity plan for an unmanned aerial device provided herein;

FIG. 5 is a schematic diagram of a speed control arrangement for an unmanned aerial vehicle provided herein;

fig. 6 is a schematic diagram of an unmanned device corresponding to fig. 1 provided in the present specification.

Detailed Description

In order to make the objects, technical solutions and advantages of the present disclosure more clear, the technical solutions of the present disclosure will be clearly and completely described below with reference to the specific embodiments of the present disclosure and the accompanying drawings. It is to be understood that the embodiments described are only a few embodiments of the present disclosure, and not all embodiments. All other embodiments obtained by a person of ordinary skill in the art based on the embodiments in the present specification without any creative effort belong to the protection scope of the present specification.

In the prior art, when there are no other vehicles and obstacles around, the unmanned aerial vehicle generally controls itself to travel at a high speed along the travel path, but when the travel path has an uneven road surface (e.g., a speed bump or a pothole), if the unmanned aerial vehicle travels at a high speed, the undulation of the uneven road surface is transmitted to the unmanned aerial vehicle in the form of vibration, so that the vibration frequency of the unmanned aerial vehicle itself is high, the vehicle bumps, and the integrity of the cargo carried by the unmanned aerial vehicle is affected. For example, when the unmanned equipment passes through a deceleration strip at the speed of 60km/h, the loaded goods are too high in vibration frequency, and the goods are splashed.

Different from the prior art that the driving speed of the unmanned equipment is determined based on obstacles and the like of the surrounding environment of the unmanned equipment, and the problem that the integrity of goods loaded on the unmanned equipment by the unmanned equipment is influenced by uneven road surfaces is solved.

The technical solutions provided by the embodiments of the present description are described in detail below with reference to the accompanying drawings.

Fig. 1 is a schematic flow chart of a speed control method of an unmanned aerial vehicle provided in this specification, and specifically includes the following steps:

s100: and determining the smooth passing speed corresponding to the uneven road surface according to the integrity of the goods loaded by the testing equipment after passing through the uneven road surface.

In one or more embodiments provided herein, as previously described, uneven roads can have an impact on the integrity of the cargo after the drone is loaded with cargo. If the speed capable of guaranteeing the integrity of the goods when the unmanned equipment passes through the uneven road surface is determined, when the uneven road surface occurs, the unmanned equipment is controlled to pass through the uneven road surface at the speed, and the integrity of the goods can be guaranteed. Based on this, the smooth passing speed corresponding to the uneven road surface can be determined according to the cargo integrity after the test equipment loads the cargo to pass through the uneven road surface.

Specifically, first, a standard container containing a standard volume of liquid may be placed in the test apparatus. Wherein the standard volume and the standard container are preset, for example, the standard volume is 500ml, and the standard container is a beaker with the volume of 700 ml. The specific standard volume value and the type, material, capacity, etc. of the standard container can be set according to the needs, which is not limited in this specification.

And then, the testing equipment can be controlled to pass through the uneven road surface at a constant speed according to preset speeds, and the residual amount of the liquid in the standard container corresponding to each speed is determined.

And finally, selecting the speed with the most residual liquid as the stable passing speed corresponding to the uneven road surface according to the residual liquid amount corresponding to each speed. Of course, a threshold value of integrity may also be preset, and for each speed, the integrity corresponding to the speed may be determined according to the remaining amount of liquid corresponding to the speed and the standard volume, where the integrity is specifically determined by using the volume of the remaining amount to the standard volume. For example, assuming a standard volume of 1L and a 30km/h velocity corresponding to a liquid remaining amount of 0.5L, the 30km/h velocity has a 50% integrity. Then, after determining the integrity corresponding to each speed, the unmanned device may determine each speed with integrity higher than the integrity threshold, and determine a smooth passing speed corresponding to the uneven road surface from each speed with integrity higher than the integrity threshold. The smooth passing speed can be randomly determined from various speeds with the integrity higher than the integrity threshold value, or the highest speed in the various speeds can be selected. Specifically, the method of selecting the smooth passing speed from among the speeds having the integrity higher than the integrity threshold value may be set as needed.

Further, the above-described type of uneven road surface is described as only one, but in practice, uneven road surfaces of different road surface flatness do not have the same effect on the integrity of loading of cargo by their own unmanned aerial vehicle. The pavement evenness is a deviation value of longitudinal concave-convex quantity of the pavement surface, and is an important technical index for evaluating the pavement quality. Generally speaking, the more uneven the road surface, the greater the driving resistance of the vehicle, the greater the vibration of the vehicle through the road surface, and the more difficult it is to ensure the integrity of the cargo when the vehicle loaded with the cargo passes through the road surface. Accordingly, the smoother the road surface, the smaller the running resistance of the vehicle, and the weaker the vibration of the vehicle passing through the road surface, the easier it is to ensure the integrity of the cargo when the vehicle carrying the cargo passes through the road surface. Based on the method, corresponding smooth passing speeds of uneven road surfaces of different road surface types can be determined so as to ensure the integrity of goods loaded when the unmanned equipment performs distribution tasks.

In addition, for different uneven road surfaces, the factors influencing the smooth passing speed of the road surface type are also inconsistent. Taking a deceleration strip in an uneven road surface as an example, the stable passing speed of the deceleration strip can be influenced by the material, height, width and the like of the deceleration strip. If the hollow road surface in the uneven road surface is taken as an example, the smooth passing speed of the hollow road surface can be influenced by the material, depth, area and the like of the hollow road surface.

The present description provides a schematic diagram of determining a corresponding smooth pass speed for a speed bump, as shown in fig. 2. In the figure, the black and white stripes represent a deceleration strip, the unmanned aerial vehicle provided with a standard container of standard volume of liquid is a test device, the container A is a standard container, the test device can be controlled to pass through the deceleration strip at a constant speed according to different speeds, and the standard container in the test device can be shown above the unmanned aerial vehicle before and after passing through the deceleration strip. It can be seen that, when the liquid in the container a is poured, the volume of the liquid remaining in the container a is the remaining amount of the liquid. From each speed based on the remaining amount of each liquid, table 1 can be obtained:

TABLE 1

Then, according to the above table 1, the standard passing speed corresponding to the speed bump can be determined.

Of course, the smooth passing speeds determined in the above steps may be taken as the respective smooth passing speeds of the unmanned aerial device that executes the speed control method provided in the present specification. In consideration of the difference between different types of unmanned devices, for each type of unmanned device, the type of unmanned device or an electronic device similar to the type of unmanned device is determined as a test device, and each smooth passing speed corresponding to the uneven road surface of each road surface type is determined. So as to ensure the integrity of the goods after the unmanned equipment of the type loads the goods on the uneven road surface in the subsequent step.

The test equipment can comprise various types of unmanned equipment, manned equipment provided with an unmanned system and the like. Of course, for each type of unmanned equipment, the closer the mechanical structure of the test equipment is to the type of unmanned equipment, the higher the probability that the unmanned equipment will have the cargo intact after passing through an uneven road surface at a smooth passing speed obtained by the test of the test equipment. The structure and type of the specific test equipment can be set according to the needs, and the description does not limit the structure and type.

It should be noted that the step of determining the smooth passing speed of the uneven road surface of each road surface type is a previous step of executing the method, that is, when the unmanned aerial vehicle performs the distribution task, only the subsequent steps S102 to S106 need to be executed, and each smooth passing speed in step S100 is determined before the unmanned aerial vehicle performs the task.

S102: and determining road surface data corresponding to the driving path according to the driving path of the unmanned equipment.

In one or more embodiments provided herein, the unmanned aerial vehicle needs to determine a travel path when performing a task to travel along the travel path to perform the task. Here, the unmanned device referred to herein may refer to an unmanned vehicle, a robot, an automatic distribution device, and the like, which are capable of realizing automatic driving. Based on this, the speed control method for the unmanned aerial vehicle provided by the specification can be particularly applied to the field of distribution using the unmanned aerial vehicle, such as business scenes of distribution such as express delivery, logistics and takeaway using the unmanned aerial vehicle. In order to ensure the completeness of the distribution tasks that the unmanned device can execute in these service scenes, the accuracy of the speed control of the unmanned device needs to be ensured.

In one or more embodiments provided in this specification, the execution subject of the speed control on the unmanned device may be the unmanned device itself, or may be a server of the service provider, that is, the server of the service provider may perform speed planning and control on the unmanned device through data uploaded by the unmanned device. For convenience of description, the method for planning the speed of the unmanned aerial vehicle provided by the present specification will be described below with only the unmanned aerial vehicle as an execution subject.

The present specification provides a method for controlling a speed of an unmanned aerial vehicle, which is a method for adjusting a vehicle speed according to an uneven road surface in a driving route of the unmanned aerial vehicle on the assumption that the speed of the unmanned aerial vehicle is positively correlated with a vibration frequency, that is, the higher the speed is, the higher the vibration frequency is, so that the vibration frequency is lower when the unmanned aerial vehicle passes through the uneven road surface, and the integrity of a cargo loaded on the unmanned aerial vehicle is not sufficiently affected, and therefore, the unmanned aerial vehicle needs to acquire road surface data corresponding to the driving route.

Specifically, the unmanned aerial vehicle may first determine its own travel path. The driving path is a reference path which is determined in advance when the unmanned equipment executes the distribution task. Of course, the driving path may also be obtained by planning a path by the unmanned device according to a predetermined reference path and a real-time sensed obstacle around the unmanned device. At present, various methods for determining a driving path exist and are already mature prior art, so the description of how to determine the driving path is not repeated, and the description of how to determine the driving path is specifically made without limitation.

Second, the drone may acquire ambient environmental data. The environment data can be at least one of surrounding images of the unmanned equipment acquired by image acquisition equipment, point cloud data around the unmanned equipment acquired by equipment such as laser radar and high-precision map data prestored in the unmanned equipment.

Then, the unmanned device can project the driving path to the environment data, and determine the area environment data corresponding to the driving path in the environment data. That is, the image collected by the unmanned device usually includes a part of a non-driving path, and the unmanned device can determine environmental data such as an image, point cloud data, high-precision map data and the like of the part of the driving path so as to ensure the accuracy of the subsequent identification step.

Finally, the unmanned device can determine road surface data in the area environment data as road surface data corresponding to the driving path. That is, the road surface data in the image, the point cloud data, and the high-precision map data of the travel route portion is determined as the road surface data corresponding to the travel route.

The high-precision map in the present specification is a map in which the type and position information of each rough road surface are accurately plotted for the purpose of facilitating the unmanned aerial vehicle to travel. That is, a map in which the type and position information of each uneven road surface are marked can be used as a high-precision map in this specification.

S104: and when uneven road surfaces exist according to the road surface data, determining the distance between the unmanned equipment and the uneven road surfaces.

In one or more embodiments provided herein, upon determining that an uneven road surface exists in the road surface data, the drone may determine a distance between itself and the uneven road surface for subsequent determination of a motion maneuver.

Specifically, the unmanned aerial vehicle may recognize the road surface data of the travel path determined in step S102, and determine whether or not the target object, that is, the uneven road surface, exists in the road surface data. If so, the drone may determine the distance of the drone from the uneven road surface based on the current coordinates of the drone, the coordinates of the target object, and so on.

After determining uneven road surface, in order to facilitate speed control of the unmanned equipment, the unmanned equipment can ensure the integrity of goods passing through the uneven road surface, and the unmanned equipment can also determine the distance between the unmanned equipment and the uneven road surface.

Specifically, the unmanned device can determine the conversion relation between a geodetic coordinate system and an environmental data coordinate system, determine the coordinates of the uneven road surface according to the current pose of the unmanned device, and further determine the distance between the unmanned device and the uneven road surface. Of course, the distance may also be determined by various means such as a scale.

In addition, in the present specification, the high-precision map data is recognized not by acquiring an image or a point cloud corresponding to the high-precision map and then recognizing the image or the point cloud, but by determining whether or not each target object exists within a preset distance in front of the unmanned aerial vehicle from the high-precision map to which each target object is previously marked. If so, determining whether a target object exists within five hundred meters in front of the unmanned device in the driving path. The specific identification area of the high-precision map can be set as required, and the specification does not limit the specific identification area.

In the present specification, the identification of the target object based on the image data and the point cloud data means that the accurate type, position, size, and the like of the target object can be identified and determined to determine whether the target object is an uneven road surface of the road surface type in the present specification, rather than identifying only the type of the target object. That is, in the present specification, the identified target object is a road surface type corresponding to the rough road surface.

In this specification, a training sample can be determined by manual labeling or the like, and then a recognition model can be determined to recognize environmental data, or the unmanned device can determine that the position is an uneven road surface according to the self vibration frequency, and then determine the environmental data of the position from the historically collected environmental data as a training sample, and train the recognition model based on the sample. Specifically, it is a mature prior art to identify the target object according to the image data and the point cloud data, and this description is not repeated herein.

In addition, if there is no uneven road surface in front of the drone, the drone may continue to determine the condition of the road surface in front of the drone until it is determined that there is an uneven road surface in front of the drone or the drone performs a completion task.

S106: determining a motion strategy of the unmanned equipment according to the current speed of the unmanned equipment, the stable passing speed and the distance between the unmanned equipment and the uneven road surface, and controlling the unmanned equipment to pass through the uneven road surface at the stable passing speed according to the motion strategy.

In one or more embodiments provided herein, as previously described, it may be difficult to ensure the integrity of the cargo carried by the drone if the drone is traversing uneven roads at relatively high speeds. On the assumption that the higher the speed of the unmanned equipment passing through the deceleration strip is, the more difficult the integrity of the loaded goods is to be ensured, the unmanned equipment needs to ensure that the speed of the unmanned equipment does not exceed the stable passing speed when the unmanned equipment reaches uneven road surfaces, so that the driving safety of the unmanned equipment is ensured.

Specifically, the unmanned aerial vehicle may first determine whether the current speed does not exceed a smooth passing speed corresponding to the unstable road surface. And if so, the unmanned equipment can control the unmanned equipment to drive according to the current speed. If not, the unmanned equipment can pass through the road according to the current speed, the stable passing speed and the distance between the unmanned equipment and the uneven road surface

Wherein d is the distance between the unmanned equipment and the uneven road surface,

in order to smooth the passage of the speed,

for the current speed, the drone may then determine a target acceleration

And determining a motion strategy of the unmanned equipment according to the target acceleration.

Further, the higher the speed of the unmanned aerial vehicle is, the shorter the time required for the unmanned aerial vehicle to perform the delivery task is, and the higher the efficiency of performing the delivery task is. Therefore, in order to ensure the efficiency of the unmanned aerial vehicle in performing the distribution task, the unmanned aerial vehicle needs to ensure that the unmanned aerial vehicle travels at a high speed as much as possible, and thus the unmanned aerial vehicle can determine a target distance for the unmanned aerial vehicle to decelerate from the current speed to a smooth passing speed based on the maximum braking acceleration of the unmanned aerial vehicle, the current speed of the unmanned aerial vehicle, and the smooth passing speed, and determine a motion strategy of the unmanned aerial vehicle according to the maximum braking acceleration and the target distance.

After the movement strategy is determined, the unmanned equipment can be controlled to run at the current speed according to the movement strategy, and when the unmanned equipment runs to the position where the distance between the unmanned equipment and the uneven road surface is the target distance, the unmanned equipment is controlled to decelerate according to the maximum braking acceleration, so that when the unmanned equipment reaches the uneven road surface, the unmanned equipment decelerates to the stable passing speed, and passes through the uneven road surface according to the stable passing speed. As shown in fig. 3A and 3B.

Fig. 3A is a schematic diagram of a velocity plan for an unmanned aerial device provided herein. Wherein,

is the current position of the drone device,

at a target distance from the uneven road surface,

in order to be the target distance,

in order to be the starting point of the speed bump,

and the distance between the current position of the unmanned equipment and the uneven road surface is Y. The unmanned device can control the unmanned device to run at the current speed, and when the distance between the unmanned device and the deceleration strip is the target distance, the unmanned device is controlled to decelerate at the maximum braking acceleration, and when the unmanned device reaches the deceleration strip, the unmanned device passes through the deceleration strip at the smooth passing speed.

Then, based on the above, a velocity profile of the drone, as shown in figure 3B, may be determined. Similar to fig. 3A, wherein,

is the current position of the drone device,

at a target distance from the uneven road surface,

in order to be the target distance,

in order to be the starting point of the speed bump,

at the end of the deceleration strip, the unmanned equipment is

Is driven at the current speed in the course of

In the process, the speed is reduced according to the maximum braking acceleration and the speed is passed through with the stable passing speed

I.e. at a steady passing speed through the deceleration strip.

Furthermore, the acceleration of the unmanned device may affect the integrity of the cargo, so that the unmanned device can control the unmanned device to decelerate in stages in order to ensure the integrity of the cargo as much as possible and avoid the vehicle from decelerating at the maximum braking acceleration.

Specifically, first, the unmanned aerial vehicle may determine a target distance at which the unmanned aerial vehicle decelerates from the current speed to the smooth passing speed, and determine a position ahead of the uneven road surface with the uneven road surface distance as the target distance, as the second deceleration position. And determining a first deceleration position between the current position of the drone and the second deceleration position. The first deceleration position may be determined randomly, and generally, the closer the first deceleration position is to the current position of the drone, the longer the deceleration process of the drone is, and the lower the distribution efficiency thereof.

The drone may then control itself to travel at the current speed, and when the drone reaches the first deceleration position, select a first braking acceleration from among braking accelerations that are less than the maximum braking acceleration, and control the drone to decelerate at the first braking acceleration. And when the unmanned equipment reaches the second deceleration position, determining second braking acceleration according to the speed, the stable passing speed and the target distance of the unmanned equipment at the second deceleration position, and controlling the unmanned equipment to run according to the second braking acceleration, so that when the unmanned equipment reaches the uneven road surface, the unmanned equipment is decelerated to the stable passing speed and passes through the uneven road surface according to the stable passing speed. As shown in fig. 4.

Fig. 4 is a schematic diagram of a velocity profile of the unmanned aerial vehicle provided in the present specification, in which a solid line a represents a velocity-time curve of the unmanned aerial vehicle performing a uniform deceleration process from a current position to an uneven road surface, and a dotted line b represents a velocity-time curve of the unmanned aerial vehicle performing a stepwise deceleration process from the current position to the uneven road surface, and it is apparent that the solid line a is drawn from the current position

The area enclosed by the time and the coordinate axis and the dotted line b

The area enclosed by the time and the coordinate axis is the same, i.e. the solid line a is

At the moment of reaching the rough road surface, the dotted line b is

The moment of arrival on uneven ground, it is clear that the dotted line b is more efficient in performing the delivery task. Wherein,

as the current time of day, the time of day,

at the moment in dashed line b when the drone reaches the first deceleration position,

at the moment in dashed line b when the drone reaches the second deceleration position,

at the moment when the drone reaches an uneven road surface in dotted line b,

the moment when the drone reaches an uneven road surface in solid line a,

at the moment when the drone leaves the uneven road surface in dotted line b,

the moment when the drone leaves an uneven road surface in solid line a. Obviously, the delivery efficiency of the delivery task performed according to the dashed line b is higher than that of the delivery task performed according to the solid line a, and the dashed line b is less than the maximum braking acceleration because the acceleration is used, so that the influence of the excessive acceleration on the integrity of the goods is also avoided.

The first braking acceleration may be randomly determined from 0 to the maximum braking acceleration. Generally, the greater the first braking acceleration, the faster it decelerates between the first position and the second position, and the less efficient it is to perform a dispensing task.

In addition, the unmanned equipment can firstly judge whether the current speed of the unmanned equipment exceeds the smooth passing speed, and if not, the unmanned equipment can control the unmanned equipment to continuously run at the current speed and accelerate after passing through the uneven road surface. Of course, the unmanned device can also control the unmanned device to accelerate and control the unmanned device to run at a constant speed after the speed reaches the stable passing speed.

In the present specification, the speed control method of the unmanned aerial vehicle is only to control the speed of the unmanned aerial vehicle, and is not to plan the driving path of the unmanned aerial vehicle again. That is, in the case where the travel path has been determined, the unmanned aerial vehicle can perform speed control based on an uneven road surface or the like and travel along the travel path.

Further, since the speed of the unmanned aerial vehicle when traveling along the travel path changes, the position of the unmanned aerial vehicle at each time changes. Therefore, another unmanned device having an intersection point between the travel path and the travel path of the unmanned device may collide with the unmanned device. Thus, to avoid this, the drone may send the newly determined speed of the drone at each time to the server.

The server may determine the location of the drone at each time based on the received re-determined speed of the drone at each time. And judging whether other unmanned equipment which can collide with the unmanned equipment exists, if so, the server can re-determine the driving path or driving speed and the like of the other unmanned equipment, and sends a control instruction to the other unmanned equipment according to the re-determined driving path or driving speed to avoid collision between the other unmanned equipment and the unmanned equipment. Of course, the specific content, control rule, control method, etc. of the control command may be set as required, and this specification does not limit this.

Of course, under the condition that the current speed of the unmanned equipment does not exceed the stable passing speed, the unmanned equipment can also control the unmanned equipment to accelerate to the stable passing speed and drive at the stable passing speed at a constant speed until the unmanned equipment passes through an uneven road surface. The specific method for determining the motion strategy of the unmanned aerial vehicle based on the current speed, the smooth passing speed and the like can be set as required, and the method is not limited in the specification.

Based on the speed control method of the unmanned equipment shown in fig. 1, according to the integrity of the goods loaded by the test equipment after passing through the uneven road surface, the stable passing speed corresponding to the uneven road surface is determined, when the uneven road surface exists in the running path of the unmanned equipment, the nursing between the unmanned equipment and the uneven road surface is determined, so that the motion strategy of the unmanned equipment is determined according to the current speed, the stable passing speed and the distance between the unmanned equipment and the uneven road surface, and the unmanned equipment is controlled to pass through the uneven road surface at the stable passing speed according to the motion strategy. The movement strategy of the unmanned equipment determined by the method considers the influence of an uneven road surface area on the integrity of objects loaded on the unmanned equipment in the driving process, and ensures the completion degree of the distribution task. The movement strategy of the unmanned equipment determined by the method considers the influence of an uneven road surface area on the integrity of objects loaded on the unmanned equipment in the driving process, and ensures the completion degree of the distribution task.

In addition, the smooth passing speed is determined according to the residual amount of the liquid, because in a take-away distribution scene, the integrity of the non-solid goods is difficult to guarantee, and the integrity of other goods can be affected, so that the distribution efficiency is low, and the distribution cost is increased due to the need of cleaning the inside of the unmanned equipment. For example, the goods are coffee, and when the unmanned device passes through uneven road surfaces at a high speed, the vibration frequency is too high, so that the coffee is poured, other goods in the unmanned device and the unmanned device are soaked, and the execution efficiency of the distribution task is reduced.

However, in an actual situation, there is a case where the goods of the distribution task are fragile goods, and therefore, the unmanned aerial vehicle can also determine a smooth passing speed corresponding to the road surface type based on the integrity of the fragile goods in step S100.

Specifically, taking a glass tube as an example, first, a preset number of glass tubes may be placed in a standard container, and the standard container with the glass tubes placed therein is placed in an unmanned device, so that the unmanned device may be used as a test device. Wherein the predetermined number and the standard containers are predetermined similar to the standard volume and the standard container. For example, the preset number is 50, and the standard containers are cartons with the length, width and height of 40cm, 40cm and 60cm respectively. The specific preset number and the type of the standard container may be set according to the requirement, and the specification does not limit this.

Then, aiming at different road surface types, the testing equipment can control the testing equipment to pass through uneven road surfaces containing the road surface type at a constant speed according to preset speeds, and the number of the residual complete glass tubes in the standard container corresponding to the speeds is determined.

Finally, the unmanned equipment can select the speed with the maximum number of the remaining complete glass tubes as the stable passing speed corresponding to the road surface type according to the number of the remaining complete glass tubes corresponding to each speed. Of course, the integrity threshold value can be preset by the unmanned device, and the integrity corresponding to each speed can be determined by the unmanned device according to the number of the remaining intact glass tubes corresponding to the speed and the preset number. And selecting the maximum speed with the integrity higher than the threshold value of the integrity as the smooth passing speed corresponding to the road surface type. The integrity can be determined in particular by the number of remaining intact glass tubes compared to a predetermined number.

Further, the integrity can also be characterized by the degree of deflection of the cargo. Specifically, a cargo with a preset weight and a preset volume can be placed in the unmanned equipment, and the unmanned equipment on which the cargo is placed is used as the test equipment. Then, aiming at different road surface types, the test equipment can control the test equipment to pass through uneven road surfaces containing the road surface type at a constant speed according to preset speeds, and determine the deviation degree of the goods corresponding to the speeds. Finally, the unmanned equipment can select the speed with the minimum deviation degree as the stable passing speed corresponding to the road surface type according to the deviation degree corresponding to each speed. Of course, the deviation degree threshold value can be preset on the unmanned device, and the unmanned device can select the maximum speed of the deviation degree first to the deviation degree threshold value as the smooth passing speed corresponding to the road surface type. The degree of offset may be determined based on the offset angle of the cargo. The degree of offset is inversely proportional to the degree of integrity. Of course, the preset weight, the standard volume, and the like can be determined according to the weight, the volume, and the like of each cargo in the actual distribution process, and specific numerical values and the like can be set as needed. This is not limited by the present description.

Further, as previously mentioned, there are various types of rough surfaces, and the different types of rough surfaces do not contribute to the integrity of the cargo after the unmanned equipment is loaded with the cargo over the rough surface. For example, for the same unmanned vehicle loaded with the same cargo at the same speed, the rubber deceleration strip and the cast steel deceleration strip have different effects on the integrity of the loaded cargo. Therefore, in order to ensure the integrity of the goods after the unmanned device passes through various uneven road surfaces, in step S104, the road surface data of the driving path is also required to be identified, and the type of the uneven road surface is determined.

Specifically, the unmanned aerial vehicle may recognize road surface data of the travel route determined in step S102, and determine whether each target object exists in the road surface data. Such as road joints, potholes, speed bumps, and the like. Wherein, if the target object exists, the determined target object has characteristics of size and the like, for example, the target object is a deceleration strip with the height of 3 cm. At this time, the obtained object is recognized as a rough road surface of each specific road surface type.

Thus, in the case where it is determined that the target object exists, the unmanned aerial vehicle can treat each target object as each uneven road surface. That is, it may be determined that there is an uneven road surface in front of the drone that may affect the integrity of the cargo after the drone passes.

In addition, as described above, since there are a plurality of types of uneven road surfaces, and different uneven road surfaces have different influences on the integrity of the load after the unmanned aerial vehicle has loaded the load thereon, it is also necessary to determine the type of uneven road surface and select a smooth passing speed of the corresponding type of uneven road surface to perform the subsequent steps in step S104.

Specifically, for uneven road surfaces of different road surface types, smooth passing speeds corresponding to the different road surface types are prestored in the unmanned device, so that the unmanned device can determine the smooth passing speed corresponding to the road surface type of the uneven road surface from the preset smooth passing speeds corresponding to the different road surface types according to the road surface type of the uneven road surface determined in step S104, so as to execute the subsequent steps.

In addition, since the travel path may have an influence on the magnitude of the acceleration of the unmanned aerial vehicle, for example, in a place where the curvature is large, if the braking acceleration of the unmanned aerial vehicle is too large, the unmanned aerial vehicle may be caused to roll over. Therefore, in order to ensure the driving safety of the unmanned device, in step S106, the unmanned device may further determine, according to the driving path, a maximum braking acceleration of the unmanned device when the unmanned device drives along the driving path as a candidate braking acceleration, and determine whether the candidate braking acceleration is greater than the maximum braking acceleration of the unmanned device, if so, keep the maximum braking acceleration of the unmanned device unchanged, and if not, take the candidate braking acceleration as the maximum braking acceleration of the unmanned device. That is, from the maximum braking acceleration of the unmanned aerial vehicle and the candidate braking acceleration, the smallest acceleration is determined as the maximum braking acceleration of the unmanned aerial vehicle.

It should be noted that the re-determined maximum braking acceleration may be used in combination with the method in step S106 to determine the motion strategy of the unmanned aerial vehicle.

Further, in the process that the unmanned device controls itself to perform the periodic deceleration, a situation may occur that the first deceleration position is too close to the current position of the unmanned device, or the first braking acceleration is selected to be too large, so that the unmanned device does not reach the second deceleration position yet, and the speed of the unmanned device reaches the smooth passing speed. Therefore, in step S106, in order to avoid the situation that the unmanned device continues to decelerate when the above situation occurs, which may result in the vehicle delivery efficiency being too low, the unmanned device may monitor the vehicle speed and control the unmanned device to travel at the smooth passing speed until the rough road surface is passed when the speed reaches the smooth passing speed.

Based on the same idea, the present specification further provides a corresponding path planning apparatus for an unmanned aerial vehicle, as shown in fig. 5.

Fig. 5 is a schematic diagram of a path planning device of an unmanned aerial vehicle provided in this specification, which specifically includes:

the first determining module 200 is configured to determine a smooth passing speed corresponding to an uneven road surface according to the integrity of the goods loaded by the testing equipment after passing through the uneven road surface.

The second determining module 202 is configured to determine road surface data corresponding to a driving path of the unmanned aerial vehicle according to the driving path.

A third determining module 204, configured to determine a distance between the unmanned aerial vehicle and an uneven road surface when it is determined that the uneven road surface exists according to the road surface data.

And the control module 206 is configured to determine a motion strategy of the unmanned aerial vehicle according to the current speed of the unmanned aerial vehicle, the smooth passing speed, and the distance between the unmanned aerial vehicle and the uneven road surface, and control the unmanned aerial vehicle to pass through the uneven road surface at the smooth passing speed according to the motion strategy.

Optionally, the second determining module 202 is specifically configured to determine a driving path of the unmanned aerial vehicle and environment data around the unmanned aerial vehicle, project the driving path into the environment data, determine area environment data corresponding to the driving path in the environment data, and determine road surface data in the area environment data as the road surface data corresponding to the driving path, where the environment data includes at least one of high-precision map data, point cloud data, and image data.

Optionally, the third determining module 204 is specifically configured to perform object identification on the road surface data, and determine that the object is an uneven road surface when the object exists in the road surface data.

Optionally, the first determining module 200 is further configured to determine an unmanned device in which a standard container containing a standard volume of liquid is placed, as a testing device, control the testing device to pass through an uneven road surface at a constant speed according to preset speeds, determine the remaining amount of the liquid in the standard container corresponding to each speed, and determine a smooth passing speed corresponding to the uneven road surface according to the remaining amount of the liquid corresponding to each speed.

Optionally, the control module 206 is specifically configured to determine a target distance decelerated to the smooth passing speed according to the maximum braking acceleration of the unmanned aerial vehicle, the smooth passing speed, and the current speed, determine a motion strategy of the unmanned aerial vehicle according to the maximum braking acceleration and the target distance, control the unmanned aerial vehicle to travel according to the current speed according to the motion strategy, and control the unmanned aerial vehicle to decelerate according to the maximum braking acceleration when the distance between the unmanned aerial vehicle and the uneven road surface is the target distance, so that the unmanned aerial vehicle passes through the uneven road surface according to the smooth passing speed.

Optionally, the control module 206 is specifically configured to, when the current speed of the unmanned aerial vehicle is lower than the steady passing speed, determine a target acceleration according to the current speed of the unmanned aerial vehicle, the steady passing speed, and the distance between the unmanned aerial vehicle and the uneven road surface, determine a motion strategy of the unmanned aerial vehicle according to the target acceleration, and control the unmanned aerial vehicle to accelerate according to the target acceleration according to the motion strategy, so that the unmanned aerial vehicle passes through the uneven road surface according to the steady passing speed.

Optionally, before determining the target distance decelerated to the smooth passing speed, the control module 206 is further configured to determine a traveling path of the unmanned aerial vehicle, determine, according to the traveling path, a maximum braking acceleration of the unmanned aerial vehicle when traveling along the traveling path as a candidate braking acceleration, and determine, from the maximum braking acceleration of the unmanned aerial vehicle and the candidate braking acceleration, a minimum acceleration as the maximum braking acceleration of the unmanned aerial vehicle.

The present specification also provides a computer-readable storage medium having stored thereon a computer program operable to execute the method of controlling the speed of the unmanned aerial vehicle provided in fig. 1 above.

This description also provides a schematic block diagram of the drone shown in figure 6. As shown in fig. 6, at the hardware level, the electronic device includes a processor, an internal bus, a network interface, a memory, and a non-volatile memory, but may also include hardware required for other services. The processor reads a corresponding computer program from the non-volatile memory into the memory and then runs the computer program to implement the method for controlling the speed of the drone device described above with respect to fig. 1. Of course, besides the software implementation, the present specification does not exclude other implementations, such as logic devices or a combination of software and hardware, and the like, that is, the execution subject of the following processing flow is not limited to each logic unit, and may be hardware or logic devices.

In the 90 s of the 20 th century, improvements in a technology could clearly distinguish between improvements in hardware (e.g., improvements in circuit structures such as diodes, transistors, switches, etc.) and improvements in software (improvements in process flow). However, as technology advances, many of today's process flow improvements have been seen as direct improvements in hardware circuit architecture. Designers almost always obtain the corresponding hardware circuit structure by programming an improved method flow into the hardware circuit. Thus, it cannot be said that an improvement in the process flow cannot be realized by hardware physical modules. For example, a Programmable Logic Device (PLD), such as a Field Programmable Gate Array (FPGA), is an integrated circuit whose Logic functions are determined by programming the Device by a user. A digital system is "integrated" on a PLD by the designer's own programming without requiring the chip manufacturer to design and fabricate application-specific integrated circuit chips. Furthermore, nowadays, instead of manually making an Integrated Circuit chip, such Programming is often implemented by "logic compiler" software, which is similar to a software compiler used in program development and writing, but the original code before compiling is also written by a specific Programming Language, which is called Hardware Description Language (HDL), and HDL is not only one but many, such as abel (advanced Boolean Expression Language), ahdl (alternate Hardware Description Language), traffic, pl (core universal Programming Language), HDCal (jhdware Description Language), lang, Lola, HDL, laspam, hardward Description Language (vhr Description Language), vhal (Hardware Description Language), and vhigh-Language, which are currently used in most common. It will also be apparent to those skilled in the art that hardware circuitry that implements the logical method flows can be readily obtained by merely slightly programming the method flows into an integrated circuit using the hardware description languages described above.

The controller may be implemented in any suitable manner, for example, the controller may take the form of, for example, a microprocessor or processor and a computer-readable medium storing computer-readable program code (e.g., software or firmware) executable by the (micro) processor, logic gates, switches, an Application Specific Integrated Circuit (ASIC), a programmable logic controller, and an embedded microcontroller, examples of which include, but are not limited to, the following microcontrollers: ARC 625D, Atmel AT91SAM, Microchip PIC18F26K20, and Silicone Labs C8051F320, the memory controller may also be implemented as part of the control logic for the memory. Those skilled in the art will also appreciate that, in addition to implementing the controller as pure computer readable program code, the same functionality can be implemented by logically programming method steps such that the controller is in the form of logic gates, switches, application specific integrated circuits, programmable logic controllers, embedded microcontrollers and the like. Such a controller may thus be considered a hardware component, and the means included therein for performing the various functions may also be considered as a structure within the hardware component. Or even means for performing the functions may be regarded as being both a software module for performing the method and a structure within a hardware component.

The systems, devices, modules or units illustrated in the above embodiments may be implemented by a computer chip or an entity, or by a product with certain functions. One typical implementation device is a computer. In particular, the computer may be, for example, a personal computer, a laptop computer, a cellular telephone, a camera phone, a smartphone, a personal digital assistant, a media player, a navigation device, an email device, a game console, a tablet computer, a wearable device, or a combination of any of these devices.

For convenience of description, the above devices are described as being divided into various units by function, and are described separately. Of course, the functions of the various elements may be implemented in the same one or more software and/or hardware implementations of the present description.

As will be appreciated by one skilled in the art, embodiments of the present invention may be provided as a method, system, or computer program product. Accordingly, the present invention may take the form of an entirely hardware embodiment, an entirely software embodiment or an embodiment combining software and hardware aspects. Furthermore, the present invention may take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, and the like) having computer-usable program code embodied therein.

The present invention is described with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the invention. It will be understood that each flow and/or block of the flow diagrams and/or block diagrams, and combinations of flows and/or blocks in the flow diagrams and/or block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to a processor of a general purpose computer, special purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.

These computer program instructions may also be stored in a computer-readable memory that can direct a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer-readable memory produce an article of manufacture including instruction means which implement the function specified in the flowchart flow or flows and/or block diagram block or blocks.

These computer program instructions may also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.

In a typical configuration, a computing device includes one or more processors (CPUs), input/output interfaces, network interfaces, and memory.

The memory may include forms of volatile memory in a computer readable medium, Random Access Memory (RAM) and/or non-volatile memory, such as Read Only Memory (ROM) or flash memory (flash RAM). Memory is an example of a computer-readable medium.

Computer-readable media, including both non-transitory and non-transitory, removable and non-removable media, may implement information storage by any method or technology. The information may be computer readable instructions, data structures, modules of a program, or other data. Examples of computer storage media include, but are not limited to, phase change memory (PRAM), Static Random Access Memory (SRAM), Dynamic Random Access Memory (DRAM), other types of Random Access Memory (RAM), Read Only Memory (ROM), Electrically Erasable Programmable Read Only Memory (EEPROM), flash memory or other memory technology, compact disc read only memory (CD-ROM), Digital Versatile Discs (DVD) or other optical storage, magnetic cassettes, magnetic tape magnetic disk storage or other magnetic storage devices, or any other non-transmission medium that can be used to store information that can be accessed by a computing device. As defined herein, a computer readable medium does not include a transitory computer readable medium such as a modulated data signal and a carrier wave.

It should also be noted that the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus. Without further limitation, an element defined by the phrase "comprising an … …" does not exclude the presence of other like elements in a process, method, article, or apparatus that comprises the element.

As will be appreciated by one skilled in the art, embodiments of the present description may be provided as a method, system, or computer program product. Accordingly, the description may take the form of an entirely hardware embodiment, an entirely software embodiment or an embodiment combining software and hardware aspects. Furthermore, the description may take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, and the like) having computer-usable program code embodied therein.

This description may be described in the general context of computer-executable instructions, such as program modules, being executed by a computer. Generally, program modules include routines, programs, objects, components, data structures, etc. that perform particular tasks or implement particular abstract data types. The specification may also be practiced in distributed computing environments where tasks are performed by remote processing devices that are linked through a communications network. In a distributed computing environment, program modules may be located in both local and remote computer storage media including memory storage devices.

The embodiments in the present specification are described in a progressive manner, and the same and similar parts among the embodiments are referred to each other, and each embodiment focuses on the differences from the other embodiments. In particular, for the system embodiment, since it is substantially similar to the method embodiment, the description is simple, and for the relevant points, reference may be made to the partial description of the method embodiment.

The above description is only an example of the present specification, and is not intended to limit the present specification. Various modifications and alterations to this description will become apparent to those skilled in the art. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present specification should be included in the scope of the claims of the present specification.

Claims

1. A method of speed control of an unmanned aerial vehicle, the method comprising:

2. The method according to claim 1, wherein determining the road surface data corresponding to the travel path according to the travel path of the unmanned aerial vehicle comprises:

3. The method of claim 1, wherein determining the presence of an uneven road surface based on the road surface data comprises:

4. The method according to claim 1, wherein the determining of the smooth passing speed corresponding to the uneven road surface according to the integrity of the goods after the testing equipment loads the goods and passes through the uneven road surface comprises:

5. The method of claim 1, wherein determining a motion strategy for the drone according to the current speed of the drone, the smooth passing speed, and the distance of the drone from the uneven road surface, and controlling the drone to pass over the uneven road surface at the smooth passing speed according to the motion strategy comprises:

6. The method of claim 1, wherein determining a motion strategy for the drone according to the current speed of the drone, the smooth passing speed, and the distance of the drone from the uneven road surface, and controlling the drone to pass over the uneven road surface at the smooth passing speed according to the motion strategy comprises:

7. The method of claim 5, wherein prior to determining the target distance to decelerate to the smooth pass velocity, the method further comprises:

determining a driving path of the unmanned device;

8. The method according to claim 1, wherein the determining of the smooth passing speed corresponding to the uneven road surface according to the integrity of the goods after the testing equipment loads the goods and passes through the uneven road surface comprises:

9. The method of claim 8, wherein prior to determining the motion strategy of the unmanned device, the method further comprises:

10. A path planning apparatus for an unmanned aerial device, the apparatus comprising:

11. A computer-readable storage medium, characterized in that the storage medium stores a computer program which, when executed by a processor, implements the method of any of the preceding claims 1 to 9.

12. An unmanned aerial vehicle comprising a memory, a processor and a computer program stored on the memory and executable on the processor, wherein the processor when executing the program implements the method of any of claims 1 to 9.