CN114281069A

CN114281069A - Control method and device of unmanned equipment

Info

Publication number: CN114281069A
Application number: CN202111579412.1A
Authority: CN
Inventors: 佟源洋; 王庆全
Original assignee: Beijing Sankuai Online Technology Co Ltd
Current assignee: Beijing Sankuai Online Technology Co Ltd
Priority date: 2021-12-22
Filing date: 2021-12-22
Publication date: 2022-04-05

Abstract

The specification discloses a method and a device for controlling unmanned equipment, and particularly discloses that for each function module in an automatic driving system, environment parameters of a working environment in which the function module is located when the function module operates and operation parameters generated when the function module operates are monitored, then, according to corresponding relations between different types of environment parameters and different standard operation parameters, standard operation parameters corresponding to the function module when the function module operates in the working environment are inquired, whether the function module is in an abnormal working state or not is determined, and finally, in response to the function module in the abnormal working state existing in the automatic driving system, the automatic driving system is adjusted according to an adjustment strategy for each function module, so that the unmanned equipment is controlled based on the adjusted automatic driving system. In this way, the stability of the autopilot system can be improved.

Description

Control method and device of unmanned equipment

Technical Field

The specification relates to the technical field of unmanned driving, in particular to a control method and device of unmanned equipment.

Background

Along with the development of computer technology, unmanned equipment is increasingly used in people's daily life. In practical applications, in order to ensure the driving safety of the unmanned device, an automatic driving system of the unmanned device is generally required to be optimized.

Currently, optimization of the autopilot system of the unmanned aerial vehicle is usually based on faults occurring during the driving of the unmanned aerial vehicle. For example, it is determined that the unmanned device has a fault (e.g., drawing a dragon on the trajectory) according to the driving trajectory of the unmanned device during driving, the acquired image, and the like. At the moment, great potential safety hazards exist in the automatic driving of the unmanned equipment, a technician takes over the control right of the unmanned equipment, meanwhile, fault troubleshooting is carried out on the basis of data when the unmanned equipment breaks down, a corresponding fault point is determined, and then the automatic driving system is optimized. Therefore, the automatic driving system can be optimized only under the condition of failure, and when the unmanned equipment has failure but does not show a corresponding phenomenon (such as a trace drawing dragon), the unmanned equipment cannot be determined to have failure in time, and the unmanned equipment cannot be optimized according to the failure, so that the unmanned equipment has great potential safety hazard.

Therefore, how to identify the abnormality of the autonomous driving system before the unmanned device has a fault but does not show a corresponding appearance is an urgent problem to be solved.

Disclosure of Invention

The present specification provides a method and an apparatus for controlling 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 control method for an unmanned device, the method is applied to the field of unmanned driving, an automatic driving system is installed on the unmanned device, the automatic driving system is composed of a plurality of functional modules, and the method comprises the following steps:

monitoring an environment parameter of a working environment in which each functional module in the automatic driving system operates and an operation parameter generated in the operation of the functional module in the driving process of the unmanned equipment;

inquiring standard operation parameters corresponding to the environment parameters according to corresponding relations between different types of environment parameters and different standard operation parameters, and using the standard operation parameters as the standard operation parameters corresponding to the function module when the function module operates in the working environment;

determining whether the functional module is in an abnormal working state or not according to the operating parameters and standard operating parameters corresponding to the functional module when the functional module operates in the working environment;

and responding to the functional modules in the abnormal working state in the automatic driving system, and adjusting the automatic driving system according to the adjustment strategies aiming at the functional modules so as to control the unmanned equipment based on the adjusted automatic driving system.

Optionally, the operation parameter includes at least one of a communication time consumed for the communication between the functional module and another functional module in the automatic driving system and a time consumed for the functional module to perform a task.

Optionally, the environment parameter includes at least one of a number of hardware resources configured on the unmanned aerial vehicle, a number of unoccupied remaining hardware resources at the current time, a fluctuation value of the number of resources occupied by the functional module during operation in history, and an environment temperature at which the functional module operates at the current time.

Optionally, adjusting the automatic driving system according to an adjustment strategy for each functional module specifically includes:

determining modules with abnormity in the function modules as abnormal function modules according to the determined working states of the function modules;

aiming at each abnormal function module, judging whether the priority corresponding to the abnormal function module meets a preset priority condition or not;

if so, adjusting the abnormal function module according to a preset adjustment strategy aiming at the abnormal function module, and if not, not adjusting the abnormal function module.

Optionally, adjusting the abnormal function module according to the adjustment policy for the abnormal function module specifically includes:

determining an adjustment strategy aiming at the abnormal function module according to a preset working frequency adjustment rule;

and reducing the working frequency of the abnormal function module according to the adjustment strategy aiming at the abnormal function module.

Optionally, the method further comprises:

and generating a fault record aiming at the functional module with the abnormity, and uploading the fault record to a server.

Optionally, the method further comprises:

responding to the fact that the unmanned equipment completes task execution, uploading the monitored running data in the running process of the unmanned equipment to the server, so that the server analyzes the running data based on the fault point record, determines the fault reason of the unmanned equipment, determines an optimization strategy aiming at the fault reason according to the fault reason, and optimizes the automatic driving system through the optimization strategy.

This specification provides a controlling means of unmanned equipment, the device is applied to the unmanned field, installs the autopilot system on the unmanned equipment, autopilot comprises a plurality of functional module, includes:

the monitoring module is used for monitoring the environmental parameters of the working environment in which the functional module operates and the operating parameters generated by the functional module during operation aiming at each functional module in the automatic driving system in the driving process of the unmanned equipment;

the determining module is used for inquiring standard operating parameters corresponding to the environment parameters according to the corresponding relations between the environment parameters of different types and the operating parameters of different standards, and the standard operating parameters are used as the standard operating parameters corresponding to the functional module when the functional module operates in the working environment;

the judging module is used for determining whether the functional module is in an abnormal working state or not according to the operating parameters and the standard operating parameters corresponding to the functional module when the functional module operates in the working environment;

and the adjusting module is used for responding to the functional modules in the abnormal working state in the automatic driving system, adjusting the automatic driving system according to the adjusting strategy aiming at each functional module, and controlling the unmanned equipment based on the adjusted automatic driving system.

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

The present specification provides an unmanned aerial vehicle comprising a memory, a processor and a computer program stored on the memory and executable on the processor, the processor implementing the above-described method of controlling an unmanned aerial vehicle when executing the program.

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

in the method for controlling the unmanned aerial vehicle provided in this specification, in the course of driving the unmanned aerial vehicle, for each function module in the automatic driving system, an environmental parameter of a working environment in which the function module is operated and an operation parameter generated when the function module is operated are monitored, then, according to a correspondence between different types of environmental parameters and different standard operation parameters, a standard operation parameter corresponding to the environmental parameter is inquired out, and is used as a standard operation parameter corresponding to the function module when the function module is operated in the working environment, and then, according to the operation parameter and the standard operation parameter corresponding to the function module when the function module is operated in the working environment, whether the function module is in an abnormal working state is determined, and finally, in response to the function module in the abnormal working state existing in the automatic driving system, according to an adjustment strategy for each function module, the autonomous driving system is adjusted to control the unmanned device based on the adjusted autonomous driving system.

It can be seen from the above method that the method can directly monitor the operating parameters of the functional modules, and thus identify an abnormality of the autonomous driving system before the unmanned device has a fault but does not show a corresponding representation. Meanwhile, different standard operation parameters are adopted for different types of environment parameters, and the operation parameters generated when the functional module operates are evaluated, so that the influence of environment factors on the stability of the automatic driving system can be reduced, and the stability of the automatic driving system is improved.

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 chart of a control method of an unmanned aerial vehicle in the present specification;

fig. 2 is a detailed flowchart of an execution of the control method of the unmanned aerial vehicle provided in the present specification;

FIG. 3 is a schematic diagram of a control apparatus for an unmanned aerial vehicle provided herein;

fig. 4 is a schematic view of the drone corresponding to fig. 1 provided by the present description.

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.

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 control method of an unmanned aerial vehicle in this specification, and specifically includes the following steps:

step S100, in the driving process of the unmanned equipment, aiming at each functional module in the automatic driving system, monitoring the environmental parameters of the working environment in which the functional module operates and the operating parameters generated in the operation of the functional module.

The method for controlling the unmanned equipment is used for controlling the unmanned equipment provided with the automatic driving system, the automatic driving system is composed of a plurality of functional modules, the automatic driving system composed of the functional modules makes a decision in the driving process of the unmanned equipment and controls the unmanned equipment according to a decision result so as to realize the unmanned driving of the unmanned equipment.

In the driving process of the unmanned equipment, if the unmanned equipment breaks down, visual representations such as line pressing, vehicle body shaking, trajectory dragon drawing and the like can appear when the consumed time of the functional modules reaches a certain time length because the functional modules which are used for executing tasks exist in the functional modules in the automatic driving system. When optimizing an automatic driving system on the unmanned device, it is difficult to identify an abnormality of the automatic driving system before the unmanned device has a fault but does not show a corresponding representation.

The functional module may be a module formed by combining hardware and software, which can realize a certain function, for example, a functional module of an automatic driving system, and may include a central processing unit module, a power management module, a power monitoring module, a speed detection module, a path recognition module, a fault diagnosis module, an obstacle detection module, a motor driving module, a display module, a voice module, and the like.

Based on this, in the method, the unmanned device may monitor an operation parameter generated when the function module operates for each function module in the automatic driving system, and determine whether the unmanned device has a fault according to the monitored operation parameter and a standard operation parameter corresponding to the function module.

The operation parameters may include at least one of time consumed for communication between the functional module and other modules in the autopilot system and time consumed for the module to perform a task. The communication between the functional module and the other modules may include: the function module sends information to other modules, receives messages returned by other function modules, processes the messages sent by the function module and calls back functions of the function module by other modules, and the like. The tasks executed by the functional module may include processing the arithmetic logic, inputting and outputting data, initiating a network request, applying for resources, releasing resources, and the like that the functional module itself can implement.

And when judging whether the unmanned equipment has faults or not according to the standard operation parameters corresponding to the functional modules, determining the standard operation parameters corresponding to the functional modules in advance.

For example, the operating parameters that the unmanned aerial vehicle can intuitively realize normal driving can be obtained from the operating parameters historically monitored for the unmanned aerial vehicle, the operating parameters corresponding to each functional module are clustered, and then the maximum value of the operating parameters in the obtained cluster is used as the standard operating parameters corresponding to the functional module.

For another example, the operating parameters that the unmanned aerial vehicle can intuitively realize normal driving can be obtained from the operating parameters historically monitored for the unmanned aerial vehicle, statistical analysis is performed on the operating parameters corresponding to each functional module, the mean value and the variance of the operating parameters are determined, and then the operating parameters are determined as the standard operating parameters corresponding to the functional module according to the determined mean value and variance.

For another example, the operating parameters that the unmanned aerial vehicle can intuitively realize normal driving can be obtained from the operating parameters historically monitored for the unmanned aerial vehicle, then, for each functional module, the distribution of the operating parameters met by the operating parameters corresponding to the functional module is fitted according to the operating parameters corresponding to the functional module, and then, based on the distribution of the operating parameters and the preset corresponding proportion of the functional module in the abnormal working state, the standard operating parameters corresponding to the functional module are determined.

Further, when the unmanned device runs, the working environment of each functional module in the automatic driving system is different, and the standard operating parameters corresponding to the functional modules may be different. For example, the higher the temperature at which the functional module operates, the lower the standard operating parameter corresponding to the functional module, so as to avoid the abnormal operating state of the functional module caused by the over-high temperature at which the functional module operates.

Therefore, in this specification, different standard operation parameters may be set for different types of environment parameters, and thus, according to the environment parameter of the operating environment in which the functional module operates, the standard operation parameter corresponding to the functional module operating in the operating environment corresponding to the environment parameter may be determined, and further, according to the operation parameter generated during the operating of the functional module and the standard operation parameter corresponding to the functional module operating in the operating environment corresponding to the environment parameter, whether the unmanned equipment has a fault may be determined.

The environment parameters of the working environment in which the functional module operates refer to a hardware resource configuration condition of the unmanned device in which the automatic driving system including the functional module is located (e.g., the number of computing resources of a CPU installed on the unmanned device, the number of memory resources installed on the unmanned device, and the like), a usage condition of the hardware resources on the unmanned device in which the functional module operates (e.g., the number of computing resources of a remaining CPU, the number of remaining memory resources, and the like), and an actual environment in which the functional module operates (e.g., a temperature at which the functional module operates, a humidity at which the functional module operates, and the like).

In addition, the quantity of the resources historically occupied by the functional module during operation can be acquired for each functional module, then, the difference value between the maximum value and the minimum value of the quantity of the resources historically occupied by the functional module during operation is determined, and the difference value is used as the fluctuation value of the quantity of the resources historically occupied by the functional module during operation. Therefore, after the fluctuation value of the number of resources occupied by each functional module during operation and the use condition of hardware resources on the unmanned equipment are determined, whether the number of the current residual resources can meet the requirement that the number of the resources used by each functional module changes suddenly or not can be judged. And further, the safety of the unmanned equipment can be guaranteed to a greater extent.

Specifically, when the environmental parameters of different types and the standard operating parameters correspond to each other, the operating parameters that the unmanned aerial vehicle can intuitively realize normal driving can be obtained from the operating parameters historically monitored for the unmanned aerial vehicle, then, the operating parameters corresponding to each functional module are divided based on the environmental parameters according to each functional module to obtain the operating parameters under the environmental parameters of different types, and then, under each type of environmental parameters, the standard operating parameters corresponding to the functional module during operation are determined in the manner of determining the standard operating parameters described above and stored.

There are various ways in which the drone divides different types of environmental parameters. For example, each environmental parameter may be divided according to a preset interval, and then randomly combined to obtain different types of environmental parameters. The operation parameters and the environment parameters when the operation parameters are collected can be clustered to obtain different types of environment parameters.

Step S102, according to the corresponding relation between different types of environment parameters and different standard operation parameters, inquiring the standard operation parameters corresponding to the environment parameters, and using the standard operation parameters as the standard operation parameters corresponding to the operation of the functional module in the working environment.

Step S104, determining whether the function module is in an abnormal working state according to the operation parameters and the standard operation parameters corresponding to the function module when the function module operates in the working environment

In specific implementation, for each functional module, according to an environmental parameter of a working environment in which the functional module operates, the unmanned device queries a standard operating parameter corresponding to the functional module in operation in the working environment corresponding to the environmental parameter from a corresponding relationship between environmental parameters of different types and different standard operating parameters, which are predetermined based on the different types. And then, the unmanned equipment can compare the monitored operation parameters generated when the functional module operates with the corresponding standard operation parameters respectively, if the operation parameters are greater than the standard operation parameters, the functional module is determined to be in an abnormal working state, and if not, the functional module is determined to be in a normal working state.

And S106, responding to the functional modules in the abnormal working state in the automatic driving system, and adjusting the automatic driving system according to the adjustment strategies aiming at the functional modules so as to control the unmanned equipment based on the adjusted automatic driving system.

In specific implementation, the unmanned device responds to the functional modules in abnormal working states in the automatic driving system, determines the modules with abnormal working states in the functional modules as abnormal functional modules according to the determined working states of the functional modules, then judges whether the priority corresponding to the abnormal functional modules meets preset priority conditions or not for each abnormal functional module, if so, adjusts the abnormal functional modules according to an adjustment strategy for the abnormal functional modules, and if not, does not adjust the abnormal functional modules.

In the above process, it is necessary to set corresponding priorities in advance according to contributions of each functional module to the automatic driving system when the automatic driving system is automatically driven, and the higher the priority of the functional module is, the more important the normal operation of the functional module is when the unmanned device realizes the unmanned function.

In a specific implementation, when the priority corresponding to the abnormal functional module meets a condition, it may be determined that the priority corresponding to the abnormal functional module meets a preset priority condition. For example, if the unmanned device determines that no other function module with a priority lower than the priority corresponding to the abnormal function module exists in the currently running function modules, it determines that the priority corresponding to the abnormal function module meets a preset priority condition. For another example, when the unmanned device determines that a set number of function modules are searched from the function module with the lowest priority step by step upwards for adjustment according to the priority corresponding to the abnormal function module, and the abnormal function module is included, it is determined that the priority corresponding to the abnormal function module meets a preset priority condition. Other examples are not given.

Furthermore, each function module included in the automatic driving system is not all core function modules for realizing the automatic driving function, so that when the function module in the abnormal working state in the automatic driving system is determined, the function module can be further divided into three levels, namely a core function module, a secondary core function module and a common module, and the function realized by the core function module is defined as the indispensable function for realizing the automatic driving function, the core function modules can not be closed, and the working frequency can not be changed. The functions realized by the secondary core function modules are relatively important, the secondary core function modules cannot be closed, the working frequency is the lowest working frequency, when the working frequency of the function modules is reduced to the set lowest working frequency, the control right of the unmanned equipment needs to be handed over to workers, the workers carry out remote control on the unmanned equipment, or the unmanned equipment automatically drives to a roadside berthable area to carry out side berthing parking so as to ensure the driving safety of the unmanned equipment.

The correlation between the functions implemented by the general modules and the automatic driving function is low, and these function modules.

In this way, when the unmanned device adjusts the abnormal function module according to the adjustment strategy for the abnormal function module, the adjustment strategy for the abnormal function module is determined according to the preset working frequency adjustment rule, and then the working frequency of the abnormal function module is reduced according to the adjustment strategy for the abnormal function module.

For example, it is assumed that the function modules assigned to the first priority include function module 1, function module 2, and function module 3, the function modules assigned to the second priority include function module 4 and function module 5, and the function modules assigned to the third priority include function module 6, function module 7, function module 8, and function module 9.

When the unmanned equipment monitors that the functional modules in the abnormal working state exist in the automatic driving system and are the functional module 4, the functional module 7 and the functional module 8, the working frequency of the functional module 7 and the functional module 8 can be reduced according to the preset working frequency step value.

Then, when the unmanned device monitors that the function modules in the abnormal working state in the automatic driving system are the function module 4, the function module 7 and the function module 8 again, the working frequency of the function module 7 and the function module 8 can be further reduced according to a preset working frequency step value (for example, the working frequency is reduced by 10% every time), until the function module 7 and the function module 8 are closed.

Subsequently, if the unmanned device monitors that a function module in an abnormal working state exists in the automatic driving system as the function module 4, the working frequency of the function module 4 can be continuously reduced according to a preset working frequency step value (for example, the working frequency is reduced by 10% every time), until all the function modules in the automatic driving system are monitored to be in a normal working state, or the working frequency of the function module 4 is determined to be reduced to the lowest working frequency, the control right of the unmanned device needs to be handed over to a worker, the worker remotely controls the unmanned device, or the unmanned device automatically drives to a roadside berthable area to berth at the same time to park at the same time, so that the driving safety of the unmanned device is ensured.

In an actual service, the preset operating frequency step value corresponding to the functional module with a high priority may be smaller than the preset operating frequency step value corresponding to the functional module with a low priority.

In addition, in this specification, the unmanned aerial vehicle may also directly sort the function modules according to the priorities corresponding to the function modules, in descending order of the priorities, select the function module located behind the set position as the function module to be adjusted, and reduce the operating frequency of the function modules according to the preset operating frequency step value.

By the method, the operation parameters of the functional modules can be directly monitored, so that the abnormity of the automatic driving system can be identified before the unmanned device has a fault but does not show a corresponding representation. Meanwhile, different standard operation parameters are adopted for different types of environment parameters, and the operation parameters generated when the functional module operates are evaluated, so that the influence of environment factors on the stability of the automatic driving system can be reduced, and the stability of the automatic driving system is improved.

In specific implementation, in the driving process of the unmanned equipment, if it is determined that the functional module in the abnormal working state exists in the automatic driving system, the automatic driving system is adjusted according to the adjustment strategy for each functional module, and meanwhile, a fault record for the functional module with the abnormal working state can be generated and uploaded to the server. In this way, it is possible to obtain an abnormality detected by the unmanned aerial vehicle during the task execution.

The fault record for the functional module with the abnormality at least may include a time when the functional module has the abnormality, a processing measure to be taken, a standard operating parameter to be used, and the like.

In actual business, driving data monitored in the driving process of the unmanned equipment also needs to be uploaded to a server. The driving data may include the driving data monitored by the unmanned aerial vehicle during the driving process, and the driving data is directly uploaded to the server at the time, which occupies a large amount of communication resources.

Specifically, the unmanned device uploads the driving data monitored in the driving process of the unmanned device to the server in response to the completion of task execution. And then, the server analyzes the driving data based on the fault record, determines the fault reason of the unmanned equipment, and determines an optimization strategy aiming at the fault reason according to the fault reason so as to optimize the automatic driving system through the optimization strategy.

After receiving the fault records and the running data of the abnormal functional modules, the server generates a running parameter detailed state table of each working module in the running process of the unmanned equipment according to the uploaded running data and the fault records, wherein the running parameter detailed state table of each working module can comprise the distribution of the running parameters corresponding to each functional module along with time, the running parameter average value corresponding to each functional module, the abnormal moment, the adopted processing measures, the used standard running parameters and the like.

A detailed execution process when the unmanned aerial vehicle is controlled by the control method of the unmanned aerial vehicle provided in the present specification will be given in detail below, with particular reference to fig. 2.

Step S200, in the driving process of the unmanned equipment, aiming at each functional module in the automatic driving system, monitoring the environmental parameters of the working environment in which the functional module operates and the operating parameters generated in the operation of the functional module.

Step S202, the unmanned device inquires out standard operation parameters corresponding to the functional module when the functional module operates in the working environment corresponding to the environment parameters according to the corresponding relation between the environment parameters of different types and the standard operation parameters of different types.

And step S204, the unmanned equipment determines whether the functional module is in an abnormal working state according to the monitored operating parameters and the standard operating parameters.

Step S206, if the functional module is in the abnormal working state, the unmanned equipment determines that the functional module in the abnormal working state exists in the automatic driving system.

And S208, determining abnormal functional modules with abnormity in the functional modules by the unmanned equipment according to the determined working states of the functional modules.

Step S210, the unmanned aerial vehicle determines, for each abnormal function module, whether the priority corresponding to the abnormal function module meets a preset priority condition, if so, executes step S212, otherwise, returns to execute step S200.

Step S212, the unmanned equipment determines an adjustment strategy aiming at the abnormal function module according to a preset working frequency adjustment rule, reduces the working frequency of the abnormal function module according to the adjustment strategy aiming at the abnormal function module, controls the unmanned equipment based on the adjusted automatic driving system, and continuously returns to execute the step S200.

Based on the same idea, the present specification further provides a control device of the unmanned aerial vehicle, as shown in fig. 3, for the control method of the unmanned aerial vehicle provided in one or more embodiments of the present specification.

Fig. 3 is a schematic view of a control device of an unmanned aerial vehicle provided in this specification, where the control device is applied to the field of unmanned aerial vehicle, and an automatic driving system is installed on the unmanned aerial vehicle, where the automatic driving system is composed of a plurality of functional modules, and specifically includes:

the monitoring module 300 is configured to monitor, for each functional module in the automatic driving system, an environmental parameter of a working environment in which the functional module operates and an operating parameter generated when the functional module operates during the driving process of the unmanned device;

a determining module 301, configured to query standard operating parameters corresponding to different types of environment parameters according to correspondence between the environment parameters and the standard operating parameters, and use the standard operating parameters as standard operating parameters corresponding to the functional module when the functional module operates in the working environment;

a determining module 302, configured to determine whether the functional module is in an abnormal working state according to the operating parameter and a standard operating parameter corresponding to the functional module when the functional module operates in the working environment;

an adjusting module 303, configured to, in response to a functional module in an abnormal operating state existing in the autonomous driving system, adjust the autonomous driving system according to an adjustment policy for each functional module, so as to control the unmanned device based on the adjusted autonomous driving system.

Optionally, the adjusting module 303 is specifically configured to determine, according to the determined working state of each functional module, a module with an exception in each functional module, as an exception functional module; aiming at each abnormal function module, judging whether the priority corresponding to the abnormal function module meets a preset priority condition or not; if so, adjusting the abnormal function module according to the adjustment strategy aiming at the abnormal function module, and if not, not adjusting the abnormal function module.

Optionally, the adjusting module 303 is specifically configured to determine an adjusting strategy for the abnormal function module according to a preset working frequency adjusting rule; and reducing the working frequency of the abnormal function module according to the adjustment strategy aiming at the abnormal function module.

Optionally, the apparatus further comprises:

and the fault recording module 304 is configured to generate a fault record for the functional module with the abnormality, and upload the fault record to the server.

Optionally, the fault recording module 304 is specifically configured to, in response to the unmanned aerial vehicle completing task execution, upload driving data monitored in a driving process of the unmanned aerial vehicle to the server, so that the server analyzes the driving data based on the fault point record, determines a fault cause of the unmanned aerial vehicle, and determines an optimization strategy for the fault cause according to the fault cause, so as to optimize the automatic driving system through the optimization strategy.

The present specification also provides a computer-readable storage medium storing a computer program operable to execute the method of controlling the unmanned aerial device provided in fig. 1 described above.

This description also provides a schematic block diagram of the drone shown in figure 4. As shown in fig. 4, the drone includes, at the hardware level, a processor, an internal bus, a network interface, a memory, and a non-volatile memory, although it 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 unmanned aerial vehicle described in 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 control method of unmanned equipment is characterized in that the method is applied to the field of unmanned driving, an automatic driving system is installed on the unmanned equipment, the automatic driving system is composed of a plurality of functional modules, and the method comprises the following steps:

2. The method of claim 1, wherein the operating parameters include at least one of a time consumed for communication between the functional module and other functional modules in the autopilot system, and a time consumed for the functional module to perform a task.

3. The method of claim 1, wherein the environmental parameters include at least one of an amount of hardware resources configured on the drone, an amount of remaining hardware resources unoccupied at a current time, a fluctuating value of an amount of resources historically occupied by the functional module while operating, and an ambient temperature at which the functional module operates at the current time.

4. The method of claim 1, wherein adjusting the autopilot system according to an adjustment strategy for each functional module comprises:

if so, adjusting the abnormal function module according to the adjustment strategy aiming at the abnormal function module, and if not, not adjusting the abnormal function module.

5. The method of claim 4, wherein adjusting the abnormal function module according to the adjustment policy for the abnormal function module comprises:

6. The method of claim 1, wherein the method further comprises:

7. The method of claim 6, wherein the method further comprises:

8. The utility model provides a controlling means of unmanned equipment, its characterized in that, the device is applied to the unmanned field, installs the autopilot system on the unmanned equipment, autopilot comprises a plurality of functional module, includes:

9. 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 7.

10. 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 7.