CN113778083A

CN113778083A - Data processing method and device, storage medium, electronic device and self-moving equipment

Info

Publication number: CN113778083A
Application number: CN202110991292.XA
Authority: CN
Inventors: 张晓骏
Original assignee: Dreame Technology Suzhou Co ltd
Current assignee: Dreame Technology Suzhou Co ltd
Priority date: 2021-08-26
Filing date: 2021-08-26
Publication date: 2021-12-10

Abstract

The invention discloses a data processing method, a data processing device, a computer readable storage medium, an electronic device and self-moving equipment, belonging to the technical field of artificial intelligence, wherein the data processing method comprises the following steps: acquiring environmental parameters acquired from mobile equipment within a set time, wherein the environmental parameters are acquired based on at least one environmental acquisition device; determining target environment parameters matched with different environment acquisition devices; and controlling the self-moving equipment to operate based on each target environment parameter. The data processing method can screen out more accurate environmental parameters, reduce the data interaction amount and further more quickly and accurately control the operation of the mobile equipment.

Description

Data processing method and device, storage medium, electronic device and self-moving equipment

Technical Field

The present application relates to the field of artificial intelligence technologies, and in particular, to a data processing method, a data processing apparatus, a computer-readable storage medium, an electronic apparatus, and a self-moving device.

Background

With the development of the technology, the application of the self-moving equipment is more extensive, and the self-moving equipment, such as a sweeper, a mower, an automatic irrigation machine and the like, can be automatically moved indoors or outdoors to operate, so that the labor can be greatly saved, and the working efficiency is improved.

The existing mobile equipment is usually provided with various environment acquisition devices such as a laser radar and the like, and the external environment is identified through the environment acquisition devices. For example, the distance between the obstacle and the boundary of the working area is calculated through the data acquired by the environment acquisition device, so that the position of the self-moving equipment is positioned, and the self-moving equipment can reliably move in the working area.

However, the topography of the working area is complex and various, taking the automatic lawn mower as an example, the automatic lawn mower usually works on outdoor lawn, and the lawn has high or low topography and steep or gentle and steep gradient, which causes the environmental acquisition devices such as laser radar to fluctuate and incline along with the topography, and cannot keep a specific state for acquisition, resulting in inaccurate distance measurement and being not beneficial to the accurate positioning of the automatic lawn mower. In addition, in the working process of the environment acquisition device, a large amount of data can be generated, and if the data are not screened, the data interaction amount is overlarge, the calculation speed is slowed down, and the command is not convenient for quick and accurate issuing from the mobile equipment.

Accordingly, there is a need for improvements in the art that overcome the deficiencies in the prior art.

Disclosure of Invention

The invention aims to provide a data processing method, a data processing device, a computer readable storage medium, an electronic device and a self-moving device.

In order to achieve the above object, in a first aspect, the present invention provides a data processing method, including the following steps:

acquiring environmental parameters acquired from mobile equipment within a set time, wherein the environmental parameters are acquired based on at least one environmental acquisition device;

determining target environment parameters matched with different environment acquisition devices;

and controlling the self-moving equipment to operate based on each target environment parameter.

Further, the determining target environment parameters matched with different environment acquisition devices includes:

determining a matching condition corresponding to each environment acquisition device;

and determining the target environment parameters matched with each environment acquisition device according to the matching conditions.

Further, at least two environment acquisition devices have different matching conditions.

Further, the environment acquisition devices comprise target detectors, and the determining of the matching condition corresponding to each environment acquisition device comprises:

determining a corresponding acquisition attitude matching condition of the target detector;

and taking the environmental parameters acquired by the target detector under the acquisition posture matching condition as the target environmental parameters corresponding to the target detector.

Further, before taking the environmental parameter acquired by the target detector under the acquisition posture matching condition as the target environmental parameter corresponding to the target detector, the method further includes:

and determining the acquisition attitude of the target detector based on the position sensor.

Further, the obtaining the environmental parameters collected from the mobile device within the set time includes:

obtaining a reflected electromagnetic wave signal received by the object detector for the object,

determining a position parameter of the target based on the reflected electromagnetic wave signal, the position parameter being the environmental parameter.

In a second aspect, the present invention further provides a data processing apparatus, including:

the environment parameter acquisition module is used for acquiring environment parameters acquired from the mobile equipment within set time, wherein the environment parameters are acquired based on at least one environment acquisition device;

the data processing module is used for determining each target environment parameter matched with different environment acquisition devices according to the environment parameters acquired by the environment parameter acquisition module; and

and the control module is used for controlling the self-moving equipment to operate based on each target environment parameter.

In a third aspect, the present invention provides a computer-readable storage medium, in which a program is stored, wherein the program executes the above data processing method.

In a fourth aspect, the present invention provides an electronic device comprising a memory having a computer program stored therein and a processor configured to execute the data processing method as described above by the computer program.

In a fifth aspect, the present invention provides an autonomous mobile device, including:

the environment acquisition device is used for acquiring external environment parameters;

a memory having a program stored therein; and

and the controller is in communication connection with the environment acquisition device and the memory, and the program is loaded and executed by the controller to realize the data processing method.

Compared with the prior art, the invention has the following beneficial effects: according to the data processing method, the target environment parameters matched with different environment acquisition devices are determined, and the self-moving equipment is controlled to operate based on the target environment parameters, so that on one hand, different target environment parameters can be matched for different environment acquisition devices by determining the target environment parameters matched with different environment acquisition devices, the screening flexibility is improved, the screening efficiency is improved, further, a large amount of invalid and distorted data can be screened and filtered, the data interaction amount is reduced, a control instruction can be issued more quickly, and the response and execution speed of the self-moving equipment is improved; on the other hand, the target environment parameters can reflect the surrounding environment more accurately, so that more accurate and reasonable control instructions can be issued through the target environment parameters, and the self-moving equipment can operate reliably.

Drawings

FIG. 1 is a flow chart of a data processing method according to an embodiment of the present invention.

Fig. 2 is a flowchart of step S2 according to an embodiment of the present invention.

FIG. 3 is a flowchart of step S20 in accordance with one embodiment of the present invention.

FIG. 4 is a flowchart of step S1 according to an embodiment of the present invention

FIG. 5 is a block diagram of a data processing apparatus according to an embodiment of the present invention.

FIG. 6 is a block diagram of an electronic device in accordance with an embodiment of the invention.

Fig. 7 is a schematic diagram of a self-moving device according to an embodiment of the invention.

Detailed Description

In order to make the aforementioned objects, features and advantages of the present invention comprehensible, embodiments accompanied with figures are described in detail below. It is to be understood that the specific embodiments described herein are merely illustrative of the invention and are not limiting of the invention. It should be further noted that, for the convenience of description, only some of the structures related to the present invention are shown in the drawings, not all of the structures. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.

The terms "comprising" and "having," as well as any variations thereof, in the present invention are intended to cover non-exclusive inclusions. For example, a process, method, system, article, or apparatus that comprises a list of steps or elements is not limited to only those steps or elements listed, but may alternatively include other steps or elements not listed, or inherent to such process, method, article, or apparatus.

Reference herein to "an embodiment" means that a particular feature, structure, or characteristic described in connection with the embodiment can be included in at least one embodiment of the invention. The appearances of the phrase in various places in the specification are not necessarily all referring to the same embodiment, nor are separate or alternative embodiments mutually exclusive of other embodiments. It is explicitly and implicitly understood by one skilled in the art that the embodiments described herein can be combined with other embodiments.

A data processing method according to a preferred embodiment of the present invention, as shown in fig. 1, includes the following steps:

s1, obtaining environmental parameters collected from a mobile device within a set time, wherein the environmental parameters are collected based on at least one environmental collection device;

s2, determining target environment parameters matched with different environment acquisition devices;

and S3, controlling the self-moving equipment to operate based on each target environment parameter.

In step S1, the external environment parameters are collected from the mobile device by the environment collection device mounted thereon, such as a laser radar, a millimeter wave radar, an inertial sensor (IMU), an angle sensor, a gyroscope, a nine-axis sensor, and a camera.

The control system of the self-moving equipment controls the operation of the self-moving equipment according to the environmental parameters collected by different environment collecting devices, and the posture of the self-moving equipment can be changed due to terrain and other reasons in the moving process, so that a large amount of invalid or distorted data exists in the collected environmental data, therefore, in order to screen out a large amount of invalid data and obtain more accurate effective data, the control system determines target environmental parameters matched with the different environment collecting devices and controls the operation of the self-moving equipment based on the target environmental parameters, so that the data processing speed is higher, the adopted data for controlling the operation of the self-moving equipment are more accurate, and the operation of the self-moving equipment can be better controlled.

Taking the environment acquisition device as the lidar as an example, because when the self-moving equipment is in an inclined posture, the lidar is also in an inclined state, and the distortion of the acquired data is larger at the moment, the data acquired when the lidar is in a horizontal state or a state close to the horizontal state is taken as the target environment parameter of the lidar, the position of the self-moving equipment can be more accurately determined based on the target environment parameter, and then the self-moving equipment is controlled to move.

Further, referring to fig. 2, the step S2 includes the steps of:

s20, determining a matching condition corresponding to each environment acquisition device;

and S21, determining each target environment parameter matched with each environment acquisition device according to each matching condition.

In steps S20 and S21, the control system determines the matching condition corresponding to the environment acquisition device according to the type of the environment acquisition device, and then determines the environment parameter corresponding to the matching condition as the target environment parameter, the matching condition is pre-stored in the control system, and the control system can directly call and determine the matching condition according to the obtained environment parameter.

Taking an environment acquisition device as a target detector such as a laser radar as an example, since the environment acquisition device needs to perform ranging or shooting to identify an external object or perform other functions, the matching condition is the acquisition attitude, and the external environment can be more accurately reflected by the acquired environment parameters when the acquisition attitude matching condition is met. For example, the lidar needs to meet the matching condition of its acquisition posture when it is horizontal or nearly horizontal (the included angle with the horizontal plane is within the allowable range), and for other target detectors, the required acquisition posture may be different, for example, the lidar needs to meet the matching condition of its acquisition posture when it is at a certain included angle with the horizontal plane or is perpendicular to the horizontal plane.

Therefore, referring to fig. 3, when the environment acquisition device includes the target detector, the step S20 includes the following steps:

s200, determining acquisition posture matching conditions corresponding to the target detector;

s201, taking the environmental parameters acquired by the target detector under the acquisition posture matching condition as the target environmental parameters corresponding to the target detector.

Specifically, the acquisition attitude matching condition corresponding to the target detector is determined according to the type of the target detector, the laser radar acquires the attitude matching condition for the target detector when the laser radar is horizontal or close to the horizontal, other types of target detectors also have the corresponding acquisition attitude matching condition, and then the environmental parameters acquired by the target detector under the acquisition attitude matching condition are used as the target environmental parameters corresponding to the target detector, so that a large amount of invalid or distorted data can be effectively screened out, and more accurate data can be quickly acquired to control the operation of the mobile equipment.

Of course, the matching condition is not limited to the acquisition gesture, and other conditions such as the operation speed may be applied to other types of environment acquisition devices, and as a preferred embodiment, at least two environment acquisition devices have different matching conditions.

As a preferred embodiment, the acquisition attitude of the object detector is determined using a position sensor, the attitude of which is detected by a position sensor, which may be, for example, an inertial sensor (IMU). Therefore, the following steps are also included before step S201: and determining the acquisition attitude of the target detector based on the position sensor.

The control system judges the acquisition gesture of the target detector when acquiring the environmental parameters according to the gesture data detected by the position sensor, and controls the mobile equipment to operate by taking the environmental parameters acquired under the acquisition gesture matching condition as the target environmental parameters.

As shown in fig. 4, as a preferred embodiment, the step s1 of obtaining the environmental parameters collected from the mobile device within the set time includes the following steps:

s10, obtaining a reflected electromagnetic wave signal which is received by the target detector and aims at a target;

s11, determining the position parameter of the target based on the reflected electromagnetic wave signal, and taking the position parameter as the environment parameter.

Specifically, taking the example where the target detector is a laser radar or a millimeter wave radar, which emits electromagnetic waves to the outside, and an external object can reflect the electromagnetic wave signals, and the target detector is received by the laser radar or the millimeter wave radar, a target that reflects electromagnetic wave signals having specific characteristics may be set in the working area of the mobile device, for example, a beacon made of a metal plate having a specific structure may be used as the target, and the target detector may recognize whether or not the received electromagnetic wave signals are electromagnetic wave signals reflected by the target, and the coordinate position of the target may be stored therein, so that the position parameter of the target may be determined from the reflected electromagnetic wave signals, the position parameter may be used as an environmental parameter, and the control system may calculate the position of the mobile device based on data such as the distance from the mobile device to the target and the position parameter of the target itself, therefore, the path is planned better, and the moving track is set.

According to the data processing method, the target environment parameters matched with different environment acquisition devices are determined, and the self-moving equipment is controlled to operate based on the target environment parameters, so that on one hand, a large amount of invalid and distorted data can be screened and filtered, the data interaction amount is reduced, a control instruction can be issued more quickly, and the response and execution speed of the self-moving equipment is further improved; on the other hand, the target environment parameters can reflect the surrounding environment more accurately, so that more accurate and reasonable control instructions can be issued through the target environment parameters, and the self-moving equipment can operate reliably.

Fig. 5 shows a block diagram of a data processing apparatus according to a preferred embodiment, which includes an environmental parameter obtaining module 7, a data processing module 70 communicatively connected to the environmental parameter obtaining module 7, and a control module 71 communicatively connected to the data processing module 70.

The environment parameter acquiring module 7 is configured to acquire an environment parameter acquired from the mobile device within a set time, where the environment parameter is acquired based on at least one environment acquiring device; the data processing module 70 is configured to determine, according to the environmental parameters acquired by the environmental parameter acquiring module 7, target environmental parameters matched with different environmental acquisition devices; the control module 71 is configured to control the mobile device to operate based on the target environmental parameters.

For further details, reference may be made to the above-described method embodiments. It should be noted that: the data processing apparatus provided in the above embodiment is only illustrated by the division of the above functional modules, and in practical applications, the above functions may be distributed by different functional modules according to needs, that is, the internal structure of the data processing apparatus is divided into different functional modules to complete all or part of the above described functions. The data processing means are preferably arranged inside the self-moving device.

The present invention also proposes a computer-readable storage medium in which a program is stored, which program, when running, executes the data processing method described above, for example, is loadable by a processor to execute the data processing method described above.

Fig. 6 is a block diagram of an electronic apparatus according to a preferred embodiment of the present invention, where the electronic apparatus may be a self-moving device, or may be another device that is mounted on the self-moving device and is independent from the self-moving device. The electronic device comprises at least a processor 4 and a memory 40.

The processor 4 may include one or more processing cores, such as: 4 core processors, 6 core processors, etc. The processor 4 may be implemented in at least one hardware form of a DSP (Digital Signal Processing), an FPGA (Field-Programmable Gate Array), and a PLA (Programmable Logic Array). The processor 4 may also include a main processor and a coprocessor, the main processor is a processor for processing data in an awake state, and is also called a Central Processing Unit (CPU); a coprocessor is a low power processor for processing data in a standby state. In some embodiments, the processor 4 may further include an AI (Artificial Intelligence) processor for processing computing operations related to machine learning.

Memory 40 may include one or more of a computer-readable storage medium, high speed random access memory, and non-volatile memory, such as a magnetic disk storage device, flash memory storage device, or the like. The memory 40 has stored therein a computer program by which the processor 4 is arranged to perform the data processing method described above.

In some embodiments, the electronic device may further include: a peripheral interface and at least one peripheral. The processor 4, memory 40 and peripheral interface may be connected by bus or signal lines. Each peripheral may be connected to the peripheral interface via a bus, signal line, or circuit board. Illustratively, peripheral devices include, but are not limited to: radio frequency circuit, touch display screen, audio circuit, power supply, etc.

Fig. 7 is a schematic structural diagram of a self-moving device according to an embodiment of the present invention, and as shown in fig. 7, the self-moving device at least includes: the environment acquisition device 3 and controller 5, controller 5 and environment acquisition device 3 communication link to each other.

The environment acquisition device 3 is used for acquiring external environment parameters and sending the environment parameters to the controller 5. Alternatively, the environment acquisition device 3 may be a target detector such as a laser radar.

The controller 5 is used to control the self-moving device, such as: the control is from the start, move, stop of mobile device, control is from the start, stop of each part (for example environment collection device) in the mobile device etc..

In this embodiment, the controller 5 is communicatively connected to the memory; stored in the memory is a program that is loaded and executed by the controller 5 to implement the data processing method described above.

Obviously, the self-moving device may further include other components, such as a moving device 6, the moving device 6 is used for moving the self-moving device, and it may include a motor and a wheel driven by the motor to rotate, so as to drive the self-moving device to move. The moving device 6 is in communication connection with the controller 5, and can operate under the control of the controller 5 and drive the whole moving of the self-moving equipment.

The above is only one embodiment of the present invention, and any other modifications based on the concept of the present invention are considered as the protection scope of the present invention.

Claims

1. A data processing method, comprising the steps of:

2. The data processing method of claim 1, wherein said determining target environmental parameters that match different ones of said environmental capture devices comprises:

3. The data processing method of claim 2, wherein at least two of the environment acquisition devices have different matching conditions.

4. The data processing method of claim 2, wherein the environment acquisition devices comprise target detectors, and the determining the matching condition for each of the environment acquisition devices comprises:

5. The data processing method according to claim 4, wherein before taking the environmental parameter acquired by the target detector under the acquisition posture matching condition as the target environmental parameter corresponding to the target detector, the method further comprises:

6. The data processing method of any one of claims 3 to 5, wherein the obtaining the environmental parameters collected from the mobile device within the set time comprises:

7. A data processing apparatus, comprising:

8. A computer-readable storage medium, in which a program is stored, wherein the program executes the data processing method according to any one of claims 1 to 6.

9. An electronic device comprising a memory and a processor, characterized in that the memory has stored therein a computer program, the processor being arranged to execute the data processing method of any of claims 1 to 6 by means of the computer program.

10. An autonomous mobile device, comprising:

a memory having a program stored therein; and

a controller communicatively connected to the environment acquisition device and the memory, the program being loaded and executed by the controller to implement the data processing method of any one of claims 1 to 6.