CN113633219A - Recharge path determination method, device, equipment and computer readable storage medium - Google Patents

Recharge path determination method, device, equipment and computer readable storage medium Download PDF

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Publication number
CN113633219A
CN113633219A CN202110836190.0A CN202110836190A CN113633219A CN 113633219 A CN113633219 A CN 113633219A CN 202110836190 A CN202110836190 A CN 202110836190A CN 113633219 A CN113633219 A CN 113633219A
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node
determining
intelligent mobile
active
candidate
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CN202110836190.0A
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CN113633219B (en
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周孙春
邵林
王聪
任纪颖
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Midea Robozone Technology Co Ltd
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Midea Robozone Technology Co Ltd
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Priority to PCT/CN2022/079257 priority patent/WO2023000680A1/en
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    • A—HUMAN NECESSITIES
    • A47—FURNITURE; DOMESTIC ARTICLES OR APPLIANCES; COFFEE MILLS; SPICE MILLS; SUCTION CLEANERS IN GENERAL
    • A47L—DOMESTIC WASHING OR CLEANING; SUCTION CLEANERS IN GENERAL
    • A47L11/00—Machines for cleaning floors, carpets, furniture, walls, or wall coverings
    • A—HUMAN NECESSITIES
    • A47—FURNITURE; DOMESTIC ARTICLES OR APPLIANCES; COFFEE MILLS; SPICE MILLS; SUCTION CLEANERS IN GENERAL
    • A47L—DOMESTIC WASHING OR CLEANING; SUCTION CLEANERS IN GENERAL
    • A47L11/00—Machines for cleaning floors, carpets, furniture, walls, or wall coverings
    • A47L11/40—Parts or details of machines not provided for in groups A47L11/02 - A47L11/38, or not restricted to one of these groups, e.g. handles, arrangements of switches, skirts, buffers, levers
    • A47L11/4011—Regulation of the cleaning machine by electric means; Control systems and remote control systems therefor
    • A—HUMAN NECESSITIES
    • A47—FURNITURE; DOMESTIC ARTICLES OR APPLIANCES; COFFEE MILLS; SPICE MILLS; SUCTION CLEANERS IN GENERAL
    • A47L—DOMESTIC WASHING OR CLEANING; SUCTION CLEANERS IN GENERAL
    • A47L11/00—Machines for cleaning floors, carpets, furniture, walls, or wall coverings
    • A47L11/40—Parts or details of machines not provided for in groups A47L11/02 - A47L11/38, or not restricted to one of these groups, e.g. handles, arrangements of switches, skirts, buffers, levers
    • A47L11/4061—Steering means; Means for avoiding obstacles; Details related to the place where the driver is accommodated

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  • Control Of Position, Course, Altitude, Or Attitude Of Moving Bodies (AREA)

Abstract

The embodiment of the application discloses a recharge path determining method, a device, equipment and a computer readable storage medium, wherein the method comprises the following steps: determining that the intelligent mobile equipment needs to be supplemented with electric quantity and cannot determine a recharging path, acquiring a current node where the intelligent mobile equipment is located, and determining the current node as an active node; determining at least one node which is less than a distance threshold value and can be reached by the intelligent mobile equipment as a candidate node; determining that a target node can be determined from the candidate nodes based on the attribute information of the candidate nodes, and controlling the intelligent mobile device to move from the active node to the target node; and determining that the intelligent mobile equipment can receive charging seat information, and controlling the intelligent mobile equipment to move from the target node to the position of the charging seat based on the charging seat information.

Description

Recharge path determination method, device, equipment and computer readable storage medium
Technical Field
The present application relates to the field of mobile device technologies, and relates to, but is not limited to, a method, an apparatus, a device, and a computer-readable storage medium for determining a recharge path.
Background
Along with the improvement of living standard, the popularity of intelligent mobile equipment in life is higher and higher, and for the example of a floor sweeping robot, the floor sweeping robot becomes a necessary device in a family. When the sweeping robot is used, when the power of the sweeping robot is exhausted and the sweeping robot needs to be recharged, the robot can automatically navigate to a position away from the charging seat last time.
In practice, there is a situation that the position of the charging seat changes, so under this situation, the sweeping robot needs to search for the charging seat to ensure that the electric quantity of the robot can work normally. In the related art, the sweeping robot can reach the charging seat position for charging in the following two ways, namely, the sweeping robot interrupts the recharging process, waits for external intervention, and returns to the charging seat position through the external intervention; and in the second mode, the environment is actively explored through random navigation in the environment or the whole environment is completely covered, so that the infrared signal of the charging seat can be received or the position of the charging seat can be identified in the active exploration process.
In the related art, in the first mode, the possibility that the electric quantity is completely exhausted and the position of the charging seat is not reached exists, so that the service life of the sweeping robot can be shortened; the random navigation in the second mode has the problem that the charging seat cannot be found, and the whole environment is covered completely, each node in the environment needs to be explored, so that the whole exploration process is complex and redundant.
Disclosure of Invention
In view of this, embodiments of the present application provide a backfill path determining method, apparatus, device, and computer-readable storage medium.
The technical scheme of the embodiment of the application is realized as follows:
the embodiment of the application provides a recharge path determining method, which comprises the following steps:
determining that the intelligent mobile equipment needs to be supplemented with electric quantity and cannot determine a recharging path, acquiring a current node where the intelligent mobile equipment is located, and determining the current node as an active node;
determining at least one node which is less than a distance threshold value and can be reached by the intelligent mobile equipment as a candidate node;
determining that a target node can be determined from the candidate nodes based on the attribute information of the candidate nodes, and controlling the intelligent mobile device to move from the active node to the target node;
and determining that the intelligent mobile equipment can receive charging seat information, and controlling the intelligent mobile equipment to move from the target node to the position of the charging seat based on the charging seat information.
The embodiment of the application provides a recharge path determination device, the device includes:
the system comprises an acquisition module, a processing module and a processing module, wherein the acquisition module is used for determining that the intelligent mobile equipment needs to be supplemented with electric quantity and cannot determine a recharging path, acquiring a current node where the intelligent mobile equipment is located, and determining the current node as an active node;
a determining module, configured to determine at least one node, which is less than a distance threshold and is reachable by the smart mobile device, as a candidate node;
the first control module is used for determining that a target node can be determined from the candidate nodes based on the attribute information of the candidate nodes, and controlling the intelligent mobile equipment to move from the active node to the target node;
and the second control module is used for determining that the intelligent mobile equipment can receive charging seat information and controlling the intelligent mobile equipment to move from the target node to the position of the charging seat based on the charging seat information.
The embodiment of the application provides an intelligent mobile device, intelligent mobile device includes at least:
a processor; and
a memory for storing a computer program operable on the processor;
wherein the computer program when executed by a processor implements the recharge path determination method described above.
An embodiment of the present application provides a computer-readable storage medium, in which computer-executable instructions are stored, and the computer-executable instructions are configured to execute the above recharge path determining method.
The embodiment of the application provides a method, a device, equipment and a computer readable storage medium for determining a recharge path, wherein when it is determined that a mobile device needs to be supplemented with electric quantity and cannot determine the recharge path, a current node of a position where an intelligent device is located is obtained, and the current node is determined as an active node; then, determining that the distance between the intelligent mobile equipment and the active node is smaller than a distance threshold value node set, and determining candidate nodes which can be reached by the intelligent mobile equipment from the node set; then, according to the attribute information of the candidate nodes, a target node is determined from the candidate nodes, and the intelligent mobile device is controlled to move from the active node to the target node instead of being controlled to move to each node in the environment, so that the search complexity and the redundancy are reduced; and finally, after the intelligent mobile device moves to the target node, judging whether the intelligent mobile device can receive the infrared or laser signal sent by the charging seat, and controlling the intelligent mobile device to move from the position of the target node to the position of the charging seat based on the infrared or laser signal when receiving the infrared or laser signal sent by the charging seat, so as to charge. In the whole process, external intervention is not needed, and full-process automatic exploration can be realized; and the optimization of the recharging path is realized through the target node without fully covering each node in the exploration environment, so that the exploration process is simpler, more convenient and more efficient, and the intelligent degree of the intelligent mobile device is further improved.
Drawings
In the drawings, which are not necessarily drawn to scale, like reference numerals may describe similar components in different views. The drawings illustrate generally, by way of example, but not by way of limitation, various embodiments discussed herein.
Fig. 1 is a schematic flow chart of an implementation of a recharge path determining method according to an embodiment of the present application;
fig. 2 is a schematic flow chart of another implementation of the recharge path determining method according to the embodiment of the present application;
fig. 3 is a schematic flowchart of another implementation of the recharge path determining method according to the embodiment of the present application;
fig. 4 is a schematic diagram illustrating a presentation manner of a candidate node set according to an embodiment of the present disclosure;
FIG. 5 is a schematic structural diagram of a completed exploration tree according to an embodiment of the present disclosure;
fig. 6 is a schematic structural diagram of an intelligent mobile device apparatus provided in an embodiment of the present application;
fig. 7 is a schematic structural diagram of an intelligent mobile device according to an embodiment of the present application.
Detailed Description
In order to make the objectives, technical solutions and advantages of the present application clearer, the present application will be described in further detail with reference to the attached drawings, the described embodiments should not be considered as limiting the present application, and all other embodiments obtained by a person of ordinary skill in the art without creative efforts shall fall within the protection scope of the present application.
In the following description, reference is made to "some embodiments" which describe a subset of all possible embodiments, but it is understood that "some embodiments" may be the same subset or different subsets of all possible embodiments, and may be combined with each other without conflict.
In the following description, references to the terms "first \ second \ third" are only to distinguish similar objects and do not denote a particular order, but rather the terms "first \ second \ third" are used to interchange specific orders or sequences, where appropriate, so as to enable the embodiments of the application described herein to be practiced in other than the order shown or described herein.
Unless defined otherwise, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this application belongs. The terminology used herein is for the purpose of describing embodiments of the present application only and is not intended to be limiting of the application.
Based on the problems in the related art, the present application provides a method for determining a recharge path, where the method provided by this embodiment may be implemented by a computer program, and when the computer program is executed, each step in the method for determining a recharge path provided by this embodiment is completed. In some embodiments, the computer program may control a processor in the smart mobile device to execute. Fig. 1 is a schematic flow chart of an implementation of a recharge path determining method according to an embodiment of the present application, and as shown in fig. 1, the method includes:
step S101, determining that the intelligent mobile equipment needs to be supplemented with electric quantity and cannot determine a recharging path, acquiring a current node where the intelligent mobile equipment is located, and determining the current node as an active node.
Here, the smart mobile device may be an intelligent sweeper, an intelligent mopping machine, an intelligent food delivery machine, an intelligent navigation robot, an unmanned aerial vehicle, or the like. Under the condition that the intelligent mobile device detects that the electric quantity of the intelligent mobile device is lower than an electric quantity threshold value, the intelligent mobile device is considered to need to supplement the electric quantity, wherein the electric quantity threshold value can be 5% of full electric quantity, 3% of full electric quantity and the like, and the electric quantity threshold value can be a default value or a value set by a user.
In the embodiment of the application, the fact that the recharging path cannot be determined means that the recharging path is not stored in the intelligent mobile robot when the intelligent mobile robot cannot receive infrared or laser signals sent by the charging seat and cannot acquire images of the charging seat through an image acquisition device of the intelligent mobile robot; the fact that the recharging path cannot be determined can also mean that the intelligent mobile device moves to a position away from the charging seat for the last time according to the recharging path stored by the intelligent mobile device, but cannot receive infrared or laser signals sent by the charging seat, and cannot acquire images of the charging seat through the image acquisition device of the intelligent mobile device, so that the intelligent mobile device cannot determine the recharging path under the two conditions.
Then, the intelligent mobile device acquires a current node at the current position, and sets the current node as an active node so as to continuously determine the recharge path based on the active node.
And step S102, determining at least one node which is less than the distance threshold value from the active node and can be reached by the intelligent mobile equipment as a candidate node.
Here, the distance threshold may be 1.5 meters, 1.8 meters, 2 meters, or the like, and the distance threshold may be a default value or a value set by a user.
In the embodiment of the present application, a region less than a distance threshold from the active node may be determined as a target region, and the target region may be circular in shape; then, collecting environmental information in the target area, wherein the environmental information at least comprises position information of obstacles in the target area, the position of the obstacle is a position which cannot be reached by the intelligent mobile equipment, and the obstacle can be a sofa leg, a basin, a wall surface and the like; then, determining a target area except the position of the obstacle as a reachable area; finally, the nodes in the reachable area are determined as candidate nodes, that is, the candidate nodes are nodes that the intelligent mobile device can predict to reach.
And S103, determining that a target node can be determined from the candidate nodes based on the attribute information of the candidate nodes, and controlling the intelligent mobile equipment to move from the active node to the target node.
Here, the attribute information of the candidate node may be at least one of a first distance between the candidate node and the active point, a second distance between the candidate node and the obstacle, and an information entropy of the candidate node.
In the embodiment of the application, a preset cost function can be established based on a first distance parameter between a node and an active node, a second distance parameter between the node and an obstacle, and a node information entropy parameter, and a score of any node can be determined through the preset cost function, wherein a value of the preset cost function is in direct proportion to the first distance parameter, the second distance parameter, and the information entropy parameter. Then, inputting the first distance, the second distance and the information entropy into a preset cost function, and obtaining the score of the candidate node; and finally, under the condition that the highest score reaches a score threshold value, determining the candidate node corresponding to the highest score as a target node, and controlling the intelligent mobile equipment to move from the active node to the target node.
Here, by setting the value of the preset cost function to be in direct proportion to both the first distance parameter and the second distance parameter, the characteristics that the intelligent mobile device can detect obstacles and charging seats in the target area can be fully utilized, and candidate nodes with longer distances are selected as target nodes as far as possible, so that the problems of complex and redundant path search in the recharging path determination process can be avoided; in addition, the value of the preset cost function is in direct proportion to the information entropy parameter, namely, the larger the information entropy is, the larger the score value is, and the larger the information entropy is, the larger the uncertainty is, the larger the score value is, so that the intelligent robot can be guided to explore towards an unknown area, and a charging seat can be found as soon as possible.
In some embodiments, if the target node cannot be determined based on the attribute information of the candidate node, the intelligent mobile device is controlled to return to the parent node based on the current exploration tree, the parent node is updated to be the active node, and the target node of the updated active node is continuously determined until the charging seat information is received or the target node returns to the root node of the exploration tree.
And step S104, determining that the intelligent mobile equipment can receive the charging seat information, and controlling the intelligent mobile equipment to move from the target node to the position of the charging seat based on the charging seat information.
Here, the charging seat information may be an infrared or laser signal emitted by the charging seat, and of course, the charging seat information may also be a radar signal. Then, under the condition that the intelligent mobile device receives the charging seat information, the intelligent mobile device can determine the position of the charging seat based on the charging seat information, and then the intelligent mobile device moves to the position of the charging seat from the position of the target node. And if the intelligent mobile equipment does not receive the charging seat information, the target node is updated to be an active node, and the next target node is continuously determined based on the active node until the charging seat information is received or the root node of the exploration tree is returned.
In some embodiments, when the smart mobile device acquires the image of the charging dock through its own image acquisition device, the location relationship between the charging dock and the smart mobile device may be determined based on the acquired image including the image of the charging dock, and the smart mobile device is controlled to move from the location of the target node to the location of the charging dock based on the location relationship.
The embodiment of the application provides a recharging path determining method, which includes the steps that under the condition that it is determined that mobile equipment needs to be supplemented with electric quantity and a recharging path cannot be determined, a current node of the position where intelligent equipment is located is obtained, and the current node is determined to be an active node; then, determining that the distance between the intelligent mobile equipment and the active node is smaller than a distance threshold value node set, and determining candidate nodes which can be reached by the intelligent mobile equipment from the node set; then, according to the attribute information of the candidate nodes, determining target nodes from the candidate nodes, and controlling the intelligent mobile equipment to move from the active nodes to the target nodes instead of controlling the intelligent mobile equipment to move to each node in the environment, so that the complexity and the redundancy of the backfill path search are reduced; and finally, after the intelligent mobile device moves to the target node, judging whether the intelligent mobile device can receive the infrared or laser signal sent by the charging seat, and controlling the intelligent mobile device to move from the position of the target node to the position of the charging seat based on the infrared or laser signal when receiving the infrared or laser signal sent by the charging seat, so as to charge. In the whole process, external intervention is not needed, and full-process automatic exploration can be realized; and the optimization of the recharging path is realized through the target node without fully covering each node in the exploration environment, so that the exploration process is simpler, more convenient and more efficient, and the intelligent degree of the intelligent mobile device is further improved.
Based on the foregoing embodiments, an embodiment of the present application further provides a recharge path determining method, as shown in fig. 2, the method includes:
step S201, determining that the intelligent mobile device needs to perform power supply and cannot determine a recharging path, acquiring a current node where the intelligent mobile device is located, and determining the current node as an active node.
Here, the implementation process of step S201 is similar to the implementation process of step S101, and therefore, the implementation process of step S201 may refer to the implementation process of step S101.
Step S202, determining a target area with the distance from the active node smaller than a distance threshold.
Here, the distance threshold may be 1.5 meters, 1.8 meters, 2 meters, and the like, and in practice, the distance threshold may be associated with a search range of the smart mobile device, each smart mobile device has a corresponding search range, and the smart mobile device can obtain the environmental information in the search range through its own image acquisition, signal transceiving, and the like. Because the intelligent mobile devices of different models have different performances, the intelligent mobile devices of different models generally correspond to different distance thresholds, and the distance thresholds can be factory default values or values set by users in use.
In the embodiment of the application, an area which is less than a distance threshold value from an active node is determined by taking the active node as a center position, and the area is determined as a target area. That is, a circular area is determined by taking the active node as the center of a circle and the distance threshold as the radius, and then the circular area is determined as the target area.
Step S203, determining a reachable area outside the obstacle in the target area based on the collected environment information.
The environment information refers to the relevant information of the environment where the intelligent mobile device obtains through the devices of image acquisition, signal transceiving and the like of the intelligent mobile device, the environment information at least comprises the position information of the obstacle in the target area, the position of the obstacle refers to the position where the intelligent mobile device cannot reach, and the obstacle can be a sofa leg, a basin, a wall surface and the like; then, a target area other than the obstacle position is determined as the reachable area.
And step S204, determining the nodes in the reachable area as candidate nodes.
Here, the position information of each candidate node is acquired, the position information in the reachable region is determined as the position information of the candidate node, and then the corresponding candidate node is determined based on the position information of the candidate node.
Step S205, a preset cost function is established based on a first distance parameter between the node and the active node, a second distance parameter between the node and the obstacle and the node information entropy parameter.
Here, in order to fully utilize the characteristics that the intelligent mobile device can detect an obstacle and a charging seat in a target area, select a candidate node with a longer distance as a target node as far as possible, and guide the intelligent robot to search towards an unknown area, a preset cost function can be set as a function in direct proportion to a first distance parameter, a second distance parameter and an information entropy, so that the problems of complex and redundant path search in the recharging path determination process are avoided.
Illustratively, the preset cost function may be a sum of the first distance parameter, the second distance parameter and the node information entropy parameter; in addition, a first product of the first weight and the first distance parameter, a second product of the second weight and the second distance parameter, and a third product of the third weight and the node information entropy parameter may be obtained, and then the preset cost function may be set as the sum of the first product, the second product, and the third product.
Step S206, inputting the first distance, the second distance and the information entropy into a preset cost function to obtain the score of the candidate node.
Here, the first distance refers to a distance between the candidate node and the active node, the second distance refers to a distance between the candidate node and the obstacle, and the information entropy of the candidate node refers to uncertainty of the environment around the candidate node. And the score of the candidate node is the value of the preset cost function, the first distance, the second distance and the information entropy are input into the established preset cost function, and the value of the preset cost function is determined as the score of the candidate node.
In step S207, the highest score is determined from the scores.
Here, the highest score may be determined from the scores of the candidate nodes by a pairwise comparison method.
In step S208, it is determined whether the highest score reaches a score threshold.
Here, the score threshold may be 10, 12, 14, etc., and if it is determined that the highest score is equal to or greater than the score threshold, it is considered that the highest score reaches the score threshold, and the process proceeds to step S209; if the highest score is smaller than the score threshold, the highest score is considered not to reach the score threshold, and the process proceeds to step S213.
In step S209, the candidate node corresponding to the highest score is determined as the target node.
Here, in the case where the highest score is equal to or greater than the score threshold value, a candidate node corresponding to the highest score is determined, and the determined candidate node is determined as the target node.
And step S210, controlling the intelligent mobile equipment to move from the active node to the target node.
Here, the location information of the target node is obtained first, and the intelligent mobile device is moved from the active node to the target node according to the location information of the target node.
And step S211, determining the target node as a child node of the active node.
Here, when the target node is located at the target node, the active node is used as a parent node, the target node is used as a child node, and a parent-child relationship between the active node and the target node is established.
Step S212, updating the current exploration tree based on the active node and the target node.
Here, the current exploration tree is composed of a history active node, an active node, and a target node. And finally, the target node is used as the child node of the active node and added into the current exploration tree to update the current exploration tree.
In step S213, a parent node of the active node is determined based on the current exploration tree.
Here, the highest score is smaller than the score threshold, that is, the target node cannot be determined according to the attribute information of the candidate node, and the representation indicates that there is no target node yet before, for example, the front of the intelligent mobile device may be a wall surface, and then the intelligent mobile device needs to explore other directions again, and then determines the parent node of the active node according to the current exploration tree, that is, returns to the previous node.
And step S214, controlling the intelligent mobile device to move from the active node to the parent node.
Here, the smart mobile device is moved from the active node location to the parent node location based on the parent node's location information.
Step S215, the parent node is updated to the active node.
Here, after the smart mobile device is in the parent node, the parent node is updated to be the active node.
And step S216, determining at least one node which is less than the distance threshold value and can be reached by the intelligent mobile device as a candidate node.
Here, the implementation process of step S216 is similar to the implementation process of step S102, and therefore, the implementation process of step S216 may refer to the implementation process of step S102.
Step S217, determining that a target node can be determined from the candidate nodes based on the attribute information of the candidate nodes, and controlling the intelligent mobile device to move from the active node to the target node.
Here, the implementation process of step S217 is similar to the implementation process of step S103, and therefore, the implementation process of step S217 may refer to the implementation process of step S103.
In step S218, it is determined whether the smart mobile device can receive the charging-stand information.
Here, the charging-stand information may be an infrared signal, a laser signal or a radar signal sent by the charging stand, and if the smart mobile device can receive the charging-stand information, indicating that the smart mobile device has obtained the position information of the charging stand, the process goes to step S219; if the smart mobile device still cannot receive the charging-stand information, indicating that the smart mobile device still cannot obtain the location information of the charging-stand, the process goes to step S220.
And step S219, controlling the intelligent mobile equipment to move from the target node to the position of the charging seat based on the charging seat information.
Here, the smart mobile device can receive the charging-stand information, and then the smart mobile device can determine the location of the charging-stand according to the charging-stand information, and control the smart mobile device to move from the target node location to the location of the charging-stand through the control instruction.
Step S220, the target node is updated to be the active node.
Here, the smart mobile device still cannot receive the charging-stand information, and it is characterized that the smart mobile device cannot obtain the location information of the charging stand, and it is further required to continue searching for the charging stand, and then, the target node is updated to be an active node, and the target node is continuously determined on the basis of the updated active node.
And step S221, updating at least one node which is less than the distance threshold value from the active node and can be reached by the intelligent mobile equipment as a candidate node.
Here, the implementation process of step S221 is similar to that of step S102, and therefore, the implementation process of step S221 may refer to that of step S102.
Step S222, determining that a target node can be determined from the candidate nodes based on the attribute information of the candidate nodes, and controlling the intelligent mobile device to move from the active node to the target node.
Here, the implementation process of step S222 is similar to the implementation process of step S103, and therefore, the implementation process of step S222 may refer to the implementation process of step S103.
In the embodiment of the present application, through the steps S201 to S222, when it is determined that the mobile device needs to perform power supply and cannot determine the recharging path, a current node of a location where the intelligent device is located is obtained, and the current node is determined as an active node; then, determining an area with a distance from the active node to the active node smaller than a distance threshold value as a target area, determining a reachable area outside the obstacle in the target area based on the environment information, and determining a node in the reachable area as a candidate node; then, establishing a preset cost function, inputting a first distance between a candidate node and an active node, a second distance between the candidate node and an obstacle and information entropy of the candidate node into the preset cost function to obtain scores of all the candidate nodes, determining the candidate node corresponding to the highest score as a target node under the condition that the highest score reaches a score threshold value, and controlling the intelligent mobile equipment to move from the active node to the target node instead of controlling the intelligent mobile equipment to move to each node in the environment, so that the complexity and the redundancy of recharging path searching are reduced; meanwhile, the target node is used as a child node of the active node, and the current exploration tree is updated; and if the target node cannot be determined based on the attribute information of the candidate node, determining a father node of the active node based on the exploration tree, controlling the intelligent mobile device to move to the father node, updating the father node into the active node, and further continuously determining the target node corresponding to the updated active node, so that the search path can be adjusted in time, and the search efficiency is improved. If the intelligent mobile device receives the infrared and laser signals or radar signals sent by the charging seat in the searching process, the intelligent mobile device is controlled to move to the position of the charging seat based on the received signals, and if the infrared and laser signals or radar signals sent by the charging seat are not received at the position of the target node, the target node is updated to be an active node, and the next target node is continuously determined until the charging seat information is received or the target node returns to the root node of the exploration tree, so that the whole environment can be searched through fewer target nodes, and the searching complexity is reduced.
Based on the foregoing embodiments, an embodiment of the present application further provides a recharge path determining method, where the method is applied to a situation where an intelligent mobile device has a pause before reaching a target node, as shown in fig. 3, and the method includes:
step S301, obtaining the pause time of the intelligent mobile device staying at the current pause position.
When the intelligent mobile device arrives at the current pause position, the timing device is triggered to start timing, when the intelligent mobile device leaves the position, the timing is stopped, new timing is started, and therefore the timing duration is determined as the pause time of the intelligent mobile device at the current pause position.
Step S302, judge whether the pause time is greater than the time threshold.
Here, the time threshold may be 15 seconds, 20 seconds, 25 seconds, and the like, and if the pause time is greater than the time threshold, it represents that the smart mobile device is stuck by an obstacle at the current pause position and cannot move to the target node, then step S303 is performed; if the pause time is less than or equal to the time threshold, returning to the step S301, continuing to control the intelligent mobile device to move to the target node, and continuing to count time.
Step S303, determining a third distance between the suspended node and the target node based on the position information of the current suspended position and the position information of the target node.
For example, the position information may be expressed by coordinates in a rectangular coordinate system, and then the third distance may be obtained by a distance formula between two points.
In step S304, it is determined whether the third distance is smaller than the preset distance.
Here, the preset distance may be 0.1 meter, 0.2 meter, etc., and if the third distance is smaller than the preset distance, the representation pause position is closer to the position of the target node, and step S305 is performed; if the third distance is greater than or equal to the preset distance, the characteristic pause position is farther from the position of the target node, and the step S306 is entered.
Step S305, determining the pause position as the active node.
At this time, the pause position is closer to the position of the target node, and in this case, the pause position may be directly determined as the active node.
Step S306, determining each distance between the position information and the pause position of each node of the current exploration tree.
At this time, the pause position is far from the position of the target node, and the smart mobile device cannot move to the target node, here, each distance from each node in the current exploration tree to the pause position can also be determined through a distance formula.
Step S307, determine the nearest node corresponding to the minimum distance value in each distance.
Here, the minimum distance may be determined by a pairwise comparison method, and the node corresponding to the minimum distance may be determined as the closest node. In some embodiments, the smart mobile device may also be moved to the nearest node.
And step S308, determining the nearest node as the active node.
Here, in the case where the smart mobile device reaches the nearest node, the nearest node is determined as an active node.
And step S309, continuing to determine a target node of the active node, and controlling the intelligent mobile equipment to move from the active node to the target node.
Here, a target node of the active node may be determined and the smart mobile device may be moved from the active node to the target node by a method similar to steps S102 and S103.
In this embodiment of the application, through the steps S301 to S309, if the smart mobile device obtains the pause time of staying at the current pause position when the card shell is at the current pause position in the process of moving to the target node, when the pause time is greater than the time threshold, the third distance between the current pause position and the target node is continuously determined, and if the third distance is less than the preset distance, the pause position is determined as the active node; if the third distance is larger than or equal to the preset distance, determining the nearest node closest to the pause position in the exploration tree, determining the nearest node as the active node, and further continuously determining the target node of the active node, so that a new active node can be determined in time under the condition that sudden shell blocking occurs in the motion process, further continuously searching the recharging path, avoiding the problem of shell blocking all the time, and improving self-adaptability and robustness.
Based on the foregoing embodiment, the embodiment of the present application further provides a recharge path determining method, which is applied to a sweeping robot. Firstly, abstracting the current position of the sweeping robot into nodes of a tree, adding the nodes into an exploration tree, selecting a candidate node set in a fixed range of the current node, voting candidate points in the candidate node set, selecting an optimal candidate point, or calling the optimal candidate node as a target node, starting navigating to the optimal candidate point, repeating the steps until the sweeping robot finds a charging seat or the topological tree is not expandable, and finishing the process of searching and recharging by the robot. The method can ensure the completeness of exploration, can also avoid the redundancy problem in the exploration process, and can greatly improve the exploration efficiency.
The method for determining the recharge path provided by the embodiment of the application can be realized through the following steps 1 to 13:
step 1, abstracting the current position of the sweeping robot into a root node of an exploration tree, and recording the root node as NrootAdding an exploration tree, wherein the exploration tree is marked as T, marking the current node as an active node, and marking the active node as Nactive。
Step 2, from the active node NactiveAnd traversing the exploration tree T according to the sequence of 'child-parent' to obtain a node list in the specific sequence tree, wherein the node list is marked as L.
Step 3, traversing the list L, and if the node being traversed is not expandable, and the node being traversed is marked as N, skipping the node; otherwise, jumping to the step 4; if the list L has been traversed, the process jumps to step 13.
Step 4, marking the node N which is traversing as an active node NactiveSelecting a candidate node set according to a surrounding map, the surrounding map being denoted as M and the candidate node set being denoted as S, for example, an active node NactiveFor the center, a square map with a side length of 2 meters is formed, and assuming that the distance between adjacent nodes is 0.5 meters, a candidate node set S shown in fig. 4 is formed. The candidate node set S may be selected by referring to the following formula (1).
S＝{N|IsWalkable(N,M)anddist(N,Nactive)≤threshold} (1)；
In equation (1), threshold represents a distance threshold, characterizing a candidateNode in node set S and active node NactiveDoes not exceed a distance threshold; IsWalkable (N, M) represents the screening out of reachable nodes in the surrounding map M.
Step 5, if the candidate node set S is empty, that is, the candidate node set S satisfying the formula (1) cannot be determined, marking NactiveJumping to the step 3 if the node is a non-expandable node; and if the candidate node set S is not empty, jumping to the step 6.
Step 6, scoring each node N in the sub-node candidate set S by using a cost function, and selecting the candidate point N with the highest scorebestAnd if no candidate point meeting the requirement exists, jumping to the step 3.
Here, the candidate node N having the highest score may be selected according to the following formula (2)bestThe cost function is shown in formula (3), that is, the score of each node in the candidate node set can be obtained through formula (3).
Nbest＝maxG(N)andG(N)≥th,N∈S (2)；
G(N)＝α×path(N)+β×obstacle(N)+ω×entropy(N)+ε×density(N) (3)；
Formula (2) represents NbestIt is necessary to satisfy 2 conditions simultaneously, i.e. the node with the highest score and the score is greater than or equal to the score threshold th. In formula (3), α, β, ω, and ε represent weights of corresponding cost functions, and path (N) represents N and NactiveThe path length between nodes, obstacle (N) represents the distance between the node N and the obstacle, entrypy (N) represents the information entropy of the map around the node N, and density (N) represents whether other tree nodes exist around the node, and if so, the cost function score is reduced.
And 7, starting to call a path planning and motion control module to control the sweeping robot to face NbestIn the direction of motion.
Step 8, if the navigation is successful, namely, the sweeping robot moves to N successfullybestEntering step 9 if the position is the same; if the navigation fails, namely, the sweeping robot does not move to NbestThe position of the device is determined,step 10 is entered.
Step 9, the best candidate point N is selectedbestAdding to exploration trees T, NbestIs Nactive(ii) a Next, the best candidate point N is also markedbestIs an active node Nactive(ii) a Finally, the floor sweeping robot judges that N isbestWhether the infrared or laser signal sent by the charging seat can be received or not is judged, and if the sweeping robot can receive the signal, the sweeping robot is controlled to move to the charging seat for charging; and if the sweeping robot cannot receive the signal, returning to the step 2, continuously traversing the list and determining the best candidate node.
Step 10, judging P and N according to the current sweeping robot position, wherein the current sweeping robot position is marked as PbestIf the distance is smaller than the preset threshold, the preset threshold can be recorded as the preset distance, and then the step 11 is performed; if the distance is greater than or equal to the predetermined threshold, step 12 is entered.
Step 11, based on the current machine position P, create node N of the treefailAnd will node NfailAdded to an exploration tree T, NfailIs NactiveMarking node NfailIs an active node and returns to step 2.
Step 12, searching the node N closest to the P in the exploration treenearestAnd marks node NnearestIs an active node, and then returns to step 2.
Step 13, the search backfill process is exited, and at this time, an exploration tree has been constructed in the environment, as shown in fig. 5.
Abstracting the current position to be the root node of the exploration tree, marking the current node as an active node, selecting a candidate node set according to a surrounding map, grading the nodes in the candidate node set based on a cost function, and determining the node which has the highest grade and is not less than a grade threshold value as NbestAnd controlling the floor sweeping robot to move to NbestIf the sweeping robot can be at NbestWhen receiving the signal, the scanning is controlledThe ground robot moves to a charging seat for charging; if the sweeping robot can not be at NbestWhen receiving the signal, N isbestUpdating to be an active node, and continuously determining the next NbestUntil either a signal is received or the exploration tree list has been fully traversed. Furthermore, if the sweeping robot can not reach NbestThen, an active node is created at the current position or an adjacent node is determined as an active node, and N continues to be determinedbestUntil either a signal is received or the exploration tree list has been fully traversed. The method provided by the embodiment of the application determines N according to the cost functionbestAnd move to NbestAnd each node in the full-coverage environment is not replaced, so that the time for searching and recharging of the sweeping robot is shortened, the repeated searching of the same area is avoided, the searching path can be optimized according to the searching tree, and the searching process is more efficient.
Based on the foregoing embodiments, the present application provides a recharge path determining apparatus, where the recharge path determining apparatus includes modules and units included in the modules, and the modules and the units may be implemented by a processor in a computer device; of course, the implementation can also be realized through a specific logic circuit; in the implementation process, the processor may be a CPU, a Microprocessor Unit (MPU), a Digital Signal Processor (DSP), a Field Programmable Gate Array (FPGA), or the like.
An embodiment of the present application further provides a recharge path determining apparatus, fig. 6 is a schematic structural diagram of the recharge path determining apparatus provided in the embodiment of the present application, and as shown in fig. 6, the recharge path determining apparatus 600 includes:
an obtaining module 601, configured to determine that an intelligent mobile device needs to perform power replenishment and cannot determine a recharging path, obtain a current node where the intelligent mobile device is located, and determine the current node as an active node;
a determining module 602, configured to determine, as a candidate node, at least one node that is less than a distance threshold from the active node and that can be reached by the smart mobile device;
a first control module 603, configured to determine that a target node can be determined from the candidate nodes based on the attribute information of the candidate nodes, and control the smart mobile device to move from the active node to the target node;
a second control module 604, configured to determine that the smart mobile device can receive charging-stand information, and control the smart mobile device to move from the target node to a location of a charging stand based on the charging-stand information.
In some embodiments, the determining module 602 is further configured to determine that a target node can be determined from the candidate nodes based on the attribute information of the candidate nodes, control the smart mobile device to move from the active node to the target node, and determine the target node as a child node of the active node;
the recharge path determining apparatus 600 further includes:
a first updating module for updating a current exploration tree based on the active node and the target node, wherein the current exploration tree is composed of historical active nodes, the active nodes and the target node.
In some embodiments, the recharge path determining apparatus 600 further comprises:
a second updating module, configured to determine that the smart mobile device cannot receive the charging-stand information, and update the target node to be an active node;
a third updating module, configured to update at least one node, which is less than a distance threshold and is reachable by the smart mobile device, as a candidate node;
the first control module 603 is further configured to determine that a target node can be determined from the candidate nodes based on the attribute information of the candidate nodes, and control the smart mobile device to move from the active node to the target node.
In some embodiments, the determining module 602 is further configured to determine that the target node cannot be determined from the candidate nodes based on the attribute information of the candidate nodes, and determine a parent node of the active node based on the current exploration tree.
The recharge path determining apparatus 600 further includes:
a third control module for controlling the smart mobile device to move from the active node to the parent node;
a fourth updating module, configured to update the parent node to be an active node;
the determining module 602 is further configured to determine, as a candidate node, at least one node that is less than a distance threshold from the active node and that can be reached by the smart mobile device;
the first control module 603 is further configured to determine that a target node can be determined from the candidate nodes based on the attribute information of the candidate nodes, and control the smart mobile device to move from the active node to the target node.
In some embodiments, the determining module 602 comprises:
a first determining submodule, configured to determine a target area where a distance to the active node is smaller than the distance threshold;
a second determining submodule for determining a reachable area outside the obstacle in the target area based on the acquired environmental information;
and the third determining submodule is used for determining the nodes in the reachable area as the candidate nodes.
In some embodiments, the first control module 603 comprises:
the establishing submodule is used for establishing a preset cost function based on a first distance parameter between a node and an active node, a second distance parameter between the node and an obstacle and a node information entropy parameter;
the input submodule is used for inputting the first distance, the second distance and the information entropy into the preset cost function to obtain the score of the candidate node;
a fourth determination submodule for determining a highest score from the scores;
and the fifth determining submodule is used for determining that the highest score reaches a score threshold value, and determining the candidate node corresponding to the highest score as the target node.
In some embodiments, the obtaining module 601 is further configured to obtain a pause time for the smart mobile device to stay at the current pause location;
the determining module 602 is further configured to determine that the pause time is greater than a time threshold, and determine a third distance between the pause node and the target node based on the location information of the current pause location and the location information of the target node; determining that the third distance is smaller than a preset distance, and determining the pause position as the active node;
the first control module 603 is further configured to continue to determine a target node of the active node, and control the smart mobile device to move from the active node to the target node.
In some embodiments, the determining module 602 is further configured to determine that the third distance is greater than or equal to the preset distance, and determine each distance between the position information of each node of the current exploration tree and the pause position; determining a nearest node corresponding to the distance minimum value in each distance; determining the nearest node as the active node;
the first control module 603 is further configured to continue to determine a target node of the active node, and control the smart mobile device to move from the active node to the target node.
It should be noted that the description of the recharge path determining apparatus in the embodiment of the present application is similar to the description of the method embodiment described above, and has similar beneficial effects to the method embodiment. For technical details not disclosed in the embodiments of the apparatus, reference is made to the description of the embodiments of the method of the present application for understanding.
It should be noted that, in the embodiment of the present application, if the system upgrading method is implemented in the form of a software functional module and is sold or used as a standalone product, the system upgrading method may also be stored in a computer readable storage medium. Based on such understanding, the technical solutions of the embodiments of the present application may be essentially implemented or portions thereof contributing to the related art may be embodied in the form of a software product stored in a storage medium, and including several instructions for enabling a computer device (which may be a personal computer, a server, or a network device) to execute all or part of the methods described in the embodiments of the present application. And the aforementioned storage medium includes: various media capable of storing program codes, such as a usb disk, a removable hard disk, a Read Only Memory (ROM), a magnetic disk, or an optical disk. Thus, embodiments of the present application are not limited to any specific combination of hardware and software.
Accordingly, embodiments of the present application provide a computer-readable storage medium, on which a computer program is stored, which, when being executed by a processor, implements the steps in the recharge path determination method provided in the above embodiments.
An embodiment of the present application provides an intelligent mobile device, fig. 7 is a schematic diagram of a composition structure of the intelligent mobile device provided in the embodiment of the present application, and as shown in fig. 7, the intelligent mobile device 700 includes: a processor 701, at least one communication bus 702, a user interface 703, at least one external communication interface 704 and a memory 705. Wherein the communication bus 702 is configured to enable connective communication between these components. The user interface 703 may include a display screen, and the external communication interface 704 may include standard wired and wireless interfaces, among others. The processor 701 is configured to execute a program of the recharge path determining method stored in the memory, so as to implement the steps in the recharge path determining method provided in the above embodiments. .
The above description of the embodiments of the home device and the storage medium is similar to the description of the embodiments of the method described above, and has similar beneficial effects as the embodiments of the method. For technical details not disclosed in the embodiments of the household appliance and the storage medium of the present application, reference is made to the description of the embodiments of the method of the present application for understanding.
It should be appreciated that reference throughout this specification to "one embodiment" or "an embodiment" means that a particular feature, structure or characteristic described in connection with the embodiment is included in at least one embodiment of the present application. Thus, the appearances of the phrases "in one embodiment" or "in an embodiment" in various places throughout this specification are not necessarily all referring to the same embodiment. Furthermore, the particular features, structures, or characteristics may be combined in any suitable manner in one or more embodiments. It should be understood that, in the various embodiments of the present application, the sequence numbers of the above-mentioned processes do not mean the execution sequence, and the execution sequence of each process should be determined by its function and inherent logic, and should not constitute any limitation to the implementation process of the embodiments of the present application. The above-mentioned serial numbers of the embodiments of the present application are merely for description and do not represent the merits of the embodiments.
It should be noted that, in this document, 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.
In the several embodiments provided in the present application, it should be understood that the disclosed apparatus and method may be implemented in other ways. The above-described device embodiments are merely illustrative, for example, the division of the unit is only a logical functional division, and there may be other division ways in actual implementation, such as: multiple units or components may be combined, or may be integrated into another system, or some features may be omitted, or not implemented. In addition, the coupling, direct coupling or communication connection between the components shown or discussed may be through some interfaces, and the indirect coupling or communication connection between the devices or units may be electrical, mechanical or other forms.
The units described as separate parts may or may not be physically separate, and parts displayed as units may or may not be physical units; can be located in one place or distributed on a plurality of network units; some or all of the units can be selected according to actual needs to achieve the purpose of the solution of the embodiment.
In addition, all functional units in the embodiments of the present application may be integrated into one processing unit, or each unit may be separately regarded as one unit, or two or more units may be integrated into one unit; the integrated unit can be realized in a form of hardware, or in a form of hardware plus a software functional unit.
Those of ordinary skill in the art will understand that: all or part of the steps for realizing the method embodiments can be completed by hardware related to program instructions, the program can be stored in a computer readable storage medium, and the program executes the steps comprising the method embodiments when executed; and the aforementioned storage medium includes: a removable storage device, a ROM, a magnetic or optical disk, or other various media that can store program code.
Alternatively, the integrated units described above in the present application may be stored in a computer-readable storage medium if they are implemented in the form of software functional modules and sold or used as independent products. Based on such understanding, the technical solutions of the embodiments of the present application may be embodied in the form of a software product, which is stored in a storage medium and includes several instructions for causing an AC to perform all or part of the methods described in the embodiments of the present application. And the aforementioned storage medium includes: a removable storage device, a ROM, a magnetic or optical disk, or other various media that can store program code.
The above description is only for the embodiments of the present application, but the scope of the present application is not limited thereto, and any person skilled in the art can easily conceive of changes or substitutions within the technical scope of the present application, and shall be covered by the scope of the present application. Therefore, the protection scope of the present application shall be subject to the protection scope of the claims.

Claims (11)

1. A recharge path determination method, the method comprising:
determining that the intelligent mobile equipment needs to be supplemented with electric quantity and cannot determine a recharging path, acquiring a current node where the intelligent mobile equipment is located, and determining the current node as an active node;
determining at least one node which is less than a distance threshold value and can be reached by the intelligent mobile equipment as a candidate node;
determining that a target node can be determined from the candidate nodes based on the attribute information of the candidate nodes, and controlling the intelligent mobile device to move from the active node to the target node;
and determining that the intelligent mobile equipment can receive charging seat information, and controlling the intelligent mobile equipment to move from the target node to the position of the charging seat based on the charging seat information.
2. The method of claim 1, further comprising:
determining that a target node can be determined from the candidate nodes based on the attribute information of the candidate nodes, controlling the intelligent mobile device to move from the active node to the target node, and determining the target node as a child node of the active node;
updating a current exploration tree based on the active nodes and the target nodes, wherein the current exploration tree is composed of historical active nodes, the active nodes and the target nodes.
3. The method of claim 1, further comprising:
determining that the intelligent mobile equipment cannot receive the charging seat information, and updating the target node to be an active node;
updating at least one node which is less than a distance threshold value and can be reached by the intelligent mobile equipment with the distance from the active node as a candidate node;
and determining that a target node can be determined from the candidate nodes based on the attribute information of the candidate nodes, and controlling the intelligent mobile equipment to move from the active node to the target node.
4. The method of claim 1, further comprising:
determining that the target node cannot be determined from the candidate nodes based on the attribute information of the candidate nodes, and determining a father node of the active node based on the current exploration tree;
controlling the smart mobile device to move from the active node to the parent node;
updating the parent node to be an active node;
determining at least one node which is less than a distance threshold value and can be reached by the intelligent mobile equipment as a candidate node;
and determining that a target node can be determined from the candidate nodes based on the attribute information of the candidate nodes, and controlling the intelligent mobile equipment to move from the active node to the target node.
5. The method of claim 1, wherein determining at least one node that is less than a distance threshold from the active node and that is reachable by the smart mobile device as a candidate node comprises:
determining a target area having a distance to the active node less than the distance threshold;
determining a reachable area outside the obstacle in the target area based on the collected environmental information;
determining a node within the reachable region as the candidate node.
6. The method of claim 1, wherein the attribute information comprises a first distance between the candidate node and the active node, a second distance between the candidate node and an obstacle, and an entropy of information of the candidate node; the determining, based on the attribute information of the candidate nodes, may determine a target node from the candidate nodes, including:
establishing a preset cost function based on a first distance parameter between a node and an active node, a second distance parameter between the node and an obstacle and a node information entropy parameter;
inputting the first distance, the second distance and the information entropy into the preset cost function to obtain the score of the candidate node;
determining a highest score from the scores;
and determining that the highest score reaches a score threshold value, and determining the candidate node corresponding to the highest score as the target node.
7. The method according to any one of claims 1 to 6, further comprising:
obtaining the pause time of the intelligent mobile equipment staying at the current pause position;
determining that the pause time is greater than a time threshold, and determining a third distance between the pause node and the target node based on the position information of the current pause position and the position information of the target node;
determining that the third distance is smaller than a preset distance, and determining the pause position as the active node;
continuing to determine a target node of the active node, and controlling the intelligent mobile device to move from the active node to the target node.
8. The method of claim 7, further comprising:
determining that the third distance is greater than or equal to the preset distance, and determining each distance between the position information of each node of the current exploration tree and the pause position;
determining a nearest node corresponding to the distance minimum value in each distance;
determining the nearest node as the active node;
continuing to determine a target node of the active node, and controlling the intelligent mobile device to move from the active node to the target node.
9. A recharge path determination apparatus, said apparatus comprising:
the system comprises an acquisition module, a processing module and a processing module, wherein the acquisition module is used for determining that the intelligent mobile equipment needs to be supplemented with electric quantity and cannot determine a recharging path, acquiring a current node where the intelligent mobile equipment is located, and determining the current node as an active node;
a determining module, configured to determine at least one node, which is less than a distance threshold and is reachable by the smart mobile device, as a candidate node;
the first control module is used for determining that a target node can be determined from the candidate nodes based on the attribute information of the candidate nodes, and controlling the intelligent mobile equipment to move from the active node to the target node;
and the second control module is used for determining that the intelligent mobile equipment can receive charging seat information and controlling the intelligent mobile equipment to move from the target node to the position of the charging seat based on the charging seat information.
10. A smart mobile device, comprising:
a processor; and
a memory for storing a computer program operable on the processor;
wherein the computer program when executed by a processor implements the backfill path determining method according to any one of claims 1 to 8.
11. A computer-readable storage medium having computer-executable instructions stored thereon, the computer-executable instructions configured to perform the recharge path determination method of any of the preceding claims 1 to 8.
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