CN109066857B - Method for charging patrol robot and charger robot - Google Patents

Method for charging patrol robot and charger robot Download PDF

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Publication number
CN109066857B
CN109066857B CN201810927487.6A CN201810927487A CN109066857B CN 109066857 B CN109066857 B CN 109066857B CN 201810927487 A CN201810927487 A CN 201810927487A CN 109066857 B CN109066857 B CN 109066857B
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patrol
charged
robot
robots
charging
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CN109066857A (en
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章一洲
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Seven Teng Robot Co.,Ltd.
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Chongqing Qiteng Technology Co Ltd
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    • H02J7/0027—
    • H—ELECTRICITY
    • H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
    • H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
    • H02J7/00—Circuit arrangements for charging or depolarising batteries or for supplying loads from batteries
    • H02J7/00032—Circuit arrangements for charging or depolarising batteries or for supplying loads from batteries characterised by data exchange
    • H02J7/00036—Charger exchanging data with battery
    • Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
    • Y02E—REDUCTION OF GREENHOUSE GAS [GHG] EMISSIONS, RELATED TO ENERGY GENERATION, TRANSMISSION OR DISTRIBUTION
    • Y02E60/00—Enabling technologies; Technologies with a potential or indirect contribution to GHG emissions mitigation
    • Y02E60/10—Energy storage using batteries

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  • Engineering & Computer Science (AREA)
  • Power Engineering (AREA)
  • Charge And Discharge Circuits For Batteries Or The Like (AREA)
  • Control Of Position, Course, Altitude, Or Attitude Of Moving Bodies (AREA)

Abstract

The invention provides a method for charging a patrol robot and a charger robot, wherein the method comprises the following steps: acquiring position information of a current position of a patrol robot to be charged and a current patrol plan of the patrol robot; generating a charging path using a charging path generation algorithm based on the location information and the patrol plan; and finding the patrol robot based on the charging path, and charging the patrol robot. The charging method and the charging device of the patrol robot are used for improving the charging efficiency of the patrol robot and improving the patrol safety of the patrol robot.

Description

Method for charging patrol robot and charger robot
Technical Field
The invention relates to artificial intelligence, in particular to a method for charging a patrol robot and a charger robot.
Background
With the increasing application demand of robots, the continuous progress of artificial intelligence related technologies and the increase of hardware performance, service robots have started to move from laboratories to factories and have been developed from single functions to multifunctional personal robots in recent years. Referring to robotics, one word often mentioned recently is artificial intelligence. Artificial intelligence is a discipline of using computers to implement intelligent behavior similar to that of humans. The robot itself is one of the ultimate application targets of artificial intelligence.
As a subject, the traditional artificial intelligence originated in the Dattes conference in the 50 s of the 20 th century, and after a few major landings, the traditional artificial intelligence accumulated abundant results on basic theories and methods. Machine learning and big data analysis developed from early symbolic computing systems, expert systems and the 90 s can be calculated as the category of artificial intelligence. In the fields of image, voice, search, data mining, social computing and the like, some related application researches are derived. Wherein, the robot is closely related to the robot, including computer vision, voice and natural language processing, and Agent.
According to the research progress in the robot field and the preliminary analysis of the application, the following perception and cognition techniques can be considered as the key for realizing the application.
1. Provided is a three-dimensional navigation positioning technology. Regardless of the robot, navigation positioning in a home or other environment is required as long as it is mobile. The SLAM (Simultaneous Localization and Ming) technology can be used for positioning and mapping at the same time, and a lot of technologies are accumulated in the aspect of academic research. However, for an actual system, due to the requirement of low real-time performance (for example, expensive radar equipment cannot be adopted) and the dynamic change of a home environment (placement of articles), higher requirements are put on a navigation positioning technology, and further research and development are still needed.
2. Visual perception techniques. The method comprises the related technologies of face recognition, gesture recognition, object recognition, emotion recognition and the like. Visual perception technology is a very important technology for interaction between robots and people.
3. Language interaction technology. Including speech recognition, speech generation, natural language understanding, and intelligent dialog systems.
4. A character recognition technology. In life, there are many text messages, such as labels of books, newspapers and objects, which also requires that the robot can recognize the text through a camera. Compared with the traditional character recognition after scanning, the character recognition method can perform character recognition through the camera.
5. And (4) cognitive technology. The robot needs to gradually realize cognitive functions such as planning, reasoning, memory, learning and prediction, and becomes more intelligent.
From the current research situation, the key technologies faced by the service robot are greatly improved, but a plurality of problems need to be solved.
The application scenario of the robot is that the robot patrols in a specific area. One conventional way of patrolling a robot is to preset a patrol route of the robot, and the robot patrols according to the preset patrol route.
Although the method can enable the robot to realize the patrol function, the route is preset, so that the robot is easy to be hollowed by lawbreakers, and the safety cannot be guaranteed.
Disclosure of Invention
The embodiment of the invention provides a method for charging a patrol robot and a charger robot, which are used for charging the patrol robot, so that the charging efficiency of the patrol robot can be improved, and the patrol safety of the patrol robot can be improved.
The purpose of the embodiment of the invention is realized by the following technical scheme:
a method of charging a patrol robot, comprising:
acquiring position information of a current position of a patrol robot to be charged and a current patrol plan of the patrol robot;
generating a charging path using a charging path generation algorithm based on the location information and the patrol plan;
and finding the patrol robot based on the charging path, and charging the patrol robot.
Optionally, the obtaining of the position information of the current position of the patrol robot to be charged and the current patrol plan of the patrol robot further includes:
and determining the patrol robot to be charged.
Optionally, the determining the patrol robot to be charged includes:
sending power query requests to all patrol robots, receiving power information sent by the patrol robots, and determining the patrol robots to be charged based on the power information; or
And receiving electric quantity information actively sent by the patrol robot to be charged when the electric quantity is lower than the preset charging electric quantity, and determining the patrol robot to be charged based on the electric quantity information.
Optionally, the number of the patrol robots to be charged is at least two, and before the charging path is generated by using a charging path generation algorithm based on the position information and the patrol plan, the method further includes:
judging whether the at least two patrol robots to be charged can be charged or not;
if the at least two patrol robots to be charged cannot be charged, selecting a patrol robot to be charged which meets a preset condition from the at least two patrol robots to be charged;
the generating a charging path using a charging path generation algorithm based on the location information and the patrol plan comprises:
and generating a charging path for the patrol robot to be charged meeting the preset conditions by using a charging path generation algorithm based on the position information and the patrol plan of the patrol robot to be charged meeting the preset conditions.
Optionally, if the at least two patrol robots to be charged cannot be charged, the method further includes:
and indicating other charging robots to charge the patrol robot to be charged, which does not meet the preset condition, in the at least two robots to be charged.
A charger robot, comprising:
the acquiring unit is used for acquiring the position information of the current position of the patrol robot to be charged and the current patrol plan of the patrol robot;
a generation unit configured to generate a charging path using a charging path generation algorithm based on the location information and the patrol plan;
and the charging unit is used for finding the patrol robot based on the charging path and charging the patrol robot.
Optionally, the charging robot further includes:
the determining unit is used for determining the patrol robot to be charged before the acquiring unit acquires the position information of the current position of the patrol robot to be charged and the current patrol plan of the patrol robot.
Optionally, the determining unit is specifically configured to:
sending power query requests to all patrol robots, receiving power information sent by the patrol robots, and determining the patrol robots to be charged based on the power information; or
And receiving electric quantity information actively sent by the patrol robot to be charged when the electric quantity is lower than the preset charging electric quantity, and determining the patrol robot to be charged based on the electric quantity information.
Optionally, the number of patrol robot waiting to charge is at least two, charge robot still includes:
the judging unit is used for judging whether the at least two patrol robots to be charged can be charged or not;
the selection unit is used for selecting the patrol robot to be charged which meets the preset conditions from the at least two patrol robots to be charged when the judgment unit judges that the patrol robots to be charged cannot be charged;
the generating unit is specifically configured to:
and generating a charging path for the patrol robot to be charged meeting the preset conditions by using a charging path generation algorithm based on the position information and the patrol plan of the patrol robot to be charged meeting the preset conditions.
Optionally, the charging robot further includes:
and the indicating unit is used for indicating other charging robots to charge the patrol robots to be charged, which do not meet the preset conditions, in the at least two patrol robots to be charged when the judging unit judges that the patrol robots to be charged cannot be charged.
As can be seen from the above, by using the method for charging a patrol robot provided in this embodiment, a charging path is generated by using a charging path generation algorithm based on the position information and the patrol plan of the patrol robot to be charged, so that the patrol robot to be charged is charged according to the charging path, and the patrol robot to be charged can be charged without affecting the patrol plan of the patrol robot to be charged, thereby improving the charging efficiency of the patrol robot and the patrol safety of the patrol robot.
Drawings
In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings needed to be used in the description of the embodiments will be briefly introduced below, and it is obvious that the drawings in the following description are only some embodiments of the present invention, and it is obvious for those skilled in the art to obtain other drawings based on these drawings without inventive labor.
Fig. 1 is a flowchart of a method for charging a patrol robot according to an embodiment of the present invention;
fig. 2 is a structural diagram of a charging robot according to an embodiment of the present invention.
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. 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.
First, a method for charging a patrol robot according to an embodiment of the present invention is described, and fig. 1 illustrates a flow of the method for charging a patrol robot according to an embodiment of the present invention, where the method may be performed by a charger robot. As shown in fig. 1, the method may include:
101. the method comprises the steps of obtaining position information of the current position of a patrol robot to be charged and the current patrol plan of the patrol robot.
The current position of the patrol robot to be charged can be acquired by the patrol robot and then sent to the charging robot, or the current position of the patrol robot to be charged can be acquired by the patrol robot and then sent to the server and then sent to the charging robot by the server.
The patrol plan of the patrol robot to be charged can be acquired by the patrol robot and then sent to the charging robot, and can also be sent to the charging robot by the server. The patrol plan comprises a patrol path and/or patrol time of the patrol robot to be charged.
According to the different current positions of the patrol robot to be charged, the patrol robot to be charged has different modes of acquiring the position information of the current position.
For example, when the current location is an outdoor area, the current location of the robot may be obtained using a satellite Positioning System, which may be a Global Positioning System (GPS), a beidou satellite Positioning System, a GLONASS satellite Positioning System, and/or a galileo satellite navigation System.
For example, when the current location is an indoor area, since the satellite positioning system cannot perform positioning, indoor positioning technology may be used, such as WiFi indoor positioning technology, UWB indoor positioning technology, bluetooth indoor positioning technology, infrared indoor positioning technology, RFID indoor positioning technology, ultrasonic indoor positioning technology, and the like.
It will be appreciated that the indoor location techniques described above may be used for location determination even if the current location is an outdoor area.
In one embodiment, step 101 may further include, before: and determining the patrol robot to be charged. Specifically, the determination of the patrol robot to be charged may be performed in the following manner:
sending power query requests to all patrol robots, receiving power information sent by the patrol robots, and determining the patrol robots to be charged based on the power information; namely, the charging robot actively inquires the electric quantity condition of the patrol robot, so that the patrol robot to be charged is charged; alternatively, the first and second electrodes may be,
receiving electric quantity information actively sent by the patrol robot to be charged when the electric quantity is lower than the preset charging electric quantity, and determining the patrol robot to be charged based on the electric quantity information; that is to say, the patrol robot to be charged actively sends a charging request to the charger robot, which is equivalent to the charger robot passively receiving the request of the patrol robot to be charged and then charging the patrol robot to be charged.
102. Generating a charging path using a charging path generation algorithm based on the location information and the patrol plan.
After the current position and the patrol plan of the patrol robot to be charged are known, the subsequent patrol path of the patrol robot to be charged can be known, so that a charging path can be generated based on a charging path generation algorithm, and the patrol robot to be charged can be directly found by the charger robot through the charging path, so that the patrol robot to be charged can be charged.
When the number of the patrol robots to be charged is one, the charging path may only include information related to the patrol robot to be charged, so that the charging robot may directly find the patrol robot to be charged through the charging path, thereby charging the patrol robot to be charged.
When the number of the patrol robots to be charged is at least two, the charging path needs to include information about the at least two patrol robots to be charged, for example, a charging sequence of the at least two patrol robots to be charged and respective charging numbers of the at least two patrol robots to be charged, wherein, due to a problem of charging efficiency, it may not be possible to charge the electric quantity of one patrol robot to be charged after the electric quantity of the other patrol robot to be charged is charged, so that it is possible to charge one of the patrol robots to be charged first by charging a part of the electric quantity of the other patrol robot to be charged within a patrol time, ensure that the charger robot can continue to patrol for a certain period of time, charge the other patrol robots to be charged within the patrol time, and then charge the patrol robot to be charged before the patrol time expires, therefore, the patrol of the patrol robot to be charged is not interrupted.
For example, in one embodiment, if the number of patrol robots to be charged is 3, which are a, B, and C, respectively, the charging path may be: a (20%) → B (30%) → C (20%) → B (50%) → C (40%) → a (40%) → C (70%) → a (60%) → B (80%) → a (80%) → C (100%) → a (100%) → B (100%), wherein the percentage in parentheses means the percentage of the charge amount of the patrol robot to be charged to the full charge amount. The reason why the three patrol robots to be charged are not charged in the order of a → B → C is that the patrol robots to be charged are patrolling all the time, that is, moving all the time, so that the distance between patrol robots to be charged and the distance after charging need to be considered when the charging robot generates a charging path, thereby ensuring that the moving distance of the charger robot between patrol robots to be charged is as short as possible during charging, and improving charging efficiency.
The charging path generation algorithm may be pre-trained, and the algorithm may specifically be a mathematical model, for example, a Convolutional Neural Network (CNN) model, a Recurrent Neural Network (RNN) model, or a Deep Neural Network (DNN) model.
In one embodiment, one charging robot may not be able to complete charging of all patrol robots to be charged, and therefore, when the number of patrol robots to be charged is at least two, before generating a charging path using a charging path generation algorithm based on the position information and the patrol plan, the method may further include:
judging whether the at least two patrol robots to be charged can be charged or not; the method comprises the steps of charging at least two patrol robots to be charged, wherein the charge of the at least two patrol robots to be charged can be judged according to the number of the patrol robots to be charged, the distance between the at least two patrol robots to be charged and the residual electric quantity of each patrol robot to be charged.
If the at least two patrol robots to be charged cannot be charged, selecting a patrol robot to be charged which meets a preset condition from the at least two patrol robots to be charged;
correspondingly, the generating a charging path by using a charging path generation algorithm based on the location information and the patrol plan specifically includes:
and generating a charging path for the patrol robot to be charged meeting the preset conditions by using a charging path generation algorithm based on the position information and the patrol plan of the patrol robot to be charged meeting the preset conditions.
When the at least two patrol robots to be charged cannot be charged, in order to ensure that patrol of patrol robots to be charged, which do not satisfy the preset condition, of the at least two patrol robots to be charged is not interrupted, the method may further include:
and indicating other charging robots to charge the patrol robot to be charged, which does not meet the preset condition, in the at least two robots to be charged.
103. And finding the patrol robot based on the charging path, and charging the patrol robot.
As can be seen from the above, by using the method for charging a patrol robot provided in this embodiment, a charging path is generated by using a charging path generation algorithm based on the position information and the patrol plan of the patrol robot to be charged, so that the patrol robot to be charged is charged according to the charging path, and the patrol robot to be charged can be charged without affecting the patrol plan of the patrol robot to be charged, thereby improving the charging efficiency of the patrol robot and the patrol safety of the patrol robot.
In one embodiment of the present invention, the charging path generation algorithm is deployed in a neural network, and the neural network may be composed of a plurality of neurons. In the neural network, the charging path generation algorithm may be expressed as a calculation formula as follows:
q＝f(Ap+Bw)＝f(Ap1∩Ap2∩Ap3+Bw1∩Bw2∩Bw3)
wherein q represents the generated charging path, p represents the position of the patrol robot to be charged, w represents the patrol plan of the patrol robot to be charged, p1, p2 and p3 represent the position information of three patrol robots to be charged respectively, w1, w2 and w3 represent the patrol plans of the patrol robots to be charged respectively, f () represents the activation function corresponding to the neuron, and a and B are the module parameters corresponding to the activation function. In one embodiment, the activation function f () may specifically be a sigmoid function, i.e. f () may be represented in the form:
Figure GDA0003095956920000071
module parameters of the activation function f () are trained in advance, and in one embodiment, the module parameters a and B can be obtained by training the following training functions:
Figure GDA0003095956920000081
wherein M is a parameter of a training function, N is the number of training pairs in a training set, qn is a charging path in the training set, pn is the position of the patrol robot to be charged in the training set, and wn is a patrol plan of the patrol robot to be charged in the training set.
Fig. 2 depicts a structure of a charger robot according to an embodiment of the present invention, where the charger robot may be used to implement the method for charging a patrol robot according to the foregoing embodiment. As shown in fig. 2, the charger robot may include:
the acquiring unit 201 is configured to acquire position information of a current position of a patrol robot to be charged and a current patrol plan of the patrol robot.
The current position of the patrol robot to be charged can be acquired by the patrol robot and then sent to the charging robot, or the current position of the patrol robot to be charged can be acquired by the patrol robot and then sent to the server and then sent to the charging robot by the server.
The patrol plan of the patrol robot to be charged can be acquired by the patrol robot and then sent to the charging robot, and can also be sent to the charging robot by the server. The patrol plan comprises a patrol path and/or patrol time of the patrol robot to be charged.
According to the different current positions of the patrol robot to be charged, the patrol robot to be charged has different modes of acquiring the position information of the current position.
For example, when the current location is an outdoor area, the current location of the robot may be obtained using a satellite Positioning System, which may be a Global Positioning System (GPS), a beidou satellite Positioning System, a GLONASS satellite Positioning System, and/or a galileo satellite navigation System.
For example, when the current location is an indoor area, since the satellite positioning system cannot perform positioning, indoor positioning technology may be used, such as WiFi indoor positioning technology, UWB indoor positioning technology, bluetooth indoor positioning technology, infrared indoor positioning technology, RFID indoor positioning technology, ultrasonic indoor positioning technology, and the like.
It will be appreciated that the indoor location techniques described above may be used for location determination even if the current location is an outdoor area.
A generating unit 202 configured to generate a charging path using a charging path generation algorithm based on the location information and the patrol plan.
After the current position and the patrol plan of the patrol robot to be charged are known, the subsequent patrol path of the patrol robot to be charged can be known, so that a charging path can be generated based on a charging path generation algorithm, and the patrol robot to be charged can be directly found by the charger robot through the charging path, so that the patrol robot to be charged can be charged.
When the number of the patrol robots to be charged is one, the charging path may only include information related to the patrol robot to be charged, so that the charging robot may directly find the patrol robot to be charged through the charging path, thereby charging the patrol robot to be charged.
When the number of the patrol robots to be charged is at least two, the charging path needs to include information about the at least two patrol robots to be charged, for example, a charging sequence of the at least two patrol robots to be charged and respective charging numbers of the at least two patrol robots to be charged, wherein, due to a problem of charging efficiency, it may not be possible to charge the electric quantity of one patrol robot to be charged after the electric quantity of the other patrol robot to be charged is charged, so that it is possible to charge one of the patrol robots to be charged first by charging a part of the electric quantity of the other patrol robot to be charged within a patrol time, ensure that the charger robot can continue to patrol for a certain period of time, charge the other patrol robots to be charged within the patrol time, and then charge the patrol robot to be charged before the patrol time expires, therefore, the patrol of the patrol robot to be charged is not interrupted.
For example, in one embodiment, if the number of patrol robots to be charged is 3, which are a, B, and C, respectively, the charging path may be: a (20%) → B (30%) → C (20%) → B (50%) → C (40%) → a (40%) → C (70%) → a (60%) → B (80%) → a (80%) → C (100%) → a (100%) → B (100%), wherein the percentage in parentheses means the percentage of the charge amount of the patrol robot to be charged to the full charge amount. The reason why the three patrol robots to be charged are not charged in the order of a → B → C is that the patrol robots to be charged are patrolling all the time, that is, moving all the time, so that the distance between patrol robots to be charged and the distance after charging need to be considered when the charging robot generates a charging path, thereby ensuring that the moving distance of the charger robot between patrol robots to be charged is as short as possible during charging, and improving charging efficiency.
The charging path generation algorithm may be pre-trained, and the algorithm may specifically be a mathematical model, for example, a Convolutional Neural Network (CNN) model, a Recurrent Neural Network (RNN) model, or a Deep Neural Network (DNN) model.
In one embodiment, one charging robot may not be able to complete charging of all patrol robots to be charged, and therefore, when the number of patrol robots to be charged is at least two, before generating a charging path using a charging path generation algorithm based on the position information and the patrol plan, the method may further include:
judging whether the at least two patrol robots to be charged can be charged or not; the method comprises the steps of charging at least two patrol robots to be charged, wherein the charge of the at least two patrol robots to be charged can be judged according to the number of the patrol robots to be charged, the distance between the at least two patrol robots to be charged and the residual electric quantity of each patrol robot to be charged.
If the at least two patrol robots to be charged cannot be charged, selecting a patrol robot to be charged which meets a preset condition from the at least two patrol robots to be charged;
correspondingly, the generating a charging path by using a charging path generation algorithm based on the location information and the patrol plan specifically includes:
and generating a charging path for the patrol robot to be charged meeting the preset conditions by using a charging path generation algorithm based on the position information and the patrol plan of the patrol robot to be charged meeting the preset conditions.
When the at least two patrol robots to be charged cannot be charged, in order to ensure that patrol of patrol robots to be charged, which do not satisfy the preset condition, of the at least two patrol robots to be charged is not interrupted, the method may further include:
and indicating other charging robots to charge the patrol robot to be charged, which does not meet the preset condition, in the at least two robots to be charged.
And the charging unit 203 is used for finding the patrol robot based on the charging path and charging the patrol robot.
From the above, by using the charger robot provided by this embodiment, the charging path generation algorithm is used to generate the charging path based on the position information and the patrol plan of the patrol robot to be charged, so that the patrol robot to be charged is charged according to the charging path, and the patrol robot to be charged can be charged without affecting the patrol plan of the patrol robot to be charged, thereby improving the charging efficiency of the patrol robot and the patrol safety of the patrol robot.
In one embodiment, the charging robot may further include:
the determining unit is used for determining the patrol robot to be charged before the acquiring unit 201 acquires the position information of the current position of the patrol robot to be charged and the current patrol plan of the patrol robot.
In an embodiment, the determining unit may be specifically configured to:
sending power query requests to all patrol robots, receiving power information sent by the patrol robots, and determining the patrol robots to be charged based on the power information; namely, the charging robot actively inquires the electric quantity condition of the patrol robot, so that the patrol robot to be charged is charged; or
Receiving electric quantity information actively sent by the patrol robot to be charged when the electric quantity is lower than the preset charging electric quantity, and determining the patrol robot to be charged based on the electric quantity information; that is to say, the patrol robot to be charged actively sends a charging request to the charger robot, which is equivalent to the charger robot passively receiving the request of the patrol robot to be charged and then charging the patrol robot to be charged.
In one embodiment, the number of the patrol robots to be charged is at least two, and the charge robot may further include:
the judging unit is used for judging whether the at least two patrol robots to be charged can be charged or not;
the selection unit is used for selecting the patrol robot to be charged which meets the preset conditions from the at least two patrol robots to be charged when the judgment unit judges that the patrol robots to be charged cannot be charged;
in this case, the generating unit 202 may specifically be configured to:
and generating a charging path for the patrol robot to be charged meeting the preset conditions by using a charging path generation algorithm based on the position information and the patrol plan of the patrol robot to be charged meeting the preset conditions.
In one embodiment, the charging robot may further include:
and the indicating unit is used for indicating other charging robots to charge the patrol robots to be charged, which do not meet the preset conditions, in the at least two patrol robots to be charged when the judging unit judges that the patrol robots to be charged cannot be charged.
The above-mentioned information interaction between the unit modules included in the charging robot, the execution process, and the like are based on the same concept as the method embodiment of the present invention, and specific contents may refer to the description in the method embodiment of the present invention, and are not described herein again.
It will be understood by those skilled in the art that all or part of the processes of the methods of the embodiments described above can be implemented by a computer program, which can be stored in a computer-readable storage medium, and when executed, can include the processes of the embodiments of the methods described above. The storage medium may be a magnetic disk, an optical disk, a Read-Only Memory (ROM), a Random Access Memory (RAM), or the like.
The principles and embodiments of the present invention have been described herein using specific examples, which are presented solely to aid in the understanding of the methods and concepts of the present invention; meanwhile, for a person skilled in the art, according to the idea of the present invention, there may be variations in the specific embodiments and the application scope, and in summary, the content of the present specification should not be construed as a limitation to the present invention.

Claims (2)

1. A method of charging a patrol robot, comprising:
acquiring position information of a current position of a patrol robot to be charged and a current patrol plan of the patrol robot; generating a charging path using a charging path generation algorithm based on the location information and the patrol plan;
finding the patrol robot based on the charging path, and charging the patrol robot;
the method comprises the following steps of obtaining the position information of the current position of the patrol robot to be charged and before the current patrol planning of the patrol robot, and further comprises the following steps:
determining the patrol robot to be charged;
the determining the patrol robot to be charged includes:
sending power query requests to all patrol robots, receiving power information sent by the patrol robots, and determining the patrol robots to be charged based on the power information; or
Receiving electric quantity information actively sent by the patrol robot to be charged when the electric quantity is lower than the preset charging electric quantity, and determining the patrol robot to be charged based on the electric quantity information;
the number of the patrol robots to be charged is at least two, and the method further comprises the following steps of, before generating a charging path by using a charging path generation algorithm based on the position information and the patrol plan:
judging whether the at least two patrol robots to be charged can be charged or not;
if the at least two patrol robots to be charged cannot be charged, selecting a patrol robot to be charged which meets a preset condition from the at least two patrol robots to be charged;
the generating a charging path using a charging path generation algorithm based on the location information and the patrol plan comprises:
generating a charging path for the patrol robot to be charged meeting the preset conditions by using a charging path generation algorithm based on the position information and the patrol plan of the patrol robot to be charged meeting the preset conditions;
in the neural network, the charging path generation algorithm may be expressed as a calculation formula as follows:
q＝f(Ap+Bw)＝f(Ap1∩Ap2∩Ap3+Bw1∩Bw2∩Bw3)
wherein q represents the generated charging path, p represents the position of the patrol robot to be charged, w represents the patrol plan of the patrol robot to be charged, and p1、p2And p3Respectively representing the position information, w, of three patrol robots to be charged1、w2And w3Respectively representing patrol plans of the three patrol robots to be charged, wherein f () represents an activation function corresponding to a neuron, A and B represent module parameters corresponding to the activation function, and f () represents the following form:
Figure FDA0003095956910000011
module parameters of the activation function f () are trained in advance, and the module parameters a and B are obtained by training the following training functions:
Figure FDA0003095956910000012
where M is a parameter of the training function, N is the number of training pairs in the training set, qnIs the charging path in the training set, pnIs the position of the patrol robot to be charged in the training set, wnThe patrol planning of the patrol robot to be charged in the training set is carried out; if the at least two patrol robots to be charged cannot be charged, the method further comprises the following steps:
and indicating other charging robots to charge the patrol robot to be charged, which does not meet the preset condition, in the at least two robots to be charged.
2. A charger robot, characterized by, includes:
the acquiring unit is used for acquiring the position information of the current position of the patrol robot to be charged and the current patrol plan of the patrol robot;
a generation unit configured to generate a charging path using a charging path generation algorithm based on the location information and the patrol plan; in the neural network, the charging path generation algorithm may be expressed as a calculation formula as follows:
q＝f(Ap+Bw)＝f(Ap1∩Ap2∩Ap3+Bw1∩Bw2∩Bw3)
wherein q represents the generated charging path, p represents the position of the patrol robot to be charged, w represents the patrol plan of the patrol robot to be charged, and p1、p2And p3Respectively representing the position information, w, of three patrol robots to be charged1、w2And w3Respectively representing patrol plans of the three patrol robots to be charged, wherein f () represents an activation function corresponding to a neuron, A and B represent module parameters corresponding to the activation function, and f () represents the following form:
Figure FDA0003095956910000021
module parameters of the activation function f () are trained in advance, and the module parameters a and B are obtained by training the following training functions:
Figure FDA0003095956910000022
where M is a parameter of the training function, N is the number of training pairs in the training set, qnIs the charging path in the training set, pnIs the position of the patrol robot to be charged in the training set, wnThe patrol planning of the patrol robot to be charged in the training set is carried out;
the charging unit is used for finding the patrol robot based on the charging path and charging the patrol robot; the charging robot further comprises:
the determining unit is used for determining the patrol robot to be charged before the acquiring unit acquires the position information of the current position of the patrol robot to be charged and the current patrol plan of the patrol robot;
the determining unit is specifically configured to:
sending power query requests to all patrol robots, receiving power information sent by the patrol robots, and determining the patrol robots to be charged based on the power information; or
Receiving electric quantity information actively sent by the patrol robot to be charged when the electric quantity is lower than the preset charging electric quantity, and determining the patrol robot to be charged based on the electric quantity information;
wait to charge patrol the quantity of robot and be at least two, charge the robot and still include:
the judging unit is used for judging whether the at least two patrol robots to be charged can be charged or not;
the selection unit is used for selecting the patrol robot to be charged which meets the preset conditions from the at least two patrol robots to be charged when the judgment unit judges that the patrol robots to be charged cannot be charged;
the generating unit is specifically configured to:
generating a charging path for the patrol robot to be charged meeting the preset conditions by using a charging path generation algorithm based on the position information and the patrol plan of the patrol robot to be charged meeting the preset conditions;
the charging robot further comprises:
and the indicating unit is used for indicating other charging robots to charge the patrol robots to be charged, which do not meet the preset conditions, in the at least two patrol robots to be charged when the judging unit judges that the patrol robots to be charged cannot be charged.
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Citations (4)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN104836293A (en) * 2015-05-08 2015-08-12 杭州南江机器人股份有限公司 Charging method of automatic guided vehicle (AGV), movable charging pile and charging system
CN104914870A (en) * 2015-07-08 2015-09-16 中南大学 Ridge-regression-extreme-learning-machine-based local path planning method for outdoor robot
CN105424026A (en) * 2015-11-04 2016-03-23 中国人民解放军国防科学技术大学 Indoor navigation and localization method and system based on point cloud tracks
CN107031444A (en) * 2017-04-13 2017-08-11 蔚来汽车有限公司 Method and apparatus for determining movable charging vehicle charge path

Family Cites Families (9)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
TWI231639B (en) * 2003-02-06 2005-04-21 Terakawa Soji Charger for mobile phone and operation method for the same and charging apparatus for mobile phone and charging method for the same
JP4786355B2 (en) * 2006-01-31 2011-10-05 株式会社日本自動車部品総合研究所 Power supply voltage control method for vehicles
US9346167B2 (en) * 2014-04-29 2016-05-24 Brain Corporation Trainable convolutional network apparatus and methods for operating a robotic vehicle
US9821813B2 (en) * 2014-11-13 2017-11-21 Nec Corporation Continuous occlusion models for road scene understanding
CN106936171B (en) * 2015-12-29 2020-06-19 中国移动通信集团公司 Charging control method, server, unmanned aerial vehicle, mobile charging station and system
US9776323B2 (en) * 2016-01-06 2017-10-03 Disney Enterprises, Inc. Trained human-intention classifier for safe and efficient robot navigation
CN108628904B (en) * 2017-03-23 2021-03-02 北京嘀嘀无限科技发展有限公司 Path coding method, similar path searching method, similar path coding device, similar path searching device and electronic equipment
CN107657374B (en) * 2017-09-25 2021-01-08 中南大学 On-demand charging scheduling method based on dynamic changes of energy consumption and distance
CN108556665B (en) * 2018-04-25 2020-11-06 广州市君望机器人自动化有限公司 Mobile charging pile positioning method, mobile charging pile and intelligent charging system

Patent Citations (4)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN104836293A (en) * 2015-05-08 2015-08-12 杭州南江机器人股份有限公司 Charging method of automatic guided vehicle (AGV), movable charging pile and charging system
CN104914870A (en) * 2015-07-08 2015-09-16 中南大学 Ridge-regression-extreme-learning-machine-based local path planning method for outdoor robot
CN105424026A (en) * 2015-11-04 2016-03-23 中国人民解放军国防科学技术大学 Indoor navigation and localization method and system based on point cloud tracks
CN107031444A (en) * 2017-04-13 2017-08-11 蔚来汽车有限公司 Method and apparatus for determining movable charging vehicle charge path

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