KR100962593B1 - Method and apparatus for area based control of vacuum cleaner, and recording medium thereof - Google Patents

Abstract

PURPOSE: Area based cleaner control method and apparatus are provided to control the movement of a cleaner based on an area to be cleaned by considering user preference and indoor environment without a complex operation or preference input. CONSTITUTION: An area based cleaner control method is as follows. The moving area of a cleaner according on user operation is confirmed and the moving area information is created(S510,S520). If there is no user operation during a predetermined time, statistics for each moving area is calculated by compiling statistics of moving area information(S530,S540). A weighted value of an important area is adjusted based on the statistics for each moving area(S550). The weighted value is applied to the statistics for each moving area and priority by areas is determined(S550,S560). The moving route is determined based on the priority(S570). The cleaner moves according to the determined moving route (S580).

Description

Method and apparatus for controlling area based cleaner, recording medium thereof {Method and Apparatus for area based control of vacuum cleaner, and Recording medium}

The present invention relates to movement control of a cleaner, and more particularly, to an area-based cleaner control method and apparatus, and a recording medium thereof.

In general, housework is to be done in the home, even if you use a vacuum cleaner, even if you have to carry it daily, it can be said that it is a relatively laborious task compared to other household chores.

Accordingly, research and development of a cleaning robot that performs cleaning while moving autonomously by giving a command to perform cleaning work using a remote controller (hereinafter referred to as a remote controller) is being carried out. Research on mobile robots that have complex functions plus disaster prevention functions is ongoing.

1 is a block diagram of a conventional cleaning robot.

The cleaning robot includes a driving unit 40 for moving the body, an obstacle detecting unit 30 for detecting an obstacle on the moving path, a magnetic position recognition unit 20 for recognizing its current position, The vacuum cleaner 50 for cleaning a floor, the power supply part 70 which stores and charges the power required for each part, and the control part 60 which controls each part are provided. In addition, the cleaning robot has a remote control receiver 10 to control the start / stop remotely.

The magnetic position recognition unit 20 and the obstacle detecting unit 40 include image processing boards 22 and 32 and a camera 21 and 31, respectively, to detect magnetic position recognition and obstacles.

When the cleaning robot having the above configuration is instructed to clean through the remote control receiver 10, the controller 10 performs initialization and then operates the camera 21 of the magnetic position recognition unit 20 to shoot the current position. In addition, the image data generated through photographing is transmitted to the image processing board 22 to be signal processed. Then, the controller 60 analyzes its current position by analyzing the image data transmitted from the image processing board 22. Thereafter, the control unit 60 transmits a control signal to the motor driving units 41a and 4b of the motors 42a and 42b for the left and right wheels 43a and 43b of the driving unit 40 to move the body. Make sure At this time, the controller 60 operates the camera 31 of the obstacle detecting unit 30 and controls the driving unit 40 to receive image data processed by the image processing board 32 so as to respond to the obstacle. . When the cleaning robot is moved to the corresponding place, the control signal is output to the vacuum cleaner 50 so that the cleaning operation may be performed at the corresponding position, and the driving unit 40 may perform the cleaning operation along the set path. The control signal is output to rotate and move the body.

The cleaning robot operated as described above can avoid obstacles in front of each other by performing the obstacle grasping operation at each sampling cycle set during the movement, and can move to the required position accurately by performing the magnetic position recognition operation at each sampling cycle set. .

In addition, the cleaning robot uses a CCD (charge coupled device) camera to recognize the magnetic position as described above and to detect obstacles in the driving path. In this case, since the size of the captured image data is very large, the image data is separately processed. Processors for processing image data are generally used.

The first technical problem to be achieved by the present invention is to provide an area-based cleaner control method that can control the movement of the cleaner based on the cleaning area in consideration of the user's preference, indoor environment, ease of cleaning and the like.

The second technical problem to be achieved by the present invention is to provide an area-based cleaner control device to which the area-based cleaner control method is applied.

A third object of the present invention is to provide a recording medium that can be read by a computer system as a medium on which a program for executing the area-based cleaner control method in a computer system is recorded.

According to an embodiment of the present disclosure, an area-based cleaner control method may include: generating moving area information by checking a moving area of a cleaner according to a user manipulation; Calculating a statistical value for each moving area by statistically analyzing the moving area information when there is no user operation for a preset time; Adjusting an important region weight based on the moving area statistics; Determining priority of each area by applying the important area weights to the moving area statistics; Planning a movement route based on the priority; And moving the cleaner according to the planned movement path.

In addition, the area-based cleaner control apparatus according to an embodiment of the present invention includes a moving area storage unit for generating and storing moving area information by checking the moving area of the cleaner according to a user operation; An area analyzer configured to statistically analyze the moving area information to calculate statistical values for each moving area when the user operation is not performed for a preset time; An importance calculator for adjusting an important region weight based on the statistics of each moving region; A priority calculator configured to determine the priority of each area by applying the weight of the important area to the statistical values for each moving area; A route planning unit that plans a movement route based on the priority; And a motor controller for moving the cleaner according to the planned movement path.

According to the embodiments of the present invention, the movement of the cleaner may be controlled based on the cleaning area in consideration of the user's preferences, indoor environment, and ease of cleaning, without a difficult operation or a procedure for inputting preferences, and indoor environment and terrain information. Make it easy for the cleaner to rescue.

1 is a block diagram of a conventional cleaning robot.
2A is a block diagram of an area based cleaner control apparatus according to an exemplary embodiment.
2B is a block diagram of an area based cleaner control apparatus according to another exemplary embodiment.
3 is a diagram illustrating an example of a cleaner external appearance to which an area based cleaner control apparatus is applied according to another exemplary embodiment.
4 is a block diagram of a cleaner to which an area-based cleaner control apparatus is applied according to another exemplary embodiment.
5 is a flowchart illustrating an area based cleaner control method according to an exemplary embodiment.

Hereinafter, with reference to the drawings will be described a preferred embodiment of the present invention. However, embodiments of the present invention illustrated below may be modified in various other forms, and the scope of the present invention is not limited to the embodiments described below.

2A is a block diagram of an area based cleaner control apparatus according to an exemplary embodiment.

The moving area storage unit 210 generates and stores moving area information by identifying a moving area of the cleaner according to a user operation (operating a remote control of a user or inputting other buttons).

Here, the movement area information may not reflect the movement path. In this case, there is no problem in calculating the moving area information even if the user does not move the cleaner in the shortest distance to the area to be cleaned because the operation is immature. This is because, when generating the movement area information, a path unnecessarily moved by the user is ignored when the movement area is divided. For example, even when the user manipulates the cleaner to make a round trip through a certain path, the moving area information does not reflect the moving path, so that unnecessary manipulation of the user may be filtered out. Of course, high statistics may be calculated in the moving region including unnecessary round trip paths, but the statistics may be optimized through the subsequent step of adjusting the weight of the critical region.

If there is no user operation for a preset time, the area analyzer 220 statistically analyzes moving area information of the moving area storage unit 210 to calculate statistical values for each moving area. Here, the statistical analysis may be used, such as classical statistical techniques, Bayesian statistical techniques based on the frequency (Frequency). Classical statistical techniques use a Likelihood to estimate the population, assuming the parameters as numerical concepts. Classical statistics do not look at prior information, so if the probability is the same for any of n experiments, it is assumed that all n experiments are equal. Bayesian statistical techniques estimate the population postorior by putting the concept of prior information in the sample. The parameter is assumed to be a concept of probability variation. Since basic common sense (information) is taken into account, the parameters are estimated regardless of the experiment. Bayesian statistics show prior information, so even if the probability is the same for any n experiments, they are not considered equal. By making new observations, you have a new probability that improves the priorities you had for the parameters. The next time you make a new observation, you use the population estimates from the previous observations as preliminary information and get new probabilities through the new observation data. And by repeating this process, we continue to improve our knowledge of the parameters.

The importance calculator 230 adjusts the weights of the important areas based on the statistics for each moving area. For example, the importance calculator 230 may reduce the weight of the important region for the region where the number of cleaning of the cleaner is greater than the first threshold value. For example, the importance calculator 230 may reduce the weight of the important region for the region in which the ratio of the number of times of cleaning to the other regions is greater than the second threshold. The first threshold value and the second threshold value are values that can be arbitrarily determined according to the needs of those skilled in the art.

The priority calculator 240 determines the priority of each region by applying the weight of the important region to the statistical value for each movement region. The priority calculator 240 may divide the entire cleaning area according to the priority from the area that the cleaner needs to reach first or frequently to the area of the least importance.

The route planner 250 plans the movement route based on the priority of the priority calculator 240. In order to plan the movement path, a total-order planning technique or a partial-order planning technique may be used. The pre-order planning technique involves inserting new steps (eg, the cleaner's movement path or movement area) into the plan while sequentially achieving goals (eg, the cleaner's movement path or movement area) in a certain order. It is a technique of determining a linear order with existing steps (for example, a moving path or a moving area of a cleaner) every time. The partial order planning technique is a technique in which every step in a plan continues to transform the plan until all the conditions in the plan become true, depending on the order and binding conditions between them. Therefore, in the partial order planning technique, the space of the partial order plans can be searched to obtain a complete plan. Many subsequence planning techniques use causal links as a means to protect goals that have already been achieved and track which goals have been achieved by which steps or have not been achieved. In addition, a case-based planning technique may be used for the movement path planning. Case-based planning techniques reuse similar historical case plans to solve new planning problems. Unlike a generative planning system, case-based planning techniques do not have to repeat the planning process from start to finish each time, reducing planning effort and responding to real-time needs quickly. Case-based planning goes through the steps of case retrieval, case adaptation and reuse, and case storage, as in the usual case-based reasoning approach. Case searches can help you identify past case problems (for example, designing a travel route using weighted statistics for each travel area) and plans (for example, previously designed travel paths) that are most similar to the new planning problem you are trying to solve. Searching. Case adaptation and reuse are the steps used to modify the retrieved past case plans to suit new planning issues. Case storage is the step of storing a new plan problem and the resultant plan that have been generalized and then stored as a past case for future reuse.

If there is no user operation for a preset time, the motor controller 260 moves the cleaner according to the movement route planned by the route planning unit 250.

2B is a block diagram of an area based cleaner control apparatus according to another exemplary embodiment.

The moving area storage unit 210 checks the moving area of the cleaner according to the user's operation to generate and store moving area information.

If there is no user operation for a preset time, the area analyzer 220 statistically analyzes moving area information of the moving area storage unit 210 to calculate statistical values for each moving area.

The importance calculator 230 adjusts the weights of the important areas based on the statistics for each moving area. The importance calculator 230 adjusts the important region weights by reflecting the feedback information as well as the region-specific statistics of the region analyzer 220. That is, the weight of each region may be adjusted by receiving feedback after the movement of the cleaner. For example, if a wall exists in a certain area after moving the cleaner, or a threshold or a puddle of a certain height or more exists according to the moving path plan, if the corresponding area has a characteristic that is not easy to move, the weight of the important area Can be reflected in calculations / adjustments. For example, the importance calculator 230 may adjust the important region weights for each region in consideration of at least one of different floor materials or ease of cleaning of each moving region. For example, the importance calculator 230 may readjust the important region weights based on the degree to which the cleaner follows the planned movement path and whether the cleaner fails to move along the planned movement path.

In addition, the weight of the important region may be adjusted in consideration of various factors. For example, when the area analyzer 220 calculates an obstacle occurrence frequency for each moving area, the importance calculator 230 may adjust the important area weight so that the important area weight is inversely proportional to the obstacle occurrence frequency. That is, the weight of the important region may be reduced for the moving region that frequently encounters obstacles when the cleaner moves. This will help you avoid breakdowns and collisions with people.

Alternatively, the cleaner may be set to the missed mode or the occupancy mode according to whether the person is indoors. The importance calculator 230 adjusts the weight of the important region for the specific area according to whether the cleaner is set to the missed mode. It may be. For example, in the absence mode, the weight of the important region for the living room may be increased. On the contrary, in the occupancy mode, the weight of the area where the collision with the person in the past operation was small can be increased.

Alternatively, the importance calculator 230 may adjust the weights so that important areas vary for each time zone. For example, when information about an area requiring cleaning for each time zone is previously input to the cleaner, the cleaner may adjust the weight of the important area according to the current time based on the information. According to this, the cleaner operation according to the user's operation usual cleaner operation pattern, it is possible to prioritize the area that must be cleaned according to the time zone.

Alternatively, the importance calculator 230 may increase the weight of the corresponding area when there are many adjacent areas having a high weight. According to this, since a movement route having a short movement distance can be planned, the area that can be cleaned by the robot cleaner in one charge increases.

The priority calculator 240 determines the priority of each region by applying the weight of the important region to the statistical value for each movement region.

The route planner 250 plans the movement route based on the priority of the priority calculator 240.

If there is no user operation for a preset time, the motor controller 260 moves the cleaner according to the movement route planned by the route planning unit 250.

3 illustrates an example of an appearance of a cleaner 300 to which an area-based cleaner control device according to another embodiment of the present invention is applied.

4 is a block diagram of a cleaner 400 to which an area based cleaner control apparatus is applied according to another exemplary embodiment.

The moving area storage unit 210 checks the moving area of the cleaner 400 according to a user's operation to generate and store moving area information. The remote control receiver 401 receives information about a user's remote control operation and transmits the information to the moving area storage 210 to contribute to the moving area calculation. When the cleaner 400 moves, the distance measuring sensor 402 measures a moving distance, a direction, and the like of the cleaner 400, and transfers it to the moving area storage 210 to contribute to the moving area calculation. An infrared sensor, an ultrasonic sensor, a friction force measuring sensor, or the like may be used for the distance measuring sensor 402.

The GPS receiver 403 is connected to a GPS antenna (not shown) capable of receiving satellite signals. The GPS receiver 403 estimates a current position of the cleaner 400 using periodic satellite signals. The GPS receiver 403 transmits the estimated current position to the movement area storage 210 to contribute to the movement area calculation. The image image photographed by the digital camera 404 is an image photographing the surroundings when the cleaner 400 moves and contributes to the movement area storage unit 210 to calculate the movement area through the processing of the image processor 405. .

If there is no user operation for a preset time, the area analyzer 220 statistically analyzes moving area information of the moving area storage unit 210 to calculate statistical values for each moving area.

The importance calculator 230 adjusts the weights of the important areas based on the statistical values for the moving areas of the area analyzer 220. For example, the importance calculator 230 may reduce the weight of the important region for the region where the number of cleaning of the cleaner 400 is greater than the first threshold value. For example, the importance calculator 230 may reduce the weight of the important region for the region in which the ratio of the number of times of cleaning to the other regions is greater than the second threshold.

The importance calculator 230 adjusts the critical region weight by reflecting feedback information received from the image processor 405, the obstacle detecting sensor 406, and the fast-speed measuring sensor 407. An infrared sensor, an ultrasonic sensor, a friction force measuring sensor, or the like may be used for the obstacle detecting sensor 406 and the fast measuring sensor 407.

The images processed by the image processor 405 may be used by the importance calculator 230 to determine different floor materials and ease of cleaning of each moving area. The speed-related information of the cleaner 400 measured by the speed measuring sensor 407 may be used to estimate the slipperiness of the floor. By using this, the importance calculator 230 may determine the ease of cleaning for each region. The obstacle information detected by the obstacle detecting sensor 406 may be used by the importance calculator 230 to determine the ease of cleaning for each region. The importance calculation unit 230 adjusts the weight of the important region by reflecting the floor material and the ease of cleaning for each region.

The obstacle detecting sensor 406 allows the importance calculator 230 to determine whether the cleaner 300 has failed to follow the planned movement path. The speed related information of the speed of the cleaner 400 measured by the speed measuring sensor 407 is determined by the importance calculator 230 to determine the degree to which the cleaner 400 follows the planned movement path, whether or not the movement along the planned movement path has failed. To make it possible. The importance calculator 230 readjusts the critical region weights based on the degree of following the planned movement path and whether the movement has failed along the planned movement path.

The priority calculator 240 determines the priority of each region by applying the weight of the important region to the statistical value for each movement region.

The route planner 250 plans the movement route based on the priority of the priority calculator 240.

The motor controller 260 moves the cleaner 400 by operating the wheel motor 408 according to the movement route planned by the route planner 250 when there is no user operation for a preset time. The motor controller 260 may implement a different cleaning pattern for each region by operating the dust suction motor 409 according to the movement path planned by the path planning unit 250.

5 is a flowchart illustrating an area based cleaner control method according to an exemplary embodiment.

First, when there is a user operation on the cleaner (S510), the moving area of the cleaner according to the user operation is checked to generate moving area information (S520). In this process (S520), the control signal according to the user's operation, the actual moving distance ratio of the cleaner to the motor operation of the cleaner, the current position of the cleaner measured using the infrared sensor built in the cleaner, and the GPS antenna built into the cleaner The moving area information may be generated based on the measured current position of the cleaner.

Subsequently, when there is no user operation for a preset time (S530), the moving area information is statistically analyzed to calculate statistical values for each moving area (S540). Bayesian statistical techniques, classical statistical techniques based on frequency, etc. may be applied to the statistical analysis of this process (S540). On the other hand, when there is a user operation for a preset time, the moving area information is updated by checking the moving area of the cleaner according to the user operation (S520).

Next, the weight of the important area is adjusted based on the statistics for each moving area (S550). This process (S550) may include a process of reducing the weight of the important region for the region where the number of cleaning is greater than the first threshold value. This process (S550) may include a process of reducing the weight of the important region for the region in which the ratio of the number of times of cleaning to the other regions is greater than the second threshold value. This process (S550) may include adjusting a critical region weight for each region in consideration of at least one of different floor materials or easy cleaning of each moving region. In addition, the weight of the important region may be adjusted in consideration of various factors. For example, when the obstacle occurrence frequency is calculated for each moving region in the calculation of the statistical value for each moving region (S540), the important region weight may be adjusted such that the important region weight is inversely proportional to the occurrence frequency of the obstacle. That is, the weight of the important region may be reduced for the moving region that frequently encounters obstacles when the cleaner moves. This will help you avoid breakdowns and collisions with people.

Alternatively, the cleaner may be set to the missed mode or the occupancy mode according to whether a person is indoors, and the weight of the important region for a specific area may be adjusted according to whether the cleaner is set to the missed mode. For example, in the absence mode, the weight of the important region for the living room may be increased. On the contrary, in the occupancy mode, the weight of the area where the collision with the person in the past operation was small can be increased.

Alternatively, the weight may be adjusted so that important areas vary according to time zones. For example, when information about an area requiring cleaning for each time zone is previously input to the cleaner, the cleaner may adjust the weight of the important area according to the current time based on the information. According to this, the cleaner operation according to the user's operation usual cleaner operation pattern, it is possible to prioritize the area that must be cleaned according to the time zone.

Alternatively, when there are many adjacent areas having a high weight, the weight of the corresponding area may be increased. According to this, since a movement route having a short movement distance can be planned, the area that can be cleaned by the robot cleaner in one charge increases.

One or more of the above-described weight adjustment methods may be combined. When weight adjustment methods are applied in combination, weight calculation according to each weight adjustment method may be performed sequentially or simultaneously.

Subsequently, the priority of each region is determined by applying the important region weights to the statistics for each movement region (S560).

If the priority of each region is determined, the movement route is planned based on the priority (S570).

Finally, when the planning of the movement route is completed in whole or in part, the cleaner is moved according to the planned movement route (S580). According to another embodiment of the present disclosure, after this process (S580), the process of adjusting the weight of the important region may be performed based on at least one of the degree of the cleaner following the planned movement path or whether the cleaner fails to move along the planned movement path. .

The invention can be implemented via software. Preferably, an area-based cleaner control method according to embodiments of the present invention may be provided by recording a program for executing in a computer on a computer-readable recording medium. When implemented in software, the constituent means of the present invention are code segments that perform the necessary work. The program or code segments may be stored on a processor readable medium or transmitted by a computer data signal coupled with a carrier on a transmission medium or network.

Computer-readable recording media include all kinds of recording devices that store data that can be read by a computer system. Examples of computer-readable recording devices include ROM, RAM, CD-ROM, DVD ± ROM, DVD-RAM, magnetic tape, floppy disks, hard disks, optical data storage devices, and the like. The computer readable recording medium can also be distributed over network coupled computer devices so that the computer readable code is stored and executed in a distributed fashion.

Although the present invention has been described with reference to one embodiment shown in the drawings, this is merely exemplary, and it will be understood by those skilled in the art that various modifications and variations may be made therefrom. And, such modifications should be considered to be within the technical protection scope of the present invention. Therefore, the true technical protection scope of the present invention will be defined by the technical spirit of the appended claims.

Claims (19)

Identifying a moving area of the cleaner according to a user manipulation and generating moving area information;
Calculating a statistical value for each moving area by statistically analyzing the moving area information when there is no user operation for a preset time;
Adjusting an important region weight based on the moving area statistics;
Determining priority of each area by applying the important area weights to the moving area statistics;
Planning a movement route based on the priority; And
Moving the cleaner according to the planned movement path
Including, area-based cleaner control method. The method of claim 1,
Adjusting the critical region weights
And reducing the weight of the important region for the region where the number of cleaning is greater than the first threshold value. The method of claim 1,
Adjusting the critical region weights
And reducing the weight of the important region for the region in which the ratio of the number of times of cleaning to the other regions is greater than the second threshold value. The method of claim 1,
Adjusting the critical region weights
And adjusting an important region weight for each region in consideration of at least one of different floor materials or ease of cleaning of each moving region. The method of claim 1,
Adjusting the critical region weights
And adjusting the critical region weights such that the critical region weights are inversely proportional to the frequency of occurrence of obstacles in each moving region. The method of claim 1,
Adjusting the critical region weights
And adjusting an important region weight for a specific region according to whether the cleaner is set to the missed mode. The method of claim 1,
Adjusting the critical region weights
And adjusting the weight of the important region according to a current time based on information input in advance for the region requiring cleaning for each time zone. The method of claim 1,
The moving of the cleaner
And re-adjusting the important region weights based on at least one of the degree of the cleaner following the planned movement path or whether the cleaner fails to move along the planned movement path. . The method of claim 1,
Computing the statistics for each moving area
And applying any one of Bayesian statistical techniques or classical statistical techniques based on frequency to the statistical analysis. The method of claim 1,
Generating the moving area information
The control signal according to the user operation, the actual moving distance ratio of the cleaner to the motor operation of the cleaner, the current position of the cleaner measured using the infrared sensor built in the cleaner or via the GPS antenna built into the cleaner And generating the moving area information based on any one of the measured current positions of the cleaners. A computer-readable recording medium having recorded thereon a program for executing the method of any one of claims 1 to 10. A moving area storage unit which checks a moving area of the cleaner according to a user manipulation and generates and stores moving area information;
An area analyzer configured to statistically analyze the moving area information to calculate statistical values for each moving area when the user operation is not performed for a preset time;
An importance calculator for adjusting an important region weight based on the statistics of each moving region;
A priority calculator configured to determine the priority of each area by applying the weight of the important area to the statistical values for each moving area;
A route planning unit that plans a movement route based on the priority; And
A motor controller for moving the cleaner according to the planned movement path
Included, area-based cleaner control device. The method of claim 12,
The importance calculation unit
The area-based cleaner control device, characterized in that to reduce the weight of the important area for the area where the number of cleaning is greater than the first threshold value. The method of claim 12,
The importance calculation unit
The area-based cleaner control device, characterized in that to reduce the weight of the important area for the area in which the ratio of the number of cleaning to the other area is greater than the second threshold value. The method of claim 12,
The importance calculation unit
The area-based cleaner control device, characterized in that for adjusting the important region weight for each region in consideration of at least one of different floor material or ease of cleaning of each moving region. The method of claim 12,
The importance calculation unit
And adjusting the important region weight so that the important region weight is inversely proportional to the occurrence frequency of obstacles in each moving region. The method of claim 12,
The importance calculation unit
And adjusting an important region weight for a specific region according to whether the cleaner is set to the missed mode. The method of claim 12,
The importance calculation unit
And adjusting the weight of the important region according to the current time based on information input in advance for the region requiring cleaning for each time zone. The method of claim 12,
The importance calculation unit
And re-adjust the critical region weight based on at least one of the degree of the cleaner following the planned movement path or whether the cleaner fails to move along the planned movement path.

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