JP2003345438A - Mobile robot - Google Patents

Abstract

<P>PROBLEM TO BE SOLVED: To provide a mobile robot that modifies map information by itself without depending on a human being to modify the map information every time if a position occupied by the object is frequently changed. <P>SOLUTION: The mobile robot 1 keeps an interim map information for the deployment of objects, detects an inaccurate data within the interim map information due to the mobile robot movement (S4-Y), measures the object, the position of which corresponds to the inaccurate data, and modifies the foregoing interim map on the basis of the foregoing measurement. <P>COPYRIGHT: (C)2004,JPO

Description

DETAILED DESCRIPTION OF THE INVENTION

[0001]

BACKGROUND OF THE INVENTION 1. Field of the Invention The present invention relates to a mobile robot, and more particularly to a mobile robot capable of correcting map information of the mobile robot.

[0002]

2. Description of the Related Art There is known a mobile robot which moves by detecting its surrounding environment by various sensors provided by the user. Such a mobile robot has a function of detecting an obstacle with its own sensor, determining a target object (identifying a master), and the like. In addition, the mobile robot can move to a distant target while judging the movement route. When a mobile robot moves to a target, a mobile route may be determined from a map stored by the mobile robot and information that can be detected by its own sensor. If there is an obstacle on the once determined moving route, the robot moves to the target while correcting the moving route when the obstacle is detected.

[0003] In the above description, the map to be stored by the mobile robot is a map of a place where the mobile robot is used. For example, when the mobile robot is used in a general home or the like, a layout including furniture arrangement in the room is used. Must be stored in the mobile robot.

Here, the map stored in the mobile robot may be a map defined by a human in advance. Alternatively, it is conceivable that a map of the room is constructed by storing a place where the mobile robot actually moves in the room or the like and hits (is not able to go).

[0005] In the above, for example, in a general home, furniture that hardly moves, such as a bed or a wardrobe, can be used, but a CD case, a magazine tray, a color BOX, or the like whose installation position changes (changes pattern) relatively frequently, such as a case. However, there is a problem that a human has to re-input each time.

[0006] In the above, in order to complete the boundary of the range where the mobile robot cannot go on the map, it is necessary for the mobile robot to perform an unnatural and obstructive motion such as moving along the wall of the room or the like. there were. Recognition (detection) that the mobile robot could not actually move and could not go is based only on the information of the point (local place), so in order to determine the area (area) where the mobile robot can not go, the point Must be collected to form a contour.

It is desired that a mobile robot can correct its own map information in daily operations. If there is an object whose position changes relatively frequently, it is desired that the mobile robot can correct the map information by itself without the human having to correct the map information every time the position changes. It is desired that a mobile robot can efficiently correct map information by itself. It is desired that accurate map information can be obtained without affecting the behavior of the mobile robot according to the command of the human (master).

[0008]

SUMMARY OF THE INVENTION It is an object of the present invention to provide a mobile robot which can correct its own map information in a daily operation. Another object of the present invention is to provide a mobile robot in which, when there is an object whose position changes relatively frequently, the mobile robot can correct the map information by itself without a human correcting the map information every time the position changes. It is in. Still another object of the present invention is to provide a mobile robot that can efficiently correct map information by itself. Still another object of the present invention is to provide a mobile robot capable of obtaining accurate map information without affecting the behavior of the mobile robot according to a command of a human (master).

[0009]

Means for solving the problem will be described below using the numbers and symbols used in the embodiments of the present invention. These numbers and symbols are added to clarify the correspondence between the description of [Claims] and the description of [Embodiments of the Invention]. It should not be used to interpret the technical scope of the described invention.

A mobile robot (1) according to the present invention is a mobile robot (1) having temporary map information relating to an arrangement of an object, and the mobile robot (1) is moved by the mobile robot (1). When detecting that there is an incorrect portion in the provisional map information (S4-Y), the object corresponding to the incorrect portion is measured, and the provisional map information is measured based on the measurement result. To correct.

[0011] In the mobile robot (1) of the present invention, the temporary map information stores at least one of a standard size and an arrangement location of the standard object that can be placed in a movement range of the mobile robot (1). It is created based on the information of the database (91).

[0012] In the mobile robot (1) of the present invention, information of the object whose position is fixed for a long term is registered in the temporary map information.

In the mobile robot (1) of the present invention, when the mobile robot (1) corrects the temporary map information, the size of the object included in the temporary map information is determined based on the measurement result. And at least one of the position information is corrected.

[0014] In the mobile robot (1) of the present invention, the temporary map information includes information indicating a high possibility that the object included in the temporary map information matches an actual situation. Have been.

[0015] In the mobile robot (1) of the present invention, the possibility of the corrected object in the temporary map information is set low in the information.

[0016] In the mobile robot (1) of the present invention, the object registered in the temporary map information whose position is fixed for a long time has a high possibility of being set in the information. You.

[0017] In the mobile robot (1) of the present invention, the mobile robot (1) measures the object having a low possibility, and based on the result of the measurement, determines the height of the possibility. Modify the temporary map information for the low object.

In the mobile robot (1) of the present invention, when the mobile robot (1) does not receive a command for a predetermined time (S31-Y), it measures the object having a low possibility. Then, based on the result of the measurement, the temporary map information relating to the object having a low possibility is corrected.

The robot requests only standard furniture size that can be placed in the home or the position of a bed or the like that hardly moves as prior information. This eliminates the need for a human to input small furniture that is frequently moved each time.

The robot has knowledge of the size of standard furniture that can be placed in the home, and if it encounters (cannot go) in a trial and error movement, there is standard size furniture at that location. Is created and placed on the MAP. This eliminates the need for unnatural movements such as transmission movements for extracting furniture boundaries as described above.

In the course of trial and error, when a collision that is inconsistent with the size of the furniture that is supposed to be placed (there was no furniture edge where it should have been, or it should have been missing, etc.), the assumption was made. Make corrections. The correction of the assumption is (a)
Furniture position correction, (b) furniture size correction, and (c) self-position correction.

There are various ways to adopt the above (a), (b), and (c), but basically, it is performed in association with the external recognition ability possessed by the mobile robot. That is,
If the mobile robot has a visual sensor and the size of the target can be estimated, it is first checked whether the knowledge of the size of the mobile robot should be corrected based on the estimation result.
However, with a visual sensor, it is difficult to distinguish a shadow of an object from the object itself, and erroneous detection is likely to occur. Therefore, there is a mark on the ceiling etc. for the mobile robot to confirm its own position (a mark for linking the position of the room to its own position), etc., and if it can be used (for example, a mesh on the ceiling of the room, If the mobile robot collides with something while moving, it will be divided into a plurality of sections with a serial number assigned to it. To detect the position), the self-position is checked, and the like. If the furniture has an ID tag containing information (size, type, weight, etc.), such as a barcode, the information on the furniture that the mobile robot collided with the information on the most inconsistent MAP of its own MAP is It is possible to evaluate something.

[0023]

Embodiments of a mobile robot system according to the present invention will be described below with reference to the accompanying drawings. A technique related to the present embodiment is disclosed in Japanese Patent Application No. 2002-101319 by the present inventor.

FIG. 6 shows the configuration of the mobile robot system according to the present embodiment. The mobile robot system according to the present embodiment can be used, for example, as living support or nursing care for a general household. The mobile robot system according to the present embodiment includes a mobile robot 1 and a fixed sensor 2.

The mobile robot 1 has a sensor group 10 for judging a situation around the mobile robot 1, an expression mechanism 20, an operation mechanism 30 for moving or grasping an object, and an input information processing mechanism 4.
0, a behavior information processing mechanism 41, and a communication information processing mechanism 42.

The sensor group 10 is a sensor for judging a situation around the user, and includes a camera 11, an ultrasonic distance meter 12,
It is represented by a voice detector, an infrared detector, a weight detector attached to an arm or the like. The sensor group 10 transmits information detected by the sensor to the input information processing mechanism 40.

An expression mechanism 20 is a mechanism for causing the fixed sensor 2 to detect its own position or for transmitting its own position and information to the master. 22 mag. Specifically, this is a case where the mobile robot 1 notifies the fixed sensor 2 of its own position by causing the LED 21 at the top of the head to emit light. Further, as the expression mechanism 20, an expression mechanism based on movement of an arm or a part of a mobile robot can be used, such as display of characters and figures on a liquid crystal screen. The expression mechanism 20 performs an expression action according to a command from the action information processing mechanism 41.

The operation mechanism 30 is a means for the mobile robot to move, a means for grasping or holding an object, and is represented by an arm 31, a leg 32, a wheel, a caterpillar and the like. Furthermore, an operation for changing the direction of the sensor group 10 (for example, an operation of turning the neck to change the range where the camera 11 captures an image) may be performed. The operation mechanism 30 performs an operation according to a command from the behavior information processing mechanism 41.

The input information processing mechanism 40 is a device for performing information processing, and is represented by a computer. The input information processing mechanism 40 receives and processes information from the sensor group 10 and the fixed sensor 2, and transmits the information to the behavior information processing mechanism 41. More specifically, the personal identification of a person (judgment of who) is detected from the image of the camera 11, the presence / absence and position of an obstacle, and the distance and position of the obstacle from the information of the ultrasonic rangefinder 12. Measurement, the detection of the person being called from the information of the voice sensor, the determination of the voice of the user, and the like.

The behavior information processing mechanism 41 is a device for performing information processing, and is represented by a computer. The behavior information processing mechanism 41 determines an operation plan based on information from the input information processing mechanism 40 and the fixed sensor 2, and transmits an operation command to the operation mechanism 30. Further, the behavior information processing mechanism 41 stores a map of a range in which the mobile robot 1 moves, and grasps its own current position while updating its own position data from the data of the movement result. Further, as described later with reference to FIGS. 1 to 4, the behavior information processing mechanism 41 can correct the map data (information) by itself. Further, information from the fixed sensor 2 can be obtained via the communication information processing mechanism 42, and the stored map data can be updated. Further, when any information is needed, a command is issued to the sensor group 10 via the input information processing mechanism 40 or to the fixed sensor 2 via the communication information processing mechanism 42 so as to obtain necessary information. Can be.

The communication information processing mechanism 42 is a communication device for communicating with the fixed sensor 2. The communication information processing mechanism 42 receives, from the fixed sensor 2, information about the situation around the subject, the information on the moving route, the position of the master, the status of the master, and the like. Mechanism 41
Send to In addition, necessary information is transmitted to and received from the fixed sensor 2.

Here, the map stored in the behavior information processing mechanism 41 will be described. As shown in FIG. 5, the mobile robot 1 has the above-mentioned map data inside the room in which the mobile robot 1 moves, for example, as data showing a plan view.
In the map of FIG. 5, reference numeral 81 indicates the room, circles indicate the position of the mobile robot 1, and squares 82 and 83 indicate the arrangement and size of furniture, respectively.

The above map is appropriately modified by learning by the mobile robot 1. Hereinafter, the correction of the map information will be described with reference to FIG. FIG. 1 shows a function flow in a normal state. Here, the normal time is
As described later with reference to FIG. 4, this means a time period excluding a case where there is no command for the mobile robot 1 and the mobile robot 1 performs active learning without a command.

As shown in step S1, when the above-mentioned map stored in the behavior information processing mechanism 41 is created, the MAP database 91 is created in advance. MAP
The database 91 stores general information on the size and location of standard furniture that can be placed at home (by windows, by walls, in the center of rooms, etc.). Also, M
The AP database 91 stores information specific to the home (the target where the mobile robot 1 is introduced), such as the size of furniture in the home where the mobile robot 1 is introduced. The MAP database 91 is held by the mobile robot 1.

Next, while using the MAP database 91, the position of furniture (such as a bed) which is fixed and is not moved for a long time among furniture in the home where the mobile robot 1 is introduced. Is registered in the action information processing mechanism 41 (step S2).

More specifically, the above-mentioned general information in the MAP database 91 is used as follows when creating the preliminary map in step S2. In other words, the mobile robot 1 has the size and location of standard furniture that can be placed in a general household as knowledge in the MAP database 91. And when creating the pre-map,
The mobile robot 1 performs a trial and error movement in a room or the like for initial setting, and when it hits (fails to go), there is a standard size furniture stored in the MAP database 91 at that location. And put it on the map in advance. This eliminates the need for unnatural movements such as transmission movements for extracting furniture boundaries as described above. This preliminary map is a temporary map, and the mobile robot 1
Is updated to highly accurate map information by repeating learning as described below.

After the advance map is created, step S
As shown in FIG. 3, the mobile robot 1 performs a moving operation in the room or the like. Next, as shown in step S4, the mobile robot 1 uses the map (here, the above-described pre-map) registered in the behavior information processing mechanism 41 of the mobile robot 1 in the process of the mobile operation or the result of the mobile operation. ) Is determined (inconsistency of information). If it is determined that there is no contradiction, the process returns to step S3, and the moving operation is repeated.

As a result of the determination in step S4, when it is determined that the mobile robot 1 has a contradiction (step S4-Y).
In step S5, it is determined whether the mobile robot 1 has collided with any object. Here, collision means
This includes not only that the mobile robot 1 collides with an object while moving, but also that an object is detected within the range of a distance sensor that measures the presence or absence of a surrounding object.

If it is determined in step S5 that there is a collision (step S5-Y), the process proceeds to step S6. Here, the case where it is determined that there is a collision is a case where a collision occurs in a place where there should be nothing according to the latest map registered in the mobile robot 1 (here, the above-mentioned preliminary map). is there.

In step S6, the mobile robot 1 collides with the collision position (location in the room) and the collision position / direction information indicating the direction from which the mobile robot 1 collided with the object at the time of the collision. Is recorded inside the mobile robot 1. Next, the process proceeds to step S7.

In step S7, the mobile robot 1 checks the current map (the latest map), and checks in step S7.
The furniture causing the collision determined as having the collision in step 5 (furniture that seems to be wrong: furniture causing the collision) is selected. Next, the process proceeds to step S8.

In step S8, the mobile robot 1 measures the furniture causing the collision and its surroundings. In step S8, the size and the position (including the direction) of the furniture causing the collision are described.
And the surrounding situation is measured. The mobile robot 1 always knows its position on the current map (the latest map).

Next, the mobile robot 1 proceeds to step S9 and corrects the latest map and the certainty factor based on the measurement result of step S8. The contents of step S9 will be described later with reference to FIG.

On the other hand, the mobile robot 1
If it is determined that there is no collision as a result of the determination in step 5, the current map (the latest map described above) is checked, and furniture that should be there (furniture that seems to be wrong: furniture that causes inconsistency) is specified (step). S10). Next, the process proceeds to step S11. Here, when it is determined that there is no collision, according to the latest map registered in the mobile robot 1 (here, the above-mentioned preliminary map), there is no furniture (edge) in a place where it should be. is there.

In step S11, the mobile robot 1 measures the inconsistency furniture and its surroundings. In this measurement, the conflict cause furniture is included in the current map (the latest map), so the position (including the direction) of the conflict cause furniture on the map, the size of the conflict cause furniture, and The position (including the direction) and surrounding conditions are measured. The mobile robot 1 always knows its position on the current map (the latest map).

Next, the mobile robot 1 proceeds to step S9, and based on the measurement result of step S11, corrects the latest map and corrects the certainty factor. After step S9, the process returns to step S3. The content of step S9 will be described next with reference to FIG.

As shown in step S21 in FIG. 2, the mobile robot 1 determines the contradiction between the current map (the latest map) and the actual situation based on the measurement results in steps S8 and S11 in FIG. To understand.

Next, as shown in step S22, the mobile robot 1 compares the current map (the latest map) with the actual map based on the result of the step S21 (the measurement results in steps S8 and S11 in FIG. 1). The situation (the furniture causing the collision or the furniture causing the inconsistency) determines whether there is any inconsistency in the furniture size (step S22).

If it is determined in step S22 that the furniture sizes are inconsistent (step S22-
In Y), the mobile robot 1 corrects the furniture size corresponding to the current map (the latest map) (step S2).
3). Next, the process proceeds to step S24. In step S24, the degree of certainty of the furniture arrangement is corrected.

The modification of the furniture size (step S23) and the modification of the degree of certainty of the furniture arrangement (step S24) will be described with reference to FIG. FIG.
23 shows the modification of the furniture size of 23 and the modification of the degree of certainty accompanying it.

FIGS. 3A and 3B show the map data (the map information) of the mobile robot 1. The data in the figure corresponds to a plan view of a room where the mobile robot 1 is located. In the figure, furniture 92, 93, 9
The directions of hatching applied to 4a, 94b, and 95 indicate the above-mentioned certainty factors.

FIGS. 3A and 3B show the mobile robot 1.
Is one of the beds 9
Data regarding the arrangement (size, position, and orientation) of 2, 93 has a possibility (convergence) of 4 that matches the actual situation.
It indicates that it is recognized as the highest among the stages. The furniture indicated by reference numeral 95 has the second lowest certainty factor among the above four levels.

As in step S2, the positions of the beds 92 and 93 are registered in the pre-map as long as the installation positions are fixed and will not be moved in the long term.
In response to this, the mobile robot 1 has a bed 92,
It is recognized that the degree of certainty of the map information regarding 93 is high.

Here, furniture (here, beds 92 and 93) recognized as having a high degree of certainty by the mobile robot 1 is used as a reference position when the mobile robot 1 performs the measurement in step S8 or S11. be able to.

FIG. 3A shows a case where it is determined that there is a collision as a result of the moving operation of the mobile robot 1 indicated by the arrow Y1 as a result of the determination in step S5. In that case, as shown in step S7, the mobile robot 1 identifies the furniture indicated by reference numeral 94a as the collision-causing furniture as a result of checking the current map, and determines the furniture 94a in step S8 with respect to the collision-causing furniture 94a. Perform measurement. After that, FIG. 3B shows the result of the correction of the map and the certainty factor of step S9 and FIG.

FIG. 3B shows that the mobile robot 1 performs each step in the order shown in FIG.
The case where it is determined that the size of the furniture 94a is inconsistent is shown. That is, in FIG. 3B, the furniture 9 of FIG.
It is determined that the size of the furniture 4a is smaller than the actual size (because a collision has occurred if the operation is performed according to the data of FIG. 3A), and the size of the furniture is corrected to be increased as indicated by reference numeral 94b. Is shown (step S23). In the corrected map information, the direction in which the size of the furniture is increased is the direction (the left direction in FIG. 3B) corresponding to the position and the direction of the collision recorded in step S6. In addition, in the corrected map information, how much the size of the furniture is increased depends on MA.
It is obtained based on the information on the standard size stored in the P database 91 or the size of the household furniture into which the mobile robot 1 is introduced.

In step S24, FIG.
As shown in FIG. 3A and FIG. 3B, the reliability of the arrangement of the furniture whose furniture size has been corrected is reduced (from the second to the lowest in the four stages). Immediately after the furniture size is corrected, as described above, the correction width of the furniture size (how much to increase) is determined by the MAP database 9.
1 and the cause of the collision (step S5) is truly the furniture 94b (94a).
Is not clear (for example, new furniture may have been introduced or furniture may have been remodeled), so the confidence is demoted. Step S2
After step 4, the process proceeds to step S25.

After that, the mobile robot 1 moves the furniture 9
4b is moved one or more times (step S4).
3) If there is no inconsistency with the current map (the latest map) (step S4-N), the certainty factor of the furniture 94b is upgraded (from the current lowest order to the second lowest). Can be.

On the other hand, as a result of the determination in step S22,
If it is determined that there is no inconsistency in the furniture size (step S
22-N), the process proceeds to step S25. Step S2
In step 5, based on the result of step S21 (the measurement results of steps S8 and S11 in FIG. 1), the mobile robot 1 compares the current map (the latest map) with the actual situation (the furniture causing the collision or the furniture causing the contradiction). ) Determines whether or not there is a contradiction in the position of the furniture.

As a result of the determination in step S25, when it is determined that there is a contradiction in the position of the furniture (step S25-
In Y), the mobile robot 1 corrects the position of the corresponding furniture on the current map (the latest map) (step S2).
6). The correction of the furniture position in step S26 is similar to the correction of the furniture size in step S23, and the standard furniture stored in the MAP database 91 or its mobile robot 1
Is performed based on data such as the size and location of furniture installed in the home where the is introduced. Next, the process proceeds to step S27 to correct the certainty factor of the furniture arrangement. In step S27, the certainty factor of the furniture whose position has been corrected is reduced.

On the other hand, if it is determined in step S25 that there is no inconsistency in the furniture position (step S25).
In step (-N), the process proceeds to step S28. In step S28, the mobile robot 1 determines, based on the result of step S21 (the measurement results of steps S8 and S11 in FIG. 1).
The current map (the latest map described above) and the actual situation (furniture that caused collision or furniture that caused inconsistency) are the same
It is determined whether or not there is a contradiction in the position of.

As a result of the determination in step S28, when it is determined that there is a contradiction in its own position (step S28-
In Y), the mobile robot 1 corrects its position on the current map (the latest map) (step S29). Next, the process proceeds to step S30. In step S30, it is found that the reason of step 21 is inconsistency of the self-position and there is no reason for the furniture, so that the degree of certainty of the furniture is increased.

Next, a functional flow at the time of active learning will be described with reference to FIG.

First, as shown in step S31, the mobile robot 1 determines whether there is no command (free time) for a predetermined time. As a result of the determination, when it is determined that there is no command for a predetermined time (step S31-
In N), the active learning shown in FIG. 4 is not performed, and only the normal function flow of FIG. 1 is performed.

On the other hand, if the result of determination in step S31 is that there is no command for a predetermined time (step S31-Y), the flow proceeds to step S32. In step S32, furniture with a low degree of certainty is searched for and extracted from the current map (the latest map). Next, the process proceeds to step S33.

In step S33, the mobile robot 1
Move around the furniture extracted in step S32. Next, the process proceeds to step S34.

In step S34, a current map (the latest map) is corrected for furniture having a small degree of certainty based on the same functional flow (steps S3 to S11) as in the normal case shown in FIG. . After that, as a result of the mobile robot 1 moving the position of the furniture having a low degree of certainty once or more times (step S3), there is no inconsistency with the current map (the latest map) (step S4). −
In N), the certainty factor of the furniture having the small certainty factor can be upgraded.

In the present embodiment, in order for the mobile robot 1 to recognize its own position, the following measures are taken. On the ceiling or the like, a mark (mark for linking the position of the room and the position of the room) with which the mobile robot 1 confirms its position is provided. That is, for example, on the ceiling of a room, there are provided a plurality of sections which are divided in a mesh shape and are assigned serial numbers. When the mobile robot 1 collides with something while moving, the mobile robot 1 detects the collision position based on the serial number of the section of the ceiling corresponding directly above the place.

If the furniture has an ID tag including information (size, type, weight, etc.), such as a bar code, when the mobile robot 1 performs step S7 or S10, the furniture is displayed. By evaluating what is the most inconsistent information between the ID information and the current map (the latest map) of the mobile robot 1, it is possible to identify the furniture causing the collision or the furniture causing the inconsistency.

When recording the collision position with the furniture in step S6, the mobile robot 1 can detect the collision position with the furniture as a distance from a wall (an object whose position is fixed). .

As described above, the mobile robot 1 can learn the arrangement of furniture after being placed in the home, and can correct (update) map information. The learning is
(Semi) automated. Thereby, it is possible to perform the movement avoiding the obstacle.

The fixed sensor 2 is installed to obtain information on the space in charge. It is preferable that the fixed sensor 2 is installed at a position where the fixed sensor 2 can grasp the widest possible range of the assigned space. Also, the sensor group 1 of the mobile robot 1
It is preferable that information can be detected from a viewpoint different from zero. Specifically, the fixed sensor 2 may be installed on a ceiling or the like of a room in charge. When the mobile robot 1 moves in a plurality of spaces, a fixed sensor 2 may be installed for each space. Specifically, the fixed sensor 2 may be installed in each of a plurality of rooms. Also, even if it is a single space, if the whole space cannot be covered by one fixed sensor 2 or if it is desired to improve the accuracy of the information to be detected, the fixed sensor 2 2
For example, a plurality of fixed sensors 2 may be installed.

The fixed sensor 2 includes a sensor group 50 for detecting information on the space in which the fixed sensor 2 is in charge, an expression mechanism 60, an input information processing mechanism 70, a behavior information processing mechanism 71, and a communication information processing mechanism 72.

The sensor group 50 is a sensor for detecting information on the space where the fixed sensor 2 is installed, and is represented by a fish-eye camera 51, an ultrasonic distance meter 52, a voice detector, an infrared detector, and the like. You. The sensor group 50 transmits information detected by the sensor to the input information processing mechanism 70.

The expression mechanism 60 is a mechanism for teaching the position of the fixed sensor 2 to the mobile robot 1 and for guiding the mobile robot 1 by light or voice, and is typically a light-emitting device represented by an LED 61, a voice transmitter, or the like. Is done. The expression mechanism 60 performs an expression action according to a command from the action information processing mechanism 71. In addition, the expression mechanism 60 can inform the master of the status of receiving the command. Specifically, when the mobile robot 1 is at a remote location, the fixed sensor 2 recognizes the command of the master, the LED 61 of the fixed sensor 2 is turned on, and the command can be transmitted to the mobile robot 1. , The LED 61 turns off. In addition, when any abnormality occurs in the mobile robot 1, the fixed sensor 2 can transmit information to the master such that the LED 61 blinks.

The input information processing mechanism 70 is a device for performing information processing, and is represented by a computer. The input information processing mechanism 70 receives and processes information from the sensor 50 and the mobile robot 1, and transmits the information to the behavior information processing mechanism 71 or to the mobile robot 1 via the communication information processing mechanism 72. Specifically, the input information processing mechanism 70 measures the presence / absence and position of a target or an obstacle from the image of the camera 51 or the information of the ultrasonic rangefinder 52, or detects whether the mobile robot 1 , Or judge who's calling. Further, when the present system is monitoring a specific target, the input information processing mechanism 70 may have a function of determining whether or not there is an abnormality in the target.

The behavior information processing mechanism 71 is a device for performing information processing, and is represented by a computer. The behavior information processing mechanism 71 includes the input information processing mechanism 70 and the mobile robot 1
Of the mobile robot 1 is determined based on the information from the mobile robot 1. Further, the behavior information processing mechanism 71 stores a map of a space in charge, and can update information such as the position of an obstacle on the map from information of the input information processing mechanism 70.
Further, the behavior information processing mechanism 71 is
And mobile robot 1 based on information from mobile robot 1
And the location of the master on the map. In addition, the fixed sensor 2 receives the information of the map of the mobile robot 1 from the communication information processing mechanism 42 via the communication information processing mechanism 72 as described with reference to FIGS. 71. Thereby, the latest map is shared by the mobile robot 1 and the fixed sensor 2. Further, the behavior information processing mechanism 71 gives a necessary instruction to the expression mechanism 60 when notifying the position of the fixed sensor 2 to the mobile robot 1 or guiding the mobile robot 1.

The communication information processing mechanism 72 is a mobile robot 1
A communication device that communicates with The communication information processing mechanism 72
The mobile robot 1 receives an action plan, information around the mobile robot 1, and an action plan, and transmits them to the input information processing mechanism 70 and the behavior information processing mechanism 71. In addition, necessary information is transmitted to and received from the mobile robot 1.

Next, referring to FIG.
Is used in the room 4. The fixed sensor 2 is installed on the ceiling of the room 4 to detect global information without blind spots in the room 4. Fixed sensor 2
Can detect an obstacle when the mobile robot 1 moves in the room 4 and a position of a target 3 which is a destination of the movement.

The case where the mobile robot 1 enters the room 4 from the door 7 and moves to the target 3 will be described. The mobile robot 1 stores a map of the room 4. First, the map stored by the mobile robot 1 includes the size of the room 4,
Known obstacles 5-1 and 5-2 are included, but target 3
And the positions of the movable obstacles 6-1 to 6-3 which are movable are not included. However, as described above, by performing the operations shown in FIGS. 1 to 4, the mobile robot 1 has map information corrected so as to include information on the positions of the unknown obstacles 6-1 to 3. Can be.

When there is no fixed sensor 2, the mobile robot 1
Is voice (voice of master) by voice sensor of sensor group 10
Is detected by the input information processing mechanism 40, and the camera 11
The target 3 is searched for by the sensor group 10. However, in this case, since the view to the target is blocked by the known obstacle 5-1, the target cannot be detected by the camera 11. Therefore, the mobile robot moves while judging the direction in which the sound is emitted by the voice sensor and avoiding the known obstacle 5-1 and the unknown obstacle 6-1 detected by its own sensor. However, unknown obstacles 6-2 and 6-3 that could not be detected because the visibility was blocked by the known obstacle 5-1 may become obstacles to movement. In such a case, the mobile robot 1
Alone cannot reliably determine a better travel route.

The mobile robot 1 wirelessly communicates with the fixed sensor 2 to obtain information on the room 4. The fixed sensor 2 is
Gather information about room 4. The fixed sensor 2 detects the position of the target 3, the positions 5-1 and 5-2 of the known obstacles, the positions 6-1 to 3 of the unknown obstacles, and one position of the mobile robot and transmits them to the mobile robot 1. I do. Before starting the movement, the mobile robot 1 updates the stored map of the room 4 based on the information of the fixed sensor 2 and determines the movement route from the latest map. The mobile robot 1 detects obstacles and the like that cannot be detected by the fixed sensor 2 (if there is a shadow of the object, it is difficult to distinguish the shadow from the object itself).
The user starts moving along the movement path while checking the surroundings with the sensor group 10. As described above, the mobile robot 1
The operation corresponding to FIGS. 1 to 4 is performed to correct the map information. If necessary, the fixed sensor 2 and the mobile robot 1 communicate with each other, and change information on the position of the obstacle or the position information of the mobile robot 1 is corrected.

By using the fixed sensor 2, the mobile robot 1 can avoid selecting an incorrect route. In addition, the mobile robot 1 can use global information and information approached by using information from the fixed sensor 2 and its own sensor group 10, and detect highly accurate obstacles and targets 3. Can be.

As described above, since the mobile robot 1 automatically learns the arrangement of furniture in a room (semi-), even if there is an unknown furniture (obstacle), the mobile robot 1 creates a map reflecting the furniture. Can be modified.

In the above description, the mobile robot 1
Is used together with the fixed sensor 2, but as shown in FIGS. 1 to 5, the correction of the map information and the correction of the certainty factor can be independently performed by the mobile robot 1.

[0086]

According to the mobile robot of the present invention, when there is an object whose position changes relatively frequently, each time the position changes, the mobile robot corrects the map information by itself without the human having to correct the map information. Can be.

[Brief description of the drawings]

FIG. 1 is a flowchart showing a normal function flow when a mobile robot of one embodiment of the present invention updates map information.

FIG. 2 is a flowchart illustrating another function flow in a normal state when the mobile robot according to the embodiment of the present invention updates map information.

FIG. 3A is a plan view illustrating map information before correction when the mobile robot according to the embodiment of the present invention corrects a furniture size in the map information, and FIG. FIG. 4 is a plan view showing map information corresponding to the corrected state in FIG.

FIG. 4 is a flowchart showing a functional flow at the time of active learning when the mobile robot of the embodiment of the present invention updates map information.

FIG. 5 is a schematic diagram schematically showing a state in which the mobile robot according to the embodiment of the present invention has map information.

FIG. 6 is a schematic diagram illustrating a configuration of a mobile robot system according to an embodiment of the present invention.

FIG. 7 is a schematic diagram showing a situation in which the mobile robot system according to the embodiment of the present invention is used.

[Explanation of symbols]

1 Mobile robot 2 Fixed sensor 3 goals, destinations, master 4 rooms (space) 5-1-3 Known obstacles 6-1-3 unknown obstacle 7 door 10 (Robot) sensors 11 (Robot) Camera 12 (Robot) Ultrasonic Rangefinder 20 Expression mechanism (of robot) 21 (Robot) LED 22 (Robot) Voice utterance 30 Operating mechanism 31 arm 32 legs 40 (Robot) input information processing mechanism 41 (robot) behavior information processing mechanism 42 Communication information processing mechanism (of robot) 50 sensors (of fixed sensors) 51 (fixed sensor) camera 52 (Fixed Sensor) Ultrasonic Rangefinder 60 Expression Mechanism (of Fixed Sensor) 61 LED (of fixed sensor) 70 (fixed sensor) input information processing mechanism 71 Behavior information processing mechanism (of fixed sensor) 72 Communication information processing mechanism (of fixed sensor) 91 MAP database

   ────────────────────────────────────────────────── ─── Continuation of front page    F term (reference) 3C007 CS08 KS12 KS36 KT01 KV11                       KV18 KX02 LW12 MT08 WB21                 5H301 AA02 AA10 CC03 CC06 CC10                       DD07 FF08 FF13 GG03 GG09                       GG10 GG19 LL01 LL08 LL11                       LL14 MM09 QQ06

Claims (9)

[Claims] 1. A mobile robot having temporary map information relating to an arrangement of an object, wherein the mobile robot detects that there is an inaccurate part in the temporary map information due to the movement of the mobile robot. Measuring the object corresponding to the incorrect portion;
A mobile robot that corrects the temporary map information based on a result of the measurement. 2. The mobile robot according to claim 1, wherein the temporary map information is stored in a database in which at least one of a standard size and an arrangement location of the standard object that can be placed in a movement range of the mobile robot is stored. Mobile robot created based on information. 3. The mobile robot according to claim 1, wherein information on the object whose position is fixed for a long time is registered in the temporary map information. 4. The mobile robot according to claim 1, wherein the mobile robot corrects the temporary map information based on a result of the measurement when correcting the temporary map information. A mobile robot that corrects information on at least one of a size and a position of the included object. 5. The mobile robot according to claim 1, wherein the object included in the temporary map information matches an actual situation in the temporary map information. A mobile robot that contains information indicating the height of sex. 6. The mobile robot according to claim 5, wherein the height of the possibility of the corrected object in the temporary map information is set low in the information. 7. The mobile robot according to claim 5, wherein the object registered in the tentative map information and whose position is fixed for a long time is higher in the information. Mobile robot that is set high. 8. The mobile robot according to claim 5, wherein the mobile robot measures the object having the low possibility, and based on a result of the measurement, measures the height of the possibility. A mobile robot that corrects the temporary map information regarding the object having a low level. 9. The mobile robot according to claim 8, wherein the mobile robot measures the object having a low possibility when the command is not received for a predetermined time, and outputs the result of the measurement. A mobile robot that corrects the temporary map information about the object having a low possibility based on the temporary map information.