WO2019049655A1 - Autonomous travel-type cleaner and method for updating cumulative floor area probability - Google Patents

Abstract

An autonomous travel-type cleaner provided with: a map generation unit (181) for generating a new map wherein the position of a reference member is used as a reference position; and a floor area probability update unit (184) for using the floor area probability of the new map to update, for each of element areas at positions that match, a cumulative floor area probability of a cumulative map. The floor area probability update unit (184) adds one to a cumulative map number which indicates the number of maps used so far for updates in each of the element areas, subtracts the cumulative floor area probability from the floor area probability, divides the difference therebetween by the cumulative map number obtained through the addition, adds to this quotient the cumulative floor area probability, and updates the resulting sum as the new cumulative floor area probability. On the above basis, provided is the autonomous travel-type cleaner wherein it is possible to update to a new map that accommodates changes in the environment of the cleaning area.

Description

Autonomous traveling vacuum cleaner, and cumulative floor probability update method

The present invention relates to an autonomously traveling vacuum cleaner that generates a map, which allows the user to indicate an area cleaned autonomously and cleaned, or allows the user to specify an area to be cleaned, and an accumulated floor probability updating method.

In recent years, based on the self-position estimation result under cleaning, a map of a running area is created, and based on the map, an autonomous running cleaner capable of specifying an area to be cleaned next time is disclosed (for example, patent documents 1).

First, while performing cleaning, the autonomous traveling vacuum cleaner disclosed in Patent Document 1 obtains information from various sensors provided in the vacuum cleaner, such as odometry information, a camera, and a distance measurement sensor. Next, the autonomous vacuum cleaner estimates its own relative position based on its own movement and its positional relationship with the surroundings, using the obtained information. In this way, the autonomous traveling vacuum cleaner is configured to grasp at which position in the room it is and to create a map for freely selecting the cleaning area to be cleaned next based on the information.

Also, conventionally, in the case of an autonomous traveling cleaner that does not use a sensor that acquires external information such as a camera, it is impossible to determine at which position on the map the autonomous traveling cleaner is at the start of cleaning. Therefore, there is proposed an autonomous traveling cleaner which determines the position by using the fact that the autonomous traveling cleaner stands by while charging on the charging stand when not in use (see, for example, Patent Document 2).

The autonomous traveling cleaner disclosed in Patent Document 2 records the cleaning history of the autonomous traveling cleaner, with the position of the charging stand as a starting point. Then, based on the recorded information, a map is generated to determine the position of the autonomous traveling cleaner.

However, in practice, the information from various sensors includes not a little measurement error. Therefore, when an error of a predetermined level or more occurs, it is conceivable that the autonomous traveling cleaner returns to the starting point, reconfirms the position, and corrects the measurement error. In this case, the time to return to the starting point is added to the cleaning time. Furthermore, the error can not be corrected unless the same place is reciprocated many times. In addition, even if the space between the starting point of the charging stand and the like is reciprocated and cleaned many times, it is not possible to cope with environmental changes in the cleaning area such as opening and closing of the door, the presence or absence of obstacles, and differences in floor materials.

JP, 2002-085305, A JP, 2006-110322, A

The present invention provides an autonomously traveling vacuum cleaner and a cumulative floor surface probability updating method for updating the map corresponding to the environmental change of the cleaning area based on the travel area map generated each time.

The autonomous traveling vacuum cleaner which is an example of the present invention is provided with the map generation part which generates the new map which made the standard position the position of the standard member installed in the cleaning area as a standard position. Furthermore, in the autonomous traveling vacuum cleaner, when one element obtained by dividing the new map and the accumulated map in which the already created map is accumulated into a plurality of parts at the same position is taken as an element area, The cumulative floor probability which is information indicating whether or not the floor surface is included in the cumulative map using the floor probability which is information indicating whether or not the floor surface is included in the new map. The floor probability updating unit updates the Then, the floor probability update unit adds 1 to the cumulative number indicating the number of maps used for updating so far in each element area, subtracts the cumulative floor probability from the floor probability, and adds the difference. The sum of the quotient divided by the cumulative number of sheets and the cumulative floor probability added to the quotient is updated as a new cumulative floor probability.

In the cumulative floor surface probability updating method which is another example of the present invention, the map generation unit generates a new map based on the traveling results with the position of the reference member installed in the cleaning area as the reference position. When the floor surface probability updating unit divides an element area into one element obtained by dividing the new map and the accumulated map in which the previously created map is accumulated into a plurality at the same position, the element area has a new position. A floor probability which is information indicating whether it is a floor included in the map or a cumulative floor probability which is information indicating whether it is a floor included in the cumulative map is used. Then, the floor probability update unit adds 1 to the cumulative number indicating the number of maps used for updating so far, subtracts the cumulative floor probability from the floor probability, and divides the difference by the cumulative number after addition. The sum of the quotient plus the cumulative floor probability is updated as a new cumulative floor probability.

This makes it possible to generate a map with higher accuracy corresponding to the change of the environment in the cleaning area and the change of the cleaning area itself.

FIG. 1 is a plan view showing the appearance of the autonomous traveling vacuum cleaner according to the first embodiment. FIG. 2 is a bottom view showing the appearance of the autonomous traveling cleaner. FIG. 3 is a perspective view showing the appearance of the autonomous traveling cleaner. FIG. 4 is a block diagram showing functional units related to map creation of the control unit in the first embodiment. FIG. 5 is a diagram showing an example of a newly generated new map in the first embodiment. FIG. 6 is a diagram showing an example of the old map held in the first embodiment. FIG. 7 is a diagram showing a state in which the newly generated new map and the held old map are superimposed in the first embodiment. FIG. 8 is a diagram showing an example of a newly updated and held map in the first embodiment. FIG. 9 is a block diagram showing functional units related to map creation of a control unit in the second embodiment. FIG. 10 is a plan view showing the cleaning area in the second embodiment. FIG. 11 is a diagram showing a cumulative map in the second embodiment. FIG. 12 is a diagram showing a new map in the second embodiment. FIG. 13 is a diagram showing a state in which the reference position in Embodiment 2 is matched, and the posture of the new map is aligned on the cumulative map and superimposed. FIG. 14 is a diagram showing a state in which the new map and the old map are superimposed so as to minimize the difference in the second embodiment.

Hereinafter, an embodiment of an autonomous traveling vacuum cleaner according to the present invention will be described with reference to the drawings. In addition, the following embodiment is only what showed an example of the autonomous running cleaner in this invention. Accordingly, the scope of the present invention is defined by the wording of the claims with reference to the following embodiments, and is not limited to only the following embodiments. Therefore, among the components in the following embodiments, components that are not described in the independent claim showing the highest concept of the present invention are not necessarily required to achieve the object of the present invention, It is described as constituting a preferred embodiment.

In addition, the drawings are schematic diagrams in which emphasis, omission, and adjustment of ratios are appropriately performed to illustrate the present invention, and may differ from actual shapes, positional relationships, and ratios.

Embodiment 1
Hereinafter, the configuration of the autonomous traveling vacuum cleaner according to the first embodiment will be described with reference to FIGS. 1 to 3.

FIG. 1 is a plan view showing the appearance of the autonomous traveling vacuum cleaner according to the first embodiment. FIG. 2 is a bottom view showing the appearance of the autonomous traveling cleaner. FIG. 3 is a perspective view showing the appearance of the autonomous traveling cleaner. The autonomous traveling cleaner 100 is a robot type cleaner that autonomously travels in a cleaning area, which is a target area for cleaning such as a floor surface in a home, and sucks dust present in the cleaning area. For example, the autonomous traveling cleaner 100 etc. whose plane shape is a triangle of a roulette are illustrated.

As shown in FIGS. 1 to 3, the autonomous traveling cleaner 100 according to the first embodiment includes a body 120, a drive unit 130, a cleaning unit 140, a suction unit 150, a control unit 170, and various sensors described later. Configured The body 120 carries the various components of the autonomous traveling cleaner 100. The drive unit 130 moves the body 120 in the cleaning area. The cleaning unit 140 collects waste present in the cleaning area. The suction unit 150 sucks the waste collected by the cleaning unit 140 into the inside of the body 120. The control unit 170 controls the drive unit 130, the cleaning unit 140, the suction unit 150, and the like.

The body 120 constitutes a housing that accommodates the drive unit 130, the control unit 170, and the like. The body 120 includes a lower body and an upper body, and the upper body is configured to be removable from the lower body. The body 120 is provided at the outer peripheral portion with a bumper provided displaceably with respect to the body 120. Further, as shown in FIG. 2, the body 120 has a suction port 121 for sucking the dust into the body 120.

The drive unit 130 causes the autonomous traveling cleaner 100 to travel in the cleaning area based on an instruction from the control unit 170. In the first embodiment, one drive unit 130 is disposed on each of the left side and the right side with respect to the center in the width direction of the body 120 in a plan view. The number of drive units 130 is not limited to two, and may be one or three or more.

The drive unit 130 includes a wheel traveling on the cleaning surface, a traveling motor for applying torque to the wheel, and a housing accommodating the traveling motor. The wheel is accommodated in a recess formed on the lower surface of the body 120 and is rotatably attached to the body 120.

In addition, the autonomous traveling cleaner 100 is configured by an opposing two-wheel drive system including the caster 179 as an auxiliary wheel. By independently controlling the rotation of the two wheels, the autonomous traveling cleaner 100 can freely travel such as going straight, receding, rotating left, and rotating right.

The cleaning unit 140 constitutes a unit for sucking in the dust from the suction port 121. The cleaning unit 140 includes a main brush disposed in the suction port 121, a brush drive motor for rotating the main brush, and the like.

The suction unit 150 is disposed inside the body 120. The suction unit 150 includes a fan case, an electric fan disposed inside the fan case, and the like. The electric fan sucks the air inside the trash can unit 151 and discharges the air to the outside of the body 120. As a result, the waste is sucked from the suction port 121 and accommodated in the trash can unit 151.

In addition, as described above, the autonomous traveling cleaner 100 exemplifies, for example, an obstacle sensor 173, a distance measurement sensor 174, a collision sensor (not shown), a camera 175, a floor surface sensor 176, and an acceleration sensor (shown below). It includes various sensors such as an angular velocity sensor (not shown) and the like (not shown).

The obstacle sensor 173 is a sensor that detects an obstacle present in front of the body 120. In the case of the first embodiment, for example, an ultrasonic sensor is used as the obstacle sensor 173. The obstacle sensor 173 includes a transmitting unit 171 and a receiving unit 172. The transmitting unit 171 is disposed at the center of the front of the body 120 and transmits an ultrasonic wave toward the front. The receiving unit 172 is disposed on both sides of the transmitting unit 171, and receives the ultrasonic waves transmitted from the transmitting unit 171. That is, the obstacle sensor 173 receives the reflected wave of the ultrasonic wave transmitted from the transmission unit 171 and reflected by the obstacle and returned by the reception unit 172. Thereby, the obstacle sensor 173 detects the distance and the position to the obstacle.

The distance measurement sensor 174 is a sensor that detects the distance between the body 120 and an object such as an obstacle present around the body 120. In the case of the first embodiment, the distance measurement sensor 174 is formed of, for example, an infrared sensor having a light emitting unit and a light receiving unit. That is, the distance measuring sensor 174 measures the distance to the obstacle based on the elapsed time from when the light emitted from the light emitting unit to the infrared light reflected by the obstacle returns and is received by the light receiving unit.

Specifically, the distance measurement sensor 174 is disposed, for example, on the front top on the right side and in the front top on the left side. The distance measuring sensor 174 on the right side outputs light (infrared ray) toward the front of the body 120 obliquely to the right, and the distance measuring sensor 174 on the left side outputs light toward the left front of the body 120. With this configuration, when the autonomous traveling cleaner 100 turns, the distance measurement sensor 174 detects the distance between the body 120 and an object in the vicinity closest to the contour of the body 120.

The collision sensor is, for example, a switch contact displacement sensor, and is provided on a bumper disposed around the body 120. The switch contact displacement sensor is turned on by the obstacle coming into contact with the bumper and the bumper being pushed against the body 120. Thus, the collision sensor detects contact with an obstacle.

The camera 175 is a device for capturing an image of the entire circumference of the upper space of the body 120. The image captured by the camera 175 is processed by the image recognition processing unit. By this processing, the current position of the autonomous traveling cleaner 100 can be grasped from the position of the feature point in the image.

The floor surface sensor 176 is disposed at a plurality of locations on the bottom surface of the body 120 and detects whether or not a floor area, which is a cleaning area, exists, for example. In the case of the first embodiment, the floor surface sensor 176 is configured of, for example, an infrared sensor having a light emitting unit and a light receiving unit. That is, when the light (infrared rays) emitted from the light emitting unit returns and is received by the light receiving unit, the floor sensor 176 detects “floor present”. On the other hand, when the receiving unit receives only light having a threshold value or less, the floor sensor 176 detects “floor no”.

The drive unit 130 further comprises an encoder. The encoder detects each rotation angle of a pair of wheels rotated by the traveling motor. Based on the information from the encoder, the traveling amount, the turning angle, the speed, the acceleration, the angular velocity, etc. of the autonomous traveling cleaner 100 are calculated.

The acceleration sensor detects an acceleration when the autonomous traveling cleaner 100 travels. The angular velocity sensor detects an angular velocity when the autonomous traveling cleaner 100 turns. The information detected by the acceleration sensor and the angular velocity sensor is used, for example, as information for correcting an error caused by the idle rotation of the wheel.

The obstacle sensor 173, the distance measurement sensor 174, the collision sensor, the camera 175, the floor surface sensor 176, the encoder, and the like described above are examples of sensors. Therefore, the autonomous traveling cleaner 100 does not have to include all the sensors. Moreover, the autonomous running cleaner 100 may be equipped with a sensor of a form different from the above.

As described above, the autonomous traveling cleaner 100 according to the first embodiment is configured.

Hereinafter, the operation of the functional unit of the control unit 170 will be described with reference to FIG.

FIG. 4 is a block diagram showing each functional unit of control unit 170 of autonomous traveling cleaner 100 in the first embodiment.

As shown in FIG. 4, the control unit 170 of the autonomous traveling cleaner 100 controls the drive unit 130 to cause the autonomous traveling cleaner 100 to autonomously travel and execute cleaning. Furthermore, the control unit 170 configures a unit that generates a map of a traveling area from traveling results based on the information obtained from the various sensors during autonomous traveling.

Specifically, the control unit 170 includes a map generation unit 181, a storage device 200, a map comparison unit 182, an extended area determination unit 183, a floor probability update unit 184, and the like.

The map generation unit 181 functions as a processing unit that generates a map of the travel area. That is, based on the information from the various sensors described above, the map generation unit 181 uses, for example, travel performance which is a set of self-locations of the autonomous traveling cleaner 100 at a plurality of locations under cleaning obtained by self-location estimation technology. , Generate a map.

Furthermore, the map generation unit 181 can also generate a map based on the travel results, with the position of the reference member 189 installed in the cleaning area 180 described later with reference to FIG. 10 as a reference position.

Here, the cleaning area 180 is an area where the autonomous traveling cleaner 100 can travel. That is, generally, the cleaning area 180 is approximated by, for example, the shape of the floor of a room, as shown in FIG. At this time, the area of the cleaning area 180 may change significantly, for example, when a previously closed partition is opened, or when a sofa, a table, or the like installed on a floor surface is removed. Also, the area of the cleaning area 180 may change frequently, although the area is small, for example, the position of the chair or the position of the trash can has changed.

The reference member 189 is a member such as a device serving as a reference position when the autonomous traveling cleaner 100 travels autonomously, and is disposed in the cleaning area 180. Although the reference member 189 is not particularly limited, a charging stand or the like for charging a battery provided in the autonomous traveling cleaner 100 with supplied power may be the reference member 189.

The traveling record refers to, for example, the autonomous traveling cleaning from when the autonomous traveling cleaner 100 starts traveling with the reference member 189 as a starting point based on the traveling program, for example, to the end of the cleaning assuming that the entire cleaning area 180 is cleaned. It is a trajectory of the machine 100. That is, the travel record does not necessarily have to be the track that cleaned the entire cleaning area 180.

Note that, as the reference member 189, a characteristic portion extracted from an image captured by a camera 175 or the like shown in FIG. 3 in addition to the charging stand may be used as the reference member 189.

The map generation part 181 is a reference position shown in FIG. 5 which is an outline of a region actually traveled and a position where the reference member 189 shown in FIG. 10 is arranged based on the traveling results of the autonomous traveling cleaner 100. Information indicating 202 is generated as a map. Then, the map generation unit 181 stores the generated map in the storage device 200 of the control unit 170. At this time, as shown in FIG. 10, when there is an island region 180A which can not run in the cleaning area 180, the map generation unit 181 includes information indicating the outline of the island region 180A and the position thereof. Generate a map.

In the case of the first embodiment, the map generated by the map generation unit 181 is realized as, for example, two-dimensional array data. Specifically, the map generation unit 181 divides the traveling result of the autonomous traveling cleaner 100 into, for example, quadrilaterals having a predetermined size such as 10 cm by 10 cm. Then, the map generation unit 181 regards each square as an element area of the array that configures the map, and stores the array area as the array data in the storage device 200. The specific data format to be stored is not particularly limited. The value of each element area is stored as, for example, a floor probability 204, an accumulated floor probability 304, and the like. In addition to the above, the storage device 200 may store the amount of cleaned dust, the position at which the autonomous traveling cleaner 100 has stopped, and the like as additional information.

The map comparison unit 182 combines element areas in which the floor probability 204 of the new map 201 shown in FIG. 5 differs from the cumulative floor surface probability 304 of the accumulated map 301 shown in FIG. It is a processing unit that extracts as a difference area.

In addition, the specific extraction method of a difference area is not specifically limited. For example, element areas in which the cumulative floor surface probability 304 and the floor surface probability 204 are equal to or greater than the first threshold may be extracted as a difference area by combining consecutive element areas. Furthermore, first, from the floor probability 204 of the new map 201 and the cumulative floor probability 304 of the cumulative map 301, an element area having a probability equal to or higher than the second threshold is extracted. Then, in the extracted element areas, element areas without corresponding element areas of the floor surface probability 204 and the accumulated floor surface probability 304 may be extracted as a difference area by combining consecutive element areas.

The extension area determination unit 183 is a processing unit that determines that the extracted difference area is the extension area when at least one of the following conditions is satisfied. The first condition is that, of the difference areas extracted by the map comparison unit 182, the difference area in the direction crossing the boundary between the accumulation map 301 and the difference area is the case where the area of the difference area is larger than the third threshold. This is the case where the maximum depth D (see FIG. 7) which is the maximum length is larger than the fourth threshold. The second condition is that the maximum width W, which is the maximum length of the difference area in the direction along the boundary, is larger than the fifth threshold. That is, when at least one of the first and second conditions is satisfied, the extension area determination unit 183 determines that the difference area that satisfies the condition is the extension area.

Here, the third threshold is not particularly limited, but can be, for example, 1.44 square meters. This corresponds to the size of approximately 1 tatami and is a numerical value in accordance with the actual situation. Also, the fourth threshold and the fifth threshold are not particularly limited, but, for example, numerical values corresponding to the width of the autonomous traveling cleaner 100 may be used as the fourth threshold and the fifth threshold.

The floor probability update unit 184 is a processing unit that updates the cumulative floor probability 304, which is information indicating by probability whether the floor is included in the cumulative map 301, using the floor probability 204 described below. is there. Floor surface probability 204 is a floor surface included in new map 201 in each of the element areas where the positions coincide, when one element obtained by dividing new map 201 and accumulated map 301 in the vertical and horizontal directions at the same position is used as an element area. It is information indicating whether or not there is a probability.

Specifically, the floor probability updating unit 184 first adds 1 to the cumulative number indicating the number of new maps 201 used for updating in each element area. Next, the cumulative floor probability 304 is subtracted from the floor probability 204. Then, the floor probability updating unit 184 divides the difference by the cumulative number after addition, and updates the sum of the quotient and the cumulative floor probability 304 as a new cumulative floor probability 304.

Although the method of updating the extension area determined by the extension area determination unit 183 is different from the method of updating the cumulative floor probability 304 described above, this will be described later.

The display unit 186 is a processing unit that generates a display map. The display map is generated based on the updated cumulative map 301 held by the storage device 200. This makes it possible to present the display map to the user in an easy-to-see or easy-to-use state. At this time, the display unit 186 may have a function of outputting a display map generated by a user, for example, a terminal device or the like, for display.

Control unit 170 further includes storage device 200. The storage device 200 holds a cumulative map 301 in which maps generated before the generation of the new map 201 by the map generation unit 181 is accumulated. The cumulative map 301 stored in the storage device 200 is associated with a cumulative floor probability 304, which indicates whether each coordinate point of the travel area is a floor or not. The storage device 200 is not particularly limited, and examples thereof include a hard disk and a flash memory.

As described above, the functional unit of the control unit 170 is configured and operates.

Hereinafter, the process of updating the cumulative map 301 in the control unit 170 will be described with reference to FIGS. 5 to 8.

FIG. 5 is a diagram showing an example of the newly generated new map 201 and the floor surface probability 204 included in the new map 201 in the first embodiment. FIG. 6 is a diagram showing an example of the cumulative map 301 and the cumulative floor probability 304 included in the cumulative map 301 according to the first embodiment. FIG. 7 is a diagram showing an example of the state in which the new map 201 and the cumulative map 301 are superimposed in the first embodiment and the floor probability 204 and the cumulative floor probability 304 corresponding to this. FIG. 8 is a diagram showing an example of the updated cumulative map 301 in the first embodiment.

The upper part of FIG. 5 shows the new map 201 newly generated by the map generation unit 181. Further, the lower part of FIG. 5 shows a graph of the floor surface probability 204 at the cross section 203 of the new map 201. In addition, the floor surface probability 204 of the map may be illustrated by taking two values of 0 (not a floor surface) or 1 (a floor surface). Furthermore, the floor probability 204 may be illustrated taking values between 0 and 1 based on the likelihood of self-position estimation. In the case of the first embodiment, the new map 201 shown in the upper part of FIG. 5 illustrates a portion with a floor surface probability of 0.5 or more based on the certainty of self-position estimation.

The new map 201 includes not only the floor surface probability 204 but also the reference position 202 which is information indicating the starting point. The reference position 202 may be the position of a charging stand that functions as the reference member 189 in the autonomous traveling cleaner 100 shown in FIG. Furthermore, for example, a corner or the like of a room existing in the traveling area in which the autonomous traveling cleaner 100 travels may be set as the reference position 202 based on information from each sensor.

Hereinafter, in the first embodiment, the position corresponding to the charging stand will be described as the reference position 202.

The upper part of FIG. 6 shows a cumulative map 301 obtained by accumulating maps that have already been created and held in the storage device 200. The lower part of FIG. 6 shows a graph of the cumulative floor probability 304 in the cross section 303 of the cumulative map 301. The cumulative map 301 has a cumulative reference position 302. The accumulated reference position 302 is obtained by accumulating the reference position 202 included in the generated new map 201 shown in FIG. Specifically, for example, after daily cleaning, a map is created, and the history of the created daily map is accumulated (superimposed). The reference position 202 corresponds to, for example, the position of the charging stand. Therefore, even when the new map 201 is generated one or more times, as long as the position of the charging stand does not move, the accumulated reference position 302 is the same position as the reference position 202 in the new map 201. In addition, when moving a charge stand etc., the accumulation reference position 302 is updated according to a predetermined | prescribed procedure. Thereby, the position of the latest charging stand becomes the cumulative reference position 302 of the cumulative map 301.

The upper part of FIG. 7 shows a diagram in which the map comparison unit 182 superimposes the new map 201 and the cumulative map 301 on each other. Specifically, the map comparison unit 182 superimposes the new map 201 and the cumulative map 301 for comparison. At this time, the map comparison unit 182 matches the reference position 202 of the new map 201 with the cumulative reference position 302 of the cumulative map 301, assuming that there is no change in the position of the reference member 189 in the traveling area, Do. When there is a change in the position of the reference member 189, the overlapping process is performed by the reference change check unit 300 (see FIG. 9) described later. In this case, the map comparison unit 182 superimposes the new map 201 and the cumulative map 301 after the process of the reference change check unit 300 is performed.

The lower part of FIG. 7 shows a graph of the floor probability 204 and the cumulative floor probability 304 in the cross section 403 of the upper diagram superimposed on the new map 201 and the cumulative map 301. At this time, as shown in the graph, a difference area indicated by, for example, a difference A, a difference B, and a difference C is generated between the superimposed floor probability 204 and the accumulated floor probability 304. In this case, the difference in floor probability between the cumulative floor probability 304 of the cumulative map 301 of the corresponding portion and the floor probability 204 of the new map 201 in the same portion is, for example, a first threshold such as 0.5 or more. A certain area may be used as a difference area. Also, both the floor probability 204 of the new map 201 and the cumulative floor probability 304 of the cumulative map 301 are converted into a map consisting of an area of a second threshold or more such as 0.5 or more, and then both of the converted maps Area differences may be used as difference areas.

The above difference is determined by the extension area determination unit 183 (see FIG. 4) that determines whether to extend the traveling area. Then, according to the determination result of the extension area determination unit 183, the cumulative floor probability of the cumulative map is updated by the floor probability update unit 184 shown in FIG.

The floor surface probability updating unit 184 offsets the displacement of the floor surface position due to the self position estimation error or the like by superimposing the new map 201 and the cumulative map 301. Thus, the floor surface probability updating unit 184 can increase the probability that the floor surface is correctly determined to be a floor surface.

For example, with respect to the cumulative map 301 having the cumulative floor probability 304 such as the difference A shown in FIG. 7, the floor probability update unit 184 calculates the floor surface of a portion corresponding to the difference A of the newly generated new map 201. The cumulative floor probability 304 of the cumulative map 301 is updated based on the probability 204.

When the updating is performed, the floor probability updating unit 184 first performs averaging according to the accumulated data amount, and corrects the error so as to cancel out the error. Then, the floor probability updating unit 184 generates the corrected floor probability as updated data. At this time, the floor probability updating unit 184 updates the cumulative floor probability, for example, according to (Expression 1).

Here, N (x, y) in (Expression 1) is a cumulative number indicating the number of maps superimposed so far at the coordinates (x, y) of the cumulative map 301. Mnew (x, y) in (Expression 1) is the floor surface probability 204 at the coordinates (x, y) of the new map 201. P (x, y) in (Expression 1) is the cumulative floor probability 304 at the coordinates (x, y) of the cumulative map 301.

Specifically, as shown in (Equation 1), the floor surface probability is first updated by adding 1 to the cumulative number (N (x, y)) indicating the number of maps used for the update so far. Next, the cumulative floor surface probability (p (x, y)) is subtracted from the floor surface probability (Mnew (x, y)). Next, the difference (Mnew (x, y) −p (x, y)) is divided by the cumulative number (N (x, y)) after addition. Next, the cumulative floor probability (p (x, y)) is added to the quotient obtained by the division, and the sum is taken as a new cumulative floor probability (p (x, y)). Thus, the floor probability updating unit 184 updates the cumulative floor probability.

Further, as shown in FIG. 7, when the autonomous traveling cleaner 100 actually travels the cleaning area of the difference B in order to clean the new cleaning area as in the difference B, the cumulative floor surface probability in the cumulative map 301 304 is zero or nearly zero. On the other hand, in the new map 201, the floor surface probability 204 of the portion corresponding to the above is 1 or almost 1. That is, the difference area is extracted between the new map 201 and the cumulative map 301 as described above.

Therefore, as described above, the extension area determination unit 183 determines that the extracted difference area is the extension area when at least one of the following conditions is satisfied.

The first condition is a maximum that is the maximum length of the difference area in the direction intersecting (including orthogonally) the boundary line 301A between the accumulation map 301 and the difference area when the area of the difference area is larger than the third threshold. The depth D (see the lower part of FIG. 7) is larger than the fourth threshold. The second condition is that the maximum width W (see the upper part of FIG. 7), which is the maximum length of the difference area in the (including parallel) direction along the boundary 301A, is larger than the fifth threshold. That is, when at least one or both of the first and second conditions are satisfied, the extension area determination unit 183 determines that the difference area satisfying the condition is the extension area. Thus, the floor probability updating unit 184 updates the cumulative floor probability 304 of the cumulative map 301 shown in FIG. 8 as a new cumulative floor probability 304.

A specific updating method is performed using, for example, (Expression 2) shown below. That is, as shown in (Expression 2), the cumulative number (N (x, y)) of the cumulative map 301 is set to 1 in the extension area. Further, the cumulative floor probability 304 (p (x, y)) of the cumulative map 301 is set to 1.0.

In addition, as shown in FIG. 7 as the difference C, the cumulative map 301 has the cumulative floor probability 304 at a certain level or more, but in the new map 201, when the floor probability 204 is zero or almost zero, the floor probability is Do not update. That is, since it is determined that the position indicated by the difference C is a portion where the autonomous traveling cleaner 100 could not be cleaned or a portion where it could not travel due to an obstacle, the floor probability is not updated. In this case, the portion that could not be cleaned can be separately stored in the storage device 200 as accumulated information of the non-traveling area.

By the above, as shown in FIG. 8, the result of the update process of the accumulation map in the control unit 170 is obtained.

FIG. 8 is a diagram showing an example of the updated and held map.

The upper part of FIG. 8 shows the cumulative map 301 after update. The lower part of FIG. 8 shows a graph of the updated cumulative floor probability 304 corresponding to the cross section 303 shown in the cumulative map 301.

Thus, based on the cumulative floor probability 304 of the updated cumulative map 301 shown in FIG. 8, the position having the cumulative floor probability 304 set as the second threshold, for example, 0.5 or more is set as the floor. , Can draw. At this time, the display unit 186 may generate, for example, a display map by drawing a wall around the drawn floor surface. Then, the display unit 186 may transmit the generated display map to, for example, a portable terminal or the like owned by the user for display. At this time, a user instruction receiving unit that receives an instruction may be provided, for example, in the control unit or the display map screen. The user instruction receiving unit receives an instruction from the user based on the displayed display map. Specifically, for example, an instruction on a user designated area such as an instruction on an area to be cleaned next and an instruction on a traveling area for scheduling. At this time, a user designated area determination unit may be further provided in, for example, a control unit or a display map screen. The user designated area determination unit has a function of determining whether the received user designated area is an area corresponding to a cleanable area in association with the updated map.

As described above, according to the autonomous traveling cleaner 100 and the accumulated floor probability updating method according to the first embodiment, each element area is in a state in which the plurality of maps generated by the map generation unit 181 are superimposed. The cumulative floor probability 304 of is calculated. This improves the accuracy of the map. Furthermore, when the new map 201 is generated, the map generation unit 181 compares it with the cumulative map 301 to generate a difference area (difference area). Then, the extended area determination unit 183 determines whether or not the generated difference area is to be a new floor surface or whether there is an obstacle based on a predetermined threshold value. This enables more flexible operation of the cumulative map 301.

Further, according to the method of updating the cumulative floor probability according to the first embodiment, the cumulative floor probability 304 corresponding to the extension area can be appropriately updated. This allows the cumulative map 301 to be maintained with high map accuracy throughout.

Second Embodiment
The autonomous traveling vacuum cleaner and the cumulative floor surface probability updating method according to the second embodiment will be described below with reference to FIG. In the second embodiment, parts (parts) having the same operation and function as the first embodiment and the same shape, mechanism and structure as the first embodiment may be denoted by the same reference numerals and the description thereof may be omitted. In the following, differences from the first embodiment will be mainly described, and the description of the same contents may be omitted.

FIG. 9 is a block diagram showing functional units related to map creation of the control unit 170 in the second embodiment.

That is, as shown in FIG. 9, the autonomous traveling cleaner 100 of the second embodiment differs from that of the first embodiment in that the control unit 170 further includes the reference change confirmation unit 300. The reference change confirmation unit 300 matches the inclination of the new map 201 generated by the map generation unit 181 with the accumulation map 301 and updates the accumulated reference position 302 in order to correctly overlap the element areas to be compared by the map comparison unit 182. Have a function to

The reference change confirmation unit 300 configures a processing unit that updates the accumulated reference position 302 of the accumulation map 301, and includes the longest straight line determination unit 382, the map arrangement unit 383, the difference calculation unit 384, the reference position update unit 385, and the like. Prepare.

Specifically, the reference change confirmation unit 300 first matches the posture such as the inclination of the new map 201 generated by the map generation unit 181 with the cumulative map 301. Then, the reference change confirmation unit 300 confirms from the new map 201 whether the position of the reference member 189 has been changed. At this time, if it is determined that the position of the reference member 189 has been changed, the reference change check unit 300 functions to update the cumulative reference position 302 of the cumulative map 301.

As described above, the autonomous traveling cleaner 100 according to the second embodiment is configured.

Hereinafter, the operation of the functional unit related to map creation of the control unit 170 will be described with reference to FIG. 9 and using FIGS. 10 to 12.

FIG. 10 is a plan view showing the cleaning area 180. As shown in FIG. FIG. 11 is a diagram showing the cumulative map 301. As shown in FIG. FIG. 12 is a diagram showing the new map 201. As shown in FIG.

The longest straight line determination unit 382 is a processing unit that determines the longest longest straight line component among the straight line components included in the map generated by the map generation unit 181. Here, the longest straight line component means the longest line segment included in the periphery of the map among all the line segments included in the map. At this time, if there is a line segment close to the length of the longest line segment within a certain error range, the slope of the component thereof is the line segment closest to the X axis or the Y axis as the longest straight line determination unit 382 May be determined as the longest linear component.

As in the first embodiment, the cumulative map 301 and the new map 201 shown in FIG. 11 and FIG. 12 are generated based on the traveling results of the autonomous traveling cleaner 100 traveling.

Hereinafter, correction of deviation between maps of the cumulative map 301 and the new map 201 created as described above will be described with reference to FIG.

FIG. 13 is a diagram showing a state in which the new map 201 and the cumulative map 301 are superimposed with the reference position 202 and the cumulative reference position 302 in agreement.

First, the map placement unit 383 is generated in the reference position 202 included in the new map 201 newly generated by the map generation unit 181 shown in FIG. 12 and before that shown in FIG. The cumulative reference position 302 included in the cumulative map 301 is matched. At the same time, the map arrangement unit 383 superimposes the longest straight line component 193 included in the new map 201 shown in FIG. 12 and the longest straight line component 192 included in the cumulative map 301 shown in FIG. Arrange them together.

The process of overlapping the reference position 202 of the new map 201 with the cumulative map 301 and rotating the new map 201 about the reference position 202 is executed by, for example, affine transformation of a matrix. The affine transformation of the matrix is an example of the process of rotating the map.

Here, the cumulative map 301 illustrated in FIG. 11 is a map obtained by performing statistical processing or the like on a plurality of maps generated in the past. The map generated at first among the cumulative map 301 is arranged such that the longest straight line component is along the predetermined axis (X axis or Y axis). Therefore, the cumulative map 301 and the new map 201 are all generated so that the longest straight line component is along the predetermined axis.

However, in the case of the second embodiment, as shown in FIG. 12, the new map 201 generated by the map generation unit 181 may be generated as an error in an inclined state to some extent. Therefore, as shown in FIG. 13, the map arranging unit 383 rotates the longest straight line component 192 of the cumulative map 301 so that the longest straight line component 193 of the new map 201 follows the Y axis which is a predetermined axis. Deploy. Then, the accumulated reference position 302 of the accumulated map 301 and the reference position 202 of the new map 201 are moved in parallel along the X axis so as to coincide with each other. Thereby, as described with reference to FIG. 14, the longest straight line component 192 of the cumulative map 301 and the longest straight line component 193 of the new map 201 overlap so as to be parallel, and the difference between the maps is minimized.

FIG. 14 is a diagram showing a state in which the cumulative map 301 and the new map 201 are superimposed so as to minimize the difference.

Specifically, the difference calculation unit 384 first translates the new map 201 arranged by the map arrangement unit 383 relative to the cumulative map 301 one or more times and a plurality of times. Then, the difference calculating unit 384 calculates the difference between the maps for each parallel movement. Here, the difference between the maps is a portion that does not overlap when the cumulative map 301 and the new map 201 are superimposed. That is, the difference between the maps corresponds to the hatched portion shown in FIG.

In the case of the second embodiment, the difference calculating unit 384 performs the new map 201 in the X axis direction and the Y axis direction one or more times in the form of a matrix with respect to the cumulative map 301 at predetermined intervals such as 10 cm. Translate in parallel. Then, the difference calculating unit 384 calculates the difference between the maps for each movement. At this time, the threshold may be determined, for example, by how many times the difference is calculated. Moreover, when the difference obtained continuously over multiple times always increases, the calculation of the difference may be ended at that stage.

Next, the reference position update unit 385 determines, based on the positional relationship of the reference position 202 of the new map 201 with respect to the reference position 202 of the cumulative map 301 at which the smallest difference is obtained among the differences calculated by the difference calculation unit 384. , Update the reference position of the map to be created next time. As a result, even if the reference member 189 is moved in the cleaning area 180, it is possible to appropriately generate a new map. Although FIG. 14 exemplifies the case where the reference position 202 is deviated only in the X-axis direction, the deviation of the reference position 202 is not limited to this. Usually, the deviation of the reference position 202 is deviated to at least one of the X axis and the Y axis. Therefore, the reference position update unit 385 updates the coordinates of the reference position based on the deviation of the X axis and the Y axis. Thereby, the deviation between the maps can be corrected with higher accuracy.

As described above, according to the autonomous traveling cleaner 100 of the second embodiment, even when the new map 201 is generated to be inclined with respect to the cumulative map 301 due to measurement errors of various sensors, etc., the inclination is corrected. Thus, the new map 201 can be accurately superimposed on the cumulative map 301. This makes it possible to improve the accuracy of the cumulative floor probability 304 to be updated.

Further, according to the autonomous traveling cleaner 100 of the second embodiment, when the reference member 189 moves in the cleaning area 180, the autonomous traveling cleaner 100 itself recognizes the movement of the reference member 189. Then, based on the recognized movement of the reference member 189, the cumulative reference position 302 is correctly updated. Therefore, the accuracy of the cumulative floor probability 304 can be maintained high.

The present invention is not limited to the above embodiment. For example, another embodiment realized by arbitrarily combining the components described in the present specification and excluding some of the components may be used as an embodiment of the present invention. Furthermore, modifications obtained by applying various modifications to those skilled in the art to the above embodiment without departing from the spirit of the present invention, that is, the meaning indicated by the language of the claims are also included in the present invention. included.

For example, among the configurations described in the first and second embodiments, components other than the map generation unit 181 may be configured on a computer (computer) such as a server connected to the autonomous traveling cleaner 100 via a network. . In this case, it can be considered as a vacuum cleaner system provided with the autonomous traveling vacuum cleaner 100. At this time, the new map 201 generated by the map generation unit 181 is transmitted to the computer through the network. Then, based on the transmitted new map 201, the cumulative map 301 stored by the computer is updated.

Also, the configuration may be such that the user can confirm the cleaning result on a terminal such as a smartphone based on the cumulative map 301 received from the computer.

Furthermore, the user may be configured to specify an area to be cleaned by the autonomous traveling cleaner 100 via the mobile terminal.

INDUSTRIAL APPLICABILITY The present invention is applicable to a so-called robot-type vacuum cleaner or the like that travels and cleans autonomously in a home, a factory, a large-scale facility, and the like.

Reference Signs List 100 autonomous traveling cleaner 120 body 121 suction port 130 drive unit 140 cleaning unit 150 suction unit 151 box unit 170 control unit 171 transmission unit 172 reception unit 173 obstacle sensor 174 distance measurement sensor 175 camera 176 floor sensor 179 caster 180 cleaning area 180A area 181 map generation unit 182 map comparison unit 183 extended area determination unit 184 floor surface probability update unit 186 display unit 189 reference member 192, 193 longest straight component 200 storage unit 201 new map 202 reference position 203, 303, 403 cross section 204 floor Surface probability 300 Reference change confirmation unit 301 Cumulative map 301A Boundary line 302 Cumulative reference position 304 Cumulative floor surface probability 382 Longest straight line determination unit 383 Map layout Part 384 difference calculation unit 385 a reference position update unit

Claims (7)

1. It is an autonomous traveling vacuum cleaner that travels and cleans autonomously,
   A map generation unit that generates a new map based on the traveling results with the position of the reference member installed in the cleaning area as the reference position;
   When one element obtained by dividing the new map and the accumulated map in which the already created map is divided into a plurality at the same position is used as an element area, the element is included in the new map in each of the element areas whose positions coincide. A floor surface that updates cumulative floor probability which is information indicating whether it is a floor included in the cumulative map using the floor probability which is information indicating whether it is a floor by probability or not And a probability update unit,
   The floor surface probability updating unit
   In each of the element areas, 1 is added to the cumulative number indicating the number of maps used for updating so far, the cumulative floor probability is subtracted from the floor probability, and the cumulative number after adding the difference Dividing by 、 and adding the accumulated floor probability to the quotient, and updating the sum as the new accumulated floor probability,
   Autonomous vacuum cleaner.
2. It further comprises a map comparison unit which combines the element areas of the element area different from the floor area probability of the new map with respect to the accumulated floor surface probability of the accumulated map and continues as a difference area.
   The autonomous running cleaner according to claim 1.
3. The map comparison unit
   In the element area where the accumulated floor surface probability and the floor surface probability are differences equal to or greater than a first threshold, the element areas that are continuous and combined are extracted as the difference area.
   The autonomous running cleaner according to claim 2.
4. The map comparison unit
   The element area having a probability equal to or greater than a second threshold value is extracted from the floor surface probability of the new map and the accumulated floor surface probability of the cumulative map, and the element area with no corresponding element area mutually corresponding, The consecutive element areas are combined and extracted as the difference area.
   The autonomous running cleaner according to claim 2.
5. Among the difference areas extracted by the map comparison unit, the area of the difference area is larger than a third threshold, and
   The maximum depth which is the maximum length of the difference area in the direction crossing the boundary between the accumulation map and the difference area is larger than a fourth threshold, or the maximum of the difference area in the direction along the boundary An extended area determination unit that determines that the difference area satisfying at least one of the maximum width which is the length is larger than the fifth threshold is an extended area;
   The floor surface probability updating unit
   The accumulated number of the expanded area determined by the expanded area determination unit is set to 1, and the accumulated floor probability is set to 1, or matched with the floor probability of the new map.
   The autonomous running cleaner according to any one of claims 2 to 4.
6. A longest straight line determination unit that determines a longest straight line component among straight line components included in the new map generated by the map generation unit;
   The reference position included in the new map is made to coincide with the accumulated reference position included in the cumulative map, and the longest straight line component included in the new map and the longest straight line component included in the cumulative map are parallel Or a map arrangement unit arranged in a straight line,
   The new map placed by the map placement unit is moved in parallel relative to the cumulative map one or more times, and the difference is calculated to calculate the difference between the new map and the cumulative map for each movement. Department,
   The cumulative reference position is updated based on the positional relationship of the reference position of the new map with respect to the cumulative reference position of the cumulative map from which the smallest difference is obtained among the differences calculated by the difference calculation unit. A reference position updating unit
   The autonomous running cleaner according to any one of claims 1 to 5.
7. An accumulated floor probability updating method for an autonomously traveling vacuum cleaner that travels and cleans autonomously, comprising:
   The map generation unit generates a new map based on the track record, with the position of the reference member installed in the cleaning area as the reference position,
   The floor probability update unit
   When one element obtained by dividing the new map and the accumulated map in which the already created map is accumulated into a plurality at the same position is used as an element area
   In each of the element areas whose positions coincide, a floor surface probability which is information indicating whether it is a floor surface included in the new map and a probability whether it is a floor surface included in the cumulative map Using the cumulative floor probability, which is the information shown in
   1 is added to the cumulative number indicating the number of maps used for updating so far, the cumulative floor probability is subtracted from the floor probability, the difference is divided by the cumulative number after addition, and Update the sum of the cumulative floor probabilities as the new cumulative floor probability,
   Cumulative floor probability update method.

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