JP7555017B2 - Self-propelled processing device, object determination method, and program - Google Patents

Description

The present disclosure relates to a self-propelled processing device that performs an inactivation process on an object while traveling autonomously, and inactivates any adhering matter attached to the object, a method for determining the object, and a program.

Conventionally, there are self-propelled robots that can determine their own position and move autonomously by scanning a laser distance sensor, known as LiDAR, in a horizontal plane and sensing the position and distance of objects in their surroundings.

Patent document 1 also describes a collection device that uses such a self-propelled robot to suck up and collect viruses that have been scattered on the floor.

International Publication No. 2019/064862

However, substances such as bacteria and viruses are attached as adhesions not only to floors but also to objects that people touch, and this poses a risk of infection, such as infectious diseases, that may be transmitted from the adhesions to people who secondarily touch such objects. For this reason, measures are needed to reduce the risk of infection for objects to which adhesions may adhere. Conventional collection devices are designed to suck up viruses on the floor, so it is difficult to collect adhesions when the adhesions are located higher than the floor, for example. Therefore, even after the collection of viruses using a collection device, the risk of infection from adhesions that adhere to objects located higher than the floor remains.

The present disclosure provides a self-propelled processing device and the like that efficiently reduces the risk of infection caused by attachments on objects located above the floor surface.

A self-propelled processing device according to the present disclosure is a self-propelled processing device that autonomously travels in a predetermined space and performs an inactivation process on an object, thereby inactivating an attachment attached to the object. The self-propelled processing device is equipped with a position sensor that acquires a positional relationship between the self and an object present in a two-dimensional measured space along the traveling surface of the self-propelled processing device, the position sensor acquiring a first positional relationship that is the positional relationship at a first height in a height direction intersecting with the traveling surface, and a second positional relationship that is the positional relationship at a second height in the height direction, an object determination unit that detects an object position, which is a position within the predetermined space, based on the difference between the first positional relationship and the second positional relationship, and determines the object corresponding to the detected object position as the object, and an inactivation processing unit that performs the inactivation process on the determined object.

Another object determination method of the present disclosure is an object determination method used in a self-propelled processing device that autonomously travels in a specified space and performs an inactivation process on an object to inactivate an attachment attached to the object, and obtains a first positional relationship that is a positional relationship between an object present in a two-dimensional measured space along the running surface of the self-propelled processing device and the self-propelled processing device at a first height in a height direction intersecting the running surface of the self-propelled processing device, and a second positional relationship that is a positional relationship between an object present in the measured space and the self-propelled processing device at a second height in the height direction, detects a target position that is a position within the specified space based on the difference between the first positional relationship and the second positional relationship, and determines the object corresponding to the detected target position as the object.

Another aspect of the present disclosure is a program that causes a computer to execute the above-mentioned object determination method.

According to the present disclosure, the risk of infection caused by attachments on objects located above the floor surface is effectively reduced.

FIG. 1 is a diagram for explaining the operation of a self-propelled processing device according to an embodiment. FIG. 2A is a first diagram illustrating the second height used in the self-propelled processing device according to the embodiment. FIG. 2B is a second diagram illustrating the second height used in the self-propelled processing device according to the embodiment. FIG. 3 is a diagram illustrating the functional configuration of the self-propelled processing device 100 according to the embodiment. FIG. 4 is a flowchart showing the operation of the self-propelled processing device according to the embodiment. FIG. 5 is a flow chart showing the operation of traveling and inactivation processing by the self-propelled processing device according to the embodiment. FIG. 6 is a first diagram illustrating an example of use of the imaging device according to the embodiment. FIG. 7 is a second diagram illustrating an example of use of the imaging device according to the embodiment. FIG. 8 is a diagram illustrating an example of a notification of a result of the inactivation process according to the embodiment. FIG. 9 is a schematic diagram showing a position sensor of the self-propelled processing device according to the first modification. FIG. 10 is a diagram illustrating detection of a target position by a self-propelled processing device according to the second modification.

Below, the self-propelled processing device, object determination method, and program according to the present disclosure will be described with reference to the drawings. Note that the numerical values, shapes, materials, components, positional relationships of the components, connection states, steps, and order of steps shown in the following embodiments are merely examples and are not intended to limit the present disclosure. In addition, although multiple disclosures may be described as one embodiment below, components not described in a claim are described as optional components with respect to the disclosure according to that claim. In addition, the drawings are schematic diagrams in which emphasis, omission, and ratio adjustments have been made as appropriate to explain the present disclosure, and may differ from the actual shapes, positional relationships, and ratios.

In addition, more detailed explanations than necessary may be omitted. For example, detailed explanations of matters that are already well known, or duplicate explanations of substantially identical configurations may be omitted. This is to avoid making the following explanation unnecessarily redundant and to make it easier for those skilled in the art to understand.

The accompanying drawings and the following description are provided to enable those skilled in the art to fully understand the present disclosure, and are not intended to limit the subject matter described in the claims.

Figure 1 is a diagram explaining the operation of a self-propelled processing device according to an embodiment. Figure 2A is a first diagram explaining the second height used in a self-propelled processing device according to an embodiment. Figure 2B is a second diagram explaining the second height used in a self-propelled processing device according to an embodiment.

(a) of FIG. 1 is a schematic diagram showing the self-propelled processing device 100 traveling within a specified space 150. (b) of FIG. 1 is a first diagram showing the positional relationship between the self-propelled processing device 100 and other objects acquired while the self-propelled processing device 100 is traveling. (c) of FIG. 1 is a second diagram showing the positional relationship between the self-propelled processing device 100 and other objects acquired while the self-propelled processing device 100 is traveling.

The self-propelled processing device 100 is a device that autonomously travels on the floor surface (hereinafter referred to as the traveling surface 200) of a predetermined space 150, searches for an object 81 that exists in the predetermined space 150 and may have attached matter attached thereto, and performs an inactivation process for the attached matter on the object. The object 81 is a part of an object that exists in the predetermined space 150. Note that an object is an object that can be sensed by a position sensor 10 described later, and includes fixed objects such as walls of buildings and movable objects such as chairs, tables, and sofas. On the other hand, glass that cannot be sensed depending on the type of position sensor 10 may be excluded from the object. In the example shown in FIG. 1A, the object 81 is a bench placed in the predetermined space 150. A person 99 who uses such a bench (see FIG. 2A described later) touches the bench with his or her hands, and thus bacteria, viruses, and other attached matter may adhere to the bench.

The self-propelled processing device 100 measures the positional relationship between itself and other objects in a two-dimensional measured space that is approximately parallel to the running surface 200 at a first height H1, which is a height that coincides with the running surface 200 in the height direction that intersects with the running surface 200. The positional relationship at the first height H1 is acquired as the first positional relationship shown in FIG. 1B, and is used to determine the target object 81. In FIG. 1B, the position of the self-propelled processing device 100 is conveniently shown as a circle with the reference number 100. Note that FIG. 1B shows the first positional relationship when the two-dimensional surface on which the measured space extends is viewed in a plan view. As shown in FIG. 1B, the first positional relationship includes an area outside the object as seen from the self-propelled processing device 100, which is marked with dot hatching, and other areas, and these are separated by a boundary 98.

The self-propelled processing device 100 also measures the positional relationship between itself and other objects in a two-dimensional measurement space that is approximately parallel to the running surface 200 at a second height H2, which is the height from the running surface 200 corresponding to the top plate that forms the seat surface of the bench in the height direction. The positional relationship at the second height H2 is acquired as the second positional relationship shown in (c) of FIG. 1 and is used to determine the target object 81. Like the first positional relationship, the second positional relationship also includes an area outside the object as seen from the self-propelled processing device 100, which is dot-hatched, and other areas, and these are separated by a boundary 98. Here, as shown by the outlined arrow in the figure, in the second positional relationship, a boundary different from the first positional relationship is formed by the amount corresponding to the top plate.

Therefore, as shown in FIG. 1(c), it is possible to calculate a difference area where the density of dot hatching is high. This difference area can be calculated by subtracting the areas outside the object in the first positional relationship from the second positional relationship. This difference area reflects the difference in positional relationship due to an object that does not exist at the first height but exists only at the second height, such as an object 81 such as a bench. Therefore, by setting the position corresponding to this difference area as the position of the object 81 to be inactivated, it is possible to automatically perform inactivation processing on the "bench," which is an example of the object 81. In other words, the difference area is an example of the object area.

This process does not require the user of the self-propelled processing device 100 to input the exact positions of all objects 81, so objects 81 can be efficiently inactivated, including objects 81 that the user has not yet fully identified.

As in the bench example described above, the object 81 to which the deposit may adhere is usually convex toward the inside of the specified space 150 relative to the wall surface, or concave toward the outside of the specified space relative to the wall surface. If it is flush with the wall surface, the person 99 cannot touch it by grasping it or by leaning their weight on it, so such an uneven shape is essential. When the unevenness is formed, an upper surface that faces the direction of gravity is formed. Bacteria and viruses suspended in droplets, etc. are likely to accumulate and adhere to the upper surface of the unevenness. From this perspective, it is important to perform an inactivation process on the object 81 that is concave or convex relative to the wall surface.

The self-propelled processing device 100 according to this embodiment acquires a first positional relationship corresponding to the wall surface at a first height H1, and acquires a second positional relationship reflecting the unevenness corresponding to the object 81 at a second height H2. From the difference between these, a position including the height within a specified space 150 corresponding to the unevenness can be identified, making it possible to perform an efficient inactivation process on the object 81.

Here, instead of the first positional relationship, a similar process can be performed using a floor map or the like. However, for example, when the difference area of the second positional relationship with respect to the floor map is calculated, if there are objects placed on the running surface 200 later, such as potted plants, fire extinguishers, and partitions, these objects will also be subject to the inactivation process as objects 81. Objects of this type placed on the running surface 200 are rarely touched by people 99, and therefore may not be suitable as objects for the inactivation process. Therefore, by calculating the difference area using the first positional relationship, objects of this type placed on the running surface 200 can be excluded from the objects 81, and the inactivation process for the objects 81 can be performed more efficiently.

The first height H1 does not have to be the same height as the running surface 200. If there is a protrusion such as a step that protrudes upward in the height direction from the running surface 200 in the specified space 150, the step or the like may be included in the area of the difference between the first positional relationship and the second positional relationship, so the first height H1 may be set to be higher than the protrusion such as the step. In addition, the order of the heights of the first height H1 and the second height H2 may be reversed depending on the situation.

The second height H2 is set according to the height of the object 81 that the person 99 touches. For example, as shown in FIG. 2A, if a handrail 97 or the like is assumed to be the object 81, the second height H2 is set to the height at which the handrail 97 is provided. For example, the handrail 97 is often provided at a height of 70 cm to 90 cm, and the second height H2 is set to a height of 70 cm to 90 cm in order to detect the handrail 97 as the object 81. Also, as shown in FIG. 2B, if the seat of a chair 96 or the like is assumed to be the object 81, the second height H2 is set to the height at which the seat of the chair 96 is provided. For example, the seat of the chair 96 is often provided at a height of 15 cm to 50 cm, and the second height H2 is set to a height of 15 cm to 50 cm in order to detect the seat of the chair 96 as the object 81.

In addition, although not shown, when the object 81 is assumed to be a tabletop such as a high table, the second height H2 is set to a height of 100 cm to 120 cm. In this way, the second height H2 may be set to an appropriate value based on the range of movement of the person 99's hands when standing and when sitting. More specifically, the second height H2 may be set to an appropriate value according to the object 81 assumed by the user. Since it is rare for a person 99 to touch a position higher than their shoulders, the second height H2 is set to a position lower than the person 99's shoulders, for example. Furthermore, the above is not limited to objects 81 that are likely to be touched by the person 99 even if they are higher than the shoulders.

The functional configuration of the self-propelled processing device 100 according to the present embodiment will be described below with reference to FIG. 3. FIG. 3 is a diagram for explaining the functional configuration of the self-propelled processing device 100 according to the embodiment. As shown in FIG. 3, the self-propelled processing device 100 according to the present embodiment is broadly divided into a functional unit related to the detection of objects such as the target object 81, including a position sensor 10 and an imager 13, a functional unit for determining the target object from the detection result, including an target object determination unit 20, a functional unit for generating a map related to the travel of the self-propelled processing device 100, and a functional unit related to the physical operation of the self-propelled processing device 100, including a drive unit 41 and an inactivation processing unit 45.

The position sensor 10 is a sensor that detects and acquires a first positional relationship at a first height H1 and a second positional relationship at a second height H2. The position sensor 10 includes a first sensor 11 used to detect the first positional relationship and a second sensor 12 used to detect the second positional relationship. In this embodiment, both the first sensor 11 and the second sensor 12 are 2D-LiDAR that acquire the positions and distances of surrounding objects.

The first sensor 11 and the second sensor 12 can measure the distance to an object by emitting laser light that passes through the plane of the first height H1 and the second height H2 from the traveling surface 200 and receiving the laser light reflected from the object. The first sensor 11 and the second sensor 12 can also measure the position of the object relative to the self-propelled processing device 100 by rotating the laser light in a plane parallel to the traveling surface 200 and measuring the distance to the object at each predetermined angle.

The types of the first sensor 11 and the second sensor 12 are not particularly limited as long as they can acquire the relative positional relationship, including the distance, between the self-propelled processing device 100 and objects present around the self-propelled processing device 100, and multiple types of sensors with different functions may be provided. Other examples of the first sensor 11 and the second sensor 12 mentioned above include an ultrasonic sensor, a LiDAR sensor, an RGB camera, a DEPTH camera, an infrared distance measuring sensor, a wheel odometry sensor, a gyro sensor, and the like.

The imager 13 is a device that captures an image of the surroundings of the self-propelled processing device 100 to obtain the image. Unlike the position sensor 10 described above, the imager 13 is an RGB sensor that receives natural light reflected from an object or the like with an image sensor having image sensors arranged in a two-dimensional plane, and obtains a planar image including RGB information corresponding to each image sensor on the two-dimensional plane. The image acquired by the imager 13 is used to detect an object reflected in the image by image recognition technology that makes full use of machine learning, etc. In this case, if the image acquired by the imager 13 includes distance information, it is possible to detect the object reflected in the image with higher accuracy. Therefore, the imager 13 may be an RGB-D sensor that acquires an image including RGB-D information.

The imager 13 may be a single camera capable of capturing images of the surroundings of the self-propelled processing device 100 all at once, such as a spherical camera, or may be configured with multiple cameras each capturing images in radial directions centered on the self-propelled processing device 100, or may be configured such that a single camera can change its posture to capture images of the surroundings in all directions from the self-propelled processing device 100.

The object determination unit 20 is a processing device that detects an object position relative to itself based on the first positional relationship and the second positional relationship acquired by the position sensor, based on the difference between the two positional relationships, and determines an object in a predetermined space 150 that corresponds to the detected object position as an object 81. The object determination unit 20 determines the object 81 to be subjected to the inactivation process from the first positional relationship and the second positional relationship, for example, by executing a predetermined program using a processor and a memory.

The object determining unit 20 includes a sensor data acquiring unit 21 and an object position detecting unit 25. The sensor data acquiring unit 21 includes a first acquiring unit 22, a second acquiring unit 23, and a third acquiring unit 24.
The first acquisition unit 22 is a processing unit that acquires the first positional relationship from the first sensor 11. The second acquisition unit 23 is a processing unit that acquires the second positional relationship from the second sensor 12. Furthermore, the third acquisition unit 24 is a processing unit that acquires an image from the imager 13. The processing of the image acquired by the third acquisition unit 24 will be described later.

The first positional relationship and the second positional relationship acquired by the first acquisition unit 22 and the second acquisition unit 23 are output to the target position detection unit 25. The target position detection unit 25 acquires the output first positional relationship and the second positional relationship, and calculates the area of difference between these positional relationships as described above. The target position is detected as the area of the calculated difference. For example, this target position may be determined as the target object 81 as it is, or an object corresponding to the target position remaining after a process of removing noise, etc. from the target position may be determined as the target object 81.

For example, multi-seater benches and handrails 97 often extend a certain length along a wall surface, and such information may be used to determine the target object 81 after removing objects that do not extend a sufficient length from the target position, which is the calculated difference region. In addition, various additional information and existing noise removal techniques may be applied to process the target position, which is the calculated difference region, and the object corresponding to the processed target position may be determined as the target object 81.

In the subsequent processing, the information on the target position is used. In other words, determining the target object 81 as an object is not essential in the actual processing in the self-propelled processing device 100. Determining the target object 81 may mean deciding whether or not to use the detected target position, including deciding to use the target position detected as described above, and deciding to use the target position after processing the detected target position to remove noise, etc.

The self-position detection unit 31 is a processing unit that is realized by executing a predetermined program using a processor and a memory. The self-position detection unit 31 acquires a map for self-position estimation that corresponds to a measured space, which is a space in which the position sensor 10 can measure the position and distance of an object. The self-position detection unit 31 may acquire the map for self-position estimation from a terminal device 93, a server, or the like. In the case of this embodiment, the self-position detection unit 31 generates a map for self-position estimation related to the surrounding environment of the vacuum cleaner that is parallel to the running surface 200 at the first height H1, for example by SLAM technology, based on the information acquired from the position sensor 10.

The self-position detection unit 31 may generate a map for self-position estimation by adding information from other sensors such as wheel odometry and gyro sensors in addition to the sensing information from the 2D-LiDAR position sensor 10. The generated map for self-position estimation is stored in the memory unit 33.

The self-location detection unit 31 further detects its own location using the positional relationship acquired from the position sensor 10 and the self-location estimation map. In this embodiment, the self-location detection unit 31 detects its own location by estimation using SLAM. In other words, the self-location detection unit 31 generates a self-location estimation map while detecting its own location using SLAM, and sequentially updates its own location and the self-location estimation map.

The map information generating unit 32 uses the self-location estimation map, the target position, which is the position of the object 81, the positions of obstacles, etc. on the traveling surface 200, and a floor map, etc. to generate an inactivation route that indicates the traveling route along which the self-propelled processing device 100 should travel in order to inactivate the object 81. When a new target position is detected based on the first positional relationship and the second positional relationship newly acquired while traveling within the specified space 150, the map information generating unit 32 performs the inactivation process while adding the object 81 corresponding to this target position to the new inactivation route. Therefore, the inactivation route is also updated successively as the vehicle travels.

The floor map used above is acquired by a floor map acquisition unit (not shown). There are no particular limitations on where the floor map is acquired from. For example, the floor map acquisition unit may acquire the floor map from a server or the like via a network and output it to the map information generation unit 32. The floor map acquisition unit may also accept the generation or modification of the floor map through user input via a terminal device 93 (see FIG. 8 described later). The floor map acquisition unit may also acquire a floor map generated using sensor data detected by the self-propelled processing device 100 itself when the self-propelled processing device 100 is test driven.

The map information generating unit 32 generates the above-mentioned inactivation pathway by executing a predetermined program using a processor and memory. The map information generating unit 32 may automatically generate the inactivation pathway, or may accept the generation or modification of the inactivation pathway by user input via the terminal device 93. The inactivation pathway may also include information indicating the degree and method of inactivation processing linked to the pathway. The generated inactivation pathway is stored in the memory unit 33.

When the map information generating unit 32 generates an inactivation path, if multiple objects 81 are present within the specified space 150, priority information regarding the order in which objects 81 should be given priority for inactivation processing may be used. For example, the priority is set to be higher for objects closer to the starting position where the self-propelled processing device 100 starts traveling to inactivate the objects 81. Additionally, the priority may be set based on user designation or certain rules. An example of this will be described later.

The memory unit 33 is an example of a storage device, and is a device for storing information, which is composed of a semiconductor memory or the like. The memory unit 33 acquires and stores the inactivation pathway generated as described above, and reads it out as necessary and outputs it to other components. In addition to the inactivation pathway described above, the memory unit 33 stores programs executed in various processing units. The memory unit 33 may also function as a memory when the processor of each processing unit executes a program. In this case, the memory unit 33 may be configured to have a volatile storage area in addition to a non-volatile storage area. The memory unit 33 may also store detection data acquired by the position sensor 10 and the imager 13, etc.

The drive unit 41 is a traveling mechanism for causing the self-propelled processing device 100 to travel on the traveling surface. The drive unit 41, for example, acquires a control signal from the control unit 43 described below, and transmits power according to the control signal to the wheel motor 42. The wheel motor 42 has a rotating shaft and a main body, and the main body is fixed to the housing of the self-propelled processing device 100. When the rotating shaft rotates relative to the main body in response to the power from the drive unit 41, the wheels fixed to the rotating shaft rotate, moving the main body together with the housing of the self-propelled processing device 100. In this way, the self-propelled processing device 100 travels on the traveling surface 200 in accordance with the control signal from the control unit 43.

The control unit 43 generates control signals for controlling each part of the self-propelled processing device 100 by executing a predetermined program using a processor and memory. The control unit 43 acquires the inactivation route generated by the map information generation unit 32, and the map for self-location estimation generated by the self-location detection unit 31 and the detected self-location. The acquisition of the inactivation route and the like is performed by the map information acquisition unit 44. The map information acquisition unit 44 accesses the self-location detection unit 31 and the map information generation unit 32 or the memory unit 33 to acquire the map for self-location estimation, the self-location, and the inactivation route.

The control unit 43 outputs a control signal to the drive unit 41 to drive the self-propelled processing device 100 according to the acquired inactivation path, etc. When the control unit 43 acquires from the first sensor 11, etc., that an object, etc. is present on the travel path, it outputs a control signal to drive the self-propelled processing device 100 while avoiding the object. The control unit 43 also outputs a control signal to the inactivation processing unit 45, described below, at the timing when a predetermined position on the path coincides with the control unit's own position, depending on the degree and method of inactivation processing indicated on the inactivation path, to operate the inactivation processing unit 45.

The inactivation processing unit 45 is a functional unit for performing an inactivation process on the object 81. The inactivation processing unit 45 has a sprayer 46 and a UV irradiator 47. The inactivation processing unit 45 performs an inactivation process on the object 81 by operating at least one of the sprayer 46 and the UV irradiator 47 in response to a control signal from the control unit 43.

The sprayer 46 is a device for dispersing the inactivating substance over a wide area by spraying a mist of liquid containing the inactivating substance for inactivating the target object 81. The sprayer 46 sprays the liquid by switching the spray amount and mist diameter depending on the level of inactivation treatment indicated in the inactivation path. The sprayer 46 may hold multiple types of liquid individually and switch the type of liquid to be sprayed depending on the level of inactivation treatment for the target object 81.

The sprayer 46 sprays liquid onto the object 81 from a position higher than the second height H2, thereby inactivating any deposits on the upper surface of the object 81. The sprayer 46 may also inactivate any deposits on the lower surface of the object 81 by dispersing liquid from below the object 81 so that the liquid reaches the second height H2 as necessary. Spraying may also be performed from a position away from the object 81 depending on the elevation angle or depression angle from the position where the sprayer 46 of the self-propelled processing device 100 is installed to the second height H2. For this reason, the control unit 43 may output a control signal to cause the drive unit 41 to travel to a position away from the object 81.

In addition, if the target object 81 is configured to extend in a predetermined direction, such as a handrail 97 or a multi-seater bench, the control unit 43 may control the drive unit 41 to drive the self-propelled processing device 100 in a predetermined direction while spraying with the sprayer 46.

Examples of liquids sprayed from the sprayer 46 include ethanol, hypochlorous acid water, benzalkonium chloride aqueous solution, surfactants, and other liquids such as bactericides, disinfectants, and sanitizers that have the effect of destroying and inactivating bacteria and viruses. In addition, liquids sprayed from the sprayer 46 may include sterilizing agents that more powerfully destroy bacteria, antibacterial agents that suppress the growth of bacteria, and sterilizing agents that reduce the absolute number of bacteria.

In this manner, inactivation of adhesions in this disclosure is a concept that encompasses any measure that suppresses the activity of adhesions in terms of the risk of infection, such as destroying the adhesions themselves to suppress their infectious potential, moving the adhesions to a place (such as a floor) that is less likely to be touched by humans 99 using a substance with a cleaning effect, and reducing the number of adhesions that will adhere in the future.

The UV irradiator 47 is a device that irradiates the surface of the object 81 with UV light to destroy and inactivate bacteria, viruses, and the like that are attached to the surface. The UV irradiator 47 irradiates UV light by switching the irradiation time and irradiation intensity (or wavelength) depending on the level of inactivation treatment indicated in the inactivation path.

Next, the operation of the self-propelled processing device 100 described above will be described with reference to Figures 4 to 8. Figure 4 is a flowchart showing the operation of the self-propelled processing device according to the embodiment.

As shown in FIG. 4, when the self-propelled processing device 100 starts traveling from a start position set in the specified space 150, it first acquires map information (step S101). This map information is a map for self-location estimation and an inactivated route. If the self-propelled processing device 100 has traveled within the specified space 150 in the past, the memory unit 33 reads out the stored map for self-location estimation and the inactivated route and outputs them to the map information acquisition unit 44 to acquire map information. On the other hand, if it is the first time the self-propelled processing device 100 has traveled within the specified space 150, the self-propelled processing device 100 acquires map information by generating map information while traveling.

The self-propelled processing device 100 updates the acquired map information and performs driving and deactivation processing in accordance with the map information. Specifically, the first sensor 11 acquires a first positional relationship, and the second sensor 12 acquires a second positional relationship (step S102). The self-position detection unit 31 acquires information on these positional relationships and detects its own position (step S103). The self-position detection unit 31 also sequentially updates the map for self-position estimation and its own position.

The first acquisition unit 22 acquires the first positional relationship. The second acquisition unit 23 acquires the second positional relationship. The target position detection unit 25 calculates a difference area based on the acquired first positional relationship and second positional relationship to detect the target position. The target determination unit 20 thus determines the object corresponding to the detected target position as the target object 81 (step S104).

If, for example, there is an object 81 among the determined objects 81 that is not included in the inactivation route already stored in the memory unit 33, the map information generating unit 32 updates the inactivation route by including the object 81 as a new object 81. If it is the first time that the self-propelled processing device 100 is traveling, all of the determined objects 81 are new objects 81, and therefore an inactivation route that includes all of them is generated.

Based on the map information thus generated by successively updating it, the control unit 43 drives the self-propelled processing device 100 toward the position of the object 81 (i.e., the target position) and approaches the object 81. After reaching the position where the liquid is sprayed by the sprayer 46 or the position where UV light is irradiated by the UV irradiator 47, the control unit 43 causes the inactivation processing unit to perform inactivation processing on the object 81 (step S105).

Here, FIG. 5 is a flowchart showing the operation of the travel and inactivation process by the self-propelled processing device according to the embodiment. FIG. 6 is a first diagram explaining an example of use of the imager according to the embodiment. FIG. 7 is a second diagram explaining an example of use of the imager according to the embodiment. FIG. 5 shows more detailed operations for step S105 above.

As shown in FIG. 5, when the target object 81 is determined, the self-propelled processing device 100 starts moving to the target position corresponding to the target object 81 (step S201). At this time, the imager 13 captures the surroundings of the moving self-propelled processing device 100 to acquire the image (step S202). The target determination unit 20 acquires the captured image and determines whether or not a predetermined target object 83 to be processed has been detected (step S203). Note that the surroundings of the self-propelled processing device 100 here is a range centered on the self-propelled processing device 100, in which the target object 83 is reflected in the captured image at a detectable size.

When it is determined that the object to be processed 83 has been detected in the image, for example, as shown in FIG. 6, the object to be processed 83 is present around the route along which the self-propelled processing device 100 travels. The object to be processed is an object that is difficult to determine as the object 81 because it is difficult to detect based on the difference between the first positional relationship and the second positional relationship, and is also an object that is often touched by a person 99. In the example in the figure, a call button installed on each floor to move the elevator car to each floor is detected as the object to be processed.

The call button is installed along the wall surface with almost no irregularities, making it difficult to detect as the target object 81. Other objects to be processed include objects that are composed of minute irregularities that are difficult to detect with LIDAR. For example, examples of the target object 83 include doorknobs, wall switches, and wall-mounted touch panel input devices.

The program constituting the object determination unit 20 incorporates, for example, a trained processed object detection model that has been trained on multiple images of the same type of processed object 83, and can determine whether or not a predetermined processed object 83 is included in an input image. This determination allows detection of the processed object 83 in the image.

Returning to FIG. 5, if the object determination unit 20 detects the target 83 (Yes in step S203), the detected target 83 is also inactivated. Specifically, the map information generation unit 32 adds the position where the target 83 is detected to the inactivation route by image analysis or the like, and updates the inactivation route. Based on the updated inactivation route, the control unit 43 controls the drive unit 41 to drive the self-propelled processing device 100 toward the position where the target 83 is detected. After the self-propelled processing device 100 moves to a position close to the target 83 appropriate for inactivation, the control unit 43 controls the inactivation processing unit 45 to perform inactivation processing on the target 83 (step S204).

On the other hand, if the object determination unit 20 does not detect the object to be processed 83 (No in step S203), the control unit 43 determines whether or not the object has arrived at the proximity position of the object 81 (step S205). If the control unit 43 determines that the object has not arrived at the proximity position of the object 81 (No in step S205), the process returns to step S201 and is repeated.

In this way, the self-propelled processing device 100 also performs inactivation processing on the target object 83 each time the target object 83 is detected until the self-propelled processing device 100 arrives at a position close to the target object 81. Note that the inactivation processing of the target object 83 may be performed after the target object 81. In other words, the self-propelled processing device 100 may detect the target object 83 and store its position until it arrives at a position close to the target object 81, and after the inactivation processing of the target object 81 is completed, the self-propelled processing device 100 may perform inactivation processing on the target object 83 again.

When the control unit 43 determines that the object 81 has arrived at a position close to the object 81 (Yes in step S205), the imager 13 acquires an image of the periphery of the object 81 (step S206). Thereafter, the object determination unit 20 performs image analysis in the same manner as described above to determine whether or not a person 99 has been detected in the acquired image (step S207). In other words, the object determination unit 20 determines whether or not a person 99 is present around the object 81. For example, as shown in FIG. 6, when the object 81 is a bench, the periphery of the object 81 means the three-dimensional periphery of the object 81, including the person 99 sitting on the seat of the bench. The periphery of the object 81 is a range in which the person 99 interferes with the inactivation process of the object 81, or in which the mist from the sprayer 46 or the UV light from the UV irradiator 47 reaches the person 99 by a predetermined amount or more during the inactivation process.

In such a case, the object 81 may not be appropriately inactivated, or the inactivation process may have a negative effect on the person 99. Therefore, when the object determination unit 20 determines that a person 99 has been detected in the image (Yes in step S207), the object 81 is stored as a specific object (step S208). In this embodiment, the self-propelled processing device 100 stores the object 81 that should not be inactivated at this time as a specific object in the memory unit 33, the position, the fact that the inactivation process could not be performed due to the detection of the person 99, the date and time, etc., so that when the inactivation process is performed again in the specified space 150 later, the specific object can be inactivated in priority over other objects 81.

In addition, by storing the detection of the presence of a person 99 in the memory unit 33 or the like in this manner, it is possible to calculate the frequency with which a person 99 is detected around the object 81. The higher this frequency is, the higher the priority of the inactivation process is set, and the inactivation process can be performed on each of the multiple objects 81 within the specified space 150 in order of priority.

Accordingly, even if the object 81 at the target position has a difference area calculated based on the first positional relationship and the second positional relationship, if the object is actually an object that is not often touched by a person 99, the priority of the inactivation process for such an object 81 can be lowered. On the other hand, the priority of the inactivation process for an object 81 that is estimated to be easy for a person 99 to touch because people 99 are more frequently present in the vicinity can be increased. Therefore, the inactivation process for the object 81 that is easy for a person 99 to touch can be more appropriately performed.

In particular, there are cases where an object 81 where the presence of a person 99 has not been detected in the past may be excluded from the target of the inactivation process. Therefore, the object position detection unit 25 may detect as the target position a position based on the difference between the first positional relationship and the second positional relationship, and a position around which the object determination unit 20 has previously detected the presence of a person 99. This makes it possible to prevent an object 81 that is rarely approached by a person 99 from being determined as a target of the inactivation process.

In the above example, the imager 13 is used as an example of a human sensor. Other types of human sensors, such as infrared sensors, can also be used.

Returning to FIG. 5, if the object determination unit 20 determines that a person 99 has not been detected in the image (No in step S207), the control unit 43 controls the inactivation processing unit 45 to perform inactivation processing on the object 81 (step S209).

Returning to FIG. 4, after step S105 is completed, the control unit 43 refers to the inactivation path and determines whether or not the inactivation process has been performed on all objects 81 in the specified space 150, or whether the objects 81 have been stored as specific objects (step S106). If the control unit 43 determines that none of the above processes have been performed on all objects 81 in the specified space 150 (No in step S106), the process proceeds to step S107 for the inactivation process on the next object 81. In step S107, the process is essentially the same as step S105, except that the object is the next object 81, and therefore will not be described here.

On the other hand, if the control unit 43 determines that any of the above processes have been performed on all objects 81 in the specified space 150 (Yes in step S106), the control unit 43 notifies the terminal device 93 owned by the user of the result of the inactivation process (step S108). FIG. 8 is a diagram showing an example of the notification of the result of the inactivation process according to the embodiment. For example, the control unit 43 and the terminal device 93 are capable of communicating information with a server or the like via a network or the like. As a result, the control unit 43 and the terminal device 93 are capable of communicating information with each other via a server or the like.

The terminal device 93 is equipped with a communication device that acquires information from the self-propelled processing device 100, processes the acquired information, and is equipped with a display means such as a display that can display the processed content to the user. Examples of the terminal device 93 include a so-called smartphone, a so-called tablet, a so-called notebook computer, and a so-called desktop computer. For example, as shown in FIG. 8, the result of the inactivation process is presented as a map-like image. In this map, the position of the object 81 similar to that in FIG. 1(c) (a place with high density dot hatching) and the presence or absence of the inactivation process for the object 81 are displayed by a circle or a cross mark. For example, as shown by the cross mark on the left side of the map in the figure, the image presented to the user shows the object 81 that was stored as a specific object and was not subjected to the inactivation process due to the presence of a person 99 detected in step S207.

Also, like the circle in the upper center of the map in the figure, the image presented to the user shows the location where the inactivation process was performed because the target object was detected in step S203, even if it is not the object 81. In this way, the notification is sent to the terminal device 93, so that the status of the inactivation process for the specified space 150 can be seen at a glance.

As described above, the self-propelled processing device 100 in this embodiment autonomously travels in a predetermined space and performs an inactivation process on the target object 81 to inactivate the attachment attached to the target object 81. The self-propelled processing device 10 includes a position sensor 10 that acquires a positional relationship between the self and an object present in a two-dimensional measured space along the running surface 200 of the self-propelled processing device 10, which acquires a first positional relationship that is a positional relationship of a first height H1 in a height direction intersecting with the running surface 200, and a second positional relationship that is a positional relationship of a second height H2 in the height direction, an object determination unit 20 that detects an object position, which is a position within a predetermined space 150, based on the difference between the first positional relationship and the second positional relationship, and determines an object corresponding to the detected target position as the target object 81, and an inactivation processing unit 45 that performs an inactivation process on the determined object 81.

Such a self-propelled processing device 100 can mechanically determine the object 81 located at the second height H2 based on the first positional relationship and the second positional relationship acquired by the position sensor 10. Since the object 81 can be determined mechanically, there is no need for the user to specify all the objects 81, and even if new objects 81 are added, they can be automatically detected. As a result, the object 81 located at the second height H2 in the specified space 150 can be appropriately determined and inactivation processing can be performed. Therefore, it is possible to efficiently suppress the risk of infection due to attachments on objects located higher than the floor surface.

Also, for example, the target object determination unit 20 may determine an area in the measured space where there is a difference between the first positional relationship and the second positional relationship as a target area, and detect a position in the specified space 150 that corresponds to the target area as a target position.

This allows a difference region (i.e., target region) where a difference exists between the first positional relationship and the second positional relationship to be calculated, and a position corresponding to the difference region to be detected as a target position. As a result, an object in a predetermined space 150 that corresponds to the target position is mechanically determined as a target object 81.

In addition, for example, a human sensor (e.g., an imager 13) different from the position sensor 10 may be provided, and when the inactivation processing unit 45 performs the inactivation processing on the object 81, if the human sensor detects a person 99 present around the target position, the inactivation processing unit 45 may not need to perform the inactivation processing on the object 81 corresponding to the target position around which the person 99 is detected.

According to this, when an inactivation process is performed on an object 81, if a person 99 who may be affected by the inactivation process is present, it is possible to select not to perform the inactivation process on the object 81. In other words, it is possible to safely perform the inactivation process on the object 81 in the specified space 150 without the need to notify the person 99.

In addition, for example, a storage device (e.g., storage unit 33) may be provided that stores objects 81 that have not been subjected to inactivation processing as specific objects, and the previously stored specific objects may be subjected to inactivation processing in priority over other objects 81 within the specified space 150.

This allows the inactivation process to be performed again on objects 81 (specific objects) that have not been inactivated once, with priority over other objects 81. Objects 81 that have not been inactivated for some reason have an increased risk of infection due to proliferation of attached matter, and so by performing the inactivation process with priority over other objects 81, the risk of infection can be preferentially reduced.

In addition, for example, a human sensor (e.g., an imager 13) different from the position sensor 10 may be provided, and the higher the frequency with which the human sensor detects a person 99 present around the target position, the higher the priority may be set, and the inactivation process may be performed on each of the multiple objects 81 within the specified space 150 in descending order of priority.

This allows inactivation processing to be performed with priority on objects 81 that are estimated to have a higher risk of infection and are likely to be frequently occupied by people 99 in the vicinity.

In addition, for example, a human sensor (e.g., an imager 13) different from the position sensor 10 may be provided, and the target object determination unit 20 may detect as the target position a position based on the difference between the first positional relationship and the second positional relationship, and a position where the human sensor has previously detected the presence of a person 99 nearby.

In this way, since there are no people 99 in the vicinity, objects that are unlikely to have particles attached thereto by people 99 can be excluded from the target object 81, and other targets 81 that have a relatively high risk of infection can be inactivated.

For example, the self-propelled processing device 100 may further include an imager 13 that captures an image of the surroundings of the self-propelled processing device 100 to obtain the image. When a target object 83 that is a target of inactivation processing different from the target object 81 is detected in the image, the inactivation processing device may further perform inactivation processing on the target object 83 within the specified space 150.

This allows inactivation processing to be performed on the processing target 83 discovered by the imager 13.

Also, for example, the self-propelled processing device 100 may perform inactivation processing on each of a plurality of objects 81 within a specified space 150 in the order of proximity to the starting position where the self-propelled processing device 100 starts moving.

This simplifies the calculation process for the inactivation path, etc., and reduces the cost of calculation resources, compared to when the inactivation process of the target object 81 is performed by setting priorities according to predetermined rules, etc.

The object determination method in this embodiment is an object determination method used in a self-propelled processing device 100 that autonomously travels in a specified space 150 and performs an inactivation process on the object 81 to inactivate an attachment attached to the object 81, and obtains a first positional relationship that is a positional relationship between the self-propelled processing device 100 and an object present in a two-dimensional measured space along the running surface 200 of the self-propelled processing device 100 at a first height H1 in a height direction intersecting with the running surface 200 of the self-propelled processing device 100, and a second positional relationship that is a positional relationship between the self-propelled processing device 100 and an object present in the measured space at a second height H2 in the height direction, detects an object position, which is a position within the specified space 150, based on the difference between the first positional relationship and the second positional relationship, and determines the object corresponding to the detected object position as the object 81.

This makes it possible to determine the target object 81 to achieve the same effect as the self-propelled processing device 100 described above.

The program in this embodiment is a program for causing a computer to execute the object determination method described above.

This allows a computer to be used to execute a method for determining an object 81 to achieve the same effect as the self-propelled processing device 100 described above.

(Other embodiments)
The present invention is not limited to the above-mentioned embodiment. For example, the components described in this specification may be combined in any way, or some of the components may be removed to create another embodiment of the present invention. In addition, the present invention also includes modifications that are made to the above-mentioned embodiment by those skilled in the art without departing from the spirit of the present invention, that is, the meaning of the words described in the claims.

In the above embodiment, the self-propelled processing device is realized by a single device, but it may be a self-propelled processing system realized by multiple devices working together. For example, a self-propelled processing system can be realized by enabling communication between a server device having the function of the object determination unit in the above embodiment and a self-propelled processing device having only the other functions of the self-propelled processing device in the above embodiment. In addition, the server device can be made to execute a program to detect an object position and determine an object based on a first positional relationship and a second positional relationship.

In addition, the processing performed by a specific processing unit may be executed by another processing unit. Furthermore, the communication method between the devices in the above embodiment is not particularly limited. When two devices communicate in the above embodiment, a relay device (not shown) may be interposed between the two devices.

The order of the processes described in the above embodiment is merely an example. The order of the processes may be changed, and the processes may be performed in parallel.

The above-mentioned self-propelled treatment device may also be combined with a configuration that collects bacteria, viruses, etc. scattered on the floor surface by suctioning the floor surface. It is considered that people who may touch the object tend to gather around the object described in the above embodiment. As a result, there is a possibility that a relatively large amount of bacteria, viruses, etc. may be scattered on the floor surface around the object compared to other floor surfaces. In other words, bacteria, viruses, etc. can be removed more efficiently by simply combining the floor suction function with the self-propelled treatment device.

In the above embodiment, the position sensor is configured to have separate sensors for acquiring the first positional relationship at the first height and the second positional relationship at the second height, but the position sensor is not limited to this. For example, FIG. 9 is a schematic diagram showing a position sensor of a self-propelled processing device according to variant example 1. The position sensor 10a in this example is configured to acquire the first positional relationship and the second positional relationship using only the first sensor 11a. The position sensor 10a here has a switching mechanism 11b. The switching mechanism 11b is configured to rotatably support the first sensor 11a. In addition, the switching mechanism 11b is provided with an actuator (not shown) for rotating the first sensor 11a.

The first sensor 11a can be switched between a first mode (represented by a dashed line) in which light is emitted and received toward a first height H1, and a second mode (represented by a solid line) in which light is emitted and received toward a second height, as shown by the open double-headed arrow. As a result, the first sensor 11a is capable of acquiring a first positional relationship in the first mode and acquiring a second positional relationship in the second mode, all by using a single sensor. Such a position sensor 10a may be applied to a self-propelled processing device.

Thus, in the self-propelled processing device of variant example 1, the position sensor 10a has a switching mechanism 11b that can switch between a first mode for acquiring a first positional relationship and a second mode for acquiring a second positional relationship.

This allows the position sensor for acquiring the two positional relationships to be shared, making it possible to realize a self-propelled processing device that is advantageous in terms of cost.

In the above embodiment, a configuration using only the positional relationship between the first height and the second height has been described. For example, in addition to the above, a positional relationship at a third height may also be combined. This makes it possible to detect objects such as benches at the second height and objects such as handrails at the third height. In other words, it becomes possible to simultaneously detect two or more types of objects at different heights and perform inactivation processing all at once. In this configuration, it is preferable to further include a third sensor and a fourth acquisition unit.

Furthermore, another example of using the third positional relationship at the third height will be described. FIG. 10 is a diagram for explaining detection of an object position by a self-propelled processing device according to variant example 2. FIG. 10 shows a side view of an object 81 as seen from a direction along a wall surface. In this example, an object 81 present at the second height H2 is detected using the positional relationships at the first height H1 and the third height H3 as well.

For example, when a difference area is calculated between the first positional relationship and the second positional relationship of the first height H1 and the second height H2, it may be formed by the design of the wall. Therefore, a configuration may be adopted in which the target area is detected and the target object 81 is determined only when a difference area is calculated between the first positional relationship and the second positional relationship of the first height H1 and the second height H2, and a difference area is calculated between the second positional relationship and the third positional relationship of the second height H2 and the third height H3. The relationship between the first height H1 and the second height H2 is the same as in the above embodiment, but the relationship between the second height H2 and the third height H3 is set to about 5.0 to 10 cm, which is appropriate for a person to grasp the third height H3 and the second height H2. This allows the presence or absence of unevenness between the first positional relationship and the second positional relationship to be detected, and cases in which the unevenness continues in the height direction between the second positional relationship and the third positional relationship to the extent that it is not expected for a person to grasp the object can be excluded.

In addition, by combining the third positional relationship with various thresholds, it becomes possible to detect objects that people may touch in more detail.

In this way, in the self-propelled processing device according to variant example 2, the position sensor 10 acquires a third positional relationship, which is a positional relationship at a third height H3 in a height direction intersecting with the traveling surface, and the target determination unit 20 detects a target position, which is a position within a specified space 150, based on the difference between the first positional relationship, the second positional relationship, and the third positional relationship.

This allows for more appropriate detection of the target position and determination of the target object by further combining a third positional relationship.

In addition, in the above embodiment, each component may be realized by executing a software program suitable for each component. Each component may be realized by a program execution unit such as a CPU or processor reading and executing a software program recorded on a recording medium such as a hard disk or semiconductor memory.

Furthermore, each component may be realized by hardware. For example, each component may be a circuit (or an integrated circuit). These circuits may form a single circuit as a whole, or each may be a separate circuit. Furthermore, each of these circuits may be a general-purpose circuit, or a dedicated circuit.

In addition, the general or specific aspects of the present invention may be realized as a system, an apparatus, a method, an integrated circuit, a computer program, or a computer-readable recording medium such as a CD-ROM. Also, the present invention may be realized as any combination of a system, an apparatus, a method, an integrated circuit, a computer program, and a recording medium. For example, the present invention may be implemented as a delivery notification method executed by a computer such as a delivery notification system, or may be realized as a program for causing a computer to execute such a delivery notification method. Also, the present invention may be realized as a computer-readable non-transitory recording medium on which such a program is recorded.

In addition, the present invention also includes forms obtained by applying various modifications to each embodiment that a person skilled in the art may conceive, or forms realized by arbitrarily combining the components and functions of each embodiment within the scope of the spirit of the present invention.

This disclosure can be used for inactivation processing of objects that move autonomously and can be touched by humans.

10, 10a Position sensor 11, 11a First sensor 11b Switching mechanism 12 Second sensor 13 Imaging device 20 Object determination unit 21 Sensor data acquisition unit 22 First acquisition unit 23 Second acquisition unit 24 Third acquisition unit 25 Object position detection unit 31 Self-position detection unit 32 Map information generation unit 33 Memory unit 41 Drive unit 42 Wheel motor 43 Control unit 44 Map information acquisition unit 45 Inactivation processing unit 46 Sprayer 47 UV irradiator 81 Object 83 Object to be treated 93 Terminal device 96 Chair 97 Handrail 98 Boundary 99 Person 100 Self-propelled processing device 150 Predetermined space 200 Travel surface

Claims (12)

A self-propelled treatment device that autonomously travels in a predetermined space and performs an inactivation treatment on an object, thereby inactivating an attachment attached to the object,
a position sensor that acquires a positional relationship between the self-propelled processing device and an object that exists in a two-dimensional measured space along a traveling surface of the self-propelled processing device, the position sensor acquiring a first positional relationship that is the positional relationship at a first height in a height direction intersecting the traveling surface, and a second positional relationship that is the positional relationship at a second height in the height direction that is different from the first height;
an object determination unit that detects an object position that is a position in the predetermined space based on a difference between the first positional relationship and the second positional relationship, and determines the object corresponding to the detected object position as the object;
and an inactivation processing unit that performs the inactivation processing on the determined object. The self-propelled processing device according to claim 1 , wherein the target determination unit detects an area in the measured space where a difference exists between the first positional relationship and the second positional relationship as a target area, and detects a position in the specified space corresponding to the target area as the target position. The self-propelled processing device according to claim 1 or 2, wherein the position sensor has a switching mechanism capable of switching between a first mode for acquiring the first positional relationship and a second mode for acquiring the second positional relationship. Further, a human sensor different from the position sensor is provided,
When performing the inactivation treatment on the object, the inactivation treatment unit
The self-propelled processing device according to any one of claims 1 to 3, wherein when the human sensor detects a person present around the target position, the inactivation process is not performed on the object corresponding to the target position where a person is detected around. Further, a storage device is provided for storing the object that has not been subjected to the inactivation treatment as a specific object,
The self-propelled processing device according to claim 4 , wherein the inactivation process is performed on the specific object stored in the past with priority over other objects in the predetermined space. Further, a human sensor different from the position sensor is provided,
The higher the frequency with which the human sensor detects a person present around the target position, the higher the priority is set;
The self-propelled processing device according to claim 1 , wherein the inactivation process is performed on each of the plurality of objects in the predetermined space in descending order of priority. Further, a human sensor different from the position sensor is provided,
The self-propelled processing device according to any one of claims 1 to 6, wherein the target object determination unit detects as the target position a position based on a difference between the first positional relationship and the second positional relationship, and a position where the human sensor has previously detected the presence of a human in the vicinity. the position sensor acquires a third positional relationship, which is the positional relationship at a third height different from the first height and the second height in a height direction intersecting the traveling surface;
The self-propelled processing device according to any one of claims 1 to 7, wherein the target determination unit detects a target position, which is a position within the specified space, based on a difference between the first positional relationship, the second positional relationship, and the third positional relationship. Further, an image capturing device is provided for capturing an image of the surroundings of the self-propelled processing device,
A self-propelled processing device as described in any one of claims 1 to 8, wherein when a processed object that is the subject of the inactivation treatment different from the target object is detected in the image, the inactivation processing unit further performs the inactivation treatment on the processed object within the specified space. The self-propelled processing device according to any one of claims 1 to 9, wherein the self-propelled processing device performs the inactivation treatment on each of the plurality of objects in the specified space in order of proximity to a starting position where the self-propelled processing device starts moving. A method for determining an object to be processed in a self-propelled processing device that autonomously travels in a predetermined space and performs an inactivation process on an object to inactivate an object attached thereto, comprising:
A first positional relationship is obtained, which is a positional relationship between an object present in a two-dimensional measured space along the traveling surface and the self-propelled processing device at a first height in a height direction intersecting with a traveling surface of the self-propelled processing device, and a second positional relationship is obtained, which is a positional relationship between an object present in the measured space and the self-propelled processing device at a second height different from the first height in the height direction;
a target position, which is a position within the specified space, is detected based on a difference between the first positional relationship and the second positional relationship, and the object corresponding to the detected target position is determined as the target object. A program for causing a computer to execute the object determination method according to claim 11.

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