Measurement system, measurement device, measurement method, and program

Abstract

This invention provides a measurement system, measuring device, measurement method, and program capable of measuring the shape of transparent wall materials. [Solution] The measurement system includes a detection unit that detects the presence or absence of a transparent wall material with collision prevention processing, and a measurement unit that measures the shape of the transparent wall material when the presence of the transparent wall material is detected. Collision prevention marks SE1 to SE11 are attached to the glass wall G1, and when the mobile robot 300 is performing measurements while moving, the light rays of the environmental shape measuring device LD are reflected by the collision prevention marks SE1 and SE11 at the edge of the glass wall when moving from the concrete wall to the glass wall, so that the width of the glass wall can be accurately measured.

Description

Technical Field

[0001] The present invention relates to a measurement system, a measurement device, a measurement method, and a program.

Background Art

[0002] Environmental maps are created using mobile robots indoors and the like.

[0003] For example, Patent Document 1 discloses a robot device that autonomously exhibits behavior and controls the behavior in response to input information from the outside. The robot device includes a wireless tag reading means for reading data stored in a wireless tag provided on an object existing outside from the wireless tag, and a control means for controlling the behavior based on object-related information, which is information related to the object corresponding to the data of the wireless tag read by the wireless tag reading means.

Prior Art Documents

Patent Documents

[0004]

Patent Document 1

Summary of the Invention

Problems to be Solved by the Invention

[0005] In creating an environmental map, when there is a glass wall, the light beam used for measurement may pass through the glass wall, and the shape of the glass wall may not be measurable. However, in the technique described in Patent Document 1, it is necessary to attach an RFID to the glass wall, which may damage the aesthetic appearance of the glass wall. In addition, the communication distance between the RFID attached to the glass wall and the RFID reader mounted on the mobile robot may be short, and accurate measurement may not be possible. Thus, there has been a problem that the shape of a transparent wall material cannot be measured.

[0006] The present invention has been made in view of these circumstances, and its object is to provide a measurement system, a measurement device, a measurement method, and a program that can measure the shape of a transparent wall material. [Means for solving the problem]

[0007] To solve the above-mentioned problems, one aspect of the present invention is a measurement system comprising: a detection unit for detecting the presence or absence of a transparent wall material that has been subjected to collision prevention processing; and a measurement unit for measuring the shape of the transparent wall material when the presence of the transparent wall material is detected.

[0008] Furthermore, one aspect of the present invention is a measuring device comprising: a detection unit for detecting the presence or absence of a transparent wall material that has been subjected to collision prevention processing; and a measuring unit for measuring the shape of the transparent wall material when the presence of the transparent wall material is detected.

[0009] Furthermore, one aspect of the present invention is a measurement method for a measuring device, comprising: a detection step of detecting the presence or absence of a transparent wall material that has been subjected to collision prevention processing; and a measurement step of measuring the shape of the transparent wall material when the presence of the transparent wall material is detected.

[0010] Furthermore, one aspect of the present invention is a program that causes the computer of a measuring device to execute a detection step of detecting the presence or absence of a transparent wall material that has been processed to prevent collisions, and a measurement step of measuring the shape of the transparent wall material when the presence of the transparent wall material is detected. [Effects of the Invention]

[0011] As described above, according to one aspect of the present invention, the shape of a transparent wall material can be measured. [Brief explanation of the drawing]

[0012] [Figure 1] This is a system configuration diagram showing an example of the configuration of the measurement system SYS according to the first embodiment of the present invention. [Figure 2]It is a diagram showing an example of an assumed environment according to this embodiment. [Figure 3] It is a diagram showing a specific example of an assumed environment according to this embodiment. [Figure 4] It is a block diagram showing an example of the configuration of the server system 100 according to this embodiment. [Figure 5] It is an explanatory diagram showing an example of the first measurement by the mobile robot 300 according to this embodiment. [Figure 6] It is a diagram showing an example of the reception intensity of an electrical signal obtained by the first measurement by the mobile robot 300 according to this embodiment. [Figure 7] It is an explanatory diagram showing an example of the second measurement by the mobile robot 300 according to this embodiment. [Figure 8] It is a diagram showing an example of the reception intensity of an electrical signal obtained by the second measurement by the mobile robot 300 according to this embodiment. [Figure 9] It is an explanatory diagram showing an example of the (12.1 / cosθ)-th measurement by the mobile robot 300 according to this embodiment. [Figure 10] It is a diagram showing an example of the reception intensity of an electrical signal obtained by the (12.1 / cosθ)-th measurement by the mobile robot 300 according to this embodiment. [Figure 11] It is a diagram showing an example of integrating pulses with high reception intensity obtained in each measurement according to this embodiment. [Figure 12] It is a diagram showing an example when the pulses with high reception intensity obtained in each integrated measurement according to this embodiment are subjected to discrete Fourier transform. [Figure 13] It is a diagram showing an example of generating an environmental map according to this embodiment. [Figure 14] It is a diagram showing an example of generating an environmental map according to this embodiment. [Figure 15] It is a diagram showing an example of calculating the angle θ in the measurement system SYS according to this embodiment. [Figure 16] It is a flowchart showing an example of the measurement process in the measurement system SYS according to this embodiment. [Figure 17]It is a flowchart showing an example of measurement processing in the measurement system SYS according to the present embodiment.

Mode for Carrying Out the Invention

[0013] (First Embodiment) Hereinafter, the first embodiment of the present invention will be described with reference to the drawings. FIG. 1 is a system configuration diagram showing an example of the configuration of a measurement system SYS according to the first embodiment of the present invention. The measurement system SYS includes a server system 100 and a mobile robot 300. The server system 100 and the mobile robot 300 are communicably connected by a communication line.

[0014] The mobile robot 300 is a robot that has wheels for autonomous driving and moves autonomously. The mobile robot 300 has a power source, and the wheels are driven by the power generated by the power source. The power source is preferably an electromagnetic motor. The electromagnetic motor is, for example, a DC motor, a brushless DC motor, a stepping motor, a servo motor, an induction motor, a PM motor, an AC motor, an in-wheel motor, and an ultrasonic motor. The power source may be an internal combustion engine. The number of wheels and the installation position of the wheels are not particularly limited as long as the mobile robot can travel stably.

[0015] The mobile robot 300 includes an environmental shape measurement device LD. The environmental shape measurement device LD is used to realize the SLAM (Simultaneous Localization and Mapping) technology of the mobile robot 300. SLAM is a method of estimating the current position information of the mobile robot while creating a map (map) of the surroundings of the mobile robot acquired using the environmental shape measurement device LD, and is a technology for completing the entire map while expanding a new measurement area as the mobile robot travels. The method of calculating SLAM may be any method such as a scan matching method such as the ICP method or the NDT method, or a Bayesian filter method.

[0016] The environmental shape measurement device LD can be any type of device capable of measuring the shape of real space, but a Time of Flight (ToF) device such as a LiDAR (Light Detection And Ranging) device, which is a laser range scanner, is preferred. The mobile robot 300 may be driven manually by an operator while the operator checks the images captured by the camera, or it may be driven automatically by the operator specifying the route from the starting point to the goal point using a path search algorithm A* or the like, or both manual and automatic driving may be used in combination.

[0017] The environmental shape measuring device LD according to this embodiment is, for example, a LiDAR device. The environmental shape measuring device LD comprises a light ray irradiation unit that emits a light ray from the environmental shape measuring device LD, and a light receiving unit that receives the light ray reflected by the target object. The measurement by the environmental shape measuring device LD uses the Time of Flight (ToF) method, which measures the distance by the time it takes for a light ray to be emitted, reflected by the target object, and returned. Alternatively, the shape measurement by the environmental shape measuring device LD may use the Structure from Motion (SfM) method, which reconstructs the three-dimensional shape of the target object by combining multiple camera images of the target object, or a total station device.

[0018] The environmental shape measuring device (LD) can be selected as either a scanning type or a flash type. The scanning type measures the shape by shining a light ray onto a rotating polygon mirror, projecting one ray at a time onto the object, and sequentially receiving the reflected rays. On the other hand, the flash type diffuses the light ray from the light source with a splitter (diffraction grating) and simultaneously projects thousands of light rays using an FPA (Focal Plane Array) lined up at the focal plane, measuring the entire shape of the object at once. In this embodiment, an example of the scanning type will be described.

[0019] The server system 100 is a server device. The server system 100 is composed of a communication server device, a pulse storage server device, a discrete Fourier transform server device, and a map drawing server device. In this embodiment, an example of a case in which the server system 100 is configured as an integrated device will be described. The server system 100 acquires shape measurement information measured by the mobile robot 300 and performs a discrete Fourier transform based on the shape measurement information. The server system 100 uses the shape measurement information after the discrete Fourier transform to determine the presence or absence of a transparent wall and measures the shape of the transparent wall.

[0020] Here, the transparent wall material is a permeable wall material such as glass, acrylic, polyethylene terephthalate, polycarbonate, or polyvinyl chloride. In this embodiment, an example where the transparent wall is a glass wall will be described.

[0021] Figure 2 shows an example of the assumed environment according to this embodiment. The mobile robot 300 is assumed to perform shape measurement of a room R enclosed by opaque walls W1, W2, W3, and W4. In this case, it is assumed that a portion of opaque wall W1 is composed of glass wall G1, and a portion of opaque wall W3 is composed of glass wall G2. It is also assumed that room R contains obstacles such as pillars and desks, B1, B2, and B3. In this case, when the mobile robot 300 measures the shape of the glass wall while performing SLAM using the environmental shape measuring device LD, the light rays from the environmental shape measuring device LD pass through the glass walls G1 and G2, making it impossible to measure the shape of the glass wall. Therefore, the glass wall according to this embodiment is provided with collision prevention processing. Collision prevention processing involves placing (attaching) mark-shaped objects (collision prevention marks) on the surface of the glass wall to prevent people from colliding with the glass wall.

[0022] Figure 3 shows a specific example of the assumed environment according to this embodiment. For example, collision prevention marks SE1 to SE11 are affixed to glass wall G1. Collision prevention marks generally have a simple shape that does not detract from the aesthetics of glass walls, and are often disc-shaped so that they can be applied in any direction, but this is not the only option. The size of the collision prevention mark is generally designed to be φ30mm when the outer shape is disc-shaped. In this embodiment, the size of the collision prevention mark is preferably φ20mm or more and less than φ25mm when disc-shaped, next preferably φ25mm or more and less than φ30mm, and most preferably φ30mm or more and φ40mm or less.

[0023] The height at which collision prevention marks are affixed to glass walls is generally set to 120 cm, which is the midpoint between the eye level of an adult (140 cm) and the eye level of a child (100 cm). In this embodiment, we will describe the case where the collision prevention mark is affixed at a height H of 120 cm from the floor.

[0024] The spacing between adjacent collision prevention marks in the horizontal direction is usually around 30 cm. In this embodiment, the spacing between adjacent collision prevention marks in the horizontal direction may be designed to be around 30 cm, but 30 cm to 40 cm is preferable, less than 25 cm to less than 30 cm is next preferable, and 20 cm to 25 cm is most preferable.

[0025] Here, when attaching horizontally adjacent collision prevention marks to a glass wall, it is preferable to attach the collision prevention marks to both ends of the glass wall (the boundary between glass wall G1 and concrete wall W11, and the boundary between glass wall G1 and concrete wall W12), as shown in Figure 3. By doing so, when the mobile robot 300 is performing measurements while moving, the light rays from the environmental shape measuring device LD are reflected by the collision prevention marks SE1 and SE11 at the edges of the glass wall when transitioning from the concrete wall to the glass wall, allowing for accurate measurement of the width of the glass wall.

[0026] The material of the collision prevention mark is preferably one that is resistant to deterioration from rust, ultraviolet rays, etc., even when exposed to the elements for a long period of time. The material of the collision prevention mark may be, for example, metal (stainless steel, aluminum, etc.), glass (frosted glass), plastic (excluding black), ceramic (excluding black), rubber (excluding black), etc.

[0027] Collision prevention marks should preferably diffusely reflect the 905nm wavelength light beam from the environmental shape measuring device (LD). In particular, black collision prevention marks are undesirable because they absorb the light beam from the environmental shape measuring device (LD).

[0028] Next, the configuration of server system 100 will be described.

[0029] Figure 4 is a block diagram showing an example of the configuration of the server system 100 according to this embodiment. The server system 100 is comprised of a communication unit 110, a storage unit 120, an input unit 130, an output unit 140, and a control unit 150. The communication unit 110 has the function of communicating with the mobile robot 300.

[0030] The storage unit 120 is composed of a storage medium, such as an HDD (Hard Disk Drive), flash memory, EEPROM (Electrically Erasable Programmable Read Only Memory), RAM (Random Access read / write Memory), ROM (Read Only Memory), or any combination of these storage media. This storage unit 120 can, for example, use non-volatile memory.

[0031] The memory unit 120 stores various types of data. For example, the memory unit 120 stores pulses 121. Pulse 121 is measurement information acquired from the mobile robot 300.

[0032] The input unit 130 is an input device such as a mouse or keyboard connected to the server system 100. The input unit 130 receives operation input from an external source. The input unit 130 outputs an operation signal corresponding to the operation input to the control unit 150.

[0033] The output unit 140 is an output device such as a display device. The output unit 140 outputs the information output from the control unit 150 to its own output device or to another device.

[0034] The control unit 150 has the function of controlling each part of the server system 100. The control unit 150 is comprised of an acquisition unit 151, a discrete Fourier transform unit 152, a detection unit 153, and a measurement unit 154.

[0035] The acquisition unit 151 acquires measurement information measured by the environmental shape measuring device LD of the mobile robot 300. The acquisition unit 151 stores the measurement information as pulses 121 in the storage unit 120.

[0036] The Discrete Fourier Transform unit 152 reads the pulses 121 stored in the memory unit 120 and performs the Discrete Fourier Transform processing.

[0037] The detection unit 153 determines that it has detected a collision prevention mark attached to the glass wall if, among the discrete Fourier transformed pulses, it obtains a pulse with exceptionally high power compared to other pulses, that is, if there is a pulse with a significantly higher power compared to other pulses. In other words, the detection unit 153 detects the presence or absence of a glass wall based on the discrete Fourier transformed pulses.

[0038] The measurement unit 154 generates a pulse time-electrical signal intensity graph each time the environmental shape measuring device LD takes a measurement. The measurement unit 154 extracts the frequency by performing a discrete Fourier transform on this graph using the discrete Fourier transform unit 152, measures it as a glass wall, and plots it.

[0039] Next, we will describe in detail the measurements performed by the mobile robot 300 and the processing performed by the server system 100.

[0040] Figure 5 is an explanatory diagram showing an example of the first measurement performed by the mobile robot 300 according to this embodiment. Figure 6 shows an example of the received strength of an electrical signal obtained in the first measurement by the mobile robot 300 according to this embodiment. Let's consider a scenario where the mobile robot 300's environmental shape measuring device LD travels at an angle θ to a glass wall equipped with collision prevention marks 1 to 16, which are attached at equal intervals as shown in Figure 5. Furthermore, the distance between adjacent collision prevention marks (for example, the distance between collision prevention mark 1 and collision prevention mark 2) is assumed to be 0.4 m, the mobile robot's movement speed is assumed to be 1 m / second, and the environmental shape measuring device LD is assumed to be a scanning type with a rotation frequency of 30 Hz (0.033 seconds / scan). The environmental shape measuring device LD is assumed to be rotating counterclockwise.

[0041] When the environmental shape measuring device LD of the mobile robot 300 reaches the position shown in Figure 5, in other words, when it reaches position P1 where the environmental shape measuring device LD and the collision prevention mark 1 are at the first shortest distance from each other, the environmental shape measuring device LD performs its first scan, and that time is set as the start time (0 seconds later). In this case, the time-electrical signal intensity graph generated by the discrete Fourier transform unit 152 is shown in Figure 6. Here, the numbers at the top of the graph in Figure 6 correspond to the collision prevention marks 1 to 16 shown in Figure 5. As shown in Figure 6, the time-electrical signal intensity graph shows that the electrical signal intensity of collision avoidance mark 1 is the highest during the first scan.

[0042] Figure 7 is an explanatory diagram showing an example of a second measurement performed by the mobile robot 300 according to this embodiment. Figure 8 shows an example of the received strength of an electrical signal obtained in the second measurement by the mobile robot 300 according to this embodiment. Next, when the autonomously moving environmental shape measuring device LD performs a second scan as shown in Figure 7, that is, when 0.033 seconds have elapsed from the start time (when the environmental shape measuring device LD has moved 0.033 m in the direction of travel), the glass wall between collision prevention mark 1 and collision prevention mark 2 will be at position P2, which is the second shortest distance from the environmental shape measuring device LD. In this case, the light rays from the environmental shape measuring device LD will pass through the glass wall.

[0043] On the other hand, the environmental shape measuring device LD performs measurements sequentially on collision prevention mark 1, collision prevention mark 2, collision prevention mark 3, collision prevention mark 4, ..., and collision prevention mark 16. In this case, the distance between the environmental shape measuring device LD and collision prevention mark 1 is the shortest compared to the distance between the other collision prevention marks and the environmental shape measuring device LD. As a result, the intensity of the electrical signal from the reflected light rays from collision prevention mark 1 is higher than the intensity of the electrical signals from the other marks. The time-electrical signal intensity graph generated by the discrete Fourier transform unit 152 in this case is shown in Figure 8.

[0044] Figure 9 is an explanatory diagram showing an example of the 12.1 / cosθ measurement performed by the mobile robot 300 according to this embodiment. Figure 10 shows an example of the received strength of an electrical signal obtained by the mobile robot 300 according to this embodiment during the 12.1 / cosθth measurement. Next, as shown in Figure 9, when the environmental shape measuring device LD reaches position P3, which is the third shortest distance from collision prevention mark 2 (when the environmental shape measuring device LD moves 0.4tanθ(m) in the direction of travel), the number of scans from the start time is 12.1 / cosθ (scan) from the geometric conditions in Figure 7. Multiplying this by the frequency of the environmental shape measuring device LD, 0.033 (seconds / scan), gives us that 0.4 / cosθ (seconds) have elapsed since the start time.

[0045] When the line segment connecting collision prevention mark 1 and collision prevention mark 2 is projected onto the path of the mobile robot, the projected distance between collision prevention mark 1 and collision prevention mark 2 on that path is 0.4 / cosθ(m). Dividing the projected distance of 0.4 / cosθ by the mobile robot 300's movement speed of 1 m / sec gives the movement time of the environmental shape measuring device LD between collision prevention mark 1 and collision prevention mark 2, which is 0.4 / cosθ(seconds). Furthermore, the reciprocal of the travel time 0.4 / cosθ (seconds) corresponds to the travel frequency between collision avoidance marks, so we obtain 1 / (0.4 / cosθ)(1 / second) = 2.5cosθ (Hz). In other words, the movement period at which the light beam of the environmental shape measuring device LD and the collision prevention mark are at their shortest distance is 2.5cosθ (Hz). This means that the light receiving sensor (light receiving part) of the environmental shape measuring device LD receives the reflected light beam from the collision prevention mark at a movement frequency of 2.5cosθ (Hz).

[0046] The moving frequency (2.5cosθ(Hz)) is calculated as shown in (Equation 1) below.

[0047]

number

[0048] Here, f is the rotation frequency of the environmental shape measuring device LD, d is the distance between adjacent collision prevention marks (known), v is the travel speed of the mobile robot 300 (environmental shape measuring device LD) (known), and θ is the angle formed by the glass wall and the travel path of the mobile robot 300 (known, described later).

[0049] As illustrated in Figures 6, 8, and 10, and as described above, when the light beam from the environmental shape measuring device LD is shone perpendicularly onto the collision prevention mark, that is, when the positional relationship between the collision prevention mark and the environmental shape measuring device LD is the shortest distance, the intensity of the electrical signal of the light beam reflected by the collision prevention mark is highest. Furthermore, the received pulse at that time is much stronger than the light beam that is rarely reflected by the glass wall.

[0050] Figure 11 shows an example of integrating pulses with high received intensity obtained in each measurement according to this embodiment. When the pulse with the highest electrical signal strength is acquired in each scan and plotted as a time-electrical signal strength graph, it becomes an electrical signal strength graph at equally spaced collision prevention marks, as shown in Figure 11. The period of the highest electrical signal strength in each scan is a pulse signal of 0.4 / cosθ (seconds). Here, the pulse between the pulses with the highest electrical signal intensity in Figure 11 is the pulse of the collision prevention mark with the higher electrical signal intensity when the environmental shape measuring device LD is directly facing the glass wall between adjacent collision prevention marks, and when the light rays from the environmental shape measuring device LD illuminate the left and right collision prevention marks.

[0051] Figure 12 shows an example of the case where a discrete Fourier transform is performed on pulses with high received intensity obtained from each of the integrated measurements according to this embodiment. Figure 12 shows an example of what happens when the discrete Fourier transform unit 152 processes the time-electrical signal intensity graph shown in Figure 11. The highest power in Figure 12 corresponds to the frequency of the collision prevention mark. As shown in Figure 12, if an exceptionally high power is obtained, that is, if there is a pulse with power that stands out compared to other pulses, the detection unit 153 determines that it has detected a collision prevention mark attached to the glass wall. Note that the total number of collision prevention marks affixed is 2 n If it is known in advance that there are only a certain number of elements, the Fast Fourier Transform may be used instead of the Discrete Fourier Transform. Here, n is a natural number.

[0052] Figure 13 shows an example of environment map generation according to this embodiment. Figure 14 shows an example of environment map generation according to this embodiment. As shown in Figures 13 and 14, the measurement unit 154 draws glass walls corresponding to collision prevention marks on the environment map, connecting adjacent collision prevention marks in the map created by SLAM with straight lines. As shown in Figures 13 and 14(A), the measurement unit 154 generates a time-electrical signal intensity graph for adjacent collision prevention marks for each scan (or flash) of the environment shape measurement device LD. Then, as shown in Figures 13 and 14(B), the discrete Fourier transform unit 152 extracts the frequency by sequentially performing a discrete Fourier transform on the time-electrical signal intensity graph. In this case, the measurement unit 154 generates a time-electrical signal intensity graph even when the object being measured (e.g., a concrete wall) is not a glass wall, and performs a discrete Fourier transform on the time-electrical signal intensity graph. In this case, periodicity does not appear in the time-electrical signal intensity graph for the concrete wall, but when the mobile robot 300 arrives at the position of the glass wall and the environmental shape measuring device LD scans (or flashes), periodicity due to the collision prevention marks appears in the time-electrical signal intensity graph.

[0053] By configuring it in this way, as shown in Figures 13 and 14(C), it is possible to identify the glass walls corresponding to collision prevention marks 1 to 16, and these glass walls can be drawn on the environment map, for example, as opaque walls.

[0054] Alternatively, the measurement unit 154 may not generate a time-electrical signal intensity graph for each scan or flash of the environmental shape measuring device LD, but may wait until a number of scans (or flashes) greater than 1 is performed by the environmental shape measuring device LD to generate a time-electrical signal intensity graph as shown in Figures 13 and 14(A), and then perform a discrete Fourier transform on this time-electrical signal intensity graph using the discrete Fourier transform unit 152 to extract the frequency. For example, the measurement unit 154 may generate a time-electrical signal intensity graph at the 181.5 / cosθ scan (or flash) in Figure 14(A), and then perform a discrete Fourier transform on the generated time-electrical signal intensity graph using the discrete Fourier transform unit 152 to derive the frequency.

[0055] Next, we will explain the angle θ formed by the glass wall and the travel path of the mobile robot 300.

[0056] Figure 15 shows an example of how to calculate the angle θ in the measurement system SYS according to this embodiment. As shown in Figure 15, if φ is the angle between the travel path of the mobile robot 300 (dashed line) and the shortest distance to the glass wall (solid line), r is the distance between the collision prevention marks 1 and 2 attached to the glass wall and the environmental shape measuring device LD, and φ' is the angle in the direction measured by the environmental shape measuring device LD, then the measured coordinates (x,y) can be expressed as shown in (Equation 2).

[0057]

number

[0058] When the coordinates (x,y) are approximated by the least squares method as y=ax+b, the slope a is expressed as shown in (Equation 3).

[0059]

number

[0060] Here, the superscript bar in (Equation 3) indicates the average value for i=1 to N. From this, the angle φ is derived as shown in (Equation 4).

[0061]

number

[0062] Therefore, the angle θ can be expressed as shown in (Equation 5).

[0063]

number

[0064] Next, the flow of the measurement process according to this embodiment will be described.

[0065] Figure 16 is a flowchart showing an example of the measurement process in the measurement system SYS according to this embodiment. Figure 17 is a flowchart showing an example of the measurement process in the measurement system SYS according to this embodiment. In step S101, the mobile robot 300 moves autonomously and approaches the collision avoidance mark 1. In step S102, the environmental shape measuring device LD of the mobile robot 300 starts its first scan, and this time is set as the start time (0 seconds later).

[0066] In step S103, the measurement unit 154 of the server system 100 generates a time-electrical signal intensity graph. In step S104, the discrete Fourier transform unit 152 of the server system 100 performs a discrete Fourier transform on the time-electrical signal intensity graph.

[0067] In step S105, the peak frequency detected by the detection unit 153 of the server system 100 cannot be derived. In step S106, the mobile robot 300 moves autonomously and approaches the area between collision avoidance mark 1 and collision avoidance mark 2.

[0068] In step S107, the environmental shape measuring device LD of the mobile robot 300 performs a second scan. In step S108, the measurement unit 154 of the server system 100 generates a time-electrical signal intensity graph.

[0069] In step S109, the discrete Fourier transform unit 152 of the server system 100 performs a discrete Fourier transform on the time-electrical signal intensity graph. In step S110, the peak frequency detected by the detection unit 153 of the server system 100 cannot be derived.

[0070] In step S111, the mobile robot 300 moves autonomously and approaches the collision avoidance mark 2. In step S112, the environmental shape measuring device LD of the mobile robot 300 performs the 12.1 / cosθth scan.

[0071] In step S113, the measurement unit 154 of the server system 100 generates a time-electrical signal intensity graph. In step S114, the discrete Fourier transform unit 152 of the server system 100 performs a discrete Fourier transform on the time-electrical signal intensity graph.

[0072] In step S115, the detection unit 153 of the server system 100 successfully derives the peak frequency. In step S116, the measurement unit 154 of the server system 100 draws glass walls corresponding to collision prevention mark 1 and collision prevention mark 2 on the environment map.

[0073] In step S117, the mobile robot 300 moves autonomously and approaches the area between collision avoidance mark 2 and collision avoidance mark 3. In step S118, the environmental shape measuring device LD of the mobile robot 300 performs, for example, the 20th / cosθ scan.

[0074] In step S119, the measurement unit 154 of the server system 100 generates a time-electrical signal intensity graph. In step S120, the Discrete Fourier Transform unit 152 of the server system 100 performs a Discrete Fourier Transform on the time-electrical signal intensity graph.

[0075] In step S121, the peak frequency detected by the detection unit 153 of the server system 100 cannot be derived. In step S122, the mobile robot 300 moves autonomously and approaches the collision avoidance mark 3.

[0076] In step S123, the environmental shape measuring device LD of the mobile robot 300 performs the 24.2 / cosθth scan. In step S124, the measurement unit 154 of the server system 100 generates a time-electrical signal intensity graph.

[0077] In step S125, the Discrete Fourier Transform unit 152 of the server system 100 performs a Discrete Fourier Transform on the time-electrical signal intensity graph. In step S126, the detection unit 153 of the server system 100 successfully derives the peak frequency. In step S127, the measurement unit 154 of the server system 100 draws the glass wall corresponding to the collision prevention mark 3 on the environment map.

[0078] In step S128, the mobile robot 300 moves autonomously and approaches the area between collision avoidance mark 3 and collision avoidance mark 4. In step S129, the environmental shape measuring device LD of the mobile robot 300 performs, for example, the 30th / cosθ scan.

[0079] In step S130, the measurement unit 154 of the server system 100 generates a time-electrical signal intensity graph. In step S131, the discrete Fourier transform unit 152 of the server system 100 performs a discrete Fourier transform on the time-electrical signal intensity graph.

[0080] In step S132, the peak frequency detected by the detection unit 153 of the server system 100 cannot be derived. In step S133, the mobile robot 300 moves autonomously and approaches the collision avoidance mark 4.

[0081] In step S134, the environmental shape measuring device LD of the mobile robot 300 performs the 36.3 / cosθth scan. In step S135, the measurement unit 154 of the server system 100 generates a time-electrical signal intensity graph.

[0082] In step S136, the Discrete Fourier Transform unit 152 of the server system 100 performs a Discrete Fourier Transform on the time-electrical signal intensity graph. In step S137, the detection unit 153 of the server system 100 successfully derives the peak frequency. In step S138, the measurement unit 154 of the server system 100 draws the glass wall corresponding to the collision prevention mark 4 on the environment map.

[0083] In the following steps, similar to those described above, the measurement unit 154 of the server system 100 sequentially draws the glass walls corresponding to collision prevention marks 4 through 15 onto the environment map.

[0084] In step S139, the mobile robot 300 moves autonomously and approaches the collision avoidance mark 16.

[0085] In step S140, the environmental shape measuring device LD of the mobile robot 300 performs the 181.5 / cosθth scan. In step S141, the measurement unit 154 of the server system 100 generates a time-electrical signal intensity graph.

[0086] In step S142, the Discrete Fourier Transform unit 152 of the server system 100 performs a Discrete Fourier Transform on the time-electrical signal intensity graph. In step S143, the detection unit 153 of the server system 100 successfully derives the peak frequency.

[0087] In step S144, the measurement unit 154 of the server system 100 draws the glass wall corresponding to the collision prevention mark 16 on the environment map.

[0088] Thus, the measurement system SYS according to this embodiment includes a detection unit 153 that detects the presence or absence of a transparent wall material that has been treated to prevent collisions, and a measurement unit 154 that measures the shape of the transparent wall material when the presence of the transparent wall material is detected.

[0089] This method allows for the prevention of collisions between people and glass walls using conventional collision prevention marks, while also enabling the measurement of the glass wall's shape. Furthermore, it allows for the measurement of the glass wall's shape without compromising its aesthetic appeal. In addition, because the well-known discrete Fourier transform is used for glass wall detection, system implementation is easy, and the computational processing costs and price costs of the processing server (discrete Fourier transform server) can be reduced. Moreover, for robots that move autonomously using SLAM, there is no need to incur additional costs to equip them with dedicated sensors (e.g., infrared cameras or polarizing cameras) to detect glass walls; distance measurement and glass wall detection can be performed simultaneously with a single environmental shape measurement device (LD).

[0090] Although embodiments of this invention have been described in detail above with reference to the drawings, the specific configuration is not limited to those described above, and various design changes can be made without departing from the spirit of this invention.

[0091] Furthermore, the program running on the server system 100 in one aspect of the present invention may be one or more programs that control processors such as CPUs (Central Processing Units) (programs that make a computer function) in order to realize the functions shown in the above embodiments and modifications relating to one aspect of the present invention. The term "computer" here includes quantum computers. The information handled by each of these devices may be temporarily stored in RAM (Random Access Memory) during processing, and then stored in various storage devices such as flash memory and HDDs (Hard Disk Drives), and may be read, modified, and written by the CPU or the like as needed.

[0092] Furthermore, some or all of the server system 100 in each of the embodiments and modifications described above may be implemented using a computer equipped with one or more processors. In that case, the program for implementing this control function may be recorded on a computer-readable recording medium, and the program recorded on this recording medium may be read by the computer system and executed.

[0093] In this context, "computer system" refers to the computer system built into the server system 100, including hardware such as the OS and peripheral devices. Furthermore, "computer-readable recording medium" refers to portable media such as flexible disks, magneto-optical disks, ROMs, and CD-ROMs, as well as storage devices such as hard disks built into the computer system.

[0094] Furthermore, "computer-readable recording media" may include those that dynamically hold programs for a short period of time, such as communication lines used when transmitting programs via networks such as the Internet or communication lines such as telephone lines, as well as those that hold programs for a certain period of time, such as volatile memory inside a computer system that acts as a server or client in such cases. In addition, the above-mentioned program may be for the purpose of realizing some of the functions described above, and may also be a program that can realize the above-mentioned functions in combination with a program already recorded in the computer system.

[0095] Furthermore, some or all of the server system 100 in each of the embodiments and modifications described above may be implemented as an LSI, which is typically an integrated circuit, or as a chipset. Also, each functional block of the server system 100 in each of the embodiments and modifications described above may be individually chipped, or some or all of them may be integrated into a single chip. In addition, the method of implementing the integrated circuit is not limited to LSIs; it may also be implemented using dedicated circuits and / or general-purpose processors. Furthermore, if advances in semiconductor technology lead to the emergence of integrated circuit implementation technologies that can replace LSIs, it is also possible to use integrated circuits based on those technologies.

[0096] Although various embodiments and modifications have been described in detail above with reference to the drawings as one aspect of this invention, the specific configuration is not limited to these embodiments and modifications, and includes design changes and the like that do not depart from the gist of this invention. Furthermore, various modifications are possible within the scope of the claims for one aspect of this invention, and embodiments obtained by appropriately combining the technical means disclosed in different embodiments are also included in the technical scope of this invention. In addition, configurations in which elements described in the above embodiments and modifications that produce similar effects are substituted for each other are also included. [Explanation of symbols]

[0097] 100 Server Systems 110 Communications Department 120 Storage section 121 pulses 130 Input section 140 Output section 150 Control Unit 151 Acquisition Department 152 Discrete Fourier Transform Section 153 Detection unit 154 Measurement Unit 300 Mobile Robots LD Environmental Shape Measurement Device

Claims

1. A detection unit that detects the presence or absence of a transparent wall material with collision prevention processing, When the presence of the transparent wall material is detected, a measuring unit measures the shape of the transparent wall material, A measurement system equipped with the following features.

2. The collision prevention treatment is a collision prevention mark placed at regular intervals on the transparent wall material. The measurement system according to claim 1.

3. A light irradiating unit that shines light rays onto the wall material, A light receiving unit that receives the reflected light of the aforementioned light ray, Furthermore, The detection unit detects the presence or absence of the transparent wall material based on the electrical signal intensity of the reflected light. The measurement system according to claim 1.

4. A detection unit that detects the presence or absence of a transparent wall material with collision prevention processing, When the presence of the transparent wall material is detected, a measuring unit measures the shape of the transparent wall material, A measuring device equipped with the following features.

5. A measurement method in a measuring device, A detection step to detect the presence or absence of a transparent wall material that has been treated to prevent collisions, If the presence of the transparent wall material is detected, a measurement step is performed to measure the shape of the transparent wall material, A measurement method having the following characteristics.

6. In the computer of the measuring device, A detection step to detect the presence or absence of a transparent wall material that has been treated to prevent collisions, If the presence of the transparent wall material is detected, a measurement step is performed to measure the shape of the transparent wall material, A program to execute.

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