Wall detection device, transport vehicle, control method, program, and calculation device

Abstract

To provide a wall detection apparatus which reduces risk of contact with a wall surface when a vehicle enters a region sandwiched by wall surfaces whose shapes are not necessarily simple.SOLUTION: The present invention is directed to a wall detection apparatus 100 mounted on a carrier vehicle entering the back of a container having side walls (first wall and second wall) opposed to each other and each formed of a plate having a rugged horizontal cross section. The wall detection apparatus has an acquiring unit 101 ad a detection unit 102. The acquiring unit 101 acquires a point group as coordinates of a plurality of points corresponding to the first wall and the second wall opposed to each other. Based on a model expressing a first plane expressing a rough shape of the first wall and a second plane expressing a rough shape of the second wall and also expressing that the first plane and the second plane are in parallel to each other and the acquired point group, the detection unit 102 detects a first detected wall corresponding to the first plane and a second detected wall corresponding to the second plane.SELECTED DRAWING: Figure 2

Description

[Technical field]

[0001] The present invention relates to a wall detection device, a transport vehicle, , CONTROL METHOD, PROGRAM AND COMPUTER APPARATUS Regarding. [Background technology]

[0002] A bunning robot is known as a large-sized transport vehicle equipped with a robot arm for loading cargo and a conveyor for transporting cargo. This type of transport vehicle enters an area between side walls of a container, an aisle, etc., and transports cargo to a destination via the conveyor and the robot arm, and is therefore useful for automating logistics and reducing manpower. Another type of transport vehicle known is a forklift, which enters an area between side walls of a container, an aisle, etc., and transports cargo to a destination via a fork that can be raised and lowered.

[0003] On the other hand, as these transport vehicles become larger, the risk of contacting containers or passageways increases. For this reason, transport vehicles may be equipped with a wall detection device having a sensor such as a laser range finder (LRF). The wall detection device detects the distance between the sensor and a side wall and outputs parameters representing the wall surface, thereby performing wall detection and reducing the risk of contacting the wall surface. The closer the distance between the wall surfaces is to the width of the transport vehicle and the longer the transport vehicle and passageway are, the higher the accuracy required for the wall surface parameters of such a wall detection device.

[0004] However, the walls of containers and corridors do not necessarily have simple shapes. For example, the walls of containers may be made of corrugated sheets to increase their rigidity. Also, the walls of corridors may have protrusions such as doorknobs and handrails. It is impossible to model the exact shapes of such various wall surfaces in advance.

[0005] Therefore, it is desirable for the wall detection device to reduce the risk of contacting a wall when entering an area surrounded by walls that are not necessarily of a simple shape. [Prior art documents] [Patent documents]

[0006] [Patent Document 1] JP 2020-175997 A [Non-patent literature]

[0007] [Non-Patent Document 1] MA Fischler et al., “Random Sample Consensus: A Paradigm for Model Fitting with Applications to Image Analysis and Automated Cartography,” Communications of the ACM, vol. 24, no. 6, 1981. Summary of the Invention [Problem to be solved by the invention]

[0008] The problem to be solved by the present invention is to provide a wall detection device and a transport vehicle that reduce the risk of contacting a wall when entering an area surrounded by walls that are not necessarily simple in shape. , CONTROL METHOD, PROGRAM AND COMPUTER APPARATUS The purpose of this project is to provide [Means for solving the problem]

[0009] A wall detection device according to an embodiment includes an acquisition unit and a detection unit. The acquisition unit acquires a point cloud, which is a coordinate sequence of a plurality of points corresponding to a first wall and a second wall facing each other. The detection unit detects a first detection wall corresponding to the first plane and a second detection wall corresponding to the second plane, based on a model that represents a first plane representing a general shape of the first wall and a second plane representing a general shape of the second wall and that represents that the first plane and the second plane are parallel to each other, and the acquired point cloud. [Brief description of the drawings]

[0010] [Figure 1]1 is a plan view showing a transport vehicle equipped with a wall detection device according to a first embodiment and its usage situation. [Diagram 2] 1 is a block diagram showing a configuration of a wall detection device according to a first embodiment. [Diagram 3] FIG. 2 is a schematic diagram for explaining an acquisition unit according to the first embodiment. [Figure 4] 5 is a flowchart for explaining an operation in the first embodiment. [Diagram 5] 5 is a flowchart showing a specific example of an operation in the first embodiment. [Figure 6] FIG. 4 is a schematic diagram for explaining the operation in the first embodiment. [Figure 7] FIG. 4 is a schematic diagram for explaining the operation in the first embodiment. [Figure 8] 10 is a flowchart for explaining an operation according to the second embodiment. [Figure 9] 13 is a diagram illustrating a relationship between a point cloud and a side wall in the second embodiment. [Figure 10] FIG. 11 is a diagram showing an initial extraction result in the second embodiment. [Figure 11] FIG. 11 is a diagram showing a secondary extraction result in the second embodiment. [Figure 12] 11 is a plan view showing a transport vehicle equipped with a wall detection device according to a modification of the first and second embodiments and a usage situation thereof. FIG. [Figure 13] FIG. 11 is a block diagram showing the configuration of a wall detection device according to a modification of the first and second embodiments. [Figure 14] FIG. 11 is a block diagram showing a hardware configuration of a wall detection device according to a third embodiment. [Figure 15] FIG. 13 is a block diagram showing a hardware configuration of a wall detection device according to a modified example of the third embodiment. DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[0011] Each embodiment will be described below with reference to the drawings. In the following description, a wall surface made of a corrugated sheet is taken as an example of a wall surface that is not a simple shape. A corrugated sheet is a sheet having a cross-sectional shape with periodic concaves and convexes, and is used, for example, in containers. The height of the concaves and convexes of the corrugated sheet corresponds to the outer and inner dimensions of the container. The outer and inner dimensions of the container are based on, for example, the standards of ISO (International Organization for Standardization). The height of the concaves and convexes of the corrugated sheet in the container is unknown, but can be estimated as the difference between the inner and outer dimensions.

[0012] (First embodiment) 1 is a plan view showing a transport vehicle equipped with a wall detection device according to the first embodiment and its usage. The wall detection device 100 is mounted on a transport vehicle 300 that enters the back of a container 200 having side walls 201, 202 made of corrugated sheets with uneven horizontal cross sections. An acquisition unit 101 of the wall detection device 100 is disposed at the center of the leading end of the transport vehicle 300 in the traveling direction.

[0013] 2, the wall detection device 100 includes an acquisition unit 101 that acquires a point cloud, which is a coordinate sequence of the surface of a wall, and a detection unit 102 that detects two parallel wall surfaces from the point cloud. The detection unit 102 further includes a correction unit 103. The correction unit 103 changes the positions of the detected walls, which are the two detected wall surfaces, to corrected walls 104 within a range where the transport vehicle 300 can move without touching the wall surfaces.

[0014] In detail, the acquisition unit 101 acquires a point cloud, which is a coordinate sequence of a plurality of points corresponding to a first wall and a second wall facing each other. For example, the acquisition unit 101 has, for example, an optical sensor. The sensor measures the distance between the sensor and the object by irradiating a measurement light to the object (wall) and receiving the reflected light from the object. As the optical sensor of the acquisition unit 101, for example, a laser range finder (LRF) for acquiring a point cloud, which is a coordinate sequence of two-dimensional coordinates, or a ToF (time-of-flight camera) camera for acquiring a point cloud, which is a coordinate sequence of three-dimensional coordinates, can be appropriately used. Note that the acquisition unit 101 is not limited to an optical sensor, and may have an ultrasonic sensor. The sensor may measure the distance between the sensor and the object by transmitting ultrasonic waves to the object (wall) and receiving reflected waves from the object. However, in this embodiment, a case in which the acquisition unit 101 has a laser range finder (LRF) is described as an example. For example, as shown in Fig. 3, the laser range finder 101a of the acquisition unit 101 irradiates the surroundings with laser light 101b while changing the irradiation angle with respect to the horizontal direction. Note that the laser light 101b reaches the depths of the unevenness of the side wall 201 (first wall) on the side closer to the laser range finder 101a, and only reaches a portion shallower than the center line 251 of the unevenness on the far side. The irradiated laser light 101b reaches a point p 201 (0), p 201 (1),...,p 201 (N 201 -2), p 201 (N 201 The laser range finder 101a receives the reflected light and detects each point p 201 and the relative distance of the laser range finder 101a. Hereinafter, the coordinate sequence of a plurality of points obtained from the pair of the relative distance and the irradiation angle is referred to as a point cloud. When the irradiation angle of the front side is used as a reference, the point cloud corresponding to the irradiation angle on the left side of the front side corresponds to the side wall 201 (first wall), and the point cloud corresponding to the irradiation angle on the right side of the front side corresponds to the side wall 202 (second wall). Note that the description of the side wall 201 can be similarly applied to the side wall 202 by changing the reference numeral 201 to the reference numeral 202. The acquisition unit 101 may be referred to as a point cloud acquisition unit.

[0015] On the other hand, the detection unit 102 detects a first detection wall corresponding to the first plane and a second detection wall corresponding to the second plane based on the acquired point cloud and a model that represents a first plane representing an approximate shape of the first wall and a second plane representing an approximate shape of the second wall and that represents that the first plane and the second plane are parallel to each other. Here, when the point cloud is a coordinate sequence of two-dimensional coordinates, the model may represent that the first plane and the second plane are parallel to each other by, for example, having the same inclination of a first line representing a horizontal cross section of the first plane and the inclination of a second line representing a horizontal cross section of the second plane.

[0016] Also, for example, the detection unit 102 detects a first plane from a plurality of points corresponding to the first wall, detects a second plane from a plurality of points corresponding to the second wall, and corrects the first plane and the second plane to be parallel to each other, thereby detecting the first detection wall and the second detection wall.

[0017] Specifically, for example, the detection unit 102 classifies a plurality of points in the point cloud acquired by the sensor into a first point cloud consisting of a plurality of points within a predetermined distance from the first plane and a second point cloud consisting of a plurality of points within a predetermined distance from the second plane, and associates a plurality of points in the first point cloud with the first wall, and associates a plurality of points in the second point cloud with the second wall. The detection unit 102 also detects the first detection wall and the second detection wall based on the first point cloud, the second point cloud, and the model. Note that the predetermined distance is preferably equal to or greater than the larger of the tolerance of the sensor and the height of the designed unevenness in the first wall and the second wall. For example, the predetermined distance may be the larger of the tolerance and the height of the unevenness, or may be a value obtained by adding the tolerance and the height of the unevenness. For example, the predetermined distance may be a value obtained by multiplying the value obtained by adding the tolerance and the height of the unevenness by a constant (for example, double).

[0018] Supplementally, it is not clear immediately after the point cloud obtained from the laser range finder 101a, which is a sensor, that the point cloud corresponds to which wall from which the reflection is received. Therefore, in the technology described in Non-Patent Document 1, detection of the container wall and association of the points with the detected wall are performed in parallel. When performing this association, a guideline is required as to the range in which the points obtained from the reflection from one wall vary, and this guideline is given as a range of a predetermined distance (maximum distance Lmax described later).

[0019] The correction unit 103 translates the first detection wall toward the second detection wall to correct it to the first correction wall, and translates the second detection wall toward the first detection wall to correct it to the second correction wall. In this case, the number of points in the point cloud between the first detection wall and the second correction wall is smaller than the number of points in the point cloud between the first detection wall and the second detection wall. In addition, in FIG. 2, the correction wall 104 represents the first correction wall and the second correction wall. In addition, the correction unit 103 may translate the first detection wall to a position of a point that is most deviated toward the second detection wall side among a plurality of points corresponding to the first wall. Similarly, the correction unit 103 may translate the second detection wall to a position of a point that is most deviated toward the first detection wall side among a plurality of points corresponding to the second wall. However, the method of translating the first detection wall and the second detection wall is not limited to this.

[0020] On the other hand, the transport vehicle 300 is a self-propelled transport device equipped with the wall detection device 100. More specifically, the transport vehicle 300 is a vehicle that can self-propel in an area surrounded by walls such as inside a container or inside a passageway, not limited to a wide area such as a warehouse, and can transport luggage. As the transport vehicle 300, for example, a vehicle equipped with a loading device such as a robot arm or a fork, such as a vanning robot or a forklift, can be appropriately used. Note that the vanning robot is a vehicle that has a robot arm for loading and a conveyor for transporting luggage and can transport luggage. The transport vehicle 300 may also be equipped with a control unit that controls the traveling direction (direction of the wheels) based on the first and second detection walls (or the first and second correction walls) obtained by the wall detection device 100. The control unit controls the traveling direction so that, for example, the vehicle center axis along the longitudinal direction (front-rear direction) of the transport vehicle 300 is at the center between two wall surfaces and parallel to the wall surfaces. When such a control unit is provided, the operator of the transport vehicle 300 can move the transport vehicle 300 forward or backward by simply inputting a forward or backward command without steering the vehicle.

[0021] Next, the operation of the wall detection device and the transport vehicle configured as above will be described with reference to the flowcharts of Figures 4 and 5 and the schematic diagrams of Figures 6 and 7. In the following description, an overview of the operation will be given first, followed by a specific example of the operation.

[0022] (Overview of operation) The acquisition unit 101 of the wall detection device 100 acquires a point cloud, which is a set of coordinates of a plurality of points, from the wall surfaces of the side walls 201 and 202, for example, by a sensor, as shown in FIG. 4 (step S10).

[0023] After step S10, the detection unit 102 detects the initial positions and initial orientations of two or more walls from the point cloud using, for example, the method of Non-Patent Document 1 (step S20).

[0024] After step S20, the detection unit 102 acquires two or more detected walls by calculating (re-estimating) the positions and orientations of the two walls using the condition that the relative positions of the two or more walls follow a given constraint (step S30). Note that the detection unit 102 improves the estimation accuracy of the positions and orientations of the walls by calculating the positions and orientations of the walls based on the constraints on the arrangement of the multiple walls.

[0025] After step S30, the correction unit 103 corrects the relative positions of the two or more walls to obtain a correction wall 104 (step S40). This allows the transport vehicle 300 to enter between the correction walls 104. The movement amount of the detection wall to obtain such a correction wall 104 is set to a distance that sufficiently reduces the number of points forming a point cloud within the area surrounded by the correction walls 104. This allows the risk of the transport vehicle 300 contacting the side walls 201, 202 when entering between the side walls 201, 202 to be reduced by limiting the movement range of the transport vehicle 300 equipped with the wall detection device 100 to the area sandwiched between the correction walls 104.

[0026] After step S40, the wall detection device 100 determines whether or not the wall detection has been completed (step S50), and repeats the processing of steps S10 to S50 until the wall detection is completed. The completion of the wall detection may be determined, for example, by the distance between the laser range finder 101a and the forward wall representing a dead end being equal to or less than a threshold based on the point cloud acquired by the acquisition unit 101. Alternatively, the completion of the wall detection may be determined not only by the detection of a dead end, but also by the input of an end instruction in response to an operation by the operator.

[0027] (Example of operation) Next, a specific example of the outline of the operation will be described. Note that specific examples of steps S20, S30, and S40 shown in Fig. 4 are steps S21, S31, and S41 shown in Fig. 5.

[0028] As shown in Fig. 5, the wall detection device 100 acquires a point cloud, which is a series of coordinates of points on the surfaces of the side walls 201 and 202, from the laser range finder 101a as the acquisition unit 101 (step S10). At this time, as shown in Fig. 6, the degree to which the laser light 101b penetrates the unevenness varies depending on the combination of the unevenness of the side wall 201 and the irradiation angle of the laser light 101b. That is, when the laser light 101b penetrates the unevenness to the deepest point, the point p 201 From a point on a rough surface such as (0) to a point p 201 In the case of (1), the laser beam 101b reaches the point deep inside the unevenness, and in the case of (2), the laser beam 101b does not reach the point deep inside the unevenness and reaches the point p 201 (N 201 In this case, only the uneven surface points as in the case of -2) are obtained. As a result, the point cloud has a distribution that spreads according to the height of the unevenness of the side wall 201 as the point cloud approaches the laser range finder 101a, as shown by triangle 281. Such a point cloud is acquired in step S10. The explanation regarding the distribution of triangle 281 on side wall 201 also applies to the distribution of triangle 282 on side wall 202. However, although the distributions of triangles 281 and 282 are roughly similar, to be precise, they have shapes independent of each other according to the arrival state of laser light 101b on the unevenness of side walls 201 and 202.

[0029] After step S10, the detection unit 102 obtains, for each of the side walls 201, 202, a set of points that are components of the point cloud and a straight line that models the side walls 201, 202, as shown in the following formulas (1) to (4), using, for example, the method of Non-Patent Document 1 from the obtained point cloud (step S21). In implementing Non-Patent Document 1, it is necessary to give the detection unit 102 in advance a maximum distance Lmax between the detected straight line and the point to be associated with it. It is desirable that this maximum distance Lmax is equal to or greater than the greater of the measurement error (tolerance) of the sensor, which is a distance from the wall surface that is given in advance, and the height of the unevenness of the container wall surface. If the value is smaller than this, the uneven container surface will not be detected as a single straight line, but will be divided into separate fine lines.

[0030] For example, if the first and second walls are made of corrugated steel, the height of the designed unevenness can be estimated in advance from the difference between the outer and inner dimensions of the container based on ISO standards. Also, if the first and second walls are passageways with protrusions such as doorknobs and handrails, the height of the protrusions that have been actually measured in advance can be used as the height of the designed unevenness.

[0031]

number

[0032] However, p 201 (i) is a set of points that are components of the point cloud corresponding to the side wall 201. 201 (x) is a line that models the position and orientation of the side wall 201. 202 (j) is a set of points that are components of the point cloud corresponding to the side wall 202. 202 (x) is a line that models the position and orientation of the side wall 202.

[0033] In addition, a straight line f 201 (x), f 202 (x) can be calculated not only by the method described in Non-Patent Document 1, but also by using, for example, regression analysis. In this case, the straight line f 201 (x), f 202(x) corresponds to the regression lines 291 and 292 in FIG. 6. The regression line 291 passes through the center of the points distributed in the triangle 281, and does not coincide with the center line 251 of the irregularities shown in FIG. 3. The same is true for the regression line 292 in the side wall 202. The regression lines 291 and 292 have independent slopes corresponding to the distribution of the triangles 281 and 282, which are independent of each other. The two regression lines 291 and 292 are in a state where the interval between them becomes wider as they approach the laser range finder 101a, and the interval becomes narrower as they move away from the laser range finder 101a. That is, in the existing method, the distribution of the points becomes triangular depending on the relative position between the laser range finder 101a and the container 200 and the height of the irregularities of the side walls 201 and 202, and therefore the regression lines 291 and 292 open in an inverted V shape.

[0034] Therefore, in this situation, if the long transport vehicle 300 enters along the regression line 291, the point p 201 In order to avoid this contact, the regression line 291 is temporarily aligned with the point p 201 (0) Even if the stopping area of ​​the transport vehicle 300 is set by a straight line (not shown) translated up to the top, the point p 201 (N 201 In the vicinity of the line f-2), the stopping area is narrow, so the transfer vehicle 300 cannot pass through. 201 (x), f 202 (x) is in the same situation as the regression lines 291 and 292 described above, and has a different slope a 201 , a 202 Therefore, if we assume that the line f 201 (x), f 202 (x) slope a 201 , a 202 Even if you were to correct the above, separate correction actions would be required.

[0035] Returning to FIG. 5, after step S21, the detection unit 102 detects two parallel straight lines f′ connecting the side walls 201 and 202 as shown in the following formula (5). 201 (x), f'202 (x) is used as the model. Note that the two straight lines f' 201 (x), f' 202 (x) has equal slopes a' and different intercepts b' 201 , b' 202 In addition, the detection unit 102 detects the points and each straight line f′ as shown in the following expressions (6) to (7). 201 (x), f' 202 The value corresponding to the error with (x) is E 201 (a', b' 201 ), E 202 (a', b' 202 ) and two straight lines f' 201 (x), f' 202 (x) is the slope and intercept parameter E(a', b' 201 , b' 202 ) is used as the cost function. In this case, the detection unit 102 selects parameters (A, B) that minimize the cost as shown in the following formula (8). 201 , B 202 ) is re-estimated (calculated) (step S31).

[0036]

number

[0037] As mentioned above, the regression lines 291 and 292 are the straight line f 201 (x), f 202 Also, the line f 201 3. However, in step S31, the slope A is re-estimated using the points of the two side walls 201 and 202, so that a straight line f' 201 (x) is obtained. Also, a straight line f' with the same slope A is obtained. 202 The same is true for (x). The straight line f' obtained in step S31 201 (x), f' 202 (x) corresponds to the detection wall described in step S30.

[0038] After step S31, the correction unit 103 corrects the two straight lines f' corresponding to the detection walls. 201 (x), f' 202 In order to narrow the gap between (x), point p on the side wall 201 201 Among (i), find the point that is the furthest away from the side wall 202. 201 (i) <Ax 201 (i)+B 201 Point p that satisfies (i) 201 (i) is the line f' 201 From (x) a line f' 202 It exists on the (x) side. Point p 201 (i) and line f' 201 The distance between (x) is expressed as d 201 It is represented by (i).

[0039]

number

[0040] Therefore, as shown in the following equations (10) to (11), y 201 (i) <Ax 201 (i)+B 201 Point p that satisfies (i) 201 (i) and line f' 201 Distance D between (x) 201 Based on (i), D 201 Point p where (i) is the maximum value 201 Index I points to (i) 201 The index I 201 is the point p 201 Among (i), this refers to the point furthest away from the side wall 202 side.

[0041]

number

[0042] The correction unit 103 is an index I 201 Using the above formula, a straight line f' is drawn as shown in the following formula (12). 201 Model f” of the modified wall 104 with (x) moved toward the side wall 202 201 Get (x).

[0043]

number

[0044] Similarly, the correction unit 103 calculates the distance between the point p on the side wall 202 as shown in the following equations (13) to (16). 202 From (j), the line f' 202 Model f” of the modified wall 104 with (x) moved toward the side wall 201 202 Obtain (x) (step S41).

[0045]

number

[0046] Model f″ of the modified wall 104 obtained in step S41 201 (x),f” 202 (x) is a straight line f' that corresponds to the detection wall as shown in FIG. 201 (x), f' 202 Since (x) is translated to the innermost point, there are no points of the side wall 201 and the side wall 202 between the modified wall 104. Therefore, the circumscribing rectangle of the transport vehicle 300 is model f". 201 (x),f” 202 As long as the transport vehicle 300 moves in the area between (x), it does not come into contact with the side walls 201 and 202 of the container 200. 201 (x),f” 202 Since (x) is parallel to the detection wall modeled as two parallel straight lines, the area sandwiched by the correction wall 104 does not narrow at the back of the container 200. 201 (x),f” 202 Since (x) is a modeled modified wall 104, it may be called the modified wall 104. In any case, the transport vehicle 300 can travel between the modified walls 104 obtained in step S41 without coming into contact with the side walls 201, 202.

[0047] After step S41, the wall detection device 100 determines whether or not the wall detection has been completed (step S50), and repeats the processes of steps S10 to S50 until the wall detection is completed.

[0048] As described above, according to the first embodiment, the acquisition unit 101 acquires a point cloud, which is a coordinate sequence of a plurality of points corresponding to the first wall and the second wall facing each other. The detection unit 102 detects a first detection wall corresponding to the first plane and a second detection wall corresponding to the second plane, based on the model and the acquired point cloud. Here, the model expresses a first plane representing the general shape of the first wall and a second plane representing the general shape of the second wall, and expresses that the first plane and the second plane are parallel to each other. Therefore, by detecting the first detection wall and the second detection wall modeled to be parallel to each other, the risk of contacting the wall surface when entering an area between the wall surfaces that are not necessarily simple in shape can be reduced. To supplement this, since a model is used that makes use of knowledge of the shape of the container 200, in which the general shape of the side wall 201 and the general shape of the side wall 202 are parallel to each other, the first and second detection walls can be detected with high accuracy even if the side walls 201 and 202 have an uneven shape of a corrugated plate. In addition, it is possible to calculate the range in which the transport vehicle 300 can move without touching the wall surface from data measured by a sensor on a wall surface whose shape cannot be accurately modeled in advance, such as a wall surface having corrugated irregularities or a wall surface having a doorknob. For example, the range in which the transport vehicle 300 can move can be calculated as the range between the first and second detection walls.

[0049] According to the first embodiment, the coordinate sequence is a two-dimensional coordinate sequence, and the model expresses that the first plane and the second plane are parallel to each other by making the inclination of the first line representing the horizontal cross section of the first plane and the inclination of the second line representing the horizontal cross section of the second plane the same. Therefore, it is relatively easy to implement a model expressing planes that are parallel to each other.

[0050] According to the first embodiment, the detection unit 102 detects the first plane from a plurality of points corresponding to the first wall, detects the second plane from a plurality of points corresponding to the second wall, and corrects the first plane and the second plane to be parallel to each other, thereby detecting the first detection wall and the second detection wall. Therefore, the process of detecting the first plane and the second plane before correction can be implemented relatively easily, for example, using the method described in Non-Patent Document 1 or a method such as regression analysis.

[0051] Specifically, according to the first embodiment, the acquisition unit 101 has a sensor, and acquires a point cloud by measuring the distance between each of a plurality of points and the sensor using the sensor. The detection unit 102 classifies a plurality of points in the point cloud into a first point cloud consisting of a plurality of points within a predetermined distance from a first plane and a second point cloud consisting of a plurality of points within a predetermined distance from a second plane, and associates a plurality of points in the first point cloud with a first wall, and associates a plurality of points in the second point cloud with a second wall. The predetermined distance is equal to or greater than the larger value of the tolerance of the sensor and the height of the designed unevenness in the first wall and the second wall. Thereafter, the detection unit 102 detects the first detection wall and the second detection wall based on the first point cloud, the second point cloud, and the model. In this way, when associating the point cloud immediately after acquisition with the first wall or the second wall, a predetermined distance based on the tolerance of the sensor and the unevenness of the wall is used as a reference, so that a wall detection device that is suitable for the sensor to be implemented and the unevenness of the wall can be realized.

[0052] According to the first embodiment, the detection unit 102 includes a correction unit 103. The correction unit 103 translates the first detection wall toward the second detection wall to correct it to the first correction wall, and translates the second detection wall toward the first detection wall to correct it to the second correction wall. At this time, the number of points in the point cloud between the first correction wall and the second correction wall is smaller than the number of points in the point cloud between the first detection wall and the second detection wall. Therefore, when entering between the first and second correction walls, the risk of contacting the wall surface can be reduced compared to when entering between the first and second detection walls. To supplement, according to the first embodiment, it is only necessary to translate the first and second detection walls, so that the processing for improving the detection accuracy of the wall surface is easy. In contrast, according to the regression lines 291 and 292 of the existing method, the slopes of the regression lines 291 and 292 need to be corrected separately, and the regression lines 291 and 292 after correction are not necessarily parallel to each other, so the processing load for improving the detection accuracy of the wall surface is high.

[0053] Moreover, according to the first embodiment, the correction unit 103 translates the first detection wall to the position of the point that is the most deviated toward the second detection wall among the multiple points corresponding to the first wall, and translates the second detection wall to the position of the point that is the most deviated toward the first detection wall among the multiple points corresponding to the second wall. Therefore, since the interval between the first correction wall and the second correction wall is corrected to match the innermost point, the risk of contacting the wall surface when entering between the first and second correction walls can be further reduced.

[0054] (Modification of the first embodiment) Next, a modification of the first embodiment will be described. This modification can be similarly applied to the following embodiments.

[0055] In the modified example of the first embodiment, the correction unit 103 moves the detection wall based on the standard deviation of the frequency distribution of the distance between the point cloud and the detection wall.

[0056] Supplementally, each point of the point cloud obtained from the sensor of the acquisition unit 101 fluctuates due to noise. Therefore, when a simple maximum value calculation such as equation (11) or equation (15) is used, the position of the correction wall 104 fluctuates due to noise. When controlling the transport vehicle 300, it is preferable to operate the sensor at all times, measure the position of the wall surface at all times, and provide feedback on the amount of movement and the direction of movement of the transport vehicle 300 from the viewpoint of avoiding contact with the wall surface. In this case, if the time fluctuation of the position of the correction wall 104 is large, it will have an adverse effect on the control of the transport vehicle 300.

[0057] Therefore, in the modified example of the first embodiment, in order to stabilize the position of the correction wall 104, the correction unit 103 is deformed so as to move the detection wall based on the standard deviation of the frequency distribution of the distance between the point cloud and the detection wall.

[0058] Specifically, in order to generate a corrected wall, the correction unit 103 corrects the detected wall by calculating a distance d between the point cloud and the detected wall as expressed by Equation (9) or (13). 201 (i),d 202 (j) is translated by a distance obtained by multiplying the standard deviation σ of the occurrence frequency distribution by a predetermined positive constant α. If the condition that the height of the unevenness of the side walls 201, 202 is sufficiently small compared to the sensor noise is satisfied, the occurrence frequency distribution may approach a Gaussian distribution. The probability that a random number generated according to a Gaussian distribution will exceed a constant multiple of the standard deviation σ is calculated in advance, and the risk of contact can be controlled by adjusting the magnitude of the constant α. However, in cases where the height of the unevenness of the side walls 201, 202 and the magnitude of the sensor noise do not satisfy the above condition, it is necessary to obtain the modified wall 104 by another method.

[0059] In this modified example, the distance d 201 (i),d 202 The present invention is not limited to the case where the detection wall is moved in parallel by a distance (ασ) obtained by multiplying the standard deviation σ of the occurrence frequency distribution of (j) by a predetermined positive constant α. For example, the distance d 201 (i),d 202 The detection wall may be translated by the average value L of the occurrence frequency distribution of (j). 201 (i),d 202The detection wall may be translated by a distance (L+ασ) obtained by multiplying the standard deviation σ of the occurrence frequency distribution of (j) by a predetermined positive constant α and adding the distance to the average value L. Also, the variance V may be used instead of the standard deviation σ.

[0060] Second embodiment Next, a description will be given of a wall detection device and a transport vehicle according to a second embodiment. In the following description, duplicated descriptions of parts that are the same as the components described above will be omitted, and differences will be mainly described.

[0061] In the second embodiment, the correction unit 103 extracts a plurality of points related to the convex portions of the unevenness of the side walls 201 and 202, and moves the detection wall based on the average value of the distances between the extracted plurality of points and the detection wall. The amount of movement based on the average value of the distances may be the average value of the distances, or may be a value obtained by adding a constant multiple of the standard deviation or variance of the distance distribution to the average value of the distances.

[0062] That is, the correction unit 103 translates the first detection wall based on a first average value of first distances between the first detection wall and a plurality of points obtained on the second detection wall side from the first detection wall among a plurality of points corresponding to the first wall. The correction unit 103 also translates the second detection wall based on a second average value of second distances between the second detection wall and a plurality of points obtained on the first detection wall side from the second detection wall among a plurality of points corresponding to the second wall.

[0063] Here, the correction unit 103 may add a value obtained by multiplying the variance or standard deviation of the first distance by a predetermined positive constant to the first average value, and translate the first detection wall by the obtained addition result. Similarly, the correction unit 103 may add a value obtained by multiplying the variance or standard deviation of the second distance by a predetermined positive constant to the second average value, and translate the second detection wall by the obtained addition result.

[0064] Furthermore, among the multiple points corresponding to the first wall, the multiple points obtained on the second detection wall side from the first detection wall may be a set of points that combines each point extracted on the second detection wall side from the initial extraction boundary on the second detection wall side from the first detection wall and the points sandwiched between each of the extracted points.

[0065] Similarly, among the multiple points corresponding to the second wall, the multiple points obtained on the first detection wall side of the second detection wall may be a set of points that combines each point extracted on the first detection wall side of the initial extraction boundary on the first detection wall side of the second detection wall and the points sandwiched between each of the extracted points.

[0066] The other configurations are similar to those of the first embodiment.

[0067] Next, the operation of the wall detection device and the transport vehicle configured as above will be described with reference to the flowchart of Fig. 8 and the diagrams of Fig. 9 to Fig. 11. Note that the operation of steps S41a-1 to ST41a-4 using Fig. 9 to Fig. 11 will be described mainly taking the side wall 201 as an example, but the same is also performed for the side wall 202.

[0068] Now, step S10 is executed as described above, and each point p 201 (i) and each point p of the point cloud corresponding to the side wall 202 202 (j) and are obtained.

[0069] In addition, steps S21 and S31 are executed in the same manner as described above, and two parallel straight lines f' corresponding to the detection walls are 201 (x), f' 202 (x) is detected.

[0070] FIG. 9 is a diagram showing the relationship between the point cloud and the side wall 201, and shows the relationship by enlarging a part of the side wall 201. The part of the side wall 201 shown is the part closer to the laser range finder 101a, where the laser light 101b reaches the back of the unevenness. In FIG. 9, each point p of the point cloud corresponding to the side wall 201 is 201 (i) exists near the surface of the side wall 201 with noise-induced variations.201 In (i), indexes are assigned according to the irradiation angles of the laser range finder 101a, and the indexes are connected by dashed lines in the order of the indexes. 201 (x) is obtained as a straight line passing between the convex and concave portions of the side wall 201. Here, each point p 201 In (i), because the position fluctuates due to noise, a point obtained from a convex portion may be observed on the concave side beyond the detection wall, and vice versa.

[0071] In order to avoid contact between the transport vehicle 300 and the wall surface, it is ideal to obtain a straight line connecting the convex portions of the side wall 201 as the corrected wall. 201 Among (i), it is necessary to exclude points obtained from the concave portion of the side wall 201 and select (extract) points obtained from the convex portion. This selection is performed by, for example, selecting (extracting) each point p 201 (i) may be based on whether it is closer to the container center than the detection wall. However, if the sensor noise is large compared to the height of the unevenness of the side wall 201, points obtained from the recesses may be mixed in closer to the container center than the detection wall, and this criterion may result in misjudgment.

[0072] Therefore, after step S31, the correction unit 103 obtains inner wall candidate points, which are a point group representing the positions of the convex portions of the side wall 201, by steps S41a-1 to S41a-4, which are modified versions of step S41, and translates the detected wall based on the inner wall candidate points to obtain a corrected wall, which is the inner wall.

[0073] That is, the correction unit 103 corrects a straight line f' representing the detection wall as shown in FIG. 201 An initial boundary 801 is drawn at a location moved a predetermined distance from (x) toward the center of the container (step S41a-1). Note that in Figures 9 to 11, the container center side is the side with the smaller y coordinate.

[0074] After step S41a-1, the correction unit 103 corrects each point p 201 Of (i), a point on the container center side as viewed from the initial boundary 801 is extracted as the initial extraction result 802 (step S41a-2).

[0075] After step S41a-2, the correction unit 103 corrects each point p of the point group as shown in FIG. 201 Among (i), points sandwiched between the initial extraction results 802 (points of a rectangle) are extracted as secondary extraction results 803 (points of a triangle) (step S41a-3). Supplementally, when two initial extraction results 802 sandwich a point of the secondary extraction result 803, a point of the other initial extraction result 802 exists within a range obtained by moving the dashed line to the left and right by the number of points indicated by a predetermined threshold value from a point of one initial extraction result 802. In addition, the correction unit 103 acquires inner wall candidate points representing the positions of the convex parts of the side wall 201 as the extraction result 804. The extraction result 804 is each point obtained by combining each point of the initial extraction result 802 and each point of the secondary extraction result 803. Note that the above steps S41a-1 to S41a-3 are executed not only for the side wall 201 but also for the side wall 202 in the same manner.

[0076] After step S41a-3, the correction unit 103 corrects the two straight lines f′ representing the detection wall based on the extraction result 804. 201 (x), f' 202 By narrowing (x) (step S41a-4), the model f″ of the modified wall 104 201 (x), f” 202 Get (x).

[0077] Specifically, for example, the correction unit 103 compares the extraction result 804 regarding the side wall 201 with the detected wall (f' 201 (x)) and translates the detection wall toward the center of the container by the first average value L1. Similarly, the correction unit 103 calculates the first average value L1 of the distribution P1 of the first distance between the side wall 202 and the detection wall (f' 202 A second average value L2 of the distribution P2 of the second distance between the detection wall 101 and the container 102 (x) is calculated, and the detection wall 104 is translated toward the container center by the second average value L2. This allows the correction wall 104 to stably pass near the tips of the convex portions of the side walls 201 and 202.

[0078] Alternatively, the correction unit 103 may calculate the standard deviation σ1 of the distribution P1, add the standard deviation σ1 multiplied by a predetermined positive constant α to the first average value L1, and translate the detection wall by the obtained sum (L1+α·σ1) (e.g., α=2 or 3). Similarly, the correction unit 103 may calculate the standard deviation σ2 of the distribution P2, add the standard deviation σ2 multiplied by a predetermined positive constant α to the second average value L2, and translate the detection wall by the obtained sum (L2+α·σ2). When a constant multiple of the standard deviation is added to the average value, the risk of collision with the wall surface can be further reduced. Note that the variance V may be used instead of the standard deviation σ.

[0079] After step S41a-4, step S50 is executed in the same manner as described above.

[0080] As described above, according to the second embodiment, the correction unit 103 translates the first detection wall based on a first average value of first distances between the first detection wall and a plurality of points obtained on the second detection wall side from the first detection wall among a plurality of points corresponding to the first wall. Also, the correction unit 103 translates the second detection wall based on a second average value of second distances between the second detection wall and a plurality of points obtained on the first detection wall side from the second detection wall among a plurality of points corresponding to the second wall.

[0081] Therefore, by using the configuration in which the translation is performed using the average value instead of the translation using the maximum value shown in Equation (11) or (15), the influence of noise on the amount of movement of the detection wall can be suppressed, and in addition to the effect of the first embodiment, the position of the correction wall 104 can be stabilized.

[0082] According to the second embodiment, the correction unit 103 may add a value obtained by multiplying the variance or standard deviation of the first distance by a predetermined positive constant to the first average value, and translate the first detection wall by the obtained addition result. Similarly, the correction unit 103 may add a value obtained by multiplying the variance or standard deviation of the second distance by a predetermined positive constant to the second average value, and translate the second detection wall by the obtained addition result. In this case, in addition to the above-mentioned effects, the risk of collision with the wall surface can be further reduced.

[0083] According to the second embodiment, among the points corresponding to the first wall, the points obtained on the second detection wall side from the first detection wall may be a set of points obtained by combining the points extracted on the second detection wall side from the initial extraction boundary on the second detection wall side from the first detection wall and the points sandwiched between the extracted points. Similarly, among the points corresponding to the second wall, the points obtained on the first detection wall side from the second detection wall may be a set of points obtained by combining the points extracted on the first detection wall side from the initial extraction boundary on the first detection wall side from the second detection wall and the points sandwiched between the extracted points. In this case, in addition to the above-mentioned effects, the configuration of extracting points obtained from the convex parts of the unevenness of the side walls 201 and 202 can further suppress the influence of noise on the amount of movement of the detection wall.

[0084] (Modifications of the first and second embodiments) The first and second embodiments may be modified and implemented as follows.

[0085] That is, in the first and second embodiments, the side walls 201 and 202 are modeled as two parallel straight lines f′. 201 (x), f' 202 (x) is used, but it is not limited to this. For example, two straight lines f' 201 (x), f' 202 In addition to (x), the back wall of the container is connected to the two straight lines f' 201 (x), f' 202 A third line f' has an end point close to the far end point of (x). 203 In this case, the function shown in the following formula (17) can be added to the two functions shown in formula (5).

[0086]

number

[0087] In other words, in addition to the above-mentioned representations of the first and second planes, the model further represents a third plane perpendicular to the rear end of the first plane and the rear end of the second plane. The detection unit 102 detects the first detection wall, the second detection wall, and the third detection wall corresponding to the third plane based on the model and the acquired point cloud. This makes it possible to reduce the risk of contacting the rear wall in addition to the effects of the first and second embodiments. For example, when the distance to the rear wall, which is the third detection wall, becomes equal to or less than a threshold value, it becomes possible to control the vehicle 300 to output an alarm or to stop the vehicle 300 from moving forward.

[0088] Next, in the first and second embodiments, the side walls 201 and 202 are present, and the first and second detection walls corresponding to the side walls 201 and 202 are detected, but the present invention is not limited thereto. For example, when the interval between the two walls of a container is known, the presence of the container may be determined so that the container is determined not to exist if the interval between the detection walls is far from the known interval. Instead of determining the presence of the container, the presence of the passage may be determined. In other words, when the distance between the first and second detection walls is equal to or greater than a threshold value, the detection unit 102 outputs a message indicating that a container or a passage having the first and second walls does not exist. This makes it possible to omit the calculation process for correcting the detection wall to a correction wall and the process for controlling the transport vehicle 300, in addition to the effects of the first and second embodiments, and thus reduces the processing load.

[0089] Next, in the first and second embodiments, the case where only one combination of the first detection wall and the second detection wall is detected has been described, but the present invention is not limited to this. That is, multiple combinations of the first detection wall and the second detection wall may be detected. For example, when multiple combinations of the first detection wall and the second detection wall are obtained, the detection unit 102 detects the first detection wall and the second detection wall by selecting the combination that includes the longest line segment from among the multiple combinations. This makes it possible to narrow down the candidates when multiple candidates are obtained as the first and second detection walls, in addition to the effects of the first and second embodiments.

[0090] Next, in the first and second embodiments, the acquisition unit 101 uses the laser range finder 101a that acquires a two-dimensional point cloud, but is not limited thereto. For example, the acquisition unit 101 may use a sensor that acquires a three-dimensional point cloud, such as a ToF (time-of-flight camera). In this case, the model of the two walls becomes a three-dimensional plane model, and instead of sharing the coefficient a' of x between the models as in equation (5), a constraint that the normal vectors of the three-dimensional plane are parallel may be introduced. In other words, the coordinate sequence of the point cloud is a coordinate sequence of three-dimensional coordinates, and the model expresses that the first plane and the second plane are parallel to each other by the normal vector of the first plane being the same as the normal vector of the second plane. With this method, in addition to the back wall of the above-mentioned modified example, the ceiling and floor may be modeled as planes, and the container may be treated as a rectangular parallelepiped. Conversely, if a corner of a warehouse is assumed, the number of detection walls may be reduced to two, for example, two orthogonal walls may be used as a model. Variations are possible if the geometric constraints regarding the two or more planes and their arrangement are known.

[0091] In each embodiment, one acquisition unit 101 is installed in front of the transport vehicle 300, but this is not limited thereto. For example, the acquisition unit 101 may be installed in the rear of the transport vehicle 300 in addition to the front of the transport vehicle 300. Alternatively, the acquisition unit 101 may be installed in other parts in addition to the front and rear of the transport vehicle 300. Specifically, for example, the wall detection device 100 further includes another acquisition unit 101 and a selection unit 105 provided in the detection unit 102, as shown in FIG. 12 and FIG. 13. Here, the other acquisition unit 101 is provided in the opposite direction (rearward direction) to the acquisition unit 101 arranged in the center of the tip in the traveling direction described above, and acquires a point cloud that is a coordinate sequence of multiple points corresponding to the first wall and the second wall. Accordingly, the detection unit 102 detects multiple combinations of the first detection wall and the second detection wall based on the point cloud acquired by the acquisition unit 101 and the point cloud acquired by the other acquisition unit 101. The selection unit 105 selects the combination including the longest detection wall from the multiple combinations. The detection unit 102 detects the first detection wall and the second detection wall, which are the selected combination. In this way, by acquiring detection walls individually from the point clouds acquired by each acquisition unit 101 and selecting the longest detection wall and using it as the detection result, it is possible to automatically switch the acquisition unit 101 when the container enters.

[0092] In each embodiment, the wall detection device 100 is not limited to a dedicated device, but may be implemented as a computer such as a personal computer (PC) on which a program for implementing the algorithm of each embodiment is installed. An example of implementing the wall detection device 100 as a computer will be described in the third embodiment below.

[0093] <Third embodiment> 14 is a block diagram illustrating a hardware configuration of a wall detection device according to a third embodiment. The third embodiment is a specific example of the first and second embodiments, and is a form in which a detection unit 102 connected to an acquisition unit 101 is realized by a computer.

[0094] The wall detection device 100 includes, as hardware, a CPU (Central Processing Unit) 11, a RAM (Random Access Memory) 12, a program memory 13, an auxiliary storage device 14, and an input / output interface 15. The CPU 11 communicates with the RAM 12, the program memory 13, the auxiliary storage device 14, and the input / output interface 15 via a bus. That is, the wall detection device 100 of this embodiment is realized by a computer having such a hardware configuration.

[0095] The CPU 11 is an example of a general-purpose processor. The RAM 12 is used by the CPU 11 as a working memory. The RAM 12 includes a volatile memory such as a Synchronous Dynamic Random Access Memory (SDRAM). The program memory 13 stores a program for implementing each unit according to each embodiment. For example, this program may be a program for causing a computer to implement each function of the detection unit 102 described above. Any of the functions of the detection unit 102 may be a function of the correction unit 103 or the selection unit 105. In addition, for example, a Read-Only Memory (ROM), a part of the auxiliary storage device 14, or a combination thereof is used as the program memory 13. The auxiliary storage device 14 non-temporarily stores data. The auxiliary storage device 14 includes a non-volatile memory such as a hard disc drive (HDD) or a solid state drive (SSD).

[0096] The input / output interface 15 is an interface for connecting to other devices including a sensor serving as the acquisition unit 101. Also, as shown in Fig. 15, the input / output interface 15 may be an interface for connecting to other devices including a sensor serving as another acquisition unit 101 in addition to the sensor serving as the acquisition unit 101. In any case, the input / output interface 15 is used for connecting to, for example, a sensor, a keyboard, a mouse, and a display.

[0097] The program stored in the program memory 13 includes computer executable instructions. When the program (computer executable instructions) is executed by the CPU 11, which is a processing circuit, the program causes the CPU 11 to execute a predetermined process. For example, when the program is executed by the CPU 11, the program causes the CPU 11 to execute a series of processes described with respect to each unit in FIG. 3. For example, when the computer executable instructions included in the program are executed by the CPU 11, the program causes the CPU 11 to execute a wall detection method. The wall detection method may include each step corresponding to each function of the acquisition unit 101 and the detection unit 102 described above. Furthermore, the wall detection method may include each step shown in FIG. 4, FIG. 5, and FIG. 8 as appropriate.

[0098] The program may be provided to the wall detection device, which is a computer, in a state where it is stored in a computer-readable storage medium. In this case, for example, the wall detection device further includes a drive (not shown) for reading data from the storage medium, and acquires the program from the storage medium. As the storage medium, for example, a magnetic disk, an optical disk (CD-ROM, CD-R, DVD-ROM, DVD-R, etc.), a magneto-optical disk (MO, etc.), a semiconductor memory, etc. can be appropriately used. The storage medium may be called a non-transitory computer readable storage medium. Also, the program may be stored in a server on a communication network, and the wall detection device may download the program from the server using the input / output interface 15.

[0099] The processing circuit for executing the program is not limited to a general-purpose hardware processor such as the CPU 11, but may be a dedicated hardware processor such as an ASIC (Application Specific Integrated Circuit). The term processing circuit (processing unit) includes at least one general-purpose hardware processor, at least one dedicated hardware processor, or a combination of at least one general-purpose hardware processor and at least one dedicated hardware processor. In the examples shown in Figures 14 and 15, the CPU 11, the RAM 12, and the program memory 13 correspond to the processing circuit.

[0100] According to at least one of the embodiments described above, it is possible to reduce the risk of contacting the walls when entering a region sandwiched between walls that are not necessarily of a simple shape.

[0101] Although several embodiments of the present invention have been described, these embodiments are presented as examples and are not intended to limit the scope of the invention. These embodiments can be implemented in various other forms, and various omissions, substitutions, and modifications can be made without departing from the spirit of the invention. These embodiments and their modifications are included in the scope of the invention and its equivalents as described in the claims, as well as the scope and spirit of the invention. [Explanation of symbols]

[0102] 11...CPU, 12...RAM, 13...program memory, 14...auxiliary storage device, 15...input / output interface, 100...wall detection device, 101...acquisition unit, 101a...laser range finder, 101b...laser light, 102...detection unit, 103...correction unit, 104...corrected wall, 200...container, 201, 202...side wall, 251...center line, 281, 282...triangle, 291, 292...regression line, 300...transport vehicle, 801...initial boundary, 802...initial extraction result, 803...secondary extraction result, 804...extraction result, f' 201 (x),f' 202 (x) …detection wall, f'' 201 (x),f'' 202(x) …corrected wall, p 201 (0),p 201 (1),p 201 (N 201 -2),p 201 (N 201 -1),p 202 (0),p 202 (1),p 202 (N 202 -2),p 202 (N 202 -1) …points.

Claims

1. A wall detection device that controls a transport vehicle via a control unit, an acquisition unit that acquires a point cloud that is a coordinate sequence of a plurality of points corresponding to a first wall and a second wall opposed to each other; a detection unit that detects a first detection wall corresponding to the first plane and a second detection wall corresponding to the second plane based on a model that represents a first plane that represents an approximate shape of the first wall and a second plane that represents an approximate shape of the second wall and that represents that the first plane and the second plane are parallel to each other, and the acquired point cloud; Equipped with Each of the first wall and the second wall has a shape that is different from a simple shape; The control unit controls the orientation of the wheels corresponding to the travel direction of the transport vehicle based on the detected first detection wall and second detection wall, so that the vehicle center axis along the longitudinal direction of the transport vehicle is located at the center between the two wall surfaces, the first detection wall and the second detection wall, and is oriented parallel to the wall surfaces.This is a wall detection device.

2. 2. The wall detection device of claim 1, wherein the detection unit detects the first plane from the plurality of points corresponding to the first wall, detects the second plane from the plurality of points corresponding to the second wall, and detects the first detection wall and the second detection wall by correcting the first plane and the second plane to be parallel to each other.

3. the detection unit includes a correction unit that translates the first detection wall toward the second detection wall to correct it to a first correction wall, and translates the second detection wall toward the first detection wall to correct it to a second correction wall, a number of points in the point cloud between the first modification wall and the second modification wall is less than a number of points in the point cloud between the first detection wall and the second detection wall; 3. A wall detection device according to claim 1 or 2.

4. The correction unit moving the first detection wall in parallel based on a first average value of first distances between the first detection wall and a plurality of points obtained on the second detection wall side from the first detection wall among the plurality of points corresponding to the first wall; moving the second detection wall in parallel based on a second average value of second distances between the second detection wall and a plurality of points obtained on the first detection wall side from the second detection wall among the plurality of points corresponding to the second wall; The wall detection device of claim 3.

5. The correction unit is adding a value obtained by multiplying a variance or standard deviation of the first distance by a predetermined positive constant to the first average value, and translating the first detection wall by the obtained addition result; adding a value obtained by multiplying the variance or standard deviation of the second distance by a predetermined positive constant to the second average value, and translating the second detection wall by the obtained addition result; The wall detection device of claim 4.

6. The correction unit is The first detection wall is translated to a position of a point among the plurality of points corresponding to the first wall, the point being the most distant from the second detection wall; The second detection wall is translated to a position of a point among the plurality of points corresponding to the second wall, the point being the most distant from the first detection wall. The wall detection device of claim 3.

7. the acquisition unit has a sensor, and acquires the point cloud by measuring a distance between each of the plurality of points and the sensor using the sensor; the detection unit classifies a plurality of points in the point cloud into a first point cloud consisting of a plurality of points within a predetermined distance from the first plane and a second point cloud consisting of a plurality of points within a predetermined distance from the second plane, associates a plurality of points in the first point cloud with the first wall, associates a plurality of points in the second point cloud with the second wall, and detects the first detection wall and the second detection wall based on the first point cloud, the second point cloud, and the model; The predetermined distance is equal to or greater than a larger value of a tolerance of the sensor and a height of a designed unevenness on the first wall and the second wall. A wall detection device according to any one of the preceding claims.

8. The model further represents a third plane perpendicular to the rear end of the first plane and the rear end of the second plane, the detection unit detects the first detection wall, the second detection wall, and a third detection wall corresponding to the third plane, based on the model and the acquired point cloud; A wall detection device according to any one of the preceding claims.

9. the detection unit outputs a signal indicating that a container or a passage having the first wall and the second wall does not exist when a distance between the first detection wall and the second detection wall is equal to or greater than a threshold value. A wall detection device according to any one of the preceding claims.

10. When a plurality of combinations of the first detection wall and the second detection wall are obtained, the detection unit detects the first detection wall and the second detection wall by selecting a combination including the longest line segment from the plurality of combinations. A wall detection device according to any one of the preceding claims.

11. the coordinate sequence is a two-dimensional coordinate sequence, the model expresses that the first plane and the second plane are parallel to each other by having the same gradient of a first straight line representing a horizontal cross section of the first plane and a second straight line representing a horizontal cross section of the second plane; A wall detection device according to any one of the preceding claims.

12. the coordinate sequence is a three-dimensional coordinate sequence, the model expresses that the first plane and the second plane are parallel to each other by a normal vector of the first plane and a normal vector of the second plane being identical to each other; A wall detection device according to any one of the preceding claims.

13. Another acquisition unit is provided in an opposite direction to the acquisition unit and acquires a point cloud that is a coordinate sequence of a plurality of points corresponding to the first wall and the second wall. A selection unit provided in the detection unit; Further comprising: the detection unit detects a plurality of combinations of the first detection wall and the second detection wall based on the point cloud acquired by the acquisition unit and the point cloud acquired by the other acquisition unit; The selection unit selects a combination including the longest detection wall from among the plurality of combinations, The detection unit detects the first detection wall and the second detection wall, which are the selected combination. A wall detection device according to any preceding claim.

14. A transport vehicle equipped with the wall detection device according to any one of claims 1 to 13.

15. A self-propelled transport vehicle equipped with the wall detection device and a control unit according to any one of claims 1 to 13.

16. A control method executed by a wall detection device that controls a transport vehicle via a control unit, the control unit controls the direction of the wheels corresponding to the traveling direction of the transport vehicle based on the first detection wall and the second detection wall detected by the wall detection device so that a vehicle center axis along the longitudinal direction of the transport vehicle is located at the center between the two wall surfaces of the first detection wall and the second detection wall and is in a direction parallel to the wall surfaces, The control method includes: The wall detection device acquires a point cloud that is a coordinate sequence of a plurality of points corresponding to a first wall and a second wall opposed to each other; The wall detection device detects a first detection wall corresponding to the first plane and a second detection wall corresponding to the second plane based on a model that represents a first plane representing an approximate shape of the first wall and a second plane representing an approximate shape of the second wall and that represents that the first plane and the second plane are parallel to each other, and the acquired point cloud; Equipped with The method of claim 1, wherein each of the first wall and the second wall has a shape other than a simple shape.

17. A control method executed by a self-propelled transport vehicle including a wall detection device and a control unit, The wall detection device acquires a point cloud that is a coordinate sequence of a plurality of points corresponding to a first wall and a second wall opposed to each other; The wall detection device detects a first detection wall corresponding to the first plane and a second detection wall corresponding to the second plane based on a model that represents a first plane representing an approximate shape of the first wall and a second plane representing an approximate shape of the second wall and that represents that the first plane and the second plane are parallel to each other, and the acquired point cloud; The control unit controls the direction of the wheels corresponding to the traveling direction of the transport vehicle based on the first detection wall and the second detection wall detected by the wall detection device so that a vehicle center axis along the longitudinal direction of the transport vehicle is located at the center between the two wall surfaces of the first detection wall and the second detection wall and is parallel to the wall surfaces; Equipped with The method of claim 1, wherein each of the first wall and the second wall has a shape other than a simple shape.

18. A program for causing a wall detection device to realize a function of controlling a transport vehicle via a control unit, the control unit controls the direction of the wheels corresponding to the traveling direction of the transport vehicle based on the first detection wall and the second detection wall detected by the wall detection device so that a vehicle center axis along the longitudinal direction of the transport vehicle is located at the center between the two wall surfaces of the first detection wall and the second detection wall and is in a direction parallel to the wall surfaces, The control function is A function of acquiring a point cloud that is a coordinate sequence of a plurality of points corresponding to a first wall and a second wall opposed to each other; a function of detecting a first detection wall corresponding to the first plane and a second detection wall corresponding to the second plane based on a model that represents a first plane that represents an approximate shape of the first wall and a second plane that represents an approximate shape of the second wall and that represents that the first plane and the second plane are parallel to each other, and the acquired point cloud; Equipped with Each of the first wall and the second wall has a shape that is different from a simple shape.

19. A computing device capable of communicating with an acquisition unit and a control unit and controlling a transport vehicle via the control unit, receiving a point cloud from the acquisition unit that acquires a point cloud which is a coordinate sequence of a plurality of points corresponding to a first wall and a second wall opposed to each other, calculating two parallel straight lines that model the first wall and the second wall based on the point cloud; a model expressing a first plane representing an approximate shape of the first wall and a second plane representing an approximate shape of the second wall, and expressing that the first plane and the second plane are parallel to each other based on the calculation result, and a detection unit detecting a first detection wall corresponding to the first plane and a second detection wall corresponding to the second plane based on the acquired point cloud; Each of the first wall and the second wall has a shape that is different from a simple shape; The control unit is a calculation device that controls the direction of the wheels corresponding to the traveling direction of the transport vehicle based on the detected first detection wall and second detection wall so that the vehicle center axis along the longitudinal direction of the transport vehicle is located at the center between the two wall surfaces of the first detection wall and the second detection wall and is in a direction parallel to the wall surfaces.

20. The wall detection device according to claim 1 , wherein the shape different from a simple shape has a horizontal cross section with periodic concaves and convexes.

21. The wall detection device of claim 1 , wherein the shape different from a simple shape is a shape having a protruding doorknob or handrail.

22. The wall detection apparatus of claim 1 , wherein the shape different from a simple shape is a shape whose exact shape cannot be modeled in advance.

23. 23. The wall detection apparatus of claim 22, wherein the precise shape is a different shape than the general shape.

Images