JP6630950B2 - Route calculation device, route calculation program, and route calculation method - Google Patents

Description

  The present invention relates to a route calculation device, a route calculation program, and a route calculation method, and more particularly to, for example, a route calculation device, a route calculation program, and a route calculation method for calculating a moving route of a moving object that travels automatically.

  An example of the background art of the present invention is disclosed in Patent Document 1. In the route generation device for autonomous movement disclosed in Patent Document 1, a route with the minimum traveling cost is generated by selecting a start point end point node, searching for a path between the two nodes by algorithm A *, and reviewing the start point end point node.

JP 2005-50105 [G05D 1/02, G05B 13/02]

  However, in this background technology, a route is simply generated so that the traveling cost is minimized, and at the stage of generating the route, it is completely considered whether the vehicle travels in a safe, secure and safe area. Absent.

  Therefore, a main object of the present invention is to provide a novel route calculating device, a route calculating program, and a route calculating method.

  Another object of the present invention is to provide a route calculation device, a route calculation program, and a route calculation program that can calculate a route that travels in a safe and secure area not only in a place with a short travel distance and a good view but also in a place with a bad view. Is to provide a way.

A first aspect of the present invention is a route calculating device that calculates a moving route of a moving object that automatically travels with a person thereon, and the route calculating device includes a storage unit , a visibility calculating unit, and a calculating unit. The storage means stores preset route information, preset virtual view area information indicating a virtual view area of the moving object, a line-of-sight (level of visibility) from the moving object , and a level of security obtained empirically. The grid map assigned to each cell is stored. The visibility calculating means calculates the level of the visibility based on the first viewable area and the second viewable area included in the route information and the virtual view area information. The calculating means calculates a route having a short moving distance, a high level of security, and a high level of visibility . Calculation output means, the start position and the goal position are inputted, using a predetermined algorithm, empirically obtained comfort level, and the level of the visible rate with reference to the grid map assigned to each cell , Calculate the route.

  According to the first aspect of the invention, the moving route of the moving object is calculated so that not only the moving distance is short but also the level of security and the level of visibility are increased. It is possible to calculate a route that travels in a safe and secure area even in a bad place.

  A second invention is according to the first invention, and the level of the visibility rate from the moving object assigned to each cell of the grid map is set for each approach direction to the cell.

  According to the second aspect, it is possible to appropriately calculate a route having a high visibility ratio level according to the visibility ratio level corresponding to the traveling direction of the moving object.

  A third invention is according to the second invention, and has a straight line direction perpendicular to the four sides of each cell and a direction oblique to the four sides.

  According to the third aspect, it is possible to cope with the traveling direction of the moving body including the oblique direction in addition to the front, rear, left and right as seen from the moving body, and it is possible to more appropriately calculate a route having a high visibility ratio.

  A fourth invention is according to the first to third inventions, wherein the calculating means calculates a route by weighting each of the moving distance, the level of security, and the level of visibility with empirically obtained weights. I do.

  According to the fourth aspect, the weight of each of the moving distance, the level of security, and the level of the visibility ratio can be empirically obtained by an experiment. Therefore, based on the security received by the subject, It is possible to calculate the moving route in consideration of the sense of security of the user.

  A fifth invention is according to the first to fourth inventions, wherein, in the grid map, a travelable area in the environment in which the moving object travels is obtained by extracting a geometric straight path from a shape map measured in advance. , By giving a predetermined width to the geometrical straight path.

  According to the fifth aspect, the travelable area in the grid map is created by giving a predetermined width to the geometric straight path, so that an unnecessary area can be excluded when calculating the movement route, Since it is possible to calculate a smoother route by adopting a simple shape approximating the shape of the actual passage, it is possible to improve the riding comfort of the moving body and reduce the load on the calculating means for calculating the route.

A sixth invention is a map of an environment in which a moving object travels , and is a first viewable area that is a travelable and visible area, and a second view that is a non-travelable and visible area. It is calculated based on the viewable area, the preset route information indicating the invisible and invisible area that is incapable of traveling and invisible , and the virtual view area information indicating the preset virtual view area of the moving object. Storage means that stores a grid map in which each cell is assigned a level of visibility from a moving object and a level of security obtained empirically. a route calculation program for calculating, on a computer, a first viewable area and a second viewable area included in the route information, the visible rate for calculating the level of visible rate based on the virtual viewing area information Out step, setting step sets a start position and the goal position of the moving body, and from the set start position in case of moving the moving body to the goal position, visible rate from the mobile assigned to each cell of the grid map By referring to the level and the level of security, a calculation step of calculating a route with a short moving distance, a high level of security and a high level of visibility is executed.

A seventh invention is a map of an environment in which the moving object travels , and is a first viewable area that is a travelable and viewable area, and a second view that is a non-travelable and viewable area. It is calculated based on the viewable area, the preset route information indicating the invisible and invisible area that is incapable of traveling and invisible , and the virtual view area information indicating the preset virtual view area of the moving object. Storage means that stores a grid map in which each cell is assigned a level of visibility from a moving object and a level of security obtained empirically. a route calculation method of calculating computer, the computer has a first viewable area and a second viewable area included in the route information, to calculate the level of visible rate based on the virtual viewing area information Set the start position and the goal position of the moving body, and in the case of moving the moving body from the set start position to the goal position, the level of visible rate and sense of security from a mobile assigned to each cell of the grid map By referring to the level, a route having a short moving distance, a high level of security, and a high level of visibility is calculated.

  In the sixth and seventh inventions as well, similar to the first invention, the moving path of the moving object is calculated so that not only the moving distance is short but also the level of security and the level of visibility are increased. It is possible to calculate a route that travels in a safe and secure area in a straight path and that travels in a safe and secure area even in a place with poor visibility such as a corner or an intersection.

  According to the present invention, it is possible to calculate a route that travels in a safe and secure area not only in a place with a short travel distance and good visibility but also in a place with poor visibility.

  The above and other objects, features and advantages of the present invention will become more apparent from the following detailed description of embodiments with reference to the drawings.

FIG. 1 is a block diagram showing an example of an electrical configuration of a moving object including a computer functioning as a route calculation device according to one embodiment of the present invention. FIG. 2 is an illustrative view showing one example of an external configuration of the moving body shown in FIG. 1. FIG. 3 is an illustrative view for explaining a detection range of the distance sensor shown in FIGS. 1 and 2. FIG. 4 is an illustrative view for explaining a detection range of the distance sensor shown in FIGS. 1 and 2. FIG. 5 is an illustrative view for explaining the distance between the center of the moving body and the wall in the experiment. FIG. 6 is a graph showing numerical values of the subject's sense of security when the speed of the moving object carrying the subject and the distance from the wall are variably set. FIG. 7 is a three-dimensional graph showing a sense of security corresponding to the moving speed of the moving object carrying the subject and the distance from the wall. FIG. 8 is an illustrative view showing one example of a grid map for searching for a moving route and an example of a part of the grid map. FIG. 9 is an illustrative view showing one example of a grid map in consideration of a sense of security. FIG. 10 is an illustrative view showing another example of the grid map in consideration of a sense of security. FIG. 11 is an illustrative view showing one example of a calculated route. FIG. 12 is an illustrative view showing another example of the calculated route. FIG. 13 is an illustrative view showing one example of a grid map of a corner on which the moving object travels. FIG. 14 is an illustrative view showing one example of a case where a virtual field of view is superimposed on a grid map of a corner on which a moving object travels. FIG. 15 is an illustrative view showing one example of a case where a virtual view area is superimposed on a grid map of a straight line portion where a moving object travels. FIG. 16 is an illustrative view showing one example of a case where a virtual view area is superimposed on a grid map of an intersection where a moving object travels. FIG. 17 is an illustrative view showing one example of a case where a virtual view area is superimposed on a grid map of a corner on which a moving object travels. FIG. 18 is a graph showing the numerical value of the number of times the subject felt anxious for each location having a different visibility from the moving body on which the subject was placed. FIG. 18 is a graph showing a numerical value of a rate at which the subject felt anxiety for each portion having a different visibility from the moving body on which the subject was placed. FIG. 20 is an illustrative view showing one example of a grid map in consideration of a sense of security. FIG. 21 is an illustrative view showing one example of a grid map in consideration of a sense of security. FIG. 22 is an illustrative view showing one example of a grid map in consideration of each visibility in the approach direction of each cell. FIG. 23 is an illustrative view showing a grid map of a part of the orbital route using the average value of the visibility in each approach direction of each cell. FIG. 24A is an illustrative view showing one example of a route calculated by a conventional method. FIG. 24B is an illustrative view showing one example of a route calculated by the method of the embodiment. FIG. 25 is an illustrative view showing a process of creating a grid map; FIG. 26A is an illustrative view showing one example of a grid map created by the method of the embodiment. FIG. 26B is an illustrative view showing one example of a shape map. FIG. 27A is an illustrative view showing one example of a clockwise route calculated by the conventional method and the method of the embodiment. FIG. 27B is an illustrative view showing one example of a counterclockwise route calculated by the conventional method and the embodiment. FIG. 28A is a graph showing a numerical value of the subject's sense of security when the moving object carrying the subject runs along the route. FIG. 28B is a graph showing a numerical value of the comfort of the subject when the moving body carrying the subject runs on the route. FIG. 29 is an illustrative view showing one example of a memory map of the RAM shown in FIG. 1; FIG. 30 is a flowchart showing a route calculation process of the CPU shown in FIG.

  FIG. 1 is a block diagram showing an electrical configuration of a moving body 10 according to this embodiment. The moving body 10 includes a computer 12 which also functions as a route calculation device. The computer 12 is a computer such as a general-purpose personal computer or a workstation, and includes components such as a CPU 12a, a RAM 12b, and an HDD 12c.

  Further, an input / output interface (hereinafter, simply referred to as “interface”) 14, an operation lever 16, and distance sensors 18a, 18b, 18c are connected to the computer 12. The interface 14 is connected to a motor 22a via a motor driver 20a and to a motor 22b via a motor driver 20b. Furthermore, encoders 24a and 24b are connected to the interface 14.

  The rotation shaft of the motor 22a and the rotation shaft of the left rear wheel 34a (see FIG. 2) are connected using a gear, and the rotation shaft of the motor 22b and the rotation shaft of the right rear wheel 34b (see FIG. 2) are geared. Are connected using

  Here, referring to FIG. 2 (A), a moving body 10 of this embodiment is a moving body such as an electric wheelchair, and has left and right front wheels (casters) 32a, 32b and left and right rear wheels below. 34a and 34b are provided. The operation lever 16 described above is provided above the left frame of the moving body 10. Further, the above-described distance sensor 18a is attached to the left frame of the moving body 10 and to the left of step 36a where the user places the left foot. However, the distance sensor 18a is a frame on the right side of the moving body 10, and may be attached to the right side of the step 36b where the user puts his right foot. Further, as shown in FIG. 2B, which is a schematic view of the moving body 10 viewed from above, the above-described distance sensor 18b is provided at a lower rear portion of the moving body 10. Further, a distance sensor 18c is provided at an upper rear portion of the moving body 10, and the distance sensor 18c is provided at the same height as or higher than the viewpoint of the user riding on the moving body 10.

  In this embodiment, the distance sensors 18a, 18b and 18c are attached to the front and rear of the moving body 10, but they may be mounted to the left and right of the moving body 10. The reason why the three distance sensors 18a, 18b, and 18c are provided before and after or right and left of the moving body 10 is to detect (measure) the distance around the moving body 10 over the entire circumference (360 °). is there. However, this is only an example, and two or four or more distance sensors may be provided.

  Further, in this embodiment, the distance sensors 18a, 18b and 18c are used not only for fixed objects (static obstacles) such as walls and columns in an environment but also for moving objects (dynamic objects) such as humans. Measure (detect) the distance to the obstacle.

  Returning to FIG. 2A, a box 40 is provided below the seat of the moving body 10 and between the left rear wheel 34a and the right rear wheel 34b. The computer 12, the interface 14, the motor drivers 20a and 20b, the motors 22a and 22b, and the encoders 24a and 24b are provided therein. However, the computer 12 and the interface 14 may be provided outside the box 40.

  The computer 12 controls the overall control of the mobile unit 10 of this embodiment. In this embodiment, the CPU 12a calculates a moving route of the moving body 10. The CPU 12a controls the driving of the motors 22a and 22b automatically or in response to an operation input from the operation lever 16. That is, the CPU 12a controls the movement of the moving body 10. Further, the CPU 12a acquires and stores distance data or rotation speed data detected by the distance sensors 18a, 18b, 18c and the encoders 24a, 24b. Then, the CPU 12a measures the distance to the obstacle or estimates (determines) the position of the moving object 10 according to the detected data.

  The operation lever 16 is operated by a user riding on the moving body 10, and a signal (operation input) corresponding to the operation is given to the computer 12. For example, operations such as forward, backward, stop, left turn, right turn, and turn can be performed.

  However, an operation input can be given to the computer 12 by remote control using a remote controller (not shown). In this embodiment, the operating lever 16 does not have to be provided in order to make the moving body 10 travel automatically.

  The distance sensors 18a, 18b, and 18c are, for example, general-purpose laser range finders (LRFs) that irradiate a laser and measure the distance to the object from the time it takes to reflect the object back. . For example, in the LRF, a laser emitted from a transmitter (not shown) is reflected by a rotating mirror (not shown), and is scanned in a fan-like manner at a constant angle (for example, 0.25 degrees). Further, in this embodiment, the scanning cycle of the entire detection range (see FIG. 3) is 25 msec.

  FIG. 3 is an illustrative view for explaining a detection range (measurement range) in the horizontal direction (left-right direction) of the distance sensors 18a to 18c. The measurement range of the distance sensors 18a and 18b is a fan shape having a radius R1 (R1 ≒ 10 to 15 m), and the angle of the fan is 135 ° on each of the left side and the right side with respect to the front direction. That is, the distance can be detected in a range of 270 ° centered on the front. The measurement range of the distance sensor 18c of this embodiment is indicated by a fan shape having a radius R2 (R2 ≒ 8 m). The angle of the fan is 90 ° on each of the left and right sides with respect to the front direction. That is, the distance can be detected in a range of 180 ° centered on the front. Further, as shown in FIG. 4, the measurement range in the vertical direction (up-down direction) of the distance sensor 18c also has a fan shape in the up-down direction. The angle of the fan in the vertical direction is 20 ° on each of the upper side and the lower side with respect to the front direction. That is, the distance can be detected in a range of 40 ° centered on the front. Then, the measurement range in the horizontal direction and the vertical direction of the distance sensor 18c is a virtual view range or area (virtual view area described later) of the moving body 10 (or a user riding on the moving body 10). .

  Returning to FIG. 1, the motor drivers 20a and 20b drive the motors 22a and 22b in accordance with instructions from the computer 12. The encoder 24a detects the rotation speed (rps) of the motor 22a, and inputs data on the rotation speed (rotation speed data) to the computer 12 via the interface 14. Similarly, the encoder 24b detects the rotation speed of the motor 22b, and inputs rotation speed data on the rotation speed to the computer 12 via the interface 14.

  The computer 12 acquires distance data detected by the distance sensors 18a, 18b, 18c and rotation speed data detected by the encoders 24a, 24b, and stores them in the RAM 12b (or the HDD 12c). However, the distance data detected by the distance sensor 18a, the distance data detected by the distance sensor 18b, and the distance data detected by the distance sensor 18c are distinguished, and the distance data and the rotation speed data detected at the same time are distinguished. Are associated with each other.

  The moving body 10 having such a configuration can move (run) by operating the operation lever 16 as described above. However, by inputting (setting) a start point and a goal point, the moving path 10 can be moved. , And the vehicle can automatically travel (autonomously move).

  For example, a normal travel route plan is a technique for finding the shortest distance or the shortest route. However, since a route that passes near an obstacle (such as a wall or a pillar) may be selected as the shortest distance, it is easy to give the user riding the moving object 10 fear. In addition, if the moving speed is increased, the required time can be reduced, but the fear of the user riding the moving object 10 increases because it becomes difficult for the user to predict the movement. Furthermore, when the speed of the moving body 10 is very low, it is considered safe but frustrating for the user riding on the moving body 10. That is, it is considered that the sense of security (comfort) of the user riding on the moving object 10 is related to the distance or the speed to the obstacle on the moving route.

For this reason, an experiment for quantifying the relationship between the distance between the moving body 10 and the obstacle and the speed of the moving body 10 and the sense of security of the user riding on the moving body 10 was performed. Subjects take the moving body 10 to the automatic travel, the obstacle (here, the wall) the distance d _h from to the moving body 10 (the center of) three stages (distant, moderate, close) varied, the moving body 10 Was changed in three stages (fast, medium, slow) and a total of 9 trials were performed.

However, the distance _{d h} from the wall, represents the width of the corridor at a rate in the case of the L (2.4 m), as shown in FIG. 5, when the far (F) is, L × 0.5 (1 .20 m), L × 0.35 (0.84 m) for medium (M), and L × 0.2 (0.48 m) for close (C) ). The speed v is set to 1.6 m / sec in the case of fast (F), 1.2 m / sec in the case of medium (M), and in the case of slow (L). Is set to 0.8 m / sec.

  The subjects were 22 males, 11 males and 11 females, and the average age was 23.53. In addition, the subject evaluated the sense of security on a 5-point scale for each trial. However, the case where the sense of security was the largest was "5", and the case where the sense of security was the smallest (the sense of anxiety was the largest) was "1". FIG. 6 shows the tabulated results (experimental results). The tabulation result shown in FIG. 6 is a bar graph obtained by averaging the numerical values of the sense of security in each trial for all subjects.

As can be seen with reference to FIG. 6, according to the experimental results, there is a tendency to decrease the confidence velocity v increases, for a distance d _h from the wall, the peak of the sense of security around moderate (M) Exists. Before the experiment, it was expected that the sense of security would increase as one moved away from the wall, but it was found that the wall side tended to be preferred over the center of the passage. In addition, if it is moderate the distance d _h from the wall (M), when the speed v much in the (M) and late (L), had a higher numerical value of peace of mind.

Also, according to experimental results, when modeling the sense of security, speed of the moving body 10 v (m / sec), the distance d _{h (m)} and comfort U from obstacles, elliptical as shown in FIG. 7 It is represented by a part of the surface of a sphere. As can be seen from FIG. 7, when the speed v is medium (M) and the distance dh is medium (M), the sense of security U is maximized. For example, referring to FIG. 7, an area determined by a distance d _h (m) that does not approach or collide with an obstacle or a speed v (m / sec) that does not disturb the user is It is a safe area, and it can be said that there is an area where a sense of security can be obtained in a part of the safe area. However, in FIG. 7, the sense of security U is normalized to 0 to 1. The case where the sense of security U is the largest is “1”, and the case where the sense of security U is the smallest is “0”. In FIG. 7 (similarly in FIGS. 9 and 10 described later), the case where the security is the smallest is black, the case where the security is the highest is white, and the size (level) of the security is shown in gray scale. It is.

In order to reflect this model of security in route calculation (route planning), the security is approximated by a quadratic function shown in Equation 1. However, in Equation 1, a U _(d h, x ^·) is a sense of security, _{d h} is the distance of the moving body 10 from the wall, x ^· is the velocity of the moving body 10, _{V 0} is reassurance Is the speed of the moving object 10 when the maximum value is obtained, and k ₀ L is the distance from the wall to the center of the moving object 10 when the sense of security becomes the maximum value. However, the speed V ₀ and the distance k ₀ L are values obtained by experiments. More specifically, in this embodiment, the width L is 2.4 m, the speed V _{0 is} 0.8 m / sec, and the distance k ₀ L is 0.84 m. For convenience of notation, "." Is displayed above and to the right of "x" except in mathematical expressions, but is actually displayed above "x" as shown in Expression 1, and this "." Mean differentiation. same as below.

The minimum square method (regression analysis) results of a number 1 is approximated to the comfort of the model shown in FIG. 7, the constant _{c a = 0.04, c b =} 1.08, the c c = 0.679 obtained Was.

However, in case of actually traveling the moving body 10 has determined according to a model of comfort and speed x ^· mobile 10, there is a fear that gives uneasiness to a user riding. This is because the position where the moving body 10 is actually traveling and the position on the calculated (generated) moving route may be shifted. Further, since the distance between obstructions on the grid map is not considered, when detecting no obstacle on the grid map in the actual running, be moving body 10 is not traveling at an appropriate speed x ^· It is because there is sex.

  Note that an obstacle that is not on the grid map means an object other than a pillar or a wall, or a person (passerby).

Therefore, in this embodiment, ignore the component of the velocity x ^·, are to seek a sense of security. Then, the speed when the moving body 10 is moving, the actual distance d _h the distance sensors 18a to an obstacle such as a wall, with 18b is measured, the sense of security model in accordance with the distance d _h x ^· is determined.

Therefore, Equation 1 is transformed as Equation 2. However, as a result of approximating Equation 2 by the least squares method (regression analysis) to the model of security shown in FIG. 7 without considering the speed x ^· , the constants g _a = 0.009 and g _c = 0.363 are obtained. Obtained.

  FIG. 8A is a grid map of a part of the environment in which the moving body 10 of this embodiment travels as viewed from above (directly above). In the example illustrated in FIG. 8A, a hatched portion is an obstacle such as a wall, and a white portion is a passage. Hereinafter, the same applies to FIGS. 9 to 12. FIG. 8B shows a grid map for a range surrounded by a dotted line in FIG. In the example shown in FIG. 8B, the size of each cell of the grid map is set to 30 cm × 30 cm, but is actually set to about 5 cm × 5 cm. The size of this cell is an example and should not be limited. Further, in FIG. 8B, hatched cells indicate obstacles (here, walls), and white cells indicate passages.

FIG. 9 partially shows a grid map when a model of security is applied. However, comfort U of each cell (d _h) is calculated according to Equation 2, the numerical value of the calculated confidence U (d _h) (level) is stored corresponding to each cell. As described above, the grid map shown in FIG. 9, in order to clearly show the magnitude of the value of the confidence U (d _h), a numerical gray scale comfort U calculated for each cell (d _h) Shown. However, in the example shown in FIG. 9, the model of a sense of security is applied to a portion of a straight passage described substantially at the center of the grid map. As can be seen from partially enlarged view of FIG. 9, comfort U (d _h) is the largest at a position closer to the little wall side from the center of the passage.

  FIG. 10 shows a grid map when an obstacle is placed on a passage corresponding to a portion to which the model of security shown in FIG. 9 is applied. As can be seen from the partially enlarged view of FIG. 10, a plate is provided in a part of the passage in parallel with the passage. The board is installed at a position slightly closer to one wall side (the lower side in the drawing) than the center of the corridor. Therefore, in the part where the board is installed, the width L of the corridor is divided by the board, and the distance to the wall and the distance to the board are taken into consideration, so that the sense of security is reduced.

In such a case, without considering the sense of security (k _D = 1 in Equation 3 described later), as shown in FIG. 11, the start position SP and the goal position GP are set, and the shortest moving path is determined. When the calculation is performed, a straight movement path that passes through a side where the moving body 10 can barely pass is calculated, with the distance between the plate and the wall being short in the path divided by the plate.

On the other hand, when considering not only the moving distance but also a sense of security as in this embodiment (for example, k _D = 0.5 in Equation 3 described later), as shown in FIG. In, the movement path passing through the side where the distance between the plate and the wall is long is calculated. That is, a moving route having a short moving route and a high sense of security is calculated.

As described above, the route planning in consideration of the sense of security is performed using the A * (Aster) search algorithm. Specifically, in order to consider a sense of security, the cost function f (x) is defined as in Equation 3. Here, g (x) is the distance from the starting point (start position SP) to a certain point x, h (x) is the distance from the point x to the target point (goal position GP), and m _disc (x ) Is anxiety (1-security) of the route passing through the point x. However, in Equation 3, the sense of security at the point x is _mcomfort (x). Also, the k _D is the weight of reassurance to the shortest path, the weight k _D is calculated shortest path when the 1, becomes largest route sense of security when the weight k _D is 0 is calculated. However, in the grid map, since the route is calculated on a cell basis, the point x means a certain cell.

  Further, the normal moving route planning is a method of finding the shortest distance or the shortest time route as described above. However, the shortest distance is often selected as a route that passes near obstacles (walls, pillars, etc.). Particularly, the route that passes the shortest distance at a corner turns near the wall, which makes the route with poor visibility, It is easy to give the user riding the moving object 10 fear. In addition, not only at corners, but also in places with poor visibility such as intersections, the presence of other moving objects or pedestrians is not known, and it is difficult for the user riding the moving object 10 to make predictions about the movement. Increase. In other words, it is considered that the sense of security (comfort) of the user riding on the moving body 10 is related to the visibility of the moving route.

Therefore, in this embodiment, a model of a sense of security based on the quality of the outlook (visibility) is reflected in the route calculation (route planning). However, the visibility ratio V _index is calculated according to Equation 4.

  Each element in the equation 4 will be described with reference to the moving environment of the moving body 10 shown in FIGS. The example of the environment shown in FIG. 13 and FIG. 14 is a passage partitioned by a high wall, and shows a turning right. However, in the examples shown in FIGS. 13 and 14, it is assumed that the moving body 10 cannot travel in an area other than the passage. In this embodiment, a high wall refers to a height at which the line of sight of a user riding on the moving object 10 is blocked. Furthermore, a low wall refers to a height that does not obstruct the field of view of a user riding on the moving object 10.

  As an example, when the moving body 10 is an electric wheelchair, the height of the line of sight of a user who rides on an electric wheelchair having dimensions conforming to the JIS standard is about 1.0 m to 1.1 m. Therefore, if the moving body 10 is an electric wheelchair having a general size, the threshold value for determining whether or not to block the line of sight of the user riding the electric wheelchair may be set between 1.0 m and 1.1 m. Conceivable.

  Note that the threshold value for determining whether or not to block the view of the user riding on the moving body 10 is not limited to the above-described height, and may be appropriately set in accordance with use conditions such as the height of the seat of the moving body 10 or the physique of the user. It is desirable to be set.

  As shown in FIG. 13, the passage is provided by partitioning the environment (real space) in which the moving body 10 is placed or moved by a static obstacle such as a high wall. In this embodiment, the passage is an area in which the mobile unit 10 can travel, and the travel route of the mobile unit 10 is calculated in the area in which the mobile unit 10 can travel.

R _VT in _Equation 4 is the size (area) of the visible region of the moving object 10 (or the user riding on the moving object 10), and R _NT is the moving object 10 (or the user riding on the moving object 10). User)) is the area of the invisible area. However, in this specification, the fact that the moving body 10 is visible or visible means that the distance sensor 18c of the moving body 10 can detect the distance to any object.

  Accordingly, in the horizontal and vertical measurement ranges (hereinafter, sometimes referred to as “virtual field of view”) of the distance sensor 18c shown in FIGS. 3 and 4, the area where the distance can be measured is the visible area, The area where the distance cannot be measured is the invisible area.

  That is, when the mobile object 10 travels (moves) according to the movement route, the visible area is a range or area (hereinafter, referred to as a “visible area”) that can be visually recognized by the user riding on the mobile object 10 in the virtual view area. ). In this embodiment, of the visible areas, an area that overlaps with the area in which the moving body 10 can travel (the travelable area) is referred to as a first visible area, and the area in which the moving body 10 cannot travel (the non-travelable area). ) Is referred to as a second visible region (see FIG. 17). Further, the invisible area means a range or an area in which the user cannot visually recognize the virtual view area (hereinafter, referred to as an “invisible area”).

Further, of the invisible area, an area in which the mobile unit 10 cannot travel is referred to as an invisible area, and this invisible area is excluded from the calculation of the visibility ratio V _{index in Expression} 4.

In addition, even if it is an invisible area | region and it is a runnable area | region, the area | region which is considered to drive ahead more than fixed time (for example, 5 seconds) is excluded from the visibility ratio _{Vindex of Formula} 4. This is because such a region is irrelevant when calculating the movement route at the current position of the moving object 10.

Also, as can be seen from Equation 4, if the area R _{NT of the} invisible area is large, the visibility rate V _index is low (minimum value 0), and if the area R _{NT of the} invisible area is small, the visibility rate V _index is high (maximum value). Value 1).

Further, as described above, the invisible area is not included in Equation 4. Therefore, as shown in FIG. 15, when the moving body 10 travels on a straight path that is partitioned by a high wall on both sides, in the measurement range (virtual field of view) of the distance sensor 18c, the invisible area is set. , Only the first viewable area is included. That is, as shown in FIG. 15, a straight path has only the area _{RVT of the} visible region. In such a case, the visibility ratio V _index calculated according to Equation 4 is 1.

In addition, as shown in FIG. 16, even when the moving object 10 travels upward from the bottom of the drawing so as to approach an intersection partitioned by a high wall even if it is other than a corner, the virtual view area In the above, an invisible area is generated on the left and right fronts blocked by the invisible area. That is, since the intersection has the area R _{NT of the} invisible region, the visibility ratio V _index is lower than when the vehicle travels on a straight path as shown in FIG.

  Here, the data (route information data) as the route information indicating the travelable region and the non-travelable region, and the visible region or the non-visible region in the travelable region are automatically traveled in advance by the moving body 10 in advance. It is generated according to the distance data detected by the distance sensors 18a, 18b, 18c, and stored in the RAM 12b (or the HDD 12c) corresponding to each cell of the grid map. In this embodiment, the route information data also includes data on the height of a static obstacle (for example, a wall) that separates a travelable area from a non-travelable area in each cell of the grid map. Therefore, for example, if there is a cell whose data indicating the height of a static obstacle is 2.0 m and a cell whose data is 0.3 m, the area partitioned by the obstacle having a height of 2.0 m is invisible. The area which is a possible area and is partitioned by an obstacle having a height of 0.3 m does not hinder the field of view of the user riding on the moving body 10, and thus the second area which cannot be traveled and is visible is a second visible area. (See FIG. 17).

  It should be noted that, by setting a threshold value of the height of an obstacle that does not hinder the view of the user riding on the moving object 10, whether the same location on the route becomes an unviewable area or a second viewable area is determined. May change. The setting of the threshold value as to whether or not the visual recognition is possible is set based on the viewpoint of the user riding on the moving object 10. Therefore, the above-described threshold value changes depending on the height of the sheet on the moving body 10 or the physique of the user, and may be set as appropriate.

With the above configuration, for example, as shown in FIG. 17, when the vehicle is turned rightward and a part of the corner is formed by a low wall (height 0.3 m), An area partitioned by a low wall is not an invisible area, and only an area partitioned by a high wall is an invisible area. Therefore, the non-viewable area is reduced and the range that blocks the field of view is reduced, so that the first viewable area is enlarged. Further, of the area partitioned by the low wall, an area that is not blocked by the high wall is a second viewable area that is a region in which traveling is impossible and is visible. However, the second visually recognizable area is an area surrounded by a horizontal trapezoid in the diagonally forward right of the moving body 10 in FIG. For this reason, in the corner formed by a partly low wall, the area R _{VT of the} visible region is larger than in the corner formed only by the high wall as shown in FIGS. _{The index} will be higher.

Further, an experiment was performed to quantify the relationship between the visibility ratio V _index (good or bad visibility) calculated using Equation 4 and the sense of security of the user who actually rides on the moving object 10.

In the experiments, subjects take the moving body 10 to the automatic travel, straight or a portion high visible rate V _index, such as corner partitioned by low walls, the visible rate V _index, such as partitioned corner or intersection by high walls The moving body 10 was caused to travel on a complex orbital path including both of the low and high points. Each subject was run four times clockwise and four times counterclockwise for a total of eight trials.

The number of subjects was 15 men and 15 women in total, and the average age was 21.5 years. Note that this subject is a subject in an experiment for quantifying the relationship between the distance between the moving body 10 and the obstacle and the speed of the moving body 10 and the security of the user riding the moving body 10. Some are different. The subject was instructed to press a button on the remote control when he felt danger or anxiety. FIG. 18 shows the total result (experimental result). The tabulation result shown in FIG. 18 is a bar graph showing the total value of the number of times the button of the remote controller was pressed by all the subjects (the number of button clicks) at a plurality of positions (places) having different visibility ratios V _index in the circuit route. It is. FIG. 19 shows a button click rate obtained by dividing the number of button clicks shown in FIG. 18 by the number of times all subjects passed each position.

Since there is no position where the visibility ratio V _index is less than 0.3 in the orbital route in this experiment, FIGS. 18 and 19 show the experimental results for the positions where the visibility ratio V _index is 0.3 or more. .

As can be seen from FIGS. 18 and 19, according to the experimental results, when the visibility ratio V _index decreases, the anxiety tends to increase. In the vicinity of the lowest value of the visibility ratio V _index (0.3), the button click rate was slightly less than 50%, and a result was obtained in which anxiety was felt in a portion where the visibility ratio V _index was low.

FIGS. 20 and 21 show grid maps in the case of applying a model of a sense of security in consideration of the visibility ratio V _index . In this case, the visibility ratio V _index when the mobile unit 10 is located in each cell is calculated according to _{Equation 4} , and the calculated value (level) of the visibility ratio V _index is stored corresponding to each cell. However, in this embodiment, the numerical value of the visible rate _{V index} is a numerical value of the sense of security based on the visible rate _{V index.} In addition, a numerical value of the visibility ratio V _index according to the traveling direction of the moving body 10 (for example, each of the directions of traveling clockwise and counterclockwise on the orbital route) is calculated and stored. In the examples shown in FIGS. 20 and 21, the sense of security is calculated using the visibility ratio V _index in the case where the moving body 10 runs clockwise. That is, in this embodiment, the value of the visibility ratio v _index (x) corresponding to the traveling direction of the moving object 10 is stored in addition to the above-described sense of security m _format (x) corresponding to each cell of the grid map. Is done.

In the grid maps shown in FIGS. 20 and 21, the magnitude (level) of security calculated for each cell is shown in gray scale in order to easily show the magnitude of security in consideration of the visibility rate V _index . In FIGS. 20 and 21 as well, the case where the sense of security is the lowest is black, and the case where the sense of security is the highest is white.

FIG. 20 shows a grid map for a right turn (similar to FIG. 14) separated by a high wall. In this case, the model of the sense of security based on the distance of the moving body 10 from the wall and the speed of the moving body 10 is applied to the portion of the linear passage. In the vicinity of the corner, a model of a sense of security in consideration of the visibility ratio V _index is applied. As can be seen from FIG. 20, near the turning corner, a sense of security is high in a path in which the turning angle is slightly expanded and the vehicle moves so as to turn right, and the sense of security decreases toward the inside of the turning corner.

  FIG. 21 shows a grid map in the case of a right turn (a part of the inside) formed of a low wall (0.3 m in height) (similar to FIG. 17). I have. In this case, as described above, the area partitioned by the low wall does not become the invisible area, and only the area partitioned by the high wall becomes the invisible area. For this reason, unlike the case shown in FIG. 20, there is a portion where the sense of security is high even on the path passing inside the corner. Therefore, even at the corner, as in the case of the straight path, based on the model of a sense of security based on the distance of the moving body 10 from the wall and the speed of the moving body 10, it is slightly closer to the wall than the center of the passage. The feeling of security at the position close to is the largest.

As described above, the movement route of the mobile unit 10 is calculated according to the grid map in the case where a model of a sense of security taking into account the visibility rate V _index is applied.

As described above, the route planning in consideration of the sense of security is performed using the A * (Aster) search algorithm. Specifically, the cost function f (x) is defined as shown in Expression 5 in order to consider the visibility rate V _index . Similarly to Equation 3, g (x) is the distance from the starting point (start position SP) to a certain point x, h (x) is the distance from point x to the target point (goal position GP), m _disc (x) is the anxiety (1-security) of the route passing through the point x. The sense of security at the point x based on the distance of the moving object 10 from the wall and the speed of the moving object 10 is _mcomfort (x). Further, in Equation 5, the visibility at the point x based on the visibility V _index is v _index (x).

Also, _{k D} is the weight for the shortest path, the weight _{k D} is calculated shortest path when the 1, _{k m} is the distance of the moving body 10 from the wall, and comfort _{m comfort} based on the speed of the moving body 10 is the weight of the (x), the distance of the moving body 10 from the wall when the weight _{k m} is 1, and comfort _{m comfort} based on the speed of the moving body 10 (x) is the largest becomes the path is calculated. Further, _{k v} is the weight of the visible rate based on the visual index _{V index v index} (x), the weight _{k v} visible rate _{v index} (x) is the largest, based on a visible rate _{V index} when one path Is calculated.

Here, for example, when the moving body 10 is traveling along a straight path, as long as there is no obstacle in this path, as in the case described with reference to FIG. because only contains visible prohibited areas and the first viewable area, a visible rate based on the visual index _{V index v index} (x) becomes a maximum value. Thus, when the visible rate based on the visual index _{V index v index} (x) is the maximum value, it is not necessary to consider the visible rate _{V index} In route calculation, the visible rate _{v index} of (x) it may be automatically controlled to 0 weight k _v.

Also, considering the corner or visible rate based on the visual index V _index only a blind part of such intersection v _{index (x),} when it is desired through the shortest path for the other portions is always a weight k _m Control may be performed so as to be zero.

  Also, as described above, when calculating a complex route including a straight path portion and a portion with poor visibility such as a turn or an intersection, when calculating an appropriate route, the traveling portion , It is necessary to control the weight of the moving distance, the sense of security, and the visibility ratio.

  Therefore, in this embodiment, a model of a sense of security that can eliminate the need to control the weight during traveling is reflected in a travel route plan that calculates a complex route including a straight path and a turn or an intersection. It is.

Here, the visibility ratio V _index calculated according to Expression 4 changes depending on the traveling direction of the moving body 10 even at the same position. Therefore, in order to eliminate the need for controlling the weight during traveling, it is necessary to set in advance the visibility ratio V _index according to the traveling direction of the moving object 10 in each cell of the grid map.

FIG. 22 is an illustrative view showing one example of a grid map in consideration of each visibility in the approach direction of each cell. As shown in FIG. 22, when reflecting a model of a sense of security that can eliminate the need to control the weight during traveling in a travel route plan, each cell of the grid map includes the vertical direction, the horizontal direction, For each of the eight oblique directions, the data of the visibility ratio V _index calculated according to Equation 4 is associated.

Note that the direction in which the data of the visibility ratio V _index is associated is not limited to eight. For example, data of the visibility ratio V _{index in} each of the four directions of the vertical direction and the horizontal direction of each cell of the grid map may be associated with each cell of the grid map.

FIG. 23 is an illustrative view showing a grid map of a part of the orbital route. The grid map shown in FIG. 23 indicates the average value (level) of the visibility ratio V _{index in} each of the eight directions of each cell. In this grid map, in order to clearly show the magnitude of the average value of the visible rate V _index level of each of the eight directions of each cell, the level of the visible rate V _index calculated for each cell are shown in grayscale . In FIG. 23 as well, the case where the level of the visibility ratio V _index is the lowest is black, and the case where the level of the visibility ratio V _index is the highest is white.

As can be seen from FIG. 23, the turning angle P1 at the lower left of the drawing has poor visibility, that is, the visibility ratio V _index is low. On the other hand, the turning angle P2 at the lower right of the drawing has good visibility, that is, the visibility ratio V _index is high. This is because the corner P1 at the lower left of the drawing is partitioned by a high wall as shown in FIG. 20, while the corner P2 at the lower right of the drawing is partitioned by a low wall as shown in FIG. Because it is.

In the vicinity of the corner P1 at the lower left of the drawing, the level of the visibility ratio V _index inside the passage is lower than that outside the passage. Therefore, at the corner P1 at the lower left of the figure, the sense of security is lower as the route approaches the inside of the corner than at the corner where the route moves so as to bend and expand slightly.

As described above, the movement route of the mobile unit 10 is calculated according to the grid map in the case where the model of security is applied in consideration of the level of the visibility ratio V _{index in} each of the eight directions of each cell.

As described above, the route planning in consideration of the sense of security is performed using the A * (Aster) search algorithm. Specifically, the cost function f (x) is defined as in Equation 6 in consideration of the moving distance, the sense of security _mcomfort (x), and the visibility ratio _vindex (x). Similarly to Equation 5, g (x) is the distance from the starting point (start position SP) to a certain point x, and h (x) is the distance from point x to the target point (goal position GP). The first element is an element relating to the moving distance. Further, m (x) is anxiety at a certain point x (1−security), and n (x) is anxiety at a next point x ′, which is calculated according to Equation 3. The second element is an element relating to a sense of security (anxiety). Further, p (x) is the sum of the shielding rates (1-v _index (x, θ) /0.5) from the starting point (start position SP) to a certain point x, and q (x) is It is a shielding factor at a passing point x '. However, the occlusion ratio at each point x (each cell of the grid map) is calculated according to the data of the visibility ratio V _index according to the direction of approaching each point x. The third element is an element relating to the visibility ratio (outlook). k _d , k _c , and k _v are weighting factors. For example, when k _d = 1, k _c = 0, and k _v = 0, the route with the shortest moving distance is calculated.

FIG. 24A shows, as an example, a path calculated according to the method (Equation 6) of the embodiment with the respective weighting factors being k _d = 0.9, k _c = 0.019, and k _v = 1.5. Shown. The weight coefficient is set so that the route calculated according to the method of the embodiment matches or approximates the average route obtained in an experiment in which the subject manually ran. The number of subjects was 14 men and 16 women, for a total of 30 subjects, and the average age was 21.5 years. FIG. 24B shows, as a comparison target, a route calculated according to a conventional moving route plan for finding the shortest distance or the shortest time route. As can be seen from FIGS. 24 (A) and (B), it can be seen that the path calculated according to Equation 6 turns slightly larger in turn than the path calculated by the conventional method.

  Further, a description will be given of a method of creating a grid map that allows a smoother route to be calculated when the route is calculated using the method of the present embodiment. Specifically, the shape of the grid map used in the method of the present embodiment is a simple shape corresponding to the shape of the actual passage.

The actual shape of the passage is not constant due to the presence of doors, irregularities in the walls of the passage, and changes in the width of the passage. The route calculated according to the shape of the actual passage changes according to the change in the width of the passage. This is because, as described above, when calculating the moving route, the sense of security _mcomfort (x) is taken into consideration, and the moving route is calculated so that the distance between the moving body 10 and the wall is constant. is there. When the route changes in this way, the moving body 10 also moves in the left and right directions (meanders) accordingly, so that the riding comfort of the moving body 10 deteriorates and the load on the computer 12 that calculates the route increases. There are adverse effects such as.

  In order to avoid such inconvenience, in this embodiment, the grid map is adjusted (corrected) so that the width of the passage is constant.

  For example, a map (hereinafter referred to as a map) in which the mobile object 10 automatically travels in the environment and measures the actual path according to the distance data detected by the distance sensors 18a, 18b, and 18c by using a method of Simultaneous Localization and Mapping (SLAM). , “Shape map”). In this shape map, as shown in FIG. 25, since the actual passage is kept, the width of the passage is finely changed. However, the shape map is a grid map to which the model of security is not applied.

  A topological map is created from the actual shape map using an extended Voronoi graph. A straight path is extracted from the topological map, and the width of the wall at which the vertical direction of the straight path intersects the wall is determined as the width of the path. That is, the passage is approximated to a constant width.

  In such a shape map (grid map) in which the width of the passage is approximated to a constant width, a grid map is created in which a model of security based on the distance to the wall and security based on the visibility factor is applied to each cell. You.

  However, in FIG. 25, the magnitude (level) of the sense of security is not shown.

  As shown in FIG. 26 (A), the grid map to which the security model created in this way is applied is different from the shape map shown in FIG. By excluding the region in which the straight line is formed, the straight line portion is formed, and the width of the passage of each straight line is made constant.

  For example, as can be seen from FIG. 26A, the actual shape at the corner at the lower right of the drawing changes so as to increase the width of the passage when traveling downward from the top of the drawing. On the other hand, in the grid map to which the security model is applied, a portion where the width of the passage is wide at the corner at the lower right of the drawing is excluded. In addition, the actual shape of the straight portion at the center of the drawing has irregularities in the walls of the passage, and the width of the passage changes finely. On the other hand, in the grid map to which the security model is applied, a portion where the width of the passage is finely changed in the straight portion at the center of the drawing is excluded.

  Then, an experiment was performed to quantify the relationship between the user's sense of security and comfort when riding on the moving object 10 that actually travels along the route calculated using Equation 6.

  In the experiment, the subject rides on the moving body 10 that is traveling automatically, and the moving body 10 is caused to travel in a path including two corners as shown in FIG. There are two types of routes traveled in the experiment, the shortest route calculated according to the conventional method, and the route calculated according to the method of the present embodiment (the route calculated according to Equation 6). The shortest route calculated according to the conventional method uses the above-described shape map (grid map to which the security model is not applied), and the route calculated according to the method of the present embodiment is as described above. In addition, a grid map to which a model of a sense of security based on a distance from a wall and a model of security based on a visibility rate is used.

  Then, in the experiment, for each subject, each route was run once in a clockwise direction, and each route was run once in a counterclockwise direction, for a total of four trials. In FIGS. 27A and 27B, the broken lines indicate the shortest paths calculated according to the conventional method, and the solid lines indicate the paths calculated according to the method of the present embodiment. As can be seen from FIGS. 27 (A) and (B), the route calculated according to the method of the present embodiment is slightly swelled and turns at a corner as compared with the conventional route regardless of the visibility. Is calculated.

  The number of subjects was 14 men and 16 women, for a total of 30 subjects, and the average age was 21.5 years. In addition, the subject evaluated the sense of security and comfort felt on each route on a 5-point scale for each trial. However, as for the sense of security, the case where the sense of security is the largest (the fear is small) is set to “5”, and the case where the sense of security is the smallest (the fear is large) is set to “1”. As for the comfort, "5" was assigned when the comfort was the largest, and "1" was assigned when the comfort was the smallest. FIG. 26 shows the calculation result (experimental result). The tabulation result shown in FIG. 28A is a bar graph showing the numerical value of the sense of security in each trial of all the subjects. The tabulation result shown in FIG. 28 (B) is a bar graph showing the numerical values of comfort of all the subjects in each trial.

  As can be seen from FIGS. 28A and 28B, according to the experimental results, it can be understood that the route calculated according to the method of the present embodiment has a greater sense of security than the conventional route. Further, if it is assumed that "4" or more is safe, only 15 out of 30 people, that is, 50%, of the conventional routes feel safe. On the other hand, among the routes calculated according to the method of the present embodiment, 22 out of 30 people, that is, 73% of the people feel safe.

  Further, according to the experimental results, it is understood that the route calculated according to the method of the present embodiment has higher comfort than the conventional route. Further, if it is assumed that "4" or more is comfortable, only 13 out of 30 people, that is, 43%, of the conventional routes feel comfortable. On the other hand, as for the route calculated according to the method of the present embodiment, 19 out of 30 people, that is, 63% of the people feel comfortable.

  FIG. 29 is an illustrative view showing one example of a memory map 300 of the RAM 12b shown in FIG. As shown in FIG. 29, the RAM 12b includes a program storage area 302 and a data storage area 304. An information processing program is stored in the program storage area 302. The information processing program includes a main processing program 302a, a route calculation program 302b, a movement control program 302c, and the like.

  The main processing program 302a is a program for processing a main routine for controlling the moving object 10. The route calculation program 302b is a program for calculating a movement route of the moving object 10. For example, when the route calculation program 302b is executed, cells having a short moving distance, a high sense of security, and good visibility are sequentially selected according to the formula shown in Expression 6, and the cells from the start position SP to the goal position are selected. A movement route to the GP is calculated. The movement control program 302c is a program for moving the moving body 10 according to the movement route. However, according to the movement control program 302c, the mobile unit 10 may be moved so as to avoid the obstacle in response to detecting the obstacle.

  Although illustration and detailed description are omitted, the program storage area 302 includes a program for communicating with another computer, a program for detecting an obstacle, a program for estimating the position of the moving object 10, and the like. Is also stored.

  The data storage area 304 stores map data 304a, start position data 304b, goal position data 304c, route data 304d, and the like.

The map data 304a is grid map data for an environment in which the mobile object 10 travels. The map data 304a corresponds to each cell (point x), and provides a sense of security _mcomfort (x) and a visibility ratio v _{index in} each of the eight directions. (X) is assigned. In the present embodiment, the map data 304a is grid map data to which a model of security based on the distance to the wall and a model of security based on the visibility factor is applied. The map data 304a is generated in advance and input to the computer 12, or stored in advance in the HDD 12c inside the computer 12, and is read into the RAM 12b.

  The start position data 304b is data (two-dimensional coordinate data) about the start position SP when calculating the movement route. The goal position data 304c is two-dimensional coordinate data on the goal position GP when calculating the movement route. For example, the start position SP and the goal position GP are input to the computer 12 from another computer (host computer). However, the user may input the start position SP and the goal position GP to the computer 12. The route data 304d is data on a moving route calculated according to the route calculation program 302b.

  Although not shown, the data storage area 304 stores other data (distance data or rotation speed data) necessary for information processing, and is provided with a counter (timer) or a flag. .

  FIG. 30 is a flowchart of the route calculation process of the CPU 12a shown in FIG. When the start position SP and the goal position GP are input and the movement route calculation is instructed, the CPU 12a starts a route calculation process as shown in FIG. 30, and in step S1, the start position SP and the goal position GP are determined. Set GP. Here, the CPU 12a stores the cell set as the start position SP and the cell set as the goal position GP. That is, the two-dimensional coordinate data of the cell determined as the start position SP and the two-dimensional coordinate data of the cell determined as the goal position GP are stored. These two-dimensional coordinate data are included in the route data 304d.

In the next step S3, a cell to which the mobile unit 10 should proceed next is determined. Here, the CPU 12a calculates a cost function f (x) for each of a plurality of cells in the vicinity of the cell selected immediately before according to Equation 6, and calculates a cell having the smallest cost function f (x), It is determined as a cell to which the mobile unit 10 should proceed. That is, a route that travels in a safe and secure area is calculated not only in a place with a short travel distance and a good view but also in a place with a bad view. At this time, the value of visible rate _{v index} (x) corresponding to the corresponding to the stored comfort _{m comfort} (x) and the entrance direction to the grid map of the cell (point x) is obtained. However, the weights k _d , k _c , and k _v are set in advance.

In this embodiment, when there are a plurality of cells having the smallest cost function f (x), the setting is made such that the cell having the larger value of the sense of security _mcomfort (x) is selected. However, when there are a plurality of cells having the smallest cost function f (x), a setting may be made such that a cell having a larger value of the visibility ratio v _index (x) is selected, and a user operation may be performed. It may be possible to switch the priority value by using. In addition, when a plurality of cells have the same value of security _mcomfort (x) or visibility ratio _vindex (x), a cell having the shortest distance may be selected, or a random number may be selected from the plurality of cells. One cell may be selected.

  Subsequently, in step S5, the cell determined in step S3 is stored. That is, the CPU 12a stores the two-dimensional coordinate data of the currently determined cell so as to be arranged in time series between the start position SP and the goal position GP. This two-dimensional coordinate data is also included in the route data 304d.

  Then, in a step S7, it is determined whether or not the calculation of the route is completed. That is, the CPU 12a determines whether the route to the goal position GP has been calculated. If “NO” in the step S7, that is, if the calculation of the route is not completed, the process returns to the step S3. On the other hand, if “YES” in the step S7, that is, if the calculation of the route is ended, the route calculating process is ended.

  According to this embodiment, it is possible to calculate a route that travels in a safe and secure area not only in a place with a short travel distance and good visibility but also in a place with poor visibility.

  Further, according to this embodiment, the shape of the passage in the grid map can be made a simple shape corresponding to the shape of the actual passage, and a smoother route can be calculated. As a result, the load on the computer 12 for calculating the route can be reduced.

  In the above-described embodiment, the electric wheelchair is described as an example of the moving object, but the present invention is not limited to this. Other mobile bodies may be used as long as they can automatically run with a person on them.

  Further, in the above-described embodiment, a model of a sense of security was generated from the relationship between the sense of security obtained by a plurality of subjects responding and the visibility, and this was reflected in the route calculation. The sense of security of the user riding on the body may be reflected. Also, regardless of the speed of the moving object, the distance from the obstacle, or the unambiguous visibility, for example, the brain waves, heart rate (pulse rate), skin conductance (sweating amount), and unit time of the user riding on the moving object It is also possible to measure at least one of the number of blinks in, and obtain a sense of security from the measurement result.

  Further, in the above-described embodiment, the A * search algorithm is used, but the present invention is not limited to this. The D * algorithm, the D * Lite algorithm, or the Dijkstra (Dijkstra) algorithm can also be used. When the D * algorithm or the D * Lite algorithm is used, there is an advantage that, for example, when the door is opened and closed, the environment changes, and the efficiency of recalculating the movement route is high.

  In addition, a configuration is provided that includes a speed control unit that calculates the visibility from the moving body 10 during actual traveling, and lowers the moving speed of the moving body 10 when passing through a location where the visibility is low. Is also good. In such a case, it is considered that the visibility can be calculated in consideration of the dynamically changing obstacle, and the moving speed can be controlled.

  Furthermore, the specific numerical values shown in the above-described embodiments are merely examples, and should not be limited, and can be appropriately changed according to products to be implemented.

10: Moving body 12: Computer 12a: CPU
12b… RAM
12c ... HDD
16 Operation lever 18a, 18b Distance sensor 20a, 20b Motor driver 22a, 22b Motor 24a, 24b Encoder 32a, 32b Front wheel 34a, 34b Rear wheel

Claims (7)

A route calculation device that calculates a movement route of a moving object that automatically travels with a human being thereon,
Of the environment in which the moving object travels, a first viewable area that is a runnable and visible area, a second viewable area that is a non-travelable and viewable area, and a non-travelable area. visible rate from the moving body is calculated based on the virtual viewing area information indicating preset route information indicating that there is viewing prohibited areas are invisible, and the preset virtual viewing area of the moving body was Storage means for storing a grid map in which each level is assigned to each cell with the level of security obtained empirically ,
A visibility calculating means for calculating a level of the visibility based on the first visibility area and the second visibility area included in the route information and the virtual visibility area information, and a start position of the moving body. When moving from the moving object to the goal position, referring to the level of visibility and the level of security from the moving object allocated to each cell of the grid map, the moving distance is short, the level of security. A route calculation device including a calculation unit that calculates a route having a high visibility ratio and a high visibility level.   The route calculation device according to claim 1, wherein a level of a visibility ratio from the moving object assigned to each cell of the grid map is set for each approach direction to each cell.   The route calculation device according to claim 2, wherein the approach directions are a linear direction perpendicular to four sides of each of the cells and a direction oblique to the four sides.   4. The route according to claim 1, wherein the calculation unit calculates a route by weighting each of the travel distance, the level of security, and the level of the visibility rate empirically. 5. Route calculation device.   In the grid map, in the environment in which the moving object travels, a travelable area is obtained by extracting a geometric straight path from a shape map measured in advance and giving a predetermined width to the geometric straight path. The route calculation device according to claim 1, wherein the route calculation device is created. A map showing an environment in which the moving object travels , the first viewable area being a travelable and visible area, the second viewable area being a non-travelable and visible area, and travel. From the moving object calculated based on the preset route information indicating the unrecognizable and unrecognizable unrecognizable area , and the preliminarily set virtual visual field area information indicating the virtual visual field of the mobile object. Storage means for storing a grid map in which each cell is assigned a level of visibility and a level of sense of security obtained empirically, and a path calculation for calculating a moving path of a mobile object that is automatically driven by a human being A program,
On the computer,
A visibility calculation step of calculating the level of the visibility based on the first viewable area and the second viewable area included in the route information and the virtual view area information;
A setting step of setting a start position and a goal position of the moving object; and, when the moving object is moved from the set start position to the goal position, the moving object moves from the moving object assigned to each cell of the grid map. A route calculation program for executing a calculation step of calculating a route having a short moving distance, a high level of security, and a high level of visibility with reference to the level of visibility and the level of security. . A map showing an environment in which the moving object travels , the first viewable area being a travelable and visible area, the second viewable area being a non-travelable and visible area, and travel. From the moving object calculated based on the preset route information indicating the unrecognizable and unrecognizable unrecognizable area , and the preliminarily set virtual visual field area information indicating the virtual visual field of the mobile object. Storage means for storing a grid map in which each cell is assigned a level of visibility and a level of security obtained empirically, and a computer for calculating the movement route of a mobile object that is automatically driven by a human being. A route calculation method,
The computer is
Calculating the level of the visibility rate based on the first viewable area and the second viewable area included in the route information and the virtual view area information;
Setting a start position and a goal position of the moving object, and moving the moving object from the set start position to the goal position, the visible position from the moving object assigned to each cell of the grid map; A route calculation method for calculating a route with a short moving distance, a high level of security, and a high level of visibility with reference to the level of the rate and the level of security.