JP2016218880A - Route calculation device, route calculation program and route calculation method - Google Patents

Abstract

CONSTITUTION: A moving body 10 includes a computer 12 that functions as a route calculation device, and the moving body autonomously drives in environments according to the computer. More specifically, when a start position and goal position are input to the computer, a route is calculated that is short in movement distance, high in level of a safe feeling, and high in level of a visible factor with reference to a grid map having a level of an experientially obtained safe feeling, and perspective from the moving body (level of the visible factor) allocated to each cell about the environment.EFFECT: To provide a route calculation device, route calculation program and route calculation method that can calculate a route where a movement distance is short, and a moving body drives an area of safe and safety on a straight passage, and drives an area of safe and safety even in a poor perspective site such as turn corners, or crossing points or the like.SELECTED DRAWING: Figure 1

Description

  The present invention relates to a route calculation device, a route calculation program, and a route calculation method, and more particularly, to a route calculation device, a route calculation program, and a route calculation method for calculating a movement route of a mobile body that automatically travels.

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

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

  However, in this background art, the route is simply generated so that the driving cost is minimized, and at the stage of generating the route, whether or not the vehicle travels in a safe, safe area with good visibility is completely taken into consideration. Absent.

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

  Another object of the present invention is to provide a route calculation device, a route calculation program, and a route calculation capable of calculating a route that travels in a safe and safe area not only in a place with a short moving distance and a good line of sight but also in a place with a bad line of sight. Is to provide a method.

  A first invention is a route calculation device that calculates a movement route of a mobile object that automatically travels with a person on the vehicle, and the route calculation device includes a storage unit and a calculation unit. The storage means stores a grid map in which a line of sight from the moving body (a level of visibility) and an empirically obtained level of security are assigned to each cell. The calculation means calculates a route having a short movement distance, a high level of security, and a high level of visibility. The level of the visibility is a first viewable area that is a viewable area that can be seen in the environment in which the mobile body is driven, a second viewable area that is a viewable area that is not able to run, and It is calculated on the basis of route information indicating an invisible area that is not travelable and invisible, and virtual view area information that indicates a preset virtual view area of the moving body. When the start position and the goal position are input, the calculation means refers to a grid map that assigns each cell with a level of security obtained through experience and a level of visibility using a predetermined algorithm. Calculate the route.

  According to the first invention, the moving path of the moving body 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 safe area even in a bad place.

  The second invention is dependent on the first invention, and the level of the visibility from the moving body allocated to each cell of the grid map is set for each approach direction with respect to each cell.

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

  A third invention is dependent on the second invention and has a linear direction perpendicular to the four sides of each cell and a direction oblique to the four sides.

  According to the third invention, in addition to the front, rear, left, and right viewed from the moving body, it is possible to correspond to the traveling direction of the moving body including the oblique direction, and it is possible to calculate a route with a higher level of visibility more appropriately.

  The fourth invention is dependent on the first to third inventions, and the calculation means calculates the route by weighting each of the moving distance, the level of security, and the level of visibility empirically obtained. To do.

  According to the fourth invention, since the weights of the moving distance, the level of security, and the level of visibility are obtained empirically by experiment, the human who rides on the moving body based on the security felt by the subject It is possible to calculate a movement route in consideration of the sense of security.

  The fifth invention is dependent on the first to fourth inventions, and in the grid map, the travelable area of the environment in which the mobile object is traveled is extracted from the shape map measured in advance. It is created by giving a predetermined width to the geometric linear passage.

  According to the fifth aspect of the invention, 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 in calculating the movement route. Since it is possible to calculate a smoother route with a simple shape that approximates the shape of an actual passage, it is possible to improve the ride comfort of the moving body and reduce the load on the calculating means for calculating the route.

  6th invention is the map about the environment which makes a moving body drive | work, Comprising: The route information which shows a driving | running | working area | region and a driving impossible area | region, and the virtual visual field area information which shows the virtual visual field area | region of the preset moving body A mobile body that automatically stores a human being with a storage means that stores a grid map in which each cell is assigned with a level of visibility from a mobile body calculated based on the level and a sense of security obtained experimentally. A route calculation program for calculating a moving route of the grid map when the computer sets a start step and a goal position of the moving body, and moves the moving body from the set start position to the goal position. Referring to the level of visibility from the mobile object assigned to each cell and the level of security, whether the travel distance is short or the level of security is high. To perform the calculation step of the level of the visible rate to calculate the high path.

  7th invention is the map about the environment which makes a moving body drive | work, Comprising: The route information which shows a driving | running | working area | region and a driving impossible area | region, and the virtual visual field area | region information which shows the virtual visual field area | region of a preset moving body A mobile body that automatically stores a human being with a storage means that stores a grid map in which each cell is assigned with a level of visibility from a mobile body calculated based on the level and a sense of security obtained experimentally. A computer route calculation method for calculating a movement path of a grid map when a computer sets a start position and a goal position of a moving object and moves the moving object from the set start position to the goal position. Referring to the level of visibility from the mobile object assigned to each cell and the level of security, the moving distance is short, the level of security is high, and visible Level to calculate the high path.

  In the sixth and seventh inventions, as in the first invention, not only the moving distance is short, but also the moving path of the moving body is calculated so that the level of security and the level of visibility are high. It is possible to calculate a route that travels in a safe and safe area on a straight path and travels in a safe and safe 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 safe area not only in a place where the moving distance is short and the line of sight is good, but also in a place where the line of sight is bad.

  The above object, 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 the electrical configuration of a moving object including a computer that functions as a route calculation apparatus according to an embodiment of the present invention. 2 is an illustrative view showing one example of an external configuration of the moving body shown in FIG. 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 the numerical value of the subject's sense of security when the speed of the moving body 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 and the distance from the wall of the moving body carrying the subject. FIG. 8 is an illustrative view showing an 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 an example of a grid map in consideration of a sense of security. FIG. 10 is an illustrative view showing another example of a grid map considering 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 an example of a grid map of corners on which a moving body travels. FIG. 14 is an illustrative view showing an example in which a virtual field of view is superimposed on a grid map of corners where a moving body travels. FIG. 15 is an illustrative view showing an example of a case where a virtual field of view is superimposed on a grid map of a straight line portion where a moving body travels. FIG. 16 is an illustrative view showing an example in which a virtual field of view is superimposed on a grid map of an intersection where a moving body travels. FIG. 17 is an illustrative view showing an example in which a virtual field of view is superimposed on a grid map of a corner where a moving body travels. FIG. 18 is a graph showing the numerical value of the number of times that the subject felt anxiety for each part having different visibility from the moving body carrying the subject. FIG. 18 is a graph showing a numerical value of a ratio at which the subject feels anxiety for each portion having a different visibility from the moving body on which the subject is 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 which the visibility of each approach direction of each cell is considered. FIG. 23 is an illustrative view showing a part of the grid map of the circulation route using the average value of the visibility in the entry 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 grid map creation process. 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 the numerical value of the subject's sense of security when the moving body carrying the subject travels along the route. FIG. 28 (B) is a graph showing numerical values of the subject's comfort when the moving body carrying the subject travels along the route. FIG. 29 is an illustrative view showing one example of a memory map of the RAM shown in FIG. FIG. 30 is a flowchart showing the route calculation processing of the CPU shown in FIG.

  FIG. 1 is a block diagram showing an electrical configuration of a moving body 10 of this embodiment, and the moving body 10 includes a computer 12 that also functions as a route calculation device. The computer 12 is a general-purpose personal computer or a computer such as 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 18 a, 18 b, and 18 c are connected to the computer 12. A motor 22a is connected to the interface 14 via a motor driver 20a, and a motor 22b is connected via a motor driver 20b. Furthermore, encoders 24 a and 24 b are connected to the interface 14.

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

  Here, referring to FIG. 2 (A), the moving body 10 of this embodiment is a moving body such as an electric wheelchair, and the left and right front wheels (casters) 32a and 32b and the left and right rear wheels are provided below the moving body. 34a and 34b are provided. Further, the above-described operation lever 16 is provided on the upper part of the left frame of the moving body 10. Furthermore, the distance sensor 18a described above is attached to the left side of the moving body 10 and on the left side of the step 36a where the user places his 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 the right foot. Further, as shown in FIG. 2B, which is a schematic view of the moving body 10 as viewed from above, the above-described distance sensor 18 b is provided at the lower rear portion of the moving body 10. Further, a distance sensor 18c is provided at the upper rear part 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 may be attached to the left and right of the moving body 10. The reason why the three distance sensors 18a, 18b, and 18c are provided on the front and rear sides or the right and left sides 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 merely an example, and the number of distance sensors may be two, or four or more.

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

  Returning to FIG. 2A, a box 40 is provided on the lower side of the seat of the moving body 10 and between the left rear wheel 34a and the right rear wheel 34b. In this, the above-described computer 12, interface 14, motor drivers 20a and 20b, motors 22a and 22b, and encoders 24a and 24b are provided. However, the computer 12 and the interface 14 may be provided outside the box 40.

  The computer 12 manages the overall control of the moving body 10 of this embodiment. In this embodiment, the CPU 12a calculates the moving path of the moving body 10. The CPU 12a controls 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 the distance data or the rotational 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 body 10 according to the detected data.

  The operation lever 16 is operated by a user 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). Further, in this embodiment, the operation lever 16 may not be provided to automatically move the moving body 10.

  The distance sensors 18a, 18b, and 18c are, for example, general-purpose laser range finders (LRF), and measure the distance to the object from the time it takes to irradiate the laser and reflect it back to the object. . For example, in the LRF, a laser beam emitted from a transmitter (not shown) is reflected by a rotating mirror (not shown), and scanned in a fan shape at a certain angle (for example, 0.25 degrees). In this embodiment, the period for scanning 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 fan angle 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 for a range of 270 ° centered on the front. In addition, 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 fan angle is 90 ° on each of the left and right sides with the front direction as the center. That is, the distance can be detected for a range of 180 ° centered on the front. In addition, as shown in FIG. 4, the measurement range in the vertical direction (up and down direction) of the distance sensor 18c also forms a fan shape in the up and 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 for a range of 40 ° centered on the front. The measurement range in the horizontal direction and the vertical direction of the distance sensor 18c is a virtual view range or region (a virtual view region described later) of the moving body 10 (or a user riding on the moving body 10). .

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

  The computer 12 acquires distance data detected by the distance sensors 18a, 18b, and 18c and rotation speed data detected by the encoders 24a and 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 point are distinguished. Are related to each other.

  As described above, the moving body 10 having such a configuration can move (run) by operating the operation lever 16, but by inputting (setting) the start point and the goal point, the moving path Can be calculated to automatically travel (autonomous movement).

  For example, a normal movement route plan is a method for obtaining a shortest distance or a shortest time route. However, since the shortest distance may select a route that passes near an obstacle (wall, pillar, etc.), it is easy to give fear to the user who is on the moving body 10. Further, if the moving speed is increased, the required time can be shortened. However, since it becomes difficult for the user who is on the moving body 10 to predict the movement, fear increases. Furthermore, when the speed of the moving body 10 is very slow, it is safe but it is considered to irritate the user who is on the moving body 10. That is, it is considered that the sense of security (comfort) of the user riding on the moving body 10 is related to the distance or speed with the obstacle on the moving route.

For this reason, an experiment was performed to quantify the relationship between the distance between the moving body 10 and the obstacle, the speed of the moving body 10, and the sense of security of the user riding on the moving body 10. 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 The speed v was varied in three steps (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), medium (M), L × 0.35 (0.84 m), and close (C), L × 0.2 (0.48 m) ). The speed v is set to 1.6 m / sec for fast (F), 1.2 m / sec for medium (M), and slow (L). Is set to 0.8 m / sec.

  Moreover, a test subject is a total of 22 people, 11 men and 11 women, and an average age is 23.53 years old. Moreover, the test subject evaluated the sense of security in five stages for each trial. However, “5” was assigned when the sense of security was the greatest, and “1” was assigned when the sense of relief was the smallest (the greatest sense of anxiety). The tabulation results (experimental results) are shown in FIG. The tabulation result shown in FIG. 6 is a bar graph obtained by averaging the numerical values 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 increased as the distance from the wall increased, but it turned out that the wall side tends 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.

Further, when the sense of security is modeled according to the experimental result, the speed v (m / sec) of the moving body 10, the distance d _h (m) from the obstacle, and the sense of security U are elliptical as shown in FIG. It is represented by the shape of a part of the surface of the sphere. As can be seen from FIG. 7, the sense of security U is maximized when the speed v is medium (M) and the distance dh is medium (M). For example, referring to FIG. 7, the region determined by a distance d _h (m) that does not approach or collide with an obstacle too much or a speed v (m / sec) that does not make the user uneasy. 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 0-1. The case where the sense of security U is the largest is “1”, and the case where the sense of security is the smallest is “0”. In FIG. 7 (the same applies to FIGS. 9 and 10 described later), the case where the sense of security is the smallest is black, the case where the sense of security is the highest is white, and the magnitude (level) of the sense of security is shown in gray scale. It is.

In order to reflect this sense of security model in route calculation (route planning), the sense of security is approximated by the 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 K ₀ L is the distance from the wall to the center of the moving body 10 when the sense of security is the maximum value. However, the speed V ₀ and the distance k ₀ L are values obtained by experiments. Specifically, in this embodiment, the width L is 2.4 m, and at this time, the speed V _{0 is} 0.8 m / sec, and the distance k ₀ L is 0.84 m. For the sake of notation, “·” is displayed at the upper right of “x” except for mathematical expressions, but actually, it is displayed above “x” as shown in Equation 1, and this “ Means differentiation. same as below.

In addition, as a result of approximating Formula 1 to the model of reassurance shown in FIG. 7 by the least square method (regression analysis), constants c _a = 0.04, c _b = 1.08, and c _c = 0.679 are obtained. It was.

However, when the mobile body 10 is actually run, if the speed x ^· of the mobile body 10 is determined in accordance with the model of security, there is a risk of giving anxiety to the riding user. This is because there may be a difference between the position where the mobile body 10 is actually traveling and the calculated (generated) position on the moving path. In addition, since the distance to an obstacle that is not on the grid map is not taken into consideration, when an obstacle that is not on the grid map is detected during actual traveling, the moving body 10 may not travel at an appropriate speed x ^·. It is also because of the nature.

  An obstacle not on the grid map means an object other than a pillar or a wall or a human (passerby).

Therefore, in this embodiment ^, the component of speed x ^· is ignored and the sense of security is obtained. 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 into Equation 2. However, without considering the speed x ^·, least squares method (regression analysis) the results approximate to comfort model shows the number 2 in FIG. 7, the constant _g a = _0.009, is g c = 0.363 Obtained.

  FIG. 8A is a grid map as seen from above (directly above) a part of the environment in which the moving body 10 of this embodiment travels. In the example shown in FIG. 8A, a portion indicated by diagonal lines is an obstacle such as a wall, and a portion indicated by white is a passage. The same applies to FIGS. 9 to 12 below. 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 in the grid map is set to 30 cm × 30 cm, but in practice, the size is set to about 5 cm × 5 cm. The size of this cell is an example and should not be limited. In FIG. 8B, hatched cells indicate obstacles (here, walls), and white cells indicate passages.

FIG. 9 partially shows a grid map in the case where a model of security is applied. However, the sense of security U (d _h ) of each cell is calculated according to Equation 2, and the calculated value (level) of the sense of security U (d _h ) is stored corresponding to each cell. As described above, in the grid map shown in FIG. 9, the numerical value of the sense of security U (d _h ) calculated for each cell is expressed in gray scale in order to easily show the magnitude of the value of the sense of security U (d _h ). Indicated. However, in the example shown in FIG. 9, the sense of security model is applied to the linear passage portion described in the approximate center of the grid map. As can be seen from the partially enlarged view of FIG. 9, the sense of security U (d _h ) is the largest at a position slightly closer to the wall side from the center of the passage.

  FIG. 10 shows a grid map when an obstacle is placed in a passage corresponding to a part 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 installed in a part of the passage in parallel with the passage. The board is placed at a position slightly closer to one wall side (lower side in the drawing) than the center of the hallway. Therefore, in the portion where the board is installed, the width L of the corridor is divided by the board, and the distance from the wall and the distance from the board are taken into account, so that the sense of security is lowered.

In such a case, the start position SP and the goal position GP are set as shown in FIG. 11 without considering the sense of security (k _D = 1 in Equation 3 to be described later), and the movement path that has the shortest distance is set. When the calculation is performed, a linear movement route is calculated that passes through the side where the distance between the plate and the wall is short and the movable body 10 can pass through 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. , The movement path through the side where the distance between the plate and the wall is long is calculated. That is, a travel route with a short travel route and a high sense of security is calculated.

As described above, the route planning considering the sense of security is performed by using the A * (Aster) search algorithm. Specifically, the cost function f (x) is defined as in Equation 3 in order to take into account the sense of security. However, g (x) is the distance from the departure 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-safety) of the route passing through the point x. However, in Equation 3, the sense of security at the point x is m _comfort (x). K _D is a weight of the sense of security for the shortest route. When the weight k _D is 1, the shortest route is calculated, and when the weight k _D is 0, the route with the greatest sense of security is calculated. However, in the grid map, since the route is calculated in cell units, the point x means a certain cell.

  Further, the normal movement route plan is a method for obtaining the shortest distance or the shortest time route as described above. However, in many cases, the shortest distance is selected as a route that passes near obstacles (walls, pillars, etc.), and especially the route that passes through the shortest distance at a corner is close to the wall, resulting in poor visibility. It is easy to give fear to the user riding on the moving body 10. In addition, not only at corners, but in places with poor visibility such as intersections, the presence of other moving objects or pedestrians is not known, and it is difficult for a user who is on the moving body 10 to predict movement. Will increase. That is, it is considered that the sense of security (comfort) of the user riding on the moving body 10 is related to whether the line of sight on the moving route is good or bad.

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

  Each element in this Formula 4 is demonstrated using the environment where the mobile body 10 shown to FIG. 13 and FIG. 14 moves. The example environment shown in FIG. 13 and FIG. 14 is a passage partitioned by a high wall, and shows a corner that turns to the right. However, in the example 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, the high wall refers to a height that blocks a user's line of sight on the moving body 10. Furthermore, a low wall means the height which does not block the visual field of the user who gets on the moving body 10.

  As an example, when the moving body 10 is an electric wheelchair, the height of the line of sight of the user who rides on the electric wheelchair having a size 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 to block the user's line of sight on the electric wheelchair can be set between 1.0 m and 1.1 m. Conceivable.

  Note that the threshold for determining whether or not to block the user's field of view on the moving body 10 is not limited to the above-described height, and may be appropriately set according to usage conditions such as the height of the seat of the moving body 10 or the user's physique. It is desirable to set.

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

_RVT in _Equation 4 is the size (area) of the visible region of the mobile body 10 (or the user riding on the mobile body 10), and R _NT is on the mobile body 10 (or the mobile body 10). Is the area of the invisible area of the user. 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 some object.

  Therefore, in the horizontal and vertical measurement ranges of the distance sensor 18c shown in FIG. 3 and FIG. 4 (hereinafter, also referred to as “virtual field of view”), the region where the distance can be measured is the visible region, An area where the distance cannot be measured is an invisible area.

  In other words, the visible region is a range or region (hereinafter referred to as “visible region”) that is visible to the user on the moving body 10 in the virtual field of view when the moving body 10 travels (moves) according to the movement route. .) In this embodiment, the area that overlaps the area in which the mobile body 10 can travel (travelable area) is referred to as the first visible area, and the area in which the mobile body 10 cannot travel (the travel impossible area). ) Will be referred to as a second visually recognizable region (see FIG. 17). Further, the invisible area means a range or an area in which the user cannot visually recognize (hereinafter referred to as “invisible area”) in the virtual visual field area.

In addition, of the invisible area, an area in which the moving body 10 cannot travel is referred to as an invisible area, and this invisible area is excluded from the calculation of the visibility V _{index in Expression} 4.

In addition, even if it is an invisible area and it is a driving | running | working possible area | region, the area | region considered to drive | work ahead for a fixed time (for example, 5 second) is excluded from the visibility rate _{Vindex of} several 4. This is because such an area is irrelevant when calculating the movement route at the current position of the moving body 10.

In addition, as can be seen from Equation 4, the visibility V _index decreases when the area R _{NT of the} invisible region is large (minimum value 0), and the visibility V _index increases when the area R _{NT of the} invisible region is small (maximum). Value 1).

Further, as described above, the invisible region 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 high walls on both sides, in the measurement range (virtual field of view) of the distance sensor 18c, the invisible region Is excluded, only the first viewable region is included. That is, as shown in FIG. 15, the straight path has only the visible area _RVT . In such a case, the visibility rate V _index calculated according to Equation 4 is 1.

Further, even when the vehicle 10 travels upward from the bottom of the drawing so as to approach the intersection partitioned by a high wall as shown in FIG. In, an invisible area is generated in front of left and right, which is blocked by the invisible area. That is, at the intersection, since it has the area R _{NT of the} invisible region, the visibility V _index is lower than when traveling along a straight path as shown in FIG.

  Here, the data (route information data) as route information indicating the above-described travelable region and non-travelable region, and the visually recognizable region or the unrecognizable region in them, the mobile body 10 automatically travels the route 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 partitions the runnable area and the non-runnable area in each cell of the grid map. Therefore, for example, when there is a cell whose data indicating the height of a static obstacle is 2.0 m and a cell whose height is 0.3 m, the area partitioned by the obstacle having a height of 2.0 m is not visible. Since the area that 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 who is on the moving body 10, the second visible area that is not visible and is visible (See FIG. 17).

  It should be noted that, depending on the setting of the threshold value of the height of the obstacle that does not hinder the field of view of the user riding on the moving body 10, whether the region becomes the invisible region or the second visible region even at the same location on the route. May change. The threshold value for determining whether or not visual recognition is possible is set based on the viewpoint of the user riding on the moving body 10. Therefore, the threshold value changes depending on the height of the seat in the moving body 10 or the user's physique, and may be set as appropriate.

Since it is configured as described above, for example, as shown in FIG. 17, when it is a corner that turns to the right and a portion of the corner is configured with a low wall (height 0.3 m), An area partitioned by a low wall does not become an invisible area, and only an area partitioned by a high wall becomes an invisible area. Therefore, since the invisible area decreases and the range that blocks the view is reduced, the first visible area is enlarged. Moreover, the area | region which is not obstruct | occluded by the high wall among the area | regions partitioned off by the low wall turns into a 2nd visual recognition area | region which is an area | region which cannot run and is visible. However, the second visually recognizable area is an area surrounded by a horizontally oriented trapezoid in front of the mobile object 10 diagonally to the right in FIG. Therefore, the corner part is formed at a lower wall, than corner partitioned only high walls as shown in FIGS. 13 and 14, to expand the area R _VT in the visible region, visible rate V _{The index} becomes high.

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

In the experiment, the subject rides on the mobile body 10 that automatically travels, and the visibility rate V _index such as a corner or an intersection that is divided by a high wall and a portion having a high visibility rate V _index such as a corner that is partitioned by a straight line or a low wall. The moving body 10 was caused to travel on a complex circuit route including both of the low and low portions. Each subject was run 4 times clockwise and 4 times counterclockwise, for a total of 8 trials.

Moreover, a test subject is a total of 30 people, 15 men and 15 women, and an average age is 21.5 years old. In addition, this test subject is the test subject in the experiment for quantifying the relationship between the distance between the mobile body 10 and the obstacle and the speed of the mobile body 10 and the relief of the user riding on the mobile body 10. Some are different. In addition, the subject was instructed to press a button on the remote control when they felt danger or anxiety. The tabulation result (experiment result) is shown in FIG. The tabulated result shown in FIG. 18 is a bar graph showing the total number of times (the number of button clicks) that the buttons of the above-mentioned remote controller were pressed by all subjects at a plurality of positions (locations) with different visibility rates V _index in the circuit route. It is. Further, 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 have passed each position.

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

As can be seen with reference to FIG. 18 and FIG. 19, according to the experimental results, when the visibility V _index decreases, anxiety tends to increase. Moreover, the result that the button click rate was a little less than 50% around the lowest value of the visibility V _index (0.3), and anxiety was felt at the portion where the visibility V _index was low.

FIG. 20 and FIG. 21 show grid maps in the case of applying a sense of security model that also considers the visibility V _index . In this case, the visibility V _index when the moving body 10 is located in each cell according to _{Equation 4} is calculated, and the calculated value (level) of the visibility 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.} Further, the numerical value of the visibility V _index corresponding to the traveling direction of the moving body 10 (for example, each direction when traveling clockwise and counterclockwise on the circuit route) is calculated and stored. In the example shown in FIGS. 20 and 21, the sense of security is calculated using the visibility rate V _index when the moving body 10 travels clockwise. That is, in this embodiment, the value of the visibility v _index (x) corresponding to the traveling direction of the moving body 10 is stored in addition to the above-mentioned feeling of _comfort m _comfort (x) corresponding to each cell of the grid map. Is done.

In the grid maps shown in FIG. 20 and FIG. 21, the level (level) of security calculated for each cell is shown in gray scale in order to easily show the level of security considering the visibility V _index . 20 and 21 also, 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 in the case of a corner turning to the right partitioned by a high wall (similar to FIG. 14). In this case, a 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 is applied to the linear passage portion. In the vicinity of the corner, a sense of security model considering the visibility V _index is applied. As can be seen from FIG. 20, in the vicinity of the corner, the sense of security is high on the route of moving to the right by slightly inflating the corner, and the sense of security decreases toward the inside of the corner.

  FIG. 21 shows a grid map in a case where the corner turns to the right and a part of the corner (part on the inner side) is composed of a low wall (height 0.3 m) (similar to FIG. 17). Yes. In this case, as described above, the region partitioned by the low wall is not a visually invisible region, and only the region partitioned by the high wall is an invisible region. For this reason, unlike the case shown in FIG. 20, there is a portion with a high sense of security even in a route passing through the inside of a corner. Therefore, even at a corner, like the portion of the straight passage, a little wall side from the center of the passage on the basis of a model of security based on the distance of the moving body 10 from the wall and the speed of the moving body 10 The feeling of security at the location near to is the largest.

As described above, the movement path of the moving body 10 is calculated according to the grid map in the case where the model of security in consideration of the visibility V _index is applied.

As described above, the route planning considering the sense of security is performed using the A * (Aster) search algorithm. Specifically, the cost function f (x) is defined as shown in Equation 5 in order to consider the visibility V _index . Similar 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 the point x to the target point (goal position GP), m _disc (x) is a sense of anxiety (1-safety) of the route passing through the point x. The sense of security at the point x based on the distance of the moving body 10 from the wall and the speed of the moving body 10 is m _comfort (x). Furthermore, in Formula 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. Furthermore, k _v is a weight of the visibility v _index (x) based on the visibility V _index , and when the weight k _v is 1, a path where the visibility v _index (x) based on the visibility V _index is the largest. Is calculated.

Here, for example, when the moving body 10 is traveling along a straight path portion, as long as there is no obstacle in this path, the virtual visual field region includes, as described with reference to FIG. Since only the first visually recognizable area and the invisible area are included, the visibility v _index (x) based on the visibility V _index becomes the maximum value. As described above, when the visibility v _index (x) based on the visibility V _index is the maximum value, it is not necessary to consider the visibility V _{index in} calculating the route. Therefore, the visibility v _index (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 You may control so that it may be set to 0.

  In addition, as described above, when calculating a complex route including a straight path portion and a portion with poor visibility such as a corner or an intersection, a portion that travels when trying to calculate an appropriate route Accordingly, it is necessary to control the weight of the moving distance, the sense of security and the visibility.

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

Here, the visibility V _index calculated according to Equation 4 varies depending on the traveling direction of the moving object 10 even at the same position. Therefore, in order to make it unnecessary to control the weight during traveling, it is necessary to set a visibility V _index corresponding to the traveling direction of the moving body 10 in advance in each cell of the grid map.

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

In addition, the direction with which the data of visibility V _index are matched is not limited to eight. For example, each cell of the grid map may be associated with data of the visibility V _{index in} each of the vertical direction and the horizontal direction of each cell.

FIG. 23 is an illustrative view showing a grid map of a part of the circulation route. The grid map shown in FIG. 23 shows the average value of the magnitude (level) of the visibility 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 . Also in FIG. 23, the case where the level of the visibility V _index is the lowest is black, and the case where the level of the visibility 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 V _index is low. On the other hand, the corner P2 at the lower right of the drawing has good visibility, that is, the visibility V _index is high. This is because the lower left corner P1 is partitioned by a high wall as shown in FIG. 20, whereas the lower right corner P2 is partitioned by a lower wall as shown in FIG. Because.

Further, in the vicinity of the corner P1 at the lower left of the drawing, the level of the visibility V _index inside the passage is lower than that outside the passage. Therefore, at the corner P1 at the lower left of the drawing, the sense of security becomes lower as the route approaches the inside of the corner than the sense of security about the route that moves so as to bend with the corner slightly expanded.

As described above, the movement path of the moving body 10 is calculated according to the grid map in the case where the model of security that also considers the level of the visibility V _{index in} each of the eight directions of each cell is applied.

As described above, the route planning considering 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 order to take into consideration the moving distance, the sense of security _mcomfort (x), and the visibility rate v _index (x). Similar 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 the point x to the target point (goal position GP). This first element is an element related to the movement distance. Further, m (x) is anxiety at a certain point x (1-safety), and n (x) is anxiety at the next passing point x ′, each calculated according to Equation 3. This second element is an element relating to a sense of security (anxiety). Further, p (x) is the sum of the shielding ratio (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 the shielding rate at the passing point x ′. However, the shielding rate at each point x (each cell in the grid map) is calculated according to the data of the visibility V _index corresponding to the direction of entering each point x. This third element is an element related to the visibility (line of sight). k _d , k _c , and k _v are weighting coefficients. For example, when k _d = 1, k _c = 0, and k _v = 0, a route with the shortest moving distance is calculated.

In FIG. 24A, as an example, paths calculated according to the method (Equation 6) of the embodiment with the respective weighting factors k _d = 0.9, k _c = 0.019, and k _v = 1.5 are shown. Indicated. This weighting factor is set so that a route calculated according to the method of the embodiment matches or approximates an average route obtained by an experiment in which a subject manually travels. In addition, a test subject is a total of 30 persons, 14 men and 16 women, and an average age is 21.5 years old. FIG. 24B shows a route calculated according to a travel route plan for obtaining a conventional shortest distance or shortest time route as a comparison target. As can be seen from FIGS. 24A and 24B, it can be seen that the route calculated according to Equation 6 bends with a slightly larger corner than the route calculated by the conventional method.

  A method for creating a grid map that calculates a smoother route when calculating a route using the method of this embodiment will be described. Specifically, the shape of the grid map used in the method of the present embodiment is made simple according to the actual shape of the passage.

The actual shape of the passage is not constant because there are doors, the walls of the passage are uneven, or the width of the passage changes. The route calculated according to the actual shape of the passage changes according to the change in the width of the passage. This is because, as described above, when calculating the movement route, the sense of _comfort m _comfort (x) is taken into consideration, and the movement route is calculated so that the distance between the moving body 10 and the wall is a constant distance. is there. When the route changes in this way, the moving body 10 also moves (meanders) in the right and left directions accordingly, so that the riding comfort of the moving body 10 becomes worse and the load on the computer 12 for calculating the route increases. There are harmful effects such as.

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

  For example, a map in which an actual path is measured according to the distance data detected by the distance sensors 18a, 18b, and 18c by using the SLAM (Simultaneous Localization and Mapping) technique when the moving body 10 automatically travels in the environment (hereinafter referred to as a map). , Referred to as “shape map”). In this shape map, as shown in FIG. 25, since the actual passage remains as it is, the width of the passage changes finely. However, the shape map is a grid map to which a model of security is not applied.

  A topological map is created from this actual shape map using an extended Voronoi graph. A straight passage is extracted from this topological map, and the width of the passage intersecting with the vertical direction of the straight passage is determined as the width of the passage. That is, the passage is approximated to a certain width.

  In this way, in the shape map (grid map) in which the width of the passage is approximated to a certain width, a grid map is created that applies a sense of security based on the distance to the wall and a sense of security based on the visibility to each cell. The

  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 changes the width of the passage due to the unevenness of the passage, etc., compared to the shape map shown in FIG. 26 (B). By excluding the region to be formed, only a straight portion is formed, and the width of each straight passage is made constant, so that a simple shape is obtained.

  For example, as can be seen from FIG. 26A, the actual shape at the lower right corner of the drawing changes such that the width of the passage becomes wider when traveling downward from the top of the drawing. On the other hand, in the grid map to which the sense of security model is applied, a portion where the width of the passage is widened at the corner at the lower right of the drawing is excluded. Moreover, the actual shape in the straight line portion in the center of the drawing has irregularities on the walls of the passage, and the width of the passage changes finely. On the other hand, in the grid map to which the sense of security model is applied, a portion where the width of the passage changes finely in the straight line 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 on the moving body 10 that actually travels along the route calculated using Equation 6.

  In the experiment, a subject rides on the mobile body 10 that automatically travels, and the mobile body 10 travels 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). In addition, the shortest route calculated according to the conventional method uses the above-described shape map (grid map not applying the security model), and the route calculated according to the method of the present embodiment is as described above. In addition, a grid map using a model of a sense of security based on the distance from the wall and a sense of security based on the visibility is used.

  In the experiment, each subject traveled once for each route in the clockwise direction, and traveled once in each direction in the counterclockwise direction, for a total of four trials. In FIGS. 27A and 27B, the shortest path calculated according to the conventional technique is indicated by a broken line, and the path calculated according to the technique of the present embodiment is indicated by a solid line. As can be seen from FIGS. 27 (A) and 27 (B), the route calculated according to the method of the present embodiment is slightly swollen and turns at a corner, regardless of whether the line of sight is good or bad, as compared with the conventional route. Calculated.

  Moreover, a test subject is a total of 30 people, 14 men and 16 women, and an average age is 21.5 years old. Furthermore, the subject evaluated the sense of security and comfort felt in each route on a trial-by-trial basis in five levels. However, regarding the sense of security, “5” was assigned when the sense of security was greatest (small feeling of fear), and “1” was assigned when the sense of security was minimal (high feeling of fear). As for comfort, “5” was assigned when the comfort was the highest, and “1” was assigned when the comfort was the lowest. The tabulation results (experimental results) are shown in FIG. 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 subjects. Moreover, the total result shown in FIG. 28 (B) is a bar graph which shows the numerical value of the comfort in each test of all subjects.

  As can be seen with reference to FIGS. 28A and 28B, according to the experimental results, it can be seen that the route calculated according to the method of the present embodiment is more secure than the conventional route. Also, assuming that “4” or more is safe, the conventional route is that only 15 out of 30 people, that is, 50%, feel safe. On the other hand, the route calculated according to the method of the present embodiment feels safe for 22 out of 30 people, that is, 73%.

  Furthermore, according to the experimental results, it can be seen that the route calculated according to the method of this embodiment is more comfortable than the conventional route. Further, if the user feels that “4” or more is comfortable, the conventional route is that only 13 people out of 30 people, that is, 43%, feel comfortable. On the other hand, the route calculated according to the method of this embodiment feels that 19 out of 30 people, that is, 63%, are 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, and 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 body 10. The route calculation program 302b is a program for calculating the movement route of the moving body 10. For example, when the route calculation program 302b is executed, cells having a short moving distance, a high sense of security, and a good line-of-sight are sequentially selected according to the equation shown in Equation 6, and the goal position is determined from the start position SP. A travel route to the GP is calculated. The movement control program 302c is a program for moving the moving body 10 according to the movement path. However, according to the movement control program 302c, the moving body 10 may be moved so as to avoid the obstacle according to the detection of the obstacle.

  Although illustration and detailed description are omitted, the program storage area 302 has a program for communicating with other computers, a program for detecting obstacles, a program for estimating the position of the moving object 10, and the like. Is also remembered.

  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 data of a grid map for the environment in which the mobile object 10 is traveled. The map data 304a corresponds to each cell (point x), and the safety feeling _mcomfort (x) and the visibility v _index of each of the eight directions. (X) is assigned. In this embodiment, the map data 304a is grid map data to which a model of security based on the distance from the wall and a security model based on the visibility is applied. The map data 304a is generated in advance and input to the computer 12, or stored in advance in the HDD 12c in the computer 12, and 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 for 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 into the computer 12. The route data 304d is data about a travel route calculated according to the route calculation program 302b.

  Although not shown, the data storage area 304 stores other data necessary for information processing (such as distance data or rotation speed data), or 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 calculation of the movement route 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 Set the GP. Here, the CPU 12a stores the cell set as the start position SP and also stores 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 moving body 10 should proceed next is determined. Here, the CPU 12a calculates the 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 determines the cell with the smallest cost function f (x) The mobile object 10 is determined as a cell to be advanced. That is, a route that travels in a safe and safe area is calculated not only in a place where the moving distance is short and the line of sight is good, but also in a place where the line of sight is bad. At this time, the feeling m _comfort (x) stored corresponding to the cell (point x) of the grid map and the value of the visibility v _index (x) corresponding to the approach direction are acquired. 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 cell with the larger value of the sense of security m _comfort (x) is set to be selected. However, when there are a plurality of cells having the smallest cost function f (x), the cell with the larger value of the visibility v _index (x) may be selected, or the user's operation The priority value may be switchable by. In addition, when a plurality of cells have the same value of _comfort m _comfort (x) or visibility v _index (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 cell determined this time 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.

  In step S7, it is determined whether or not the route calculation is finished. That is, the CPU 12a determines whether a 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 ended, 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 safe area not only in a place where the moving distance is short and the line of sight is good, but also in a place where the line of sight is bad.

  In addition, according to this embodiment, the shape of the passage in the grid map can be made simple according to the shape of the actual passage, and a smoother route can be calculated, so that the riding comfort of the moving body 10 is improved. Thus, the load on the computer 12 for calculating the route can be reduced.

  In the above-described embodiment, an electric wheelchair is shown as an example of the moving body, but it is not necessary to be limited to this. Any other moving body may be used as long as it can automatically run with a person on it.

  In the above-described embodiment, a sense of security model is generated from the relationship between the sense of security obtained by the responses of a plurality of subjects and the visibility, and this is reflected in the route calculation. You may make it reflect the sense of security of the user who rides on the body. In addition, regardless of the speed of the moving body, the distance from the obstacle, or the unique visibility, for example, the brain wave, heart rate (pulse rate), skin conductance (sweat volume), unit time of the user riding on the moving body At least one such as the number of blinks may be measured, and a sense of security may be obtained from the measurement result.

  Furthermore, although the A * search algorithm is used in the above-described embodiment, it is not necessary to be limited to this. The D * algorithm, D * Lite algorithm or 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 in recalculating the movement route is high.

  In addition, it is configured to include a speed control unit that calculates the visibility from the moving body 10 during actual traveling and reduces the moving speed of the moving body 10 when passing through a location where the visibility is low. Also good. In such a case, it is considered that the moving speed can be controlled by calculating the visibility rate in consideration of obstacles that change dynamically.

  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 the product to be implemented.

DESCRIPTION OF SYMBOLS 10 ... Mobile body 12 ... Computer 12a ... CPU
12b RAM
12c HDD
16 ... Control levers 18a and 18b ... Distance sensors 20a and 20b ... Motor drivers 22a and 22b ... Motors 24a and 24b ... Encoders 32a and 32b ... Front wheels 34a and 34b ... Rear wheels

Claims (7)

A route calculation device that calculates a movement route of a mobile object that automatically travels with a human being on it,
Of the environment in which the mobile body travels, a first viewable region that is a visible and visible region, a second visually recognizable region that is a non-travelable and visible region, and a non-travelable region A level of visibility from the moving object calculated based on path information indicating an invisible area that is visually invisible and virtual visual field area information indicating a virtual visual field area of the moving object set in advance; Storage means storing a grid map in which each cell is assigned an empirically obtained level of security, and when moving the moving body from a start position to a goal position, the cell map is assigned to each cell in the grid map. A route with 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 from the moving body A route calculation device comprising calculation means for calculating   The route calculation device according to claim 1, wherein the level of visibility from the moving object assigned to each cell of the grid map is set for each approach direction with respect to each cell.   The route calculation device according to claim 2, wherein the approach direction is a linear direction perpendicular to the four sides of each cell 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 moving distance, the level of security, and the level of visibility by empirically obtained weights. 5. Route calculation device.   In the grid map, the travelable area of the environment in which the moving body is driven is obtained by extracting a geometric linear path from a shape map measured in advance and giving a predetermined width to the geometric linear path. The route calculation device according to claim 1, which is created. It is a map about the environment in which a mobile body travels, and is calculated based on route information indicating a travelable area and a travel impossible area, and virtual view area information indicating a preset virtual view area of the mobile body A storage means for storing a grid map in which each cell is assigned with a level of visibility from the moving body and a level of security obtained through experience, and a moving path of the moving body that automatically travels with a person on it is provided. A route calculation program for calculating,
On the computer,
A setting step for setting a start position and a goal position of the moving body, and when moving the moving body from the set start position to the goal position, from the moving body assigned to each cell of the grid map A route calculation program that executes 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 . It is a map about the environment in which a mobile body travels, and is calculated based on route information indicating a travelable area and a travel impossible area, and virtual view area information indicating a preset virtual view area of the mobile body A storage means for storing a grid map in which each cell is assigned with a level of visibility from the moving body and a level of security obtained through experience, and a moving path of the moving body that automatically travels with a person on it is provided. A computer route calculation method for calculating,
The computer
The start position and the goal position of the moving body are set, and when the moving body is moved from the set start position to the goal position, the visible from the moving body assigned to each cell of the grid map. A route calculation method for calculating a route having a short moving distance, a high level of security, and a high level of visibility with reference to a rate level and the level of security.