JP3022889B2 - Mobile robot control method - Google Patents

Description

DETAILED DESCRIPTION OF THE INVENTION

[0001]

BACKGROUND OF THE INVENTION 1. Field of the Invention The present invention relates to a method for controlling a mobile robot, which is suitable for transporting articles by a mobile robot in a factory, for example.

[0002]

2. Description of the Related Art In a factory, a mobile robot is sometimes used when carrying articles. Usually, a guide line is buried in the ground or a floor in a building for moving the mobile robot, and the mobile robot is guided to a predetermined destination by tracing the guide line. In this way, the mobile robot can be moved to a predetermined destination without requiring a driver.

However, according to such a method, the mobile robot can always travel only on a fixed traveling route, and cannot reach the destination if there is an unintended obstacle on the way. was there.

Therefore, when an obstacle is present on the way, it is possible to temporarily move away from the guide line, avoid the obstacle, and then run the vehicle again along the guide line. It has been disclosed.

However, since such a conventional method basically proceeds along a guide line, a guide line must be provided, and when a layout of equipment in a factory is changed, a guide line is required. The lines had to be changed, which was not easy.

[0006] Therefore, a method has been proposed in which a mobile robot receives, for example, radio waves emitted from a destination and moves in a direction in which the radio waves are transmitted.

[0007]

However, according to the method of receiving radio waves, there is a problem that it is difficult to solve the problem of so-called local minimum. In other words, when moving to a predetermined position while avoiding obstacles, it happens to be a position closer to the destination than other positions, but a position where it can not approach the destination any more Has to return to the original position once, but when returning to the original position, it becomes far from the destination, and as a result, there is a problem that it is not possible to leave the minimum position.

The present invention has been made in view of such a situation, and enables a mobile robot to travel at an arbitrary position and to be able to leave a local minimum. is there.

[0009]

A mobile robot control method according to the present invention obtains a vector for a destination and a vector for an obstacle, calculates a force vector received by the mobile robot from the vectors, and obtains a chaotic steepest descent from the force vector. The method is characterized in that a velocity direction vector of the mobile robot is obtained by using the method.

The vector for the destination can be obtained by detecting a signal such as a radio wave from the destination.

[0011]

In the mobile robot control method having the above configuration,
The velocity direction vector of the mobile robot is obtained from the force vector using the chaotic steepest descent method. Therefore, it is possible to easily escape from the local minimum.

[0012]

FIG. 1 shows the appearance of a mobile robot according to the present invention. The mobile robot 1 has a front wheel 2 and rear wheels 3 and 4. The front wheel 2 can turn its direction in a predetermined direction, and the rear wheels 3 and 4 are rotated to move the mobile robot 1. Has been made possible. The plurality of range sensors 5 are arranged in an annular shape substantially at the center of the mobile robot 1 so that the direction and the distance of the obstacle 12 can be detected. The range sensor 5 can be constituted by, for example, an ultrasonic sensor or the like. The destination guidance sensor 6 can receive a signal (radio wave) output from the destination 11 and detect the direction and distance of the destination.

That is, the range sensor 5 detects a vector with respect to the obstacle 12, and the destination guidance sensor 6 can detect a vector with respect to the destination 11. The computer 7 monitors the outputs of the range sensor 5 and the destination guidance sensor 6, executes a predetermined calculation from the outputs, and controls the operation of the mobile robot 1.

FIG. 2 shows an electrical configuration of the mobile robot 1. The output of the range sensor 5 is supplied to the computer 7 via a filter 21 for removing noise. The output of the destination guidance sensor 6 is also supplied to the computer 7. The front wheel angle servo circuit 22 is controlled by the computer 7, and drives the motor 23 to drive the front wheel 2 in a predetermined direction. The drive speed control circuit 24 is controlled by the computer 7 to rotate the motor 25 at a predetermined speed. With this motor 25, the rear wheels 3,
4 is adapted to be rotated.

A transmitter 31 having an antenna 32 is arranged at the destination 11, and a radio wave output from the transmitter 31 via the antenna 32 is received by the destination guidance sensor 6. The guide to the destination can use infrared rays or the like in addition to radio waves.

Next, the operation will be described with reference to the flowchart of FIG. First, the computer 7 executes step S1.
In the chaos time evolution equation, at the next time
To calculate the position of the robot. That is, specifically
Determines the distance and direction of the destination 11 from the output of the destination guidance sensor 6 (vector). Further, the output of the range sensor 5 is received via the filter 21 and the obstacle 12
And the direction (vector) with respect to. Then, a force vector F received by the mobile robot 1 is calculated from the two vectors. That is, when the vector for the destination output by the destination guidance sensor 6 is d1 and the vector for the obstacle 12 output by the range sensor 5 is d2, the temporary force vector F received by the mobile robot 1 is obtained as follows. Can be

[0017]

(Equation 1)

In the above equation, the vectors are shown with a horizontal arrow above the code.

The vector f1 on the right side of the above equation indicates the force that the mobile robot 1 receives from the destination 11,
The closer to, the larger. The vector f2 represents the force that the mobile robot 1 receives from the obstacle 11, and becomes smaller (increases in the negative direction) as the mobile robot 1 gets closer to the obstacle 11.

Here, the functions g1 (x) and g2 (x) are the distance x
Is a non-negative function as shown in FIG. That is, the vector F is a force vector that draws the mobile robot 1 to the destination 11 without touching the obstacle 12.

Here, if the vector F is directly used as the velocity direction vector of the mobile robot 1, the above-mentioned problem of the local minimum cannot be solved.

Therefore, in the present embodiment, the vector F obtained by the above equation is substituted into the following equation, and the velocity direction vector V for the actual movement of the mobile robot 1 is obtained from the following equation.

[0023]

(Equation 2)

Here, the second term on the left side of the above equation is a vibration type nonlinear resistance. If this non-linear resistance is periodically varied with a relatively slow period ω as shown in FIG. 5, the time evolution of the above equation can escape a minimum solution.
FIG. 6 shows this relationship as a change in energy E obtained by integrating the force vector F with the distance x. That is, the two minimum solutions 1 and 2 indicated by circles in the figure are sequentially skipped, and the minimum solution 3 is reached.

The method of periodically oscillating the nonlinear resistance and finding the minimum solution is defined as a chaotic steepest descent method. For details of the chaotic steepest descent method, see, for example, August 1991, IEICE, Transaction A,
Vol. J74-No. 8, P1208-P1215,
"Dynamic characteristics of learning and memory recall in a neural network to which the chaotic steepest descent method is applied", and Japanese Patent Application Nos. 3-240467 (Japanese Patent Application Nos. 2-298894, 2-414907, 2-414907, No. 3-149688).

The computer 7 calculates the position of the mobile robot 1 at the next time in step S1 according to the chaos time evolution equation, and obtains the velocity direction vector V. Then, in step S2, the velocity direction vector V
, The front wheel angle servo circuit 22 and the drive speed control circuit 24 are controlled. The front wheel angle servo circuit 22 includes a motor 23
, The front wheel 2 is directed in a predetermined direction. Further, the drive speed control circuit 24 drives the motor 25 to rotate the rear wheels 3, 4 at a predetermined speed. As a result, the mobile robot 1 moves in a predetermined direction at a predetermined speed.

Next, in step S3, it is determined whether or not the position of the mobile robot 1 is located within a substantially allowable range with respect to the position of the destination 11, and is not within the allowable range (the destination 11). Contact <br/> Itewa if not not) was determined to reach a returns to step S1, and the subsequent processing is repeatedly executed. If it is determined that the vehicle has substantially reached the destination 11, the process proceeds to step S4, and the driving of the mobile robot 1 is stopped.

FIG. 7 shows a vector d 1 for the destination 11 from the current position of the mobile robot 1, a vector d 2 for the obstacle 12, and the destination 11 of the mobile robot 1.
The relationship between the force vector f1 received from the obstacle and the force vector f2 received from the obstacle 12 is shown. As shown in the figure, a vector d1 is expressed by a vector on a straight line connecting the mobile robot 1 and the destination 11, and a vector d2 is expressed by a straight line connecting the mobile robot 1 and the nearest position of the obstacle 12. It can be indicated by a vector. The force vector f1 can be represented as a vector in the same direction as the vector d1, and the force vector f2 can be represented as a vector in the opposite direction to the vector d2. Then, the force vector F can be shown as a combination of the force vectors f1 and f2.

FIG. 8 shows how the mobile robot 1 reaches the destination 11 while avoiding the obstacle 12.
In the drawing, a line such as a contour line represents energy, and this energy can be obtained by integrating the above-described vector F in the moving direction x. This energy becomes minimum at the destination 11, and the mobile robot 1 moves in a direction in which the energy becomes smaller.

In the case where the chaotic steepest descent method is not used, as shown in the figure, when the obstacle 12 is depressed in the direction of the destination 11, the mobile robot 1 is operated at a relatively low energy level (- When you move to position 3),
There is a problem that it becomes impossible to leave from there because energy becomes large when leaving there, but in the case of using the chaotic steepest descent method as in this embodiment, as described above, Because the nonlinear resistance is oscillated, it is not bound to this minimum solution (−3), but leaves from it and reaches the minimum solution (−6) (destination) .
You can do it.

[0031]

As described above, according to the mobile robot control method of the present invention, the force vector received by the mobile robot is calculated from the vector for the destination and the vector for the obstacle, and the chaotic steepest descent method is calculated from this force vector. Since the velocity direction vector of the mobile robot is obtained by using this, it is possible to prevent the mobile robot from stopping at the minimum solution.

[Brief description of the drawings]

FIG. 1 is a plan view showing a configuration of an embodiment of a mobile robot according to the present invention.

FIG. 2 is a block diagram showing an example of an electrical configuration of the mobile robot shown in FIG. 1;

FIG. 3 is a flowchart illustrating the operation of the mobile robot of FIG. 1;

FIG. 4 is a characteristic diagram of functions g1 (x) and g2 (x).

FIG. 5 is a diagram illustrating a state of oscillation of a nonlinear resistance by a chaotic steepest descent method.

FIG. 6 is a diagram for explaining escape from a local minimum by the chaotic steepest descent method.

FIG. 7 is a view for explaining the relationship between the mobile robot 1, the obstacle 12, and the destination 11 in the embodiment of FIG.

FIG. 8 is a diagram illustrating a state in which the mobile robot 1 reaches a destination 11 while avoiding an obstacle 12;

[Explanation of symbols]

 DESCRIPTION OF SYMBOLS 1 Mobile robot 2 Front wheel 3, 4 Rear wheel 5 Range sensor 6 Destination guidance sensor 7 Computer 11 Destination 12 Obstacle

────────────────────────────────────────────────── ─── Continuation of the front page (56) References JP-A-58-203518 (JP, A) JP-A-2-188809 (JP, A) JP-A-5-40840 (JP, A) Jun Tani "Chaos dynamics for exercise space search of robots that the application of the system ": Japan Society of mechanical Engineers robotics Mechatronics Lecture Proceedings, pp. 383-386; June 16-18, 1992 (58) investigated the field (Int.Cl. ⁷ , DB name) G05D 1/02 JICST file (JOIS) WPI (DIALOG)

Claims (2)

(57) [Claims] 1. A vector for a destination and a vector for an obstacle are obtained, a force vector received by the mobile robot is calculated from the vector, and a speed direction of the mobile robot is calculated from the force vector using a chaotic steepest descent method. A method for controlling a mobile robot, comprising determining a vector. 2. The method according to claim 1, wherein the vector for the destination is obtained by detecting a signal from the destination.