JP7158862B2 - Information processing method and information processing device - Google Patents

Description

The present invention relates to an information processing method and information processing apparatus for generating a trajectory of a robot arm.

2. Description of the Related Art Conventionally, there has been known a configuration in which an industrial robot device is arranged in a production system (production line) for industrial products such as automobiles and electric appliances to automate work such as welding and assembly. In this type of production system, robot devices, workpieces, workpiece placement tables, jigs, and other peripheral devices are arranged in a state where they may interfere (contact or collide) with each other. In recent years, a simulation using a virtual environment is sometimes used in the work of designing the motion trajectory of the arm of the robot device of such a production system.

When simulating the motion of a robot device using a simulator device off-line, 3D (three-dimensional) models such as a robot arm, a work table, jigs, and other peripheral devices are arranged in a virtual environment. For example, in such a simulator apparatus, a trajectory between teaching points of a robot arm created in advance is generated, and a 3D model of the robot arm in a virtual environment is operated on the trajectory, which is verified by performing a simulation. be. The motion of the robot arm model can be displayed on the virtual display screen of the display of the simulator device in the form of a moving image or the like.

Naturally, the simulation results differ greatly depending on the motion trajectory of the robot arm. If the trajectory of the robot arm is inappropriate, part of the motion trajectory of the robot arm may enter the robot arm's inoperable area, the robot arm may interfere with other objects, or wasteful motions may shorten the cycle time. may be delayed.

In the conventional method, the operator created teaching points for the robot arm on the screen by trial and error, satisfying the conditions that the robot arm would not enter an inoperable area or interfere with the peripheral device. . In that case, since the conditions of being movable and not interfering are taken into consideration first, a robot trajectory that can operate at an optimum operating speed is not necessarily generated, and the cycle time may become slow. In that case, it was necessary to perform a manual work of reexamining the teaching points of the robot arm and re-installing them.

On the other hand, when a robot device is used in a production system (line), a large number of man-hours are required to create teaching points for a process designer, so there is a problem of soaring labor costs. Therefore, in recent years, instead of direct teaching by a teacher, methods and devices have been proposed that use computers to improve the efficiency of robot arm teaching work.

Non-Patent Document 1 below discloses a trajectory generation method that avoids interference with obstacles around a robot arm and minimizes the torque of motors used for the joints of the robot arm. FIG. 8 schematically shows the method of generating the trajectory of the robot arm in Non-Patent Document 1. As shown in FIG. In FIG. 8, the robot arm A is a simplified robot arm with two degrees of freedom having two rotation axes J1 and J2, and Ob indicates an obstacle.

In FIG. 8, p1, p2, . Of these positions, p1 indicates the motion start position (start teaching point), and p9 indicates the target position (target teaching point) of the motion. Also, p2 to p8 indicate intermediate command values arranged between the start position (p1) and the target position (p9). For example, postures p1, p2, . In this case, the operating time of the robot arm between the start position (p1) and the target position (p9) is calculated as control cycle×(9−1). In the case of Non-Patent Document 1, the number of intermediate command values (p2 to p8) is determined as a constant in advance, and is seven in this case. In FIG. 8, the robot arm and the obstacle Ob interfere with each other at points p4 and p5.

First, the joint angles corresponding to the intermediate command values p2, p3, . . . p8 are smoothly displaced to generate N new intermediate command values ri2, ri3, . Next, the intermediate command values ri2, ri3, . . . ri8 (i=1, . . . N) are evaluated, and the intermediate command values p2, p3, . Optimize the trajectory. In Non-Patent Document 1, the amount of penetration between the robot arm A and the obstacle Ob and the motor torque used for each joint axis are used as evaluation values for the intermediate command value. By using such an evaluation value, a trajectory is generated in which the robot arm A and the obstacle Ob do not interfere with each other and the motor torque used for each joint axis does not become overloaded.

Kalakrishnan, Mrinal, et al. "STOMP: Stochastic trajectory optimization for motion planning." Robotics and Automation (ICRA), 2011 IEEE International Conference on IEEE, 2011.

As described above, the technique of Non-Patent Document 1 generates a trajectory in which the robot arm A and the obstacle Ob do not interfere with each other and the motor torque used for each joint axis does not become overloaded. However, in the technique of Non-Patent Document 1, the number of intermediate command values is a fixed number. There is a problem that time cannot be optimized. Moreover, if the operation time is fixed, it becomes difficult to satisfy the constraint of the motor torque used for each joint axis and other constraints. Constraints relating to such difficult-to-achieve robot motions include, for example, constraints relating to joint axis torque, joint angular velocity, joint angular acceleration and jerk, hand velocity and hand acceleration. That is, the conventional technique described in Non-Patent Document 1 has the following problems. That is, in areas where the number of intermediate command values is too small, there is no guarantee that the constraints on the robot's motion are met.

SUMMARY OF THE INVENTION In view of the above problems, an object of the present invention is to reliably generate an optimal trajectory that satisfies constraints on robot motion.

One aspect of the present invention is an information processing method for obtaining a trajectory for moving a robot arm between a first position and a second position, in which an intermediate taught point group defining a route from the first position to the second position is provided. and obtaining a plurality of intermediate trajectories based on the intermediate taught point group; an evaluating step of obtaining an evaluation value for the intermediate trajectory obtained in the obtaining step; and the intermediate trajectory based on the evaluation value. and an updating step of selecting a predetermined intermediate trajectory from among the trajectories and updating the trajectory based on the predetermined intermediate trajectory.

With the above configuration, according to the present invention, it is possible to reliably generate an optimal trajectory that satisfies the constraints on robot motion.

1 is an explanatory diagram showing a functional configuration of a trajectory generation device according to an embodiment of the present invention; FIG. FIG. 4 is an explanatory diagram showing a two-axis configuration in the robot arm according to the embodiment of the present invention; FIG. 4 is an explanatory diagram showing a taught point group and a trajectory according to the embodiment of the present invention; It is a flowchart figure explaining the optimization process of the track|orbit which concerns on embodiment of this invention. (a) to (e) are explanatory diagrams showing trajectory optimization processing according to the embodiment of the present invention. FIG. 4 is an explanatory diagram showing a taught point group and a trajectory according to the embodiment of the present invention; (a) to (e) are explanatory diagrams showing trajectory optimization processing according to the embodiment of the present invention. FIG. 4 is an explanatory diagram showing a technique of track control according to a conventional technique; 1 is a block diagram showing a schematic configuration of a control device applicable to an embodiment of the invention; FIG. It is an explanatory view showing a robot device that can be arranged in the production system according to the embodiment of the present invention.

BEST MODE FOR CARRYING OUT THE INVENTION Hereinafter, embodiments for carrying out the present invention will be described with reference to the accompanying drawings. The configuration shown below is merely an example, and, for example, details of the configuration can be changed as appropriate by those skilled in the art without departing from the scope of the present invention. Further, the numerical values taken up in the present embodiment are reference numerical values and do not limit the present invention.

<Embodiment 1>
FIG. 1 shows the configuration of a trajectory generation device according to this embodiment. In the present embodiment, a device for generating a trajectory according to the present invention is referred to as a "trajectory generating device", but this trajectory generating device may be provided as a product such as a robot simulator device.

The trajectory generating apparatus shown in FIG. 1 includes an arithmetic processing unit 1, an operation unit 2 for inputting data by a teacher, a recording unit 3 for recording an operation program, and a display unit for displaying the operation trajectory of a robot arm. A display unit 4 is provided. This trajectory generator can be configured by computer hardware such as a PC (personal computer), for example. Here, FIG. 9 shows a specific configuration example of the arithmetic processing unit 1. As shown in FIG.

FIG. 9 shows a configuration example of a trajectory generation device, particularly a control device 1000 corresponding to the main part of the arithmetic processing unit 1 (FIG. 1). As shown in the figure, the control device 1000 is a control system composed of blocks arranged around a CPU 1601 . It should be noted that the configuration composed of blocks arranged around the CPU 1601 can be applied almost similarly to, for example, a robot control device (200: FIG. 10), which will be described later.

The control device 1000 of FIG. 9 includes a CPU 1601 as main control means, a ROM 1602 and a RAM 1603 as storage devices. The ROM 1602 can store a control program for the CPU 1601 and constant information for realizing a control procedure to be described later. Also, the RAM 1603 is used as a work area for the CPU 1601 when executing a control procedure to be described later.

When the configuration of FIG. 9 is the arithmetic processing unit 1 (FIG. 1), the display 1608 (display unit 4 in FIG. 1) and the operation unit 1609 (operation unit 2 in FIG. 1) are used as user interface devices. 1607. The operation unit 1609 can be composed of, for example, a full keyboard and pointing device, and constitutes a user interface for an operator who performs trajectory simulation and verification.

The control device 1000 of FIG. 9 has a network interface 1605 as communication means for communicating via the network NW. Arithmetic processing unit 1 (FIG. 1) controls teaching point data, trajectory data, etc. for actual robot arm A (or its robot control device 200 (FIG. 10)) via network interface 1605 to network NW. Can send and receive information. In that case, the network interface 1605 is configured with a communication standard for wired communication such as IEEE 802.3 and wireless communication such as IEEE 802.11 and 802.15. However, the network NW may, of course, employ any other communication standard.

Note that the control program of the CPU 1601 for realizing the control procedure described later can also be stored in an external storage device 1604 such as an HDD or SSD, or a storage unit such as the ROM 1602 (for example, an EEPROM area). In that case, the control program of the CPU 1601 for realizing the control procedure described later can be supplied to each of the above-described storage units via the network interface 1605 and updated to a new (different) program. Alternatively, the control program of the CPU 1601 for realizing the control procedure described later is supplied to each of the above-described storage units via storage means such as various magnetic disks, optical disks, and flash memories, and drive devices therefor, Also, its contents can be updated. Various storage means and storage units in which the control program of the CPU 1601 for realizing the above-described control procedure is stored constitute a computer-readable recording medium storing the control procedure of the present invention.

In the case of the robot controller 200 (FIG. 10), a driver circuit for driving the motors and solenoids (not shown) of each part of the robot arm A is connected to the interface 1606 in the configuration shown in FIG. In the case of the robot controller 200, the user interface consisting of the display 1608 and the operation unit 1609 may be replaced with an operation terminal such as a teaching pendant (for example, 204 in FIG. 10).

In general, a robot arm is composed of joints and links, and there are various types of joint mechanisms such as rotary joints, linear joints, and ball joints. In this embodiment, the robot arm that generates the trajectory has a configuration in which links are connected by revolving joints as shown in FIG.

FIG. 2 shows an example of a robot arm that is a target of trajectory generation in this embodiment. The robot arm A in FIG. 2 is illustrated in a simplified configuration for ease of explanation.

The robot arm A in FIG. 2 has two axes J1 and J2 consisting of two rotary joints. Below, the joint angles (joint positions) of the axes J1 and J2 of these joints are expressed as θ1 and θ2, respectively. A TCP (Tool Center Point) is defined as a reference position at the tip of the axis J2. In this embodiment, the teaching point that defines the position of the robot arm A is expressed as the position of this TCP. Also, the generated trajectory of the robot arm A is generated as a trajectory along which this TCP moves.

In general, when the joint angles θ1 and θ2 of the axes J1 and J2 are given, the TCP position can be obtained by kinematic calculation, and when the TCP position is given, the TCP position can be obtained by inverse kinematic calculation. can obtain the joint angles θ1 and θ2 of the axes J1 and J2 when takes that position. In the following, when referring to TCP, it may simply be referred to as a "minion".

In addition, the robot arm A is illustrated as a very simplified configuration for easy understanding, but this configuration is not limited to the embodiment of the present invention. For example, when a person skilled in the art implements the present invention, as the robot arm A, a configuration of a 6-axis articulated robot arm or a direct-acting robot arm can be used. The configuration and control procedure of the control system related to the robot arm of the present embodiment described below can be easily extended when using those robot arms.

Next, the movement operation of the robot arm A will be explained. When the robot arm A is to be moved, the teaching point indicating the start position of the movement is referred to as the start teaching point, and the teaching point indicating the target position is referred to as the target teaching point. The teaching point of the robot arm A can be determined by the position and posture of the hand (TCP) or the joint axis angle. Further, by inverse kinematics calculation, the position and posture of the hand (TCP) can be converted into the joint angle of each joint axis. can be converted to the position and orientation of

Here, the start teaching point and the target teaching point are Ps and Pg, respectively. Also, the teaching points arranged between the starting teaching point and the target teaching point are called intermediate teaching points, and are expressed as P1, P2, . . . , Pn. In addition, P1, P2, . . . , Pn may be collectively referred to as an intermediate taught point group.

Interpolation methods such as Spline interpolation, B-Spline interpolation, and Bezier curve interpolation are known as methods for smoothly interpolating intermediate teaching point groups P1, P2, . By using these interpolation methods to generate a path that smoothly connects the teaching points, the robot arm A can be operated smoothly.

As used herein, the “path of motion” or “path” of the robot arm refers to the trajectory of motion of the robot arm, which does not include temporal concepts such as velocity. In addition, the "motion trajectory" or "trajectory" of the robot arm means an information body having information on the motion speed of the robot arm in addition to the above-mentioned "(motion) path" of the robot arm. It is used in a clear distinction from the above-mentioned "(movement) path". In the robot control technology, the "trajectory" may be represented by a command value data string of the joints (angles) of the robot arm for each unit time, for example, the control clock period of the robot controller.

Shortest time control is a method for generating a trajectory including velocity information for the path of the robot arm generated using the above interpolation method. By using the shortest time control, it is possible to obtain the trajectory that minimizes the operation time based on the path generated by interpolation while observing the physical restrictions of the robot arm. Note that the shortest time control is a technique for obtaining the movement speed that takes the shortest time on a predetermined path, and the path for moving the robot arm depends on the group of intermediate teaching points P1, P2, . . . Pn. Other physical constraints of the robot arm may include, for example, joint torque constraints, joint angular velocity constraints, joint angular acceleration constraints, jerk constraints, hand speed constraints, and hand acceleration constraints. Below, the trajectory generated using the shortest time control is expressed as p1, p2, .

FIG. 3 shows how a robot arm A (a 3D model simulating the robot arm model) and an obstacle Ob (a 3D model simulating the obstacle Obstacle model) are both placed in an operating environment (virtual environment). ing. 3 also shows a start teaching point Ps, a target teaching point Pg, intermediate teaching point groups P1, P2, . . . Pn, and trajectories (p1, p2, . . . pt) generated thereby.

In the trajectory (p1, p2, . . . pt) shown in FIG. 3, the robot arm A interferes with the obstacle Ob at p4 and p5. Can not. The purpose of the present embodiment is to provide optimal intermediate teaching point groups P1, P2, ... to find Pn. Note that the obstacle Ob is not limited to being stationary, and the trajectory optimization calculation can be performed even when the obstacle Ob is moving.

FIG. 4 is a flow chart describing the main control procedure of the trajectory generation method according to this embodiment. The control procedure shown in FIG. 4 can be stored in ROM 1602 (or external storage device 1604 or the like) as a control program for CPU 1601 . 5 shows the control procedure of each step in FIG. 4 in the same manner as in FIG. In the following, trajectory generation and optimization are performed with respect to the 3D models of the robot arm A and the obstacle Ob. It may be described as if it is A or an obstacle Ob.

In step S100 of FIG. 4, the model of the robot arm A in the work space where the robot arm A works, the constraint conditions, the start teaching point Ps, and the target teaching point Pg are input (FIG. 5(a)). These inputs can be made by the user through a user interface configured by the operation unit 2 and the display unit 4, for example. In particular, the start teaching point Ps and the target teaching point Pg are input by the user through a virtual display (GUI) on the display unit 4, and are determined by the CPU 1601 when the trajectory is generated by AI-like processing. may

The model of the robot arm A described above is design information for the parts that make up the robot arm, and includes information such as the moment of inertia, mass, position, attitude, number of axes, etc. of each link. Constraints define physical constraints of the robot arm, and include joint torque constraints, joint angular velocity constraints, joint angular acceleration constraints, jerk constraints, hand speed constraints, hand acceleration constraints, and the like.

In step S101, intermediate teaching points (first group of intermediate teaching points) P1, P2, . generated (FIG. 5(b)). In this embodiment, as shown in FIG. 5B, the number of intermediate taught points to be generated is n, and the intermediate taught points are P1, P2, . . . Pn in order.

A route planning algorithm that calculates a route avoiding obstacles may be used as a method for generating the intermediate taught points. Path generation methods include many methods such as the potential method, PRM (Probabilistic Road Map), and RRT (Rapidly-exploring Random Tree). Further, the route generating means is not limited to the above, and other route generating methods such as the visible graph method, the cell division method, the Voronoi diagram method, etc. may be applied. Alternatively, a process of simply linearly interpolating between the start teaching point and the target teaching point may be used without using the path planning algorithm. Note that the above-described route planning technique only calculates a route that guarantees interference avoidance only when teaching points are connected by straight lines. Therefore, there are cases where interference avoidance is not necessarily guaranteed on a route obtained by interpolating the group of intermediate taught points P1, P2, . . . , Pn with curved lines.

For example, as shown in FIG. 5B, intermediate taught point groups P1, P2, . In this embodiment, even if processing is started from intermediate taught point groups P1, P2, . Groups P1, P2, . . . Pn (first group of intermediate taught points) can be moved.

Alternatively, intermediate taught point groups P1, P2, . You can also set it by performing an operation to plot on .

In step S102 in FIG. 4, the intermediate taught point groups P1, P2, . 2 intermediate taught point group) (FIG. 5(c): intermediate taught point generation step). As a method of giving this displacement, for example, a method of adding a random value as a parameter for giving spatial displacement to each of the intermediate teaching points can be considered. However, if a method of simply applying random random values is adopted, the teaching points are arranged oscillatingly, and the motion of the robot arm may not be smooth. In general, when the motion of the robot arm vibrates, the motion time tends to increase, so it is not desirable to arrange the teaching points in a vibratory manner.

Therefore, in order to give a spatial displacement, a correlation is given between random numbers acting on adjacent intermediate teaching points, thereby smoothing the trajectory (path). For example, let the joint values of one axis of the robot arm be θ11, θ12, . . . . By giving a positive value to the covariance in the variance-covariance matrix in this way, the joint values of adjacent intermediate taught points can be correlated, and smooth random numbers along the path can be generated. It becomes possible.

In step S103, curves are interpolated between intermediate taught point groups R1, R2, . Here, for the purpose of avoiding a stationary obstacle, it is sufficient to evaluate the interference of the robot arm A on the "path" interpolated by a curved line. Since the axis must also be taken into account, in this embodiment we consider "trajectory".

In step S104, it is determined whether the generated trajectory satisfies the constraints. If the trajectory does not satisfy the constraints, the process returns to S102, and if the trajectory satisfies the constraints, the process proceeds to S105. The constraints determined in step S104 are constraints that cannot be constrained by the shortest time control technique used in step S103. The constraint condition determined in step S104 is that the mechanism of the robot arm A does not protrude out of the movable range at least on the trajectory generated in step S103. Other constraints determined in step S104 may include, for example, joint torque constraints, joint angular velocity constraints, joint angular acceleration constraints, jerk constraints, hand speed constraints, or hand acceleration constraints of the robot arm. In step S104, a determination can be made to generate a trajectory that satisfies any one or more of these constraints.

In step S105, intermediate taught point groups R1, R2, . . . Rn and trajectories generated based thereon are stored. The stored intermediate taught point groups are denoted by Ri1, Ri2, . . . Rin in order to distinguish them from other stored intermediate taught point groups. i is the saved order.

In step S106, it is determined whether or not the number of stored intermediate taught point groups and trajectories has reached a certain constant N. In step S106, if the number of stored intermediate teaching point groups and trajectories has not reached N, the process returns to step S102, and if the number has reached N, the process proceeds to step S107.

In step S107, evaluation values are given to the stored N intermediate taught point groups Ri1, Ri2, . . . Rin (i=1 to N) (FIG. 5(d): evaluation step). In this embodiment, this evaluation value is used to displace (move) the group of intermediate taught points P1, P2, .

Also, this evaluation value is generated, for example, by evaluating trajectories corresponding to intermediate taught point groups Ri1, Ri2, . . . Rin (i=1 to N). For example, in the present embodiment, the amount of interference between the robot arm and the obstacle is used as an evaluation value in order to obtain a trajectory that avoids interference with the obstacle Ob. For example, the amount of interference may be the amount of interference for which the robot arm and the obstacle occupy the same space, the amount of penetration or the distance of interference (or the overlapping volume of their sweeping spaces). In the present embodiment, for example, an interference time is adopted as an interference amount and used as an evaluation value.

In the example of FIG. 5(d), the evaluation values generated by the amount of interference (interference time or penetration amount) are shown for three intermediate taught point groups. This evaluation value is 10 for the second intermediate teaching point group R11, R12 . . . R1n, 30 for R21, R22 . Here, the intermediate taught point groups R11, R12, .

For purposes other than avoiding interference with the obstacle Ob, other methods may be employed to evaluate the trajectories corresponding to the intermediate taught point groups Ri1, Ri2, . . . Rin (i=1 to N).

In step S108, the intermediate taught point groups P1, P2, . . . Pn are moved based on the evaluation values of the N intermediate taught point groups Ri1, Ri2, . ). As one of the methods of this movement, for example, in the group of intermediate taught points Ri1, Ri2, . . . A method of moving the groups P1, P2, . . . Pn is conceivable. 5(e), intermediate taught point groups P1, P2, . is moving.

In addition, the weights of the N intermediate taught point groups Ri1, Ri2, . A method of taking the attached average and moving the group of intermediate taught points P1, P2, . . . Pn may also be used.

In step S109, it is determined whether a condition for terminating the processing from step S102 to step S108 is satisfied. If the termination condition is not satisfied, the process returns to step S102, and if the termination condition is satisfied, the process proceeds to step S110.

Alternatively, an upper limit number of times for executing the loop of steps S102 to S109 may be set. In that case, if the upper limit number of times has been reached in step S109, further trials are given up and the process proceeds to step S110. Alternatively, error processing such as outputting an appropriate error message on the display unit 4 may be performed.

The termination condition determined in step S109 is, for example, to generate an evaluation value similar to step S107 for the post-movement intermediate taught point group P1, P2, . . . Pn (first intermediate taught point group). The condition is that a predetermined condition is satisfied. For example, the purpose of this embodiment is to avoid interference between the robot arm A and the obstacle Ob. Therefore, it is assumed that the evaluation value generated for the group of intermediate taught points P1, P2, . As a result, an optimum trajectory that satisfies the constraints on robot motion can be generated (trajectory determination step).

In step S110, intermediate taught point groups P1, P2, . . . Pn are output as optimized taught points. This output is obtained, for example, by operating a 3D model (robot arm model) of the robot arm A on a trajectory generated by the optimized group of intermediate teaching points P1, P2, . conduct. Alternatively, step S110 is a process of outputting intermediate teaching point groups P1, P2, . There may be.

In this embodiment, since the object is to avoid interference, when reaching step S110, as shown in FIG. 6, trajectories (p1, p2, . . pt), the robot arm is in a state where it does not interfere with the interfering object.

According to this embodiment, a plurality of intermediate taught point groups Ri1, Ri2, . . . Rin (i=1 to N) are generated, and the intermediate taught point groups P1, P2 , . . . move Pn. Conditions relating to physical constraints such as joint torque constraints are used for trajectory evaluation, and obstacle avoidance achievement conditions are used as escape conditions for the process of moving intermediate taught point groups P1, P2, . . . , Pn. With such a configuration, according to the present embodiment, it is possible to avoid obstacles and generate a smooth curved trajectory that satisfies physical constraints such as joint torque constraints.

<Embodiment 2>
Hereinafter, with reference to FIG. 7, an example of optimization processing for generating a trajectory that enables (the 3D model of) the robot arm A to avoid interference with the obstacle Ob and move in the shortest time will be described. Configurations other than that shown in FIG. 7, such as the hardware configurations of the trajectory generation device and its control device, are the same as those of the first embodiment.

The control procedure of the trajectory generation method of the present embodiment is the same as the flowchart of FIG. 4 of the first embodiment. The values, how the trajectories are constrained, how the trajectories are evaluated, and the censoring criteria are different. FIG. 7 shows how the trajectory (first intermediate teaching point) is optimized in this embodiment. FIG. 7 shows the processing of each step of FIG. 4 in this embodiment in a format similar to that of FIG.

In the first embodiment described above, in step S101 of FIG. 4, intermediate taught point groups P1, P2, . I gave an example. On the other hand, in this embodiment, intermediate taught point groups P1, P2, ... Pn (FIGS. 6 and 7B) output through the optimization process of Embodiment 1 in step S101 of FIG. 4 are used. .

By using the group of intermediate taught points P1, P2, . can. Thus, the optimization control procedure of the present invention (FIG. 4) can be used in two passes (or more passes), in which case different constraints are applied in each pass so that each A trajectory optimized for the constraints can be obtained.

In the first embodiment, a new group of intermediate taught points R1, R2, . When determining whether the trajectory of the point cloud satisfies the constraints, it is determined whether or not the robot arm A is within the movable range. In this embodiment, a new group of intermediate taught points R1, R2, . It is determined whether or not A interferes with the obstacle Ob. If it interferes with an obstacle, invalidate the group of intermediate taught points R1, R2, .

Further, in the first embodiment, in step S107 of FIG. 4, the trajectory is evaluated using the interference time or the penetration amount as an evaluation value. In this embodiment, the trajectory is evaluated using the operation time of the robot arm A as an evaluation value (FIG. 7(d)). Thus, intermediate taught point groups P1, P2, . In the example of FIG. 7D, the evaluation values of the second intermediate teaching point group related to the operation time are 180 for R11, R12...R1n, 120 for R21, R22...R2n, and 150 for R31, R32...R3n. It's becoming Here, the intermediate taught point groups R21, R22, .

Moreover, in the first embodiment, the evaluation value becomes 0 as one of the termination conditions in step S109 of FIG. On the other hand, in the present embodiment, there is a method of setting an upper limit number of repetitions of steps S102 to S109, or a method of setting the number of evaluation values of intermediate taught point groups P1, P2, . . . A method of setting an upper limit is used. For example, if the operation time is not shortened any further, the loop of steps S102 to S109 is exited, and intermediate taught point groups P1, P2, . ). Alternatively, in the second embodiment, in step S110, the group of intermediate taught points P1, P2, . For example, a change history of intermediate taught point groups P1, P2, .

As described above, according to this embodiment, it is possible to avoid obstacles, observe physical constraints such as torque constraints, and generate a trajectory that minimizes the operation time. In particular, the optimization control procedure (FIG. 4) can be used in two passes (or more passes), where each pass optimizes for each constraint by applying a different constraint. It is possible to obtain the trajectory

Here, a more specific configuration example of the robot arm A and a configuration when the robot arm A is applied to a production system will be shown.

FIG. 10 shows the overall configuration of the robot arm A more specifically than the schematic configuration of FIG. In FIG. 10, a robot arm A (robot device) includes an arm body 201 of, for example, a vertical multi-joint type with six axes (joints). Each joint of the arm body 201 can be controlled to a desired position and orientation by servo-controlling a servomotor provided for each joint.

For example, a tool such as a hand 202 is attached to the tip (end of hand) of the arm body 201. The hand 202 can be used to grip a work 203 and perform production work such as assembling or processing the work 203. can. The workpiece 203 is, for example, a part of an industrial product such as an automobile or an electrical product, and the robot arm A can be arranged as a production device in such a production system (production line).

The movement of the arm body 201 of the robot arm A is controlled by a robot control device 200 (robot controller). The operation of the robot arm A can also be programmed (instructed) by an operation terminal 204 (for example, a teaching pendant) connected to the robot controller 200 . For example, by sequentially designating teaching points using the operation terminal 204, it is possible to program an operation to move a specific part of the robot arm A (for example, TCP: tool mounting surface at the tip of the arm) along a desired trajectory.

Also, the robot arm A or the robot controller 200 receives intermediate teaching points or trajectory data optimized as described above from the trajectory generator (or robot simulator: FIG. 1) via the network NW. be able to. As a result, robot arm A can be placed in a production system (production line) based on the intermediate teaching points or trajectory data optimized by the above process, and can be operated as a production device to manufacture articles.

The present invention supplies a program that implements one or more functions of the above-described embodiments to a system or device via a network or storage medium, and one or more processors in the computer of the system or device read and execute the program. processing is also feasible. It can also be implemented by a circuit (for example, ASIC) that implements one or more functions.

A... robot arm, J1, J2... joint axis, Ob... obstacle, Ps... start teaching point, Pg... target teaching point, P1, P2,... Pn... (first) intermediate teaching point group, Ri1, Ri2, Rin... (second) intermediate teaching point group, 1... arithmetic processing section, 2... operating section, 3... recording section, 4... display section.

Claims (26)

In an information processing method for obtaining a trajectory for moving a robot arm between a first position and a second position,
an acquisition step of setting a plurality of intermediate taught point groups that define a route from the first position to the second position, and acquiring a plurality of intermediate trajectories based on the intermediate taught point groups;
an evaluation step of obtaining an evaluation value for the intermediate trajectory obtained in the obtaining step;
an updating step of selecting a predetermined intermediate trajectory from among the intermediate trajectories based on the evaluation value and updating the trajectory based on the predetermined intermediate trajectory;
An information processing method characterized by: In the information processing method according to claim 1,
In the obtaining step, the plurality of intermediate taught point groups are set by giving different displacements to intermediate taught points of a predetermined intermediate taught point group.
An information processing method characterized by: In the information processing method according to claim 2,
the displacement is given based on correlated random numbers;
An information processing method characterized by: In the information processing method according to claim 3,
Correlating the random numbers by assigning a positive value to the covariance in the variance-covariance matrix;
An information processing method characterized by: In the information processing method according to any one of claims 1 to 4,
In the acquisition step, the intermediate trajectory that satisfies physical constraints regarding the drive mechanism of the robot arm is acquired.
An information processing method characterized by: In the information processing method according to claim 5,
wherein the constraint is the movable range of the robot arm ;
An information processing method characterized by: In the information processing method according to claim 5 or 6,
The constraint is any one or more of a joint torque constraint, a joint angular velocity constraint, a joint angular acceleration constraint, a jerk constraint, a hand speed constraint, or a hand acceleration constraint regarding the robot arm ,
An information processing method characterized by: In the information processing method according to any one of claims 5 to 7,
In the evaluation step, the evaluation value is obtained based on the amount of interference between the robot arm and an object placed in the space where the robot arm operates on the intermediate trajectory.
An information processing method characterized by: In the information processing method according to claim 8,
The amount of interference is an interference time or an interference distance in which the robot arm and the object occupy the same space.
An information processing method characterized by: In the information processing method according to claim 8 or 9,
In the acquisition step, if the constraint is satisfied, a predetermined intermediate trajectory in which interference occurs between the robot arm and the object is also acquired as the plurality of intermediate trajectories.
An information processing method characterized by: In the information processing method according to any one of claims 8 to 10,
determining in the updating step that no interference has occurred between the robot arm and the object when the evaluation value becomes 0;
An information processing method characterized by: In the information processing method according to any one of claims 1 to 11,
repeatedly performing the acquiring step, the evaluating step, and the updating step;
An information processing method characterized by: In the information processing method according to any one of claims 1 to 12,
In the obtaining step, the plurality of intermediate trajectories are obtained so that an operation time for operating the robot arm is shortened.
An information processing method characterized by: In the information processing method according to any one of claims 1 to 13,
In the evaluation step, the evaluation value is obtained based on an operation time when the robot arm is operated on the plurality of intermediate trajectories.
An information processing method characterized by: In the information processing method according to any one of claims 1 to 14,
In the updating step, on condition that the evaluation value satisfies a predetermined condition, the update of the trajectory is stopped.
An information processing method characterized by: In the information processing method according to claim 15,
The predetermined condition is a case where the change in the evaluation value is constant even if the trajectory is updated a predetermined number of times.
An information processing method characterized by: In the information processing method according to any one of claims 1 to 14,
stopping the update of the trajectory based on the number of repetitions of updating the trajectory reaching a predetermined number of times;
An information processing method characterized by: In the information processing method according to any one of claims 1 to 17,
In the acquiring step, acquiring the plurality of intermediate trajectories using at least one of a potential method, PRM, RRT, visible graph method, cell division method, and Voronoi projection method.
An information processing method characterized by: In the information processing method according to any one of claims 1 to 18,
smoothing the plurality of intermediate trajectories using at least one of Spline interpolation, B-Spline interpolation, and Bezier curve interpolation in the obtaining step;
An information processing method characterized by: In the information processing method according to any one of claims 1 to 19,
Further comprising an output step of displaying the updated trajectory on a display device,
An information processing method characterized by: In the information processing method according to any one of claims 1 to 19,
further comprising an output step of outputting the updated trajectory to a control device that controls the robot arm ;
An information processing method characterized by: A program that causes a computer to execute each step of the information processing method according to any one of claims 1 to 21. A computer-readable recording medium storing the program according to claim 22. In an information processing device that acquires a trajectory for operating a robot arm between a first position and a second position,
setting a plurality of intermediate taught point groups that define a route from the first position to the second position, obtaining a plurality of intermediate trajectories based on the intermediate taught point groups;
obtaining an evaluation value in the obtained intermediate trajectory;
selecting a predetermined intermediate trajectory from among the intermediate trajectories based on the evaluation value, and updating the trajectory based on the predetermined intermediate trajectory;
An information processing device characterized by: A production system for manufacturing articles by assembling workpieces by operating the robot arm along a trajectory obtained by using the information processing method according to any one of claims 1 to 22. 23. An article manufacturing method comprising assembling a workpiece by operating the robot arm along a trajectory obtained by using the information processing method according to any one of claims 1 to 22, and manufacturing an article.

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