JP7635442B2 - Information processing method, information processing device, program, recording medium, production system, robot system, and method for manufacturing an article - Google Patents

Description

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

Conventionally, there has been known a configuration in which industrial robot devices are arranged in production systems (production lines) for industrial products such as automobiles and electrical products to automate tasks such as welding and assembly. In this type of production system, the robot device, workpieces, workpiece placement tables, jigs, and other peripheral equipment are arranged in a state where there is a possibility of interference (contact, collision) with one another. In recent years, simulations using virtual environments are sometimes used in the design work of the motion trajectory of the arms of the robot devices in such production systems.

When simulating the operation of a robot device using a simulator offline, 3D (three-dimensional) models of the robot arm, workpiece stand, jigs, and other peripheral equipment are placed in a virtual environment. For example, some such simulator devices generate a trajectory between pre-created teaching points of the robot arm, and verify the operation by simulating the operation of the 3D model of the robot arm in the virtual environment along that trajectory. The operation of the robot arm model can be displayed in video format on the virtual display screen of the simulator device's display.

Naturally, the simulation results will vary greatly depending on the robot arm's motion trajectory. If the robot arm's trajectory is inappropriate, part of the robot arm's motion trajectory may enter an area where the robot arm cannot move, the robot arm may interfere with other objects, or unnecessary motions may result in slower cycle times.

In the old method, the operator would create teaching points for the robot arm on the screen by trial and error, so that the robot arm would not enter areas where it could not operate, or interfere with peripheral equipment. In this case, because the conditions of being movable and not interfering were taken into consideration first, the robot trajectory that allowed it to operate at the optimal operating speed was not necessarily generated, which could result in slow cycle times. In such cases, it was necessary to manually reconsider and reposition the teaching points for the robot arm.

On the other hand, when using robotic devices in a production system (line), the process designer must spend a lot of time creating teaching points, which leads to rising labor costs. In recent years, therefore, methods and devices have been proposed that use computers to make the teaching work of robotic arms more efficient, instead of direct teaching by an instructor.

The following non-patent document 1 discloses a method for generating a trajectory that avoids interference with obstacles around the robot arm and minimizes the torque of the motor used in the joints of the robot arm. Figure 8 shows an outline of the method for generating a trajectory for a robot arm in non-patent document 1. In Figure 8, robot arm A is a simplified robot arm with two degrees of freedom having two rotation axes J1 and J2, and Ob represents an obstacle.

In FIG. 8, p1, p2, ..., p9 indicate the positions to which the end of the robot arm A (TCP: Tool Center Point) is moved. Of these positions, p1 indicates the start position (start teaching point) of the operation, and p9 indicates the target position (target teaching point) of the operation. Also, p2 to p8 indicate intermediate command values to be placed between the start position (p1) and the target position (p9). For example, the postures of p1, p2, ..., p9 can be commanded to the robot arm A in sequence for each control cycle, and the robot arm A can perform an operation from p1 to p9. In this case, the operation time of the robot arm between the start position (p1) and the target position (p9) is calculated as the control cycle x (9-1). In the case of Non-Patent Document 1, the number of intermediate command values (p2 to p8) is determined in advance as a constant, which is seven in this case. In Figure 8, the robot arm and obstacle Ob interfere with each other at p4 and p5, but a trajectory that can avoid the interference can be generated by the following method.

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, ..., ri8 (i = 1, ..., N). Next, the intermediate command values ri2, ri3, ..., ri8 (i = 1, ..., N) are evaluated, and the process of displacing the intermediate command values p2, p3, ..., p8 based on the evaluation values is repeated to 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 values. By using such evaluation values, 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 technology 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 technology of Non-Patent Document 1, the number of intermediate command values is fixed, and therefore the operation time from the start teaching point (p1) to the target teaching point (p9) is fixed, which causes a problem that, for example, the operation time of the arm cannot be optimized. In addition, when the operation time is fixed, it becomes difficult to satisfy the constraint conditions of the motor torque used for each joint axis and other constraint conditions. Such constraint conditions on the robot operation that are difficult to achieve include, for example, constraint conditions on the joint axis torque, joint angular velocity, joint angular acceleration and jerk, hand speed and hand acceleration. That is, the conventional technology described in Non-Patent Document 1 has the following problems. That is, in an area where the number of intermediate command values is too small, there is no guarantee that the constraint conditions on the robot operation are satisfied, and conversely, in an area where the number of intermediate command values is too large, a trajectory with an optimal operation time cannot be obtained.

In view of the above problems, the objective of the present invention is to reliably generate an optimal trajectory that satisfies the constraints on robot operation.

One aspect of the present invention is an information processing method for acquiring a trajectory for operating a robot arm, the information processing method comprising the steps of: accepting a user's setting of a first teaching point and a second teaching point at which the robot arm is desired to operate ; acquiring at least two intermediate teaching points that define a path from the first teaching point to the second teaching point; acquiring a group of intermediate teaching points by displacing the at least two intermediate teaching points as a group; acquiring an intermediate trajectory based on the group of intermediate teaching points; and acquiring a trajectory for operating the robot arm based on the intermediate trajectory .
Another aspect of the present invention is an information processing method for acquiring a trajectory for operating a robot arm, the information processing method comprising the steps of: accepting a user's setting of a first teaching point and a second teaching point at which the robot arm is desired to operate; acquiring at least two intermediate teaching points that define a path from the first teaching point to the second teaching point; acquiring an intermediate teaching point group by displacing the at least two intermediate teaching points as a group; acquiring an intermediate trajectory based on the intermediate teaching point group; and evaluating the intermediate trajectory.
Another aspect of the present invention is an information processing device that acquires a trajectory for operating a robot arm, the information processing device accepts a user's setting of a first teaching point and a second teaching point at which the robot arm is desired to operate, acquires at least two intermediate teaching points that define a path from the first teaching point to the second teaching point, acquires a group of intermediate teaching points by displacing the at least two intermediate teaching points as a group, acquires an intermediate trajectory based on the group of intermediate teaching points, and acquires a trajectory for operating the robot arm based on the intermediate trajectory .
Another aspect of the present invention is an information processing device that acquires a trajectory for operating a robot arm, the information processing device accepts a user's setting of a first teaching point and a second teaching point at which the robot arm is desired to operate, acquires at least two intermediate teaching points that define a path from the first teaching point to the second teaching point, acquires a group of intermediate teaching points by displacing the at least two intermediate teaching points as a group, acquires an intermediate trajectory based on the group of intermediate teaching points, and evaluates the intermediate trajectory.

With the above configuration, the present invention can reliably generate an optimal trajectory that satisfies the constraints on robot operation.

FIG. 2 is an explanatory diagram showing a functional configuration of a trajectory generation device according to an embodiment of the present invention. FIG. 1 is an explanatory diagram showing a two-axis configuration of a robot arm according to an embodiment of the present invention. FIG. 2 is an explanatory diagram showing a teaching point group and a trajectory according to an embodiment of the present invention. FIG. 11 is a flowchart illustrating a trajectory optimization process according to an embodiment of the present invention. 5A to 5E are explanatory diagrams showing a trajectory optimization process according to an embodiment of the present invention. FIG. 2 is an explanatory diagram showing a teaching point group and a trajectory according to an embodiment of the present invention. 5A to 5E are explanatory diagrams showing a trajectory optimization process according to an embodiment of the present invention. FIG. 1 is an explanatory diagram showing a method of orbit control according to the prior art. 1 is a block diagram showing a schematic configuration of a control device applicable to an embodiment of the present invention. FIG. 1 is an explanatory diagram showing a robot device that can be arranged in a production system according to an embodiment of the present invention.

Below, a description will be given of an embodiment of the present invention with reference to the attached drawings. Note that the configuration shown below is merely an example, and those skilled in the art can appropriately change the detailed configuration, for example, without departing from the spirit of the present invention. Also, the numerical values used in this embodiment are for reference only and do not limit the present invention.

<Embodiment 1>
Fig. 1 shows the configuration of a trajectory generating device according to this embodiment. In this embodiment, the term "trajectory generating device" refers to a device that performs trajectory generation according to the present invention, but this trajectory generating device may be provided as a product such as a robot simulator device.

The trajectory generating device in FIG. 1 comprises a calculation processing unit 1, an operation unit 2 for an instructor to input data, a recording unit 3 for recording operation programs, and a display unit 4 for displaying the motion trajectory of the robot arm. This trajectory generating device can be configured with computer hardware such as a PC (personal computer). Here, a specific configuration example of the calculation processing unit 1 is shown in FIG. 9.

Figure 9 shows an example of the configuration of a trajectory generation device, in particular a control device 1000 that corresponds to the main part of the calculation processing unit 1 (Figure 1). As shown in the figure, this control device 1000 is a control system made up of each block arranged around a CPU 1601. Note that this configuration made up of each block arranged around the CPU 1601 can be applied in a similar manner to, for example, a robot control device (200: Figure 10) described below.

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

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

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

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

In the case of the robot control device 200 (FIG. 10), driver circuits for driving the motors and solenoids (not shown) of each part of the robot arm A in the configuration of FIG. 9 are connected to the interface 1606. In addition, in the case of the robot control device 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 (e.g., 204 in FIG. 10).

Generally, 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 rotary joints, as shown in Figure 2.

Figure 2 shows an example of a robot arm for which trajectory generation is to be performed in this embodiment. Robot arm A in Figure 2 is shown 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. Hereinafter, the joint angles (joint positions) of the axes J1 and J2 of these joints are expressed as θ1 and θ2, respectively. Furthermore, 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. Furthermore, the trajectory of the robot arm A to be generated is generated as the trajectory along which this TCP moves.

In general, when the joint angles θ1 and θ2 of the axes J1 and J2 are given, the position of the TCP can be obtained by kinematic calculations, and when the position of the TCP is given, the joint angles θ1 and θ2 of the axes J1 and J2 when the TCP is in that position can be obtained by inverse kinematic calculations. In the following, when referring to the TCP, it may be simply called the "hand".

The robot arm A is illustrated as having a very simplified configuration for ease of understanding, but this configuration is not intended to be limiting in the implementation of the present invention. For example, when a person skilled in the art implements the present invention, the robot arm A may be configured as a six-axis articulated robot arm or a linear motion robot arm. The configuration and control procedures of the control system for the robot arm of this embodiment shown below can be easily extended to cases where such a robot arm is used.

Next, the movement operation of robot arm A will be explained. When moving robot arm A, the teaching point indicating the start position of the movement is called the start teaching point, and the teaching point indicating the target position is called the target teaching point. The teaching points of robot arm A can be determined by the position and posture of the hand (TCP) or the joint axis angle. Furthermore, by inverse kinematics calculation, the position and posture of the hand (TCP) can be converted into the joint angles of each joint axis, and conversely, by (forward) kinematics calculation, the joint angles of each joint axis can be converted into the position and posture of the hand.

Here, the start teaching point and the target teaching point are Ps and Pg, respectively. The teaching points located between the start teaching point and the target teaching point are called intermediate teaching points and expressed as P1, P2, ..., Pn. When P1, P2, ..., Pn are collectively referred to, they may be called a group of intermediate teaching points.

As a method for smoothly interpolating the group of intermediate teaching points P1, P2, ... Pn with a curve, there are known interpolation methods such as Spline interpolation, B-Spline interpolation, and Bezier curve interpolation. By using these interpolation methods to generate a path that smoothly connects the teaching points, it is possible to operate the robot arm A smoothly.

In this specification, the "motion path" or "path" of a robot arm refers to the trajectory of the robot arm's motion, without including any temporal concepts such as speed. Furthermore, the "motion trajectory" or "path" of a robot arm refers to an information body that has information on the motion speed of the robot arm in addition to the above-mentioned "(motion) path" of the robot arm, and is used in this specification to clearly distinguish it from the above-mentioned "(motion) path." Note that in robot control technology, a "path" may also be expressed by a command value data string for the joints (angles) of the robot arm per unit of time, for example, per control clock cycle of the robot controller.

As a method for generating a trajectory including speed information for the path of the robot arm generated using the above-mentioned interpolation method, there is a method of time-saving control. By using time-saving control, it is possible to obtain a trajectory that has the shortest operating time while observing the physical constraints of the robot arm based on the path generated by interpolation. Note that time-saving control is a technique for obtaining a moving speed that takes the shortest time while passing through a fixed path, and the path for operating the robot arm depends solely on the intermediate teaching point group P1, P2, ... Pn. Other possible physical constraints of the robot arm include, for example, joint torque constraints, joint angular velocity constraints, joint angular acceleration constraints, jerk constraints, hand velocity constraints, and hand acceleration constraints. In the following, the trajectory generated using time-saving control is expressed as p1, p2, ... pt as a sequence of position command values of the robot arm for each control cycle.

Figure 3 shows a robot arm A (3D model simulating it: robot arm model) and an obstacle Ob (3D model simulating it: obstacle model) both placed in an operating environment (virtual environment). Figure 3 also shows a start teaching point Ps, a target teaching point Pg, and a group of intermediate teaching points P1, P2, ... Pn, and the trajectory (p1, p2, ... pt) generated thereby.

In the trajectory (p1, p2, ... pt) shown in Figure 3, the robot arm A interferes with the obstacle Ob at p4 and p5, and on this trajectory it is not possible to move from the starting teaching point Ps to the target teaching point Pg. The objective of this embodiment is to find an optimal group of intermediate teaching points P1, P2, ... Pn between the starting teaching point Ps and the target teaching point Pg, where the robot arm does not interfere with the obstacle (and other constraints are also satisfied). Note that the obstacle Ob is not limited to being stationary, and even if it is moving, the optimization calculation of the trajectory is possible.

Figure 4 is a flowchart describing the main control procedures of the trajectory generation method according to this embodiment. The control procedures shown in Figure 4 can be stored in ROM 1602 (or external storage device 1604, etc.) as a control program for CPU 1601. Also, Figure 5 shows the control procedures for each step of Figure 4 in a format similar to that of Figure 3. In the following, trajectory generation and optimization are performed for 3D models of robot arm A and obstacle Ob, but to simplify the description, the "3D model" may be omitted and the subject of control may be described as if it were robot arm A or obstacle Ob.

In step S100 in FIG. 4, a model of robot arm A in the workspace in which robot arm A performs work, as well as constraint conditions, starting teaching point Ps, and target teaching point Pg are input (FIG. 5(a)). These inputs can be made by the user via a user interface constituted by the operation unit 2 and display unit 4, for example. In particular, the starting teaching point Ps and the target teaching point Pg can be input by the user via a virtual display (GUI) on the display unit 4, or they can be determined by the CPU 1601 when trajectory generation is performed by AI processing.

The model of robot arm A above is design information for the parts that make up the robot arm, and includes information such as the moment of inertia, mass, position, posture, and number of axes of each link. In addition, the constraint conditions define the physical constraints of the robot arm, and include joint torque constraints, joint angular velocity constraints, joint angular acceleration constraints, jerk constraints, hand velocity constraints, and hand acceleration constraints.

In step S101, intermediate teaching points (first group of intermediate teaching points) P1, P2, ... Pn are generated as initial values between the starting teaching point Ps and the target teaching point Pg of the robot arm A given in step S100 (Figure 5 (b)). In this embodiment, as shown in Figure 5 (b), the number of intermediate teaching points to be generated is n, and the intermediate teaching points are named P1, P2, ... Pn in order.

A method for generating intermediate teaching points is to use a path planning algorithm that calculates a path that avoids obstacles. There are many methods for generating paths, such as the potential method, PRM (Probabilistic RoadMap), and RRT (Rapidly-exploring Random Tree). In addition, the path generation method is not limited to the above, and other path generation methods such as the visibility graph method, cell division method, and Voronoi diagram method may also be applied. In addition, a process of linearly interpolating a starting teaching point and a target teaching point with a straight line may be used simply without using a path planning algorithm. Note that the above-mentioned path planning technology calculates a path that guarantees interference avoidance only when teaching points are connected with a straight line. Therefore, interference avoidance may not necessarily be guaranteed in a path in which the intermediate teaching point group P1, P2, ... Pn is interpolated with a curve.

For example, as shown in FIG. 5(b), the intermediate teaching point group P1, P2, ... Pn (first intermediate teaching point group) corresponds to a trajectory that interferes with an obstacle Ob, for example. In this embodiment, even if processing is started from such an intermediate teaching point group P1, P2, ... Pn (first intermediate teaching point group) as an initial value, the intermediate teaching point group P1, P2, ... Pn (first intermediate teaching point group) can be moved to generate an optimal trajectory.

Alternatively, the initial intermediate teaching point group P1, P2, ... Pn (first intermediate teaching point group) may be set by the user through the user interface of the operation unit 2 and the display unit 4 by plotting the points in the virtual environment on the screen.

In step S102 in FIG. 4, a spatial displacement is given to the intermediate teaching point group P1, P2, ... Pn (first intermediate teaching point group) to generate a new intermediate teaching point group R1, R2, ... Rn (second intermediate teaching point group) (FIG. 5(c): intermediate teaching point generation process). One possible method for giving this displacement is, for example, adding (adding) a random number value as a parameter for giving a spatial displacement to each of the intermediate teaching points. However, if a method is adopted in which a random number value is simply applied, the teaching points may be arranged in a vibratory manner, which may cause the robot arm to move unsmoothly. In general, when the robot arm moves in a vibratory manner, the operating time tends to increase, so it is not desirable to arrange the teaching points in a vibratory manner.

Therefore, to impart spatial displacement, correlation is imparted between the random numbers acting on adjacent intermediate teaching points, which makes it possible to smooth the trajectory (path). For example, let the joint values of one axis of a robot arm in the group of intermediate teaching points P1, P2, ... Pn be θ11, θ12, ... θ1n, and consider a multivariate normal distribution with these as variables. In this way, by giving a positive value to the covariance in the variance-covariance matrix, it is possible to impart correlation to the joint values of adjacent intermediate teaching points, making it possible to generate smooth random numbers along the path.

In step S103, the intermediate teaching points R1, R2, ... Rn are interpolated with a curve, and a trajectory is generated using minimum time control (trajectory generation process). If the objective is to avoid a stationary obstacle, it is sufficient to evaluate the interference of robot arm A on the "route" interpolated with a curve. However, when considering a moving obstacle, the time axis must also be taken into account, so in this embodiment, the "trajectory" is taken into account.

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. If the trajectory satisfies the constraints, the process proceeds to S105. The constraint conditions determined in step S104 are constraints that cannot be constrained by the time-optimal control technique used in step S103. The constraint conditions determined in step S104 are at least those that the mechanism of robot arm A does not go outside the movable range on the trajectory generated in step S103. The constraint conditions determined in step S104 may also include other conditions, such as a joint torque constraint, a joint angular velocity constraint, a joint angular acceleration constraint, a jerk constraint, a hand velocity constraint, or a hand acceleration constraint of the robot arm. In step S104, a determination can be made to generate a trajectory that satisfies one or more of these constraint conditions.

In step S105, the intermediate teaching point groups R1, R2, ... Rn and the trajectory generated based on them are saved. The saved intermediate teaching point groups are denoted as Ri1, Ri2, ... Rin to distinguish them from other saved intermediate teaching point groups. i indicates the order in which they were saved.

In step S106, it is determined whether the number of stored intermediate teaching points and trajectories has reached a certain constant N. If the number of stored intermediate teaching points and trajectories has not reached N in step S106, 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 assigned to the N stored intermediate teaching point groups Ri1, Ri2, ... Rin (i = 1 to N) (Figure 5 (d): evaluation step). In this embodiment, these evaluation values are used to displace (move) the intermediate teaching point group P1, P2, ... Pn (first intermediate teaching point group) to generate an optimal trajectory.

This evaluation value is generated, for example, by evaluating the trajectory corresponding to the intermediate teaching point group Ri1, Ri2, ... Rin (i = 1 to N). For example, in this embodiment, in order to find a trajectory that avoids interference with an obstacle Ob, the amount of interference between the robot arm and the obstacle is used as the evaluation value. For example, this amount of interference may be the interference time during which the robot arm and the obstacle occupy the same space, the amount of penetration, or the interference distance (or the overlapping volume of the swept spaces of both). In this embodiment, for example, the interference time is used as the amount of interference, and is used as the evaluation value.

The example in Figure 5(d) shows evaluation values generated for three intermediate teaching point groups based on the amount of interference (interference time or amount of penetration). The evaluation value is 10 for the second intermediate teaching point group R11, R12...R1n, 30 for R21, R22...R2n, and 50 for R31, R32...R3n. The intermediate teaching point group R11, R12...R1n with the smallest amount of interference (close to 0) has the best evaluation value.

Note that other methods may be used to evaluate the trajectory corresponding to the intermediate teaching point group Ri1, Ri2, ... Rin (i = 1 to N) for purposes other than avoiding interference with the obstacle Ob.

In step S108, the intermediate teaching point group P1, P2, ... Pn is moved based on the evaluation values of the N intermediate teaching point groups Ri1, Ri2, ... Rin (i = 1 to N) (Figure 5 (e)). One method of this movement is, for example, to move the intermediate teaching point group P1, P2, ... Pn to the intermediate teaching point group with the lowest (best) evaluation value among the intermediate teaching point groups Ri1, Ri2, ... Rin (i = 1 to N). In the example of Figure 5 (e), the intermediate teaching point group P1, P2, ... Pn (in the first intermediate teaching point group) is moved to the position of the intermediate teaching point group R11, R12 ... R1n with the smallest (closest to 0) interference amount.

Alternatively, a method may be used in which the inverse of the evaluation value of the intermediate teaching point group Ri1, Ri2, ... Rin (i = 1 to N) is used as the weight, a weighted average of N intermediate teaching point groups Ri1, Ri2, ... Rin (i = 1 to N) is taken, and the intermediate teaching point groups P1, P2, ... Pn are moved.

In step S109, it is determined whether the conditions for aborting the processing from step S102 to step S108 are met. If the conditions are not met, the process returns to step S102; if the conditions are met, the process proceeds to step S110.

Alternatively, an upper limit on the number of times the loop from step S102 to step S109 is executed may be set. In this case, if the upper limit is reached in step S109, further attempts are abandoned and the process proceeds to step S110. Alternatively, an error handling process may be performed, such as outputting an appropriate error message on the display unit 4.

The termination condition determined in step S109 is, for example, that an evaluation value similar to that in step S107 is generated for the intermediate teaching point group P1, P2, ... Pn (first intermediate teaching point group) after the movement, and that the evaluation value satisfies a predetermined condition. For example, the objective of this embodiment is to avoid interference between the robot arm A and the obstacle Ob. Therefore, the evaluation value generated for the intermediate teaching point group P1, P2, ... Pn (first intermediate teaching point group) after the movement is set to 0 (amount of interference: interference time and amount of intrusion are 0). This makes it possible to generate an optimal trajectory that satisfies the constraints on the robot operation (trajectory determination process).

In step S110, the group of intermediate teaching points P1, P2, ... Pn is output as the optimized teaching points. This output is performed, for example, by operating a 3D model of the robot arm A (robot arm model) on a trajectory generated by the optimized group of intermediate teaching points P1, P2, ... Pn within a virtual display on the display unit 4. Alternatively, step S110 may be a process of outputting the optimized group of intermediate teaching points P1, P2, ... Pn or the trajectory data generated thereby to the actual robot arm A or its robot control device (200: FIG. 10).

In this embodiment, the purpose is to avoid interference, so when step S110 is reached, the robot arm will not interfere with any interfering object on the trajectory (p1, p2, ... pt) generated based on the intermediate teaching point group P1, P2, ... Pn after the movement, as shown in Figure 6.

According to this embodiment, multiple intermediate teaching point groups Ri1, Ri2, ... Rin (i = 1 to N) are generated, and the intermediate teaching point groups P1, P2, ... Pn are moved based on the results of evaluating the trajectory defined by them. Conditions related to physical constraints such as joint torque constraints are used for evaluating the trajectory, and the condition for achieving obstacle avoidance is used as the escape condition for the process of moving the intermediate teaching point groups P1, P2, ... Pn. With this configuration, this embodiment can generate a smooth curved trajectory that avoids obstacles and satisfies physical constraints such as joint torque constraints.

<Embodiment 2>
An example of optimization processing for generating a trajectory that allows the robot arm A (3D model thereof) to move in the shortest time while avoiding interference with an obstacle Ob will be described below with reference to Fig. 7. The configuration other than that shown in Fig. 7, for example, the hardware configuration of the trajectory generation device and its control device, is assumed to be the same as that of the first embodiment.

The control procedure of the trajectory generation method of this embodiment is equivalent to the flowchart of FIG. 4 of embodiment 1, but this embodiment 2 differs from embodiment 1 in the initial values of the intermediate teaching point group P1, P2, ... Pn, the trajectory constraint method, the trajectory evaluation method, and the termination conditions. FIG. 7 shows the optimization of the trajectory (first intermediate teaching point) performed in this embodiment. FIG. 7 shows the processing of each step of FIG. 4 in this embodiment in the same format as FIG. 5.

In the above embodiment 1, an example was shown in which, in step S101 in FIG. 4, a group of intermediate teaching points P1, P2, ... Pn was generated by path planning technology between the starting teaching point Ps and the target teaching point Pg (FIG. 7(a)). In contrast, in the present embodiment, the group of intermediate teaching points P1, P2, ... Pn (FIGS. 6 and 7(b)) output in step S101 in FIG. 4 after going through the optimization process of embodiment 1 is used.

By using the intermediate teaching point group P1, P2, ... Pn that has already been output through the optimization process of embodiment 1 as initial values, it is possible to perform optimization to shorten the operating time of a trajectory that has already avoided obstacles. In this way, the optimization control procedure of the present invention (Figure 4) can be used in two passes (or multiple passes), in which case a trajectory optimized for each constraint condition can be obtained by applying different constraint conditions in each pass.

In the first embodiment, a new intermediate teaching point group R1, R2, ... Rn (second intermediate teaching point group) is generated (FIG. 5(c)), and in step S104 of FIG. 4, when determining whether the trajectory of this second intermediate teaching point group satisfies the constraints, it is determined whether it is within the movable range of the robot arm A. In this embodiment, a new intermediate teaching point group R1, R2, ... Rn (second intermediate teaching point group) is generated (FIG. 7(c)), and in addition to determining whether it is within the movable range, it is also determined whether the robot arm A is interfering with an obstacle Ob. If it is interfering with an obstacle, the intermediate teaching point group R1, R2, ... Rn is invalidated, and the process returns to step S102.

In the first embodiment, in step S107 in FIG. 4, the trajectory is evaluated using the interference time or the amount of penetration as the evaluation value. In this embodiment, the trajectory is evaluated using the operation time of the robot arm A as the evaluation value (FIG. 7(d)). This makes it possible to generate an intermediate teaching point group P1, P2, ... Pn that has the shortest operation time. In the example of FIG. 7(d), the evaluation value of the second intermediate teaching point group related to the operation time is 180 for R11, R12 ... R1n, 120 for R21, R22 ... R2n, and 150 for R31, R32 ... R3n. Here, the intermediate teaching point group R21, R22 ... R2n with the smallest amount of interference (small operation time value) has the best evaluation value.

In the first embodiment, one of the conditions for aborting step S109 in FIG. 4 is that the evaluation value becomes 0. In contrast, in the present embodiment, a method of setting an upper limit on the number of times steps S102 to S109 are repeated, or a method of setting an upper limit on the number of times the evaluation value of the intermediate teaching point group P1, P2, ... Pn does not change (almost) continuously, is used. For example, if the operation time cannot be shortened any further, the loop of steps S102 to S109 is exited, and the intermediate teaching point group P1, P2, ... Pn that provides the shortest time is output in step S110 (FIG. 7(e)). Alternatively, in the second embodiment, in step S110, it is not necessary to output the intermediate teaching point group P1, P2, ... Pn in the final moving state as the optimized teaching point. For example, a history of changes in the intermediate teaching point group P1, P2, ... Pn in the repetition of steps S102 to S108 may be recorded, and the one with the highest evaluation may be output.

As described above, this embodiment has the advantage of being able to generate a trajectory that avoids obstacles, observes physical constraints such as torque constraints, and also minimizes the operating time. In particular, the optimization control procedure (Figure 4) can be used in two passes (or multiple passes), in which case a trajectory optimized for each constraint can be obtained by applying different constraint conditions in each pass.

Here, we will provide a more specific example of the configuration of robot arm A, as well as the configuration when robot arm A is applied to a production system.

Figure 10 shows a more specific overall configuration of the robot arm A than the schematic configuration of Figure 2. In Figure 10, the robot arm A (robot device) has an arm body 201 of a vertical multi-joint type with, for example, six axes (joints). Each joint of the arm body 201 can be controlled to a desired position and posture by servo-controlling a servo motor provided at each joint.

A tool such as a hand 202 is attached to the tip (hand tip) of the arm body 201, and this hand 202 can grip a workpiece 203 and perform production work such as assembling or processing the workpiece 203. 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 placed in such a production system (production line) as a production device.

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

In addition, via the network NW, the robot arm A or the robot control device 200 can receive the intermediate teaching points or trajectory data optimized as described above from the trajectory generation device (or the robot simulator: FIG. 1). As a result, based on the intermediate teaching points or trajectory data optimized by the above processing, the robot arm A can be placed in the production system (production line) and operated as a production device to manufacture an article.

The present invention can also be realized by supplying a program that realizes one or more of the functions of the above-mentioned embodiments to a system or device via a network or storage medium, and having one or more processors in the computer of the system or device read and execute the program. It can also be realized by a circuit (e.g., an ASIC) that realizes 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 unit, 2...operation unit, 3...recording unit, 4...display unit.

Claims (28)

1. An information processing method for acquiring a trajectory for operating a robot arm, comprising:
Accepting a user's setting of a first teaching point and a second teaching point at which the robot arm is to be operated;
obtaining at least two intermediate teaching points that define a path from the first teaching point to the second teaching point;
Obtaining a group of intermediate teaching points by displacing at least two of the intermediate teaching points as a group;
Acquire an intermediate trajectory based on the intermediate teaching point group;
obtaining a trajectory for moving the robot arm based on the intermediate trajectory;
23. An information processing method comprising: 2. The information processing method according to claim 1,
obtaining a trajectory for moving the robot arm by displacing at least two of the intermediate teaching points and not displacing the first teaching point and the second teaching point;
23. An information processing method comprising: 3. The information processing method according to claim 1 ,
The at least two intermediate teaching points are obtained using at least one of a potential method, a probabilistic road map (PRM), a rapidly-exploring random tree (RRT), a visibility graph method, a cell division method, and a Voronoi diagram method;
23. An information processing method comprising: 3. The information processing method according to claim 1,
Accepting a user's setting of at least two of the intermediate teaching points;
23. An information processing method comprising: 5. The information processing method according to claim 1 ,
Adding a value to each of at least two of the intermediate teaching points to displace them as a group, thereby obtaining the group of intermediate teaching points.
23. An information processing method comprising: 6. The information processing method according to claim 5,
The displacement is based on correlated random numbers.
23. An information processing method comprising: 7. The information processing method according to claim 6,
At least two of the intermediate teaching points are adjacent to each other, and the displacement is given to the at least two adjacent intermediate teaching points based on the random number.
23. An information processing method comprising: 8. The information processing method according to claim 6,
Correlating the random numbers by assigning positive values to the covariances in a variance-covariance matrix;
23. An information processing method comprising: 9. The information processing method according to claim 1 ,
Obtaining at least two groups of intermediate teaching points by displacing at least two of the intermediate teaching points as a group;
At least two of the intermediate teaching point groups are subjected to curve interpolation to obtain at least two of the intermediate trajectories;
evaluating interference between the robot arm and an object in at least two of the intermediate trajectories obtained by curved line interpolation;
23. An information processing method comprising: 10. The information processing method according to claim 9 ,
evaluating interference between the robot arm and an object in at least two of the intermediate trajectories obtained by curved interpolation; and selecting a predetermined intermediate trajectory from the at least two intermediate trajectories obtained by curved interpolation based on the interference evaluation;
Further modifying the predetermined intermediate trajectory and using the interference between the robot arm and the object as a constraint condition to obtain at least two new intermediate trajectories in which the robot arm and the object do not interfere with each other;
Evaluating items other than interference between the robot arm and an object in the at least two new intermediate trajectories.
23. An information processing method comprising: The information processing method according to claim 10,
Acquire a new group of intermediate teaching points by displacing at least two intermediate teaching points on the predetermined intermediate trajectory;
A new intermediate trajectory is obtained by performing curve interpolation on the new intermediate teaching point group.
If the robot arm interferes with an object when operating the robot arm on the new intermediate trajectory, the new intermediate teaching point group is invalidated;
again, by displacing at least two intermediate teaching points on the predetermined intermediate trajectory, a new group of intermediate teaching points is obtained, and a new intermediate trajectory is obtained by performing curve interpolation on the new group of intermediate teaching points.
23. An information processing method comprising: 12. The information processing method according to claim 10,
As an item other than the interference between the robot arm and an object, the evaluation is based on an operation time for operating the robot arm.
23. An information processing method comprising: 13. The information processing method according to claim 9 ,
Curve-interpolating at least two of the intermediate teaching point groups using at least one of Spline interpolation, B-Spline interpolation, and Bezier curve interpolation;
23. An information processing method comprising: 5. The information processing method according to claim 4 ,
At least two of the intermediate teaching points are obtained by a user's input to a display unit.
23. An information processing method comprising: 15. The information processing method according to claim 14 ,
displaying a virtual environment on a display unit, the virtual environment being a virtual display of a space in which the robot arm operates; and receiving a user's input to the virtual environment to obtain at least two of the intermediate teaching points;
23. An information processing method comprising: 16. The information processing method according to claim 1,
accepting settings of the first teaching point and the second teaching point through a user's input to a display unit;
23. An information processing method comprising: The information processing method according to claim 16 ,
displaying a virtual environment on a display unit, the virtual environment being a virtual display of a space in which the robot arm operates, and accepting settings of the first teaching point and the second teaching point by a user's input into the virtual environment;
23. An information processing method comprising: The information processing method according to any one of claims 1 to 17 ,
If a trajectory for moving the robot arm that satisfies a predetermined condition cannot be acquired, an error is notified.
23. An information processing method comprising: The information processing method according to any one of claims 1 to 18 ,
displaying the acquired trajectory for moving the robot arm on a display unit;
23. An information processing method comprising: The information processing method according to any one of claims 1 to 19 ,
outputting the acquired trajectory for moving the robot arm to a control device that controls the robot arm ;
23. An information processing method comprising: 1. An information processing method for acquiring a trajectory for operating a robot arm, comprising:
Accepting a user's setting of a first teaching point and a second teaching point at which the robot arm is to be operated;
obtaining at least two intermediate teaching points that define a path from the first teaching point to the second teaching point;
Obtaining a group of intermediate teaching points by displacing at least two of the intermediate teaching points as a group;
Acquire an intermediate trajectory based on the intermediate teaching point group;
evaluating the intermediate trajectory;
23. An information processing method comprising: A program causing a computer to execute 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,
Accepting a user's setting of a first teaching point and a second teaching point at which the robot arm is to be operated;
obtaining at least two intermediate teaching points that define a path from the first teaching point to the second teaching point;
Obtaining a group of intermediate teaching points by displacing at least two of the intermediate teaching points as a group;
Acquire an intermediate trajectory based on the intermediate teaching point group;
obtaining a trajectory for moving the robot arm based on the intermediate trajectory;
23. An information processing apparatus comprising: In an information processing device that acquires a trajectory for operating a robot arm,
Accepting a user's setting of a first teaching point and a second teaching point at which the robot arm is to be operated;
obtaining at least two intermediate teaching points that define a path from the first teaching point to the second teaching point;
Obtaining a group of intermediate teaching points by displacing at least two of the intermediate teaching points as a group;
Acquire an intermediate trajectory based on the intermediate teaching point group;
evaluating the intermediate trajectory;
23. An information processing apparatus comprising: A production system that manufactures an article by operating the robot arm along a trajectory acquired using the information processing method according to any one of claims 1 to 21 to assemble a workpiece. A robot system comprising the robot arm, the operation of which is controlled based on a trajectory obtained using the information processing method according to any one of claims 1 to 21 . A method for manufacturing an article, comprising operating the robot arm along a trajectory acquired using the information processing method according to any one of claims 1 to 21 to assemble a workpiece and manufacture the article.

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