JP2019135076A - Locus generation method and device - Google Patents

Abstract

To provide a locus generation method and device capable of satisfying a constraint condition to a robot operation and surely generating an optimal locus.SOLUTION: The locus generation method and device are configured to apply displacement to first intermediate teaching point groups between a start teaching point and a target teaching point of a locus on which a robot arm (A) is operated, and generate second intermediate teaching point groups (S102), then, generate a locus of the robot arm (A) based on the second intermediate teaching point groups (S103), then generate an evaluation value of each second intermediate teaching point group and a locus thereof (S107), then move the first intermediate teaching point group based on the evaluation values (S108), repeat these processes, then determine the first intermediate teaching point group satisfying the prescribed condition, as an intermediate teaching point group used for generating the locus on which the robot arm is operated (S110).SELECTED DRAWING: Figure 4

Description

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

  2. Description of the Related Art Conventionally, a configuration is known in which an industrial robot apparatus is arranged in an industrial product production system (production line) such as an automobile or an electric product to automate operations such as welding and assembly. In this type of production system, a robot apparatus, a workpiece, a workpiece table, a jig, and other peripheral devices are arranged in a state where there is a possibility of mutual interference (contact, collision). In recent years, a simulation using a virtual environment is sometimes used in the design work of the motion trajectory of the arm of the robot apparatus of such a production system.

  When performing an operation simulation of a robot apparatus offline using a simulator apparatus, a 3D (three-dimensional) model such as a robot arm, a work table, a jig, and other peripheral devices is arranged in a virtual environment. For example, in such a simulator device, a trajectory between teaching points of a robot arm created in advance is generated, and a simulation for operating a 3D model of the robot arm in a virtual environment on the trajectory is performed for verification. is there. The operation of the robot arm model can be displayed in a moving image format or the like on the virtual display screen of the display of the simulator device.

  Naturally, the simulation results vary greatly depending on the motion trajectory of the robot arm. If the robot arm trajectory is inadequate, part of the robot arm motion trajectory may be in an inoperable area of the robot arm, the robot arm may interfere with other objects, or useless motion may cause cycle time. May be slow.

  In the conventional method, the operator created the teaching points of the robot arm on the screen on a trial and error basis that satisfies the condition that the robot arm does not enter the inoperable area or the peripheral device does not interfere with the robot arm. . In that case, since the conditions of being movable and not interfering are first considered, there is a case where a robot trajectory that can operate at an optimal operation speed is not necessarily generated, and the cycle time may be delayed. In that case, it was necessary to perform manual work to reexamine the teaching points of the robot arm and re-install it.

  On the other hand, when a robot apparatus is used in a production system (line), since the man-hour for creating teaching points by the process designer is large, the labor cost is also a problem. Therefore, in recent years, a method and an apparatus for improving the efficiency of teaching work of a robot arm using a computer have been proposed in place of direct teaching by a teacher.

  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 for the joint of the robot arm. FIG. 8 schematically shows a method for generating the trajectory of the robot arm in Non-Patent Document 1. In FIG. 8, a robot arm A is a robot arm that is simplified to two degrees of freedom having two rotation axes J1 and J2, and Ob represents an obstacle.

  In FIG. 8, p1, p2,..., P9 indicate positions where the hand of the robot arm A (TCP: Tool Center Point) is moved. Of these positions, p1 indicates the start position (start teaching point) of the motion, and p9 indicates the target position (target teaching point) of the motion. Moreover, p2-p8 has shown the intermediate command value arrange | positioned between a starting position (p1) and a target position (p9). For example, for each control cycle, the postures p1, p2,..., P9 can be instructed in order to the robot arm A, and an operation of reaching p9 from p1 can be performed. In this case, the operation 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 in this case is seven. In FIG. 8, the robot arm and the obstacle Ob interfere with each other at p4 and p5, but a trajectory capable of avoiding interference can be generated by the following method.

  First, the joint angle corresponding to the intermediate command values p2, p3,... P8 is smoothly displaced, and N new intermediate command values ri2, ri3,... Ri8 (i = 1,... N) are generated. Next, by evaluating the intermediate command values ri2, ri3,... Ri8 (i = 1,... N) and repeating the process of displacing the intermediate command values p2, p3,. Optimize the trajectory. In Non-Patent Document 1, as the evaluation value of the intermediate command value, the amount of engagement between the robot arm A and the obstacle Ob and the motor torque used for each joint axis are used. 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 shaft is not overloaded. However, in the technique of Non-Patent Document 1, the number of intermediate command values is a fixed number, and therefore the operation time from the start teaching point (p1) to the target teaching point (p9) is fixed. There is a problem that time cannot be optimized. Further, when the operation time is fixed, it becomes difficult to satisfy the constraint condition of the motor torque used for each joint axis and other constraint conditions. Such constraint conditions related to robot operations that are difficult to achieve include, for example, constraint conditions related to joint axis torque, joint angular velocity, joint angular acceleration and jerk, and hand speed and hand acceleration. That is, the conventional technique described in Non-Patent Document 1 has the following problems. That is, in a region where the number of intermediate command values is too small, there is no guarantee that the constraint condition regarding the robot operation is satisfied. Conversely, in a region where the number of intermediate command values is too large, an optimal trajectory cannot be obtained.

  In view of the above-described problems, an object of the present invention is to reliably generate an optimal trajectory that satisfies a constraint condition related to robot operation.

  In order to solve the above problems, in the present invention, in a trajectory generation method for generating a trajectory for operating a robot arm between a start teaching point and a target teaching point, the control device starts the trajectory starting teaching point for operating the robot arm. And an intermediate teaching point generation step of generating a second intermediate teaching point group by applying a displacement to the first intermediate teaching point group arranged between the target teaching points and the control device comprising: Based on the teaching point group, a trajectory generating step for generating a trajectory for operating the robot arm model simulating the robot arm, and the control device, in the intermediate teaching point generating step, for the first intermediate teaching point group An evaluation step for generating evaluation values for a plurality of trajectories respectively generated by the trajectory generation step from a plurality of second intermediate teaching point groups generated by giving different displacements; The control device moves the first intermediate teaching point group based on the evaluation values for the plurality of trajectories generated in the evaluation step, and generates the intermediate teaching point with respect to the first intermediate teaching point group after the movement. A first intermediate teaching point group satisfying a predetermined condition is determined as an intermediate teaching point group used for generating a trajectory for operating the robot arm. A configuration including an orbit determination step.

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

It is explanatory drawing which showed the functional structure of the track | orbit production | generation apparatus which concerns on embodiment of this invention. It is explanatory drawing which showed the 2 axis | shaft structure in the robot arm which concerns on embodiment of this invention. It is explanatory drawing which showed the teaching point group and track | orbit concerning embodiment of this invention. It is a flowchart figure explaining the optimization process of a track concerning an embodiment of the present invention. (A)-(e) is explanatory drawing which showed the optimization process of the track | orbit based on embodiment of this invention. It is explanatory drawing which showed the teaching point group and track | orbit concerning embodiment of this invention. (A)-(e) is explanatory drawing which showed the optimization process of the track | orbit based on embodiment of this invention. It is explanatory drawing which showed the method of the track control by a prior art. It is the block diagram which showed schematic structure of the control apparatus applicable to embodiment of this invention. It is explanatory drawing which showed the robot apparatus which can be arrange | positioned at the production system which concerns on embodiment of this invention.

  Hereinafter, embodiments for carrying out the present invention will be described with reference to the accompanying drawings. In addition, the structure shown below is an example to the last, For example, it can change suitably for those skilled in the art in the range which does not deviate from the meaning of this invention about a detailed structure. Moreover, the numerical value taken up by this embodiment is a reference numerical value, Comprising: This invention is not limited.

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

  The trajectory generation device of FIG. 1 displays an arithmetic processing unit 1, an operation unit 2 for a teacher to input data, a recording unit 3 for recording an operation program, an operation trajectory of a robot arm, and the like. A display unit 4 is provided. The trajectory generation device can be configured by computer hardware such as a PC (personal computer). Here, a specific configuration example of the arithmetic processing unit 1 is shown in FIG.

  FIG. 9 shows a configuration example of a control device 1000 corresponding to the trajectory generating device, particularly 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 the CPU 1601. It should be noted that the configuration composed of the blocks arranged around the CPU 1601 can be applied in substantially the same manner to, for example, a robot control device (200: FIG. 10) described later.

  The control device 1000 in FIG. 9 includes a CPU 1601 as main control means, a ROM 1602 as a storage device, and a RAM 1603. The ROM 1602 can store a control program for the CPU 1601 and constant information for realizing a control procedure to be described later. 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 in FIG. 9 is the arithmetic 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 interfaced as user interface devices. 1607 is connected. The operation unit 1609 can be constituted by a full keyboard and a pointing device, for example, and constitutes a user interface for an operator who performs trajectory simulation and verification.

  The control apparatus 1000 of FIG. 9 includes a network interface 1605 as communication means for communicating via the network NW. The arithmetic processing unit 1 (FIG. 1) controls the teaching point data and the trajectory data for the actual robot arm A (or its robot controller 200 (FIG. 10)) via the network interface 1605 to the network NW. Information can be sent and received. In this case, the network interface 1605 is configured by a communication standard such as wired communication such as IEEE 802.3 and wireless communication such as IEEE 802.11 or 802.15. However, of course, any other communication standard may be adopted for the network NW.

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

  In the case of the robot control apparatus 200 (FIG. 10), a driver circuit that drives motors, solenoids, and the like (not shown) of each part of the robot arm A in the configuration shown in FIG. In the case of the robot control apparatus 200, the user interface including the display 1608 and the operation unit 1609 may be replaced with an operation terminal (eg, 204 in FIG. 10) such as a teaching pendant.

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

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

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

  Generally, 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 calculation, and when the position of the TCP is given, the TCP position is obtained by inverse kinematic calculation. Can obtain the joint angles θ1, θ2 of the axes J1, J2 when taking the position. Hereinafter, when referring to TCP, it may be simply referred to as “hand”.

  The robot arm A is illustrated as a very simplified configuration for easy understanding, but this configuration is not limited to the embodiment for carrying out the present invention. For example, when a person skilled in the art implements the present invention, as the robot arm A, 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 shown below can be easily spread when using those robot arms.

  Next, the movement operation of the robot arm A will be described. When the robot arm A is moved, the teaching point indicating the starting position of the movement is referred to as a starting teaching point, and the teaching point indicating the target position is referred to as a target teaching point. The teaching point of the robot arm A can be determined by the position, posture or joint axis angle of the hand (TCP). In addition, the position and posture of the hand (TCP) can be converted into the joint angle of each joint axis by inverse kinematic calculation, and conversely, the joint angle of each joint axis can be calculated by (forward) kinematic calculation. It is possible to convert to the position and posture.

  Here, the starting teaching point and the target teaching point are Ps and Pg, respectively. In addition, the teaching point arranged between the starting teaching point and the target teaching point is called an intermediate teaching point and expressed as P1, P2,..., Pn. Further, when P1, P2,..., Pn are collectively referred to, they may be referred to as intermediate teaching point groups.

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

  In this specification, the “operation path” or “path” of the robot arm refers to a trajectory of the operation of the robot arm that does not include a temporal concept such as speed. 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 “(motion) path” of the robot arm. It is clearly distinguished from the above “(operation) path”. In the robot control technology, the “trajectory” may be expressed by a command value data string of joints (angles) of the robot arm for each unit time, for example, every control clock cycle of the robot controller.

  There is a shortest time control as a method for generating a trajectory including speed information for a path of a robot arm generated using the above-described interpolation method. By using the shortest time control, it is possible to obtain a trajectory having the shortest operation time based on the path generated by the interpolation while keeping the physical restrictions of the robot arm. Note that the shortest time control is a technique for obtaining a moving speed that takes the shortest time when passing along a predetermined route, and the route for operating the robot arm depends solely on the intermediate teaching point groups P1, P2,. Other physical constraints of the robot arm may include, for example, a joint torque constraint, a joint angular velocity constraint, a joint angular acceleration constraint, a jerk constraint, a hand speed constraint, and a hand acceleration constraint. In the following, the trajectory generated using the shortest time control is expressed as p1, p2,... Pt as a sequence of robot arm position command values for each control cycle.

  FIG. 3 shows a state in which the robot arm A (3D model simulating: robot arm model) and the obstacle Ob (3D model simulating: obstacle model) are both arranged in the operating environment (virtual environment). ing. 3 shows the start teaching point Ps, the target teaching point Pg, the intermediate teaching point groups P1, P2,... Pn, and the trajectory (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, and the trajectory moves from the start teaching point Ps to the target teaching point Pg. Can not. The purpose of the present embodiment is to set the optimum intermediate teaching point groups P1, P2, and the like so that the robot arm and the obstacle do not interfere (and other constraints are satisfied) between the starting teaching point Ps and the target teaching point Pg. ... to find Pn. The obstacle Ob is not limited to be stationary, and the trajectory optimization calculation is possible even when the obstacle Ob is moving.

  FIG. 4 is a flowchart describing main control procedures of the trajectory generation method according to the present embodiment. The control procedure shown in FIG. 4 can be stored in the ROM 1602 (or the external storage device 1604) as a control program of the CPU 1601. FIG. 5 shows the control procedure of each step in FIG. 4 in the same manner as in FIG. In the following, the trajectory generation and optimization are performed with respect to the 3D model of the robot arm A and the obstacle Ob. However, in order to simplify the description, in the following, the “3D model” is omitted and the control target is the robot arm. 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, the constraint condition, the start teaching point Ps, and the target teaching point Pg in the work space where the robot arm A performs work are input (FIG. 5A). These inputs can be performed by the user via 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 via a virtual display (GUI) on the display unit 4, and the CPU 1601 determines when generating a trajectory by AI processing. May be.

  The model of the robot arm A is design information of parts constituting the robot arm, and includes information such as the moment of inertia, mass, position, posture, and number of axes of each link. The constraint conditions 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 intermediate teaching point group) P1, P2,... Pn as initial values are provided between the starting teaching point Ps and the target teaching point Pg of the robot arm A given in step S100. (FIG. 5B). In the present embodiment, as shown in FIG. 5B, the number of intermediate teaching points to be generated is n, and the intermediate teaching points are P1, P2,.

  As a method for generating intermediate teaching points, it is conceivable to use a route planning algorithm for calculating a route that avoids an obstacle. There are many route generation methods such as a potential method, PRM (Probabilistic RoadMap), and RRT (Rapidly-exploring Random Tree). Further, the present invention is not limited to the above route generation means, and other route generation methods such as a visible graph method, a cell division method, and a Voronoi diagram method may be applied. Alternatively, a process of linearly interpolating between the start teaching point and the target teaching point with a straight line may be used without using the path planning algorithm. Note that the route planning technique as described above calculates a route in which interference avoidance is guaranteed only when the teaching points are connected by a straight line. Therefore, there is a case where interference avoidance is not always guaranteed in a path obtained by interpolating the intermediate teaching point groups P1, P2,.

  For example, as shown in FIG. 5B, the intermediate teaching point groups P1, P2,... Pn (first intermediate teaching point group) correspond to trajectories that interfere with the obstacle Ob, for example. In this embodiment, even if processing is started from such intermediate teaching point groups P1, P2,... Pn (first intermediate teaching point group) as initial values, intermediate teaching points are generated so as to generate an optimal trajectory. The groups P1, P2,... Pn (first intermediate teaching point group) can be moved.

  Alternatively, intermediate teaching point groups P 1, P 2,... Pn (first intermediate teaching point group) as initial values are stored in the virtual environment on the screen by the user via the user interface of the operation unit 2 and the display unit 4. It may be set by performing a plotting operation.

  In step S102 of FIG. 4, a spatial displacement is applied to the intermediate teaching point groups P1, P2,... Pn (first intermediate teaching point group), and new intermediate teaching point groups R1, R2,. 2 intermediate teaching point group) (FIG. 5C: intermediate teaching point generation step). As a method of giving this displacement, for example, a method of adding (adding) a random value as a parameter for giving a spatial displacement to each of the intermediate teaching points can be considered. However, if a method of simply applying a random random number value is employed, the teaching points are arranged in a vibrational manner, and the operation of the robot arm may not be smooth. In general, when the robot arm moves in vibration, the operation time tends to increase. Therefore, it is not desirable to arrange the teaching points in vibration.

  Therefore, a correlation is given between random numbers applied to adjacent intermediate teaching points in order to give a spatial displacement, whereby the trajectory (path) can be smoothed. For example, consider a multivariate normal distribution in which the joint values of one axis of the robot arm in the intermediate teaching point groups P1, P2,... Pn are θ11, θ12,. In this way, by giving a positive value to the covariance in the variance-covariance matrix, it is possible to correlate the joint values of adjacent intermediate teaching points and generate smooth random numbers along the path. It becomes possible.

  In step S103, the intermediate teaching point groups R1, R2,... Rn are interpolated with a curve, and a trajectory is generated using the shortest time control (trajectory generating step). Here, for the purpose of avoiding the stationary obstacle, it is sufficient to evaluate the interference of the robot arm A on the “path” interpolated by the curve, but when considering the moving obstacle, In this embodiment, “trajectory” is considered because the axis must also be taken into consideration.

  In step S104, it is determined whether the generated trajectory satisfies the constraint. If the trajectory does not satisfy the constraint, the process returns to S102, and if the trajectory satisfies the constraint, the process proceeds to S105. The constraint condition determined in step S104 is a constraint that cannot be constrained by the shortest time control technique used in step S103. The restriction condition determined in step S104 is that the mechanism of the robot arm A does not protrude beyond the movable range at least on the trajectory generated in step S103. Further, the constraint conditions determined in step S104 may be other conditions such as a robot arm 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. In step S104, a determination can be made to generate a trajectory that satisfies any one or more of these constraints.

  In step S105, the intermediate teaching point groups R1, R2,... Rn and the trajectory generated based on them are stored. The intermediate teaching point group to be stored is expressed as Ri1, Ri2,... Rin in order to distinguish it from other stored intermediate teaching point groups. i is the order of saving.

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

  In step S107, an evaluation value is given to the stored N intermediate teaching 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 intermediate teaching point groups P1, P2,... Pn (first intermediate teaching point group) so as to generate an optimal trajectory.

  Further, this evaluation value is generated, for example, by evaluating a trajectory corresponding to the intermediate teaching point group Ri1, Ri2,... Rin (i = 1 to N). For example, in this embodiment, in order to obtain a trajectory that avoids interference with the obstacle Ob, the robot arm and the obstacle use the interference amount as an evaluation value. For example, the amount of interference may be the interference time in which the robot arm and the obstacle occupy the same space, the amount of interference or the interference distance (or the overlapping volume of the two sweep spaces). In the present embodiment, for example, an interference time is adopted as an interference amount and is set as an evaluation value.

  In the example of FIG. 5D, the evaluation values generated by the interference amount (interference time or amount of interference) are shown for the three intermediate teaching point groups. This evaluation value is 10 for the second intermediate teaching point group R11, R12... R1n, 30 for R21, R22... R2n, and 50 for R31, R32. Here, the best evaluation value is the intermediate teaching point group R11, R12... R1n having a small amount of interference (close to 0).

  For the purpose other than avoiding the interference of the obstacle Ob, other methods may be adopted for evaluating the trajectory corresponding to the intermediate teaching point groups Ri1, Ri2,... Rin (i = 1 to N).

  In step S108, the intermediate teaching point groups P1, P2,... Pn are moved based on the evaluation values of the N intermediate teaching point groups Ri1, Ri2,... Rin (i = 1 to N) (FIG. 5E). ). As one of the moving methods, for example, the intermediate teaching point is set to the intermediate teaching point group having the lowest (good) evaluation value among the intermediate teaching point groups Ri1, Ri2,... Rin (i = 1 to N). A method of moving the groups P1, P2,. In the example of FIG. 5E, intermediate teaching point groups P1, P2,... Pn (in the first intermediate teaching point group) at the positions of the intermediate teaching point groups R11, R12. Is moving.

  Also, the weights of the N intermediate teaching point groups Ri1, Ri2,... Rin (i = 1 to N) with the reciprocal of the evaluation value of the intermediate teaching point groups Ri1, Ri2,... Rin (i = 1 to N) as weights. A method of moving the intermediate teaching point groups P1, P2,.

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

  Or you may define the upper limit frequency | count which performs the loop of step S102-step S109. In that case, if the upper limit number has been reached in step S109, it gives up more trials and proceeds to step S110. Alternatively, error processing such as outputting an appropriate error message on the display unit 4 may be performed.

  The abort 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. It is a condition that a predetermined condition is satisfied. For example, an object of the present 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 intermediate teaching point group P1, P2,... Pn (first intermediate teaching point group) after the movement is 0 (interference amount: interference time and interference amount is 0). As a result, it is possible to generate an optimal trajectory that satisfies the constraints related to the robot motion (trajectory determination step).

  In step S110, intermediate teaching point groups P1, P2,... Pn are output as optimized teaching points. This output is obtained by operating the 3D model (robot arm model) of the robot arm A in the trajectory generated by the optimized intermediate teaching point groups P1, P2,... Pn in the virtual display of the display unit 4, for example. Do. Alternatively, step S110 is a process of outputting intermediate teaching point groups P1, P2,... Pn optimized for the actual robot arm A or its robot controller (200: FIG. 10) or trajectory data generated thereby. There may be.

  In this embodiment, since the purpose is to avoid interference, when the process reaches step S110, as shown in FIG. 6, trajectories (p1, p2,...) Generated based on the intermediate teaching point groups P1, P2,. At pt), the robot arm does not interfere with the interference.

  According to the present embodiment, a plurality of intermediate teaching point groups Ri1, Ri2,... Rin (i = 1 to N) are generated, and based on the result of evaluating the trajectory defined thereby, intermediate teaching point groups P1, P2 ... Pn is moved. Conditions for physical constraints such as joint torque constraints are used for trajectory evaluation, and conditions for achieving obstacle avoidance are used as escape conditions for the process of moving the intermediate teaching point groups P1, P2,. With this configuration, according to the present embodiment, it is possible to avoid an obstacle and generate a smooth curved track that satisfies physical constraints such as joint torque constraints.

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

  The control procedure of the trajectory generation method of the present embodiment is equivalent to the flowchart of FIG. 4 of the first embodiment, but in the second embodiment, the initial teachings of the intermediate teaching point groups P1, P2,. Values, trajectory constraint methods, trajectory evaluation methods, and censoring conditions are different. FIG. 7 shows how the trajectory (first intermediate teaching point) is optimized in the present embodiment. FIG. 7 shows the processing of each step of FIG. 4 in the present embodiment in the same format as FIG.

  In the first embodiment, intermediate teaching point groups P1, P2,... Pn are generated between the starting teaching point Ps and the target teaching point Pg (FIG. 7A) by the path planning technique in step S101 of FIG. An example is shown. On the other hand, in the present embodiment, the intermediate teaching point groups P1, P2,... Pn (FIG. 6 and FIG. 7B) output through the optimization process of the first embodiment in step S101 of FIG. .

  The intermediate teaching point groups P1, P2,..., Pn that have already been output through the optimization processing of the first embodiment are set as initial values, thereby performing optimization that shortens the operation time of a trajectory that has already avoided an obstacle. it can. As described above, the optimization control procedure of the present invention (FIG. 4) can be used in two passes (or more than one pass), and in this case, by applying different constraints on each pass, Trajectories optimized for the constraints can be acquired.

  In the first embodiment, a new intermediate teaching point group R1, R2,... Rn (second intermediate teaching point group) is generated (FIG. 5C), and in step S104 of FIG. When determining whether the trajectory of the point cloud satisfies the constraint, it is determined whether or not the robot arm A is within the movable range. In this embodiment, a new intermediate teaching point group R1, R2,... Rn (second intermediate teaching point group) is generated (FIG. 7C), and in addition to the determination as to whether or not it is within the movable range, the robot arm It is determined whether A interferes with the obstacle Ob. If there is an interference with the obstacle, the intermediate teaching point groups R1, R2,... Rn are invalidated, and the process returns to step S102.

  In the first embodiment, the trajectory is evaluated in step S107 of FIG. 4 using the interference time or the amount of penetration 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. 7D). Accordingly, it is possible to generate intermediate teaching point groups P1, P2,. In the example of FIG. 7D, 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, 150 for R31, R32. It has become. Here, the intermediate evaluation point groups R21, R22,... R2n having the smallest evaluation value (small operation time value) have the best evaluation values.

  In the first embodiment, it is considered that the evaluation value becomes 0 as one of the termination conditions in step S109 in FIG. On the other hand, in the present embodiment, a method of setting the upper limit number of times for repetition from step S102 to step S109, or the number of times the evaluation values of the intermediate teaching point groups P1, P2,. A method of setting an upper limit is used. For example, if the operation time is not shortened further, the loop of step S102 to step S109 is exited, and intermediate teaching point groups P1, P2,... Pn that can obtain the shortest time are output in step S110 (FIG. 7 (e) ). Alternatively, in the second embodiment, it is not always necessary to output the intermediate teaching point groups P1, P2,... Pn in the final moving state as the optimized teaching points in step S110. For example, the history of changes in the intermediate teaching point groups P1, P2,... Pn in the repetition from step S102 to step S108 may be taken, and the highest evaluation may be output.

  As described above, according to the present embodiment, there is an effect that it is possible to generate a trajectory having the shortest operation time while avoiding obstacles and keeping physical constraints such as torque constraints. In particular, the optimization control procedure (FIG. 4) can be used in two paths (or more than one path), in which case optimization is performed for each constraint condition by applying different constraint conditions in each path. The acquired trajectory can be acquired.

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

  FIG. 10 shows an entire configuration of the robot arm A more concrete than the schematic configuration of FIG. In FIG. 10, a robot arm A (robot device) includes, for example, a six-axis (joint) vertical articulated arm body 201. Each joint of the arm body 201 can be controlled to a desired position and orientation by servo-controlling a servo motor provided in each joint.

  A tool such as a hand 202 is attached to the tip (hand) of the arm main body 201, and the hand 202 can be used to perform a production operation such as gripping the workpiece 203 and assembling or processing the workpiece 203. it 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 apparatus in such a production system (production line).

  The operation of the arm main 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 (teached) 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, an operation for moving a specific part of the robot arm A (for example, TCP: a tool mounting surface at the tip of the arm) along a desired locus can be programmed.

  Further, the robot arm A or the robot controller 200 receives the intermediate teaching point or the trajectory data optimized as described above from the trajectory generator (or the robot simulator: FIG. 1) via the network NW. be able to. Thereby, based on the intermediate teaching point or trajectory data optimized by the above processing, the robot arm A can be arranged in the production system (production line) and operated as a production apparatus to manufacture an article.

  The present invention supplies a program that realizes one or more functions of the above-described embodiments to a system or apparatus via a network or a storage medium, and one or more processors in a computer of the system or apparatus read and execute the program. It can also be realized by processing. It can also be realized by a circuit (for example, 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 (14)

In a trajectory generation method for generating a trajectory for operating a robot arm between a start teaching point and a target teaching point,
Intermediate teaching in which a control device applies displacement to a first intermediate teaching point group arranged between a starting teaching point and a target teaching point of a trajectory for operating a robot arm, and generates a second intermediate teaching point group A point generation process;
A trajectory generating step in which the control device generates a trajectory for operating a robot arm model simulating the robot arm based on a second intermediate teaching point group;
In the intermediate teaching point generation step, the control device generates each of the second intermediate teaching point groups generated by giving different displacements to the first intermediate teaching point group by the trajectory generation step. An evaluation process for generating evaluation values for a plurality of trajectories;
The control device moves the first intermediate teaching point group based on the evaluation values for the plurality of trajectories generated in the evaluation step, and the intermediate teaching point with respect to the first intermediate teaching point group after the movement. The generation step, the trajectory generation step, and the evaluation step are repeatedly executed, and a first intermediate teaching point group that satisfies a predetermined condition is determined as an intermediate teaching point group used for generation of a trajectory for operating the robot arm. A trajectory determination method comprising: a trajectory determination step.   2. The trajectory generation method according to claim 1, wherein, in the intermediate teaching point generation step, the robot arm model generates a plurality of intermediate teaching points that can avoid an obstacle model arranged in a space in which the robot arm model operates. Orbit generation method.   3. The trajectory generation method according to claim 1, wherein in the intermediate teaching point generation step, parameters that are included in the second intermediate teaching point group and correlate to adjacent intermediate teaching points are applied, and A trajectory generation method for smoothing a path connecting intermediate teaching points.   4. The trajectory generation method according to claim 1, wherein, in the trajectory generation step, a trajectory in which an operation time for operating the robot arm model is shortened based on the second intermediate teaching point group. 5. The trajectory generation method to generate.   5. The trajectory generation method according to claim 1, wherein in the trajectory to be evaluated in the evaluation step, the robot arm model and an obstacle model disposed in a space in which the robot arm model operates A trajectory generation method for generating the evaluation value based on the amount of interference between.   6. The trajectory generation method according to claim 5, wherein the interference amount is an interference time or an interference distance in which the robot arm model and the obstacle model occupy the same space.   The trajectory generation method according to claim 1, wherein in the evaluation step, the evaluation value is generated based on an operation time when the robot arm model is operated in the trajectory to be evaluated. Method.   The trajectory generation method according to any one of claims 1 to 7, wherein an evaluation value of a trajectory for operating the robot arm model generated based on the first intermediate teaching point group after movement in the trajectory determination step. Is a trajectory generation method for determining the first intermediate teaching point group as an intermediate teaching point group used for generating a trajectory for operating the robot arm.   9. The trajectory generation method according to claim 1, wherein in the trajectory generation step, based on the second intermediate teaching point group, a joint torque constraint, a joint angular velocity constraint, and a joint angular acceleration related to the robot arm. A trajectory generation method for generating a trajectory that satisfies any one or more of constraints, jerk constraints, hand speed constraints, or hand acceleration constraints.   The control program which makes the said control apparatus perform each process of the orbital generation method of any one of Claim 1 to 9.   A computer-readable recording medium storing the control program according to claim 10. In a trajectory generating device for generating a trajectory for operating a robot arm between a starting teaching point and a target teaching point,
An intermediate teaching point generation step of generating a second intermediate teaching point group by applying displacement to the first intermediate teaching point group arranged between the starting teaching point and the target teaching point of the trajectory for operating the robot arm; ,
A trajectory generating step for generating a trajectory for operating a robot arm model simulating the robot arm based on a second intermediate teaching point group;
In the intermediate teaching point generation step, evaluation of a plurality of trajectories respectively generated by the trajectory generation step from a plurality of second intermediate teaching point groups generated by giving different displacements to the first intermediate teaching point group An evaluation process for generating values;
Moving the first intermediate teaching point group based on the evaluation values for the plurality of trajectories generated in the evaluation step, the intermediate teaching point generating step with respect to the first intermediate teaching point group after the movement; A trajectory determination step of repeatedly executing the trajectory generation step and the evaluation step and determining a first intermediate teaching point group satisfying a predetermined condition as an intermediate teaching point group used for generating a trajectory for operating the robot arm; ,
A trajectory generation device provided with a control device for executing.   A production system for manufacturing an article by assembling a workpiece by operating the robot arm on a trajectory generated by using the trajectory generating method according to claim 1.   An article manufacturing method for manufacturing an article by assembling a workpiece by operating the robot arm on a trajectory generated using the trajectory generating method according to claim 1.

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