JP6821987B2 - Robot system, robot system control method, program - Google Patents

Description

The present invention relates to a robot system that causes a robot to perform a predetermined work, a control method of the robot system, and a program.

Conventionally, in factories and the like, work spaces are partitioned by fences and the like, and robots and humans individually perform work in each work space. In recent years, instead of a physical fence or the like, a light curtain, a virtual fence, or the like has been used to virtually divide the work space. Since there is no partition in the adjacent work space, the robot is provided with a safety device that operates under predetermined conditions in order to ensure safety. Further, in factories and the like, a robot system in which a robot assists a human movement and the human and the robot perform one task has also been proposed (see, for example, Patent Document 1).

Japanese Unexamined Patent Publication No. 2004-017256

By the way, robots or robots and humans are required to work individually in the same work space. In this case, on the premise that both the robot and the human work with a fixed movement, it is possible to work individually in the same work space without interfering with each other's movements. However, since humans do not always perform routine movements, it has become difficult to actually make robots and humans work in the same work space.

The present invention has been made in view of the above points, and provides a robot system, a robot system control method, and a program capable of allowing a controlled object and a non-controlled object to work in the same space while ensuring safety. The purpose is to do.

The robot system of the present invention is a robot system that causes a controlled object to perform a predetermined operation in the same space as the non-controlled object, and is a recognition that outputs recognition data for recognizing the non-controlled object in three dimensions in chronological order. The control unit includes a unit, a prediction unit that predicts the movement of the non-controlled object from changes over time in recognition data, and a control unit that controls the movement of the controlled object based on the prediction result of the prediction unit. From the first mode in which the control target is moved toward the first target to perform the first operation, the control target is avoided while avoiding the non-control target based on the prediction result of the prediction unit. Is characterized in that the movement of the controlled object is orbitally corrected so as to move toward the second target and change to the second mode in which the second operation is performed .

According to the present invention, since the movement of the controlled object is controlled based on the prediction result of the motion of the non-controlled object, the controlled object and the non-controlled object perform different operations in the same space. However, the non-controlled object and the controlled object do not interfere with each other. Therefore, it is possible to have the controlled object and the non-controlled object work at the same time in the same space while ensuring safety.

It is a schematic diagram of the production line of this embodiment. It is explanatory drawing of the control process of the robot system of the comparative example. It is explanatory drawing of the generation process of the distance image of this embodiment. It is explanatory drawing of the trajectory correction processing of the robot arm of this embodiment. It is explanatory drawing of the learning process of this embodiment. It is a flowchart which shows the control method of the robot system of this embodiment. It is a schematic diagram of another production line of this embodiment.

Hereinafter, the robot system of the present embodiment will be described with reference to the attached drawings. FIG. 1 is a schematic view of the production line of the present embodiment. FIG. 2 is an explanatory diagram of the control process of the robot system of the comparative example. Although the robot system of the production line will be described in this embodiment, it can also be applied to a robot working outside the production line. Further, in the following description, an example in which the robot and the human perform the work in the same space will be described, but the robots may perform the work in the same space.

As shown in FIG. 1, a robot space 10 and a worker space 20 are provided on the upstream side of the production line with a work table 30 interposed therebetween, and a robot arm R of the robot space 10 and a human H of the worker space 20 are provided. The work space on the work table 30 is shared by. The robot arm R sorts parts 37 from the box 35 in the robot space 10 by type and conveys them to the box 31 on the work table 30, and the human H assembles the parts 37 in the box 31 on the conveyor 21. In this way, since the robot arm R and the human H are collaborating in the same work space, it is necessary to ensure safety so that the robot arm R and the human H do not come into contact with each other.

Normally, as shown in FIG. 2A, for example, when the robot arm R and the human H approach a certain distance, the robot arm R is urgently stopped to ensure safety, but the robot arm R is returned from the stopped state. It takes time to make it work, and productivity decreases. Therefore, the human H is required to perform regular movements so as to always maintain a distance from the robot arm R. On the other hand, as shown in FIG. 2B, even if the robot arm R and the human H approach each other to a certain distance, they do not come into contact unless the movement loci of the robot arm R and the human H intersect. Even so, the robot arm R is stopped.

Therefore, in the robot system 1 of the present embodiment, the movement of the human H, which is not the control target of the system, is predicted, and the robot arm R, which is the control target, avoids contact with the human H. At this time, since the movement of the robot arm R is corrected to avoid the movement of the human H, the robot arm R does not stop even if the robot arm R and the human H come close to each other. Therefore, since it is possible to avoid contact with the human H without stopping the work of the robot arm R, it is possible to ensure safety without deteriorating productivity.

Returning to FIG. 1, in the robot system 1, the robot arm R is attached to the upper center 12 of the housing frame 11, and the imaging device (recognition unit) 15 is attached to the portal frame 14 on the housing frame 11. The robot arm R is an articulated robot that positions the hand portion at the tip at an arbitrary position in a three-dimensional space, and the movement of the robot arm R is controlled by a robot controller (control unit) 16. The image pickup device 15 recognizes the human H operating in the work space on the work table 30 in three dimensions, and the distance image (recognition data) is output from the image pickup device 15 to the computer (prediction unit) 17 in real time. ..

Then, the computer 17 predicts the movement of the human H from the change over time of the distance image, and the robot controller 16 maintains the movement in the direction of avoiding the human H based on the prediction result output from the computer 17. The movement of R has been corrected. In this way, the robot system 1 makes it possible for the robot arm R to perform a predetermined operation in the same space as the human H. As the robot arm R, for example, a vertical articulated robot or a horizontal articulated robot can be used. As the image pickup device 15, for example, a 3D scanner, a stereo camera, or a monocular camera can be used. As the robot controller 16, a personal computer or a microcontroller can be used.

Further, various processes of the image pickup device 15, the computer 17, and the robot controller 16 of the robot system 1 are executed by the processor and the memory. The memory is composed of one or a plurality of storage media such as ROM (Read Only Memory) and RAM (Random Access Memory) depending on the intended use. Further, the memory stores a program that executes various processes of each part of the robot system 1.

Hereinafter, the details of the robot system will be described with reference to FIGS. 3 to 5. FIG. 3 is an explanatory diagram of the distance image generation process of the present embodiment. FIG. 4 is an explanatory diagram of the trajectory correction process of the robot arm of the present embodiment. FIG. 5 is an explanatory diagram of the learning process of the present embodiment.

As shown in FIG. 3A, when the work space on the work table 30 is imaged by the image pickup device 15, a distance image including distance information from the image pickup device 15 to the uncontrolled human H and the part 37 is generated. .. The image pickup device 15 continuously generates a distance image, and the distance image is output from the image pickup device 15 to the computer 17 (see FIG. 1) in chronological order. In this way, the change over time in the work space on the work table 30 is output as the distance z of the coordinates (x, y) at time t. In the present embodiment, the recognition data that recognizes the imaging target in three dimensions is output as a distance image, but it may be output as distance information for each coordinate instead of the image format.

Next, as shown in FIG. 3B, in the computer 17 (see FIG. 1), the point cloud data of the distance image is grouped by the work table 30, the human H, and the parts 37. In this case, the difference between the distance images before and after the time is taken, and the point cloud data indicating the difference between the distance images is grouped with reference to the upper surface of the work table 30. The work table 30 itself is set to group 1, the object on the work table 30 is set to group 2 showing parts 37, and the object in the space above the work table 30 is set to group 3 showing human H (only the hand is shown in FIG. 3). .. In this way, the part 37 and the human H are distinguished by the height from the upper surface of the work table 30.

For example, between time t1 and time t2, a newly appearing stationary object on the upper surface of the work table 30 is set in group 2 indicating the part 37. Further, between the time t2 and the time t3, the newly appearing object in the space above the work table 30 is set in the group 3 indicating the human H. The robot arm R is also located in the space above the work table 30, but since the computer 17 grasps the movement of the robot arm R, it is possible to distinguish between the human H and the robot arm R. It is also possible to set the point cloud data of the robot arm R to the group 4.

As shown in FIG. 4A, when the human H is recognized by grouping, the movement of the human H is predicted by the computer 17 (see FIG. 1) from the change over time of the distance image. In this case, the point of interest P _R at the tip portion of the robot arm R is set, the point of interest P _H from the notice point P _R of the robot arm R in distance is closest point data of the point cloud data showing the person H is Set. Then, the moving direction and the moving speed of the point of interest P _H of the human H is calculated from the temporal change of the distance image. Incidentally, the moving direction and the moving speed of the point of interest P _R of the robot arm R, which is a control object is grasped by the computer 17.

Further, in the computer 17, the first prediction space S _R is determined around the target point P _R in accordance with the moving direction and the moving speed of the point of interest P _R of the robot arm R, the movement of the target point P _H of the human H second prediction space S _H is determined around the target point P _H depending on the direction and the moving speed. The first prediction space S _R anticipates range point of interest P _R of the robot arm R can move in a unit time, can move the point of interest P _H of the second predicted space S _H is a human H unit time Predicting the range. In this way, the movement of the robot arm R and the movement of the human H are constantly monitored in the work space.

The first prediction space S _R, has directivity in the direction of movement of the target point P _R of the robot arm R, it has a size corresponding to the moving speed of the target point P _R of the robot arm R. Second prediction space S _H has a directivity in the moving direction of the target point P _H of the human H, it has a size corresponding to the moving speed of the target point P _H of the human H. When the robot arm R and the human H approaches, second prediction around the attention point P _H of the first predicted space S _R human H around the attention point P _R of the robot arm R by the robot controller 16 movement of the robot arm R so as not to overlap the space S _H is on track.

In fact, as shown in FIG. 4B, the target point of the robot arm R and the human H P _R, the movement of the robot arm R by the relative velocity of P _H is on track. In this case, target point P _R of the robot arm R and the human _H, prompts the relative speed on the straight line L connecting the shortest distance to P _H, avoidance operation of the robot arm R is controlled by the relative speed on the straight line L. Therefore, when the moving direction of the robot arm R and the human H is long oppositely on the straight line L, attention point P _R of the robot arm R and the human H and the relative speed on the straight line L is _increased, far is P _H Also avoidance action is performed. On the other hand, avoiding if completely different direction the moving direction of the robot arm R and the human H, attention point P _R of the robot arm R and the human H and the relative speed on the straight line L becomes _small, even if nearly P _H No action is taken.

Then, the current target point P _R, the shortest distance between the relative velocity and the two points between P _H, the contact between the robot arm R and the human H are predicted, first, second prediction space S _R , avoidance operation of the robot arm R is performed is determined that S _H overlaps. On the other hand, the current target point P _R, the shortest distance between the two points and the relative speed between P _H, when it is predicted that there is no contact between the robot arm R and the human H, first, second prediction space S _R, it is determined that S _H do not overlap not performed avoidance operation of the robot arm R. That is, first the second prediction space S _R, S _H, the robot arm R and the human target point H P _R, is a space that is virtually recognized in the working space by the relative velocity of P _H ..

In this way, since the movement of the robot arm R is corrected by predicting the contact between the robot arm R and the human H, the contact between the robot arm R and the human H is suppressed. In particular, since the distance is nearest point from the target point P _R of the tip portion of the robot arm R to human H is set to the attention point P _H of the human H, contact closest to location of the robot arm R and the human H Can be avoided and safety can be ensured. The first, second prediction space S _R, because of its size that S _H is in accordance with the directivity and moving speed corresponding to the moving direction, suitably course correction in accordance with the movement of the robot arm R and the human H Is done.

That is, even if the distance between the robot arm R and the human H is close, if the moving destinations of the robot arm R and the human H are different and there is no possibility of contact, the avoidance operation by the robot arm R is not performed. Therefore, since the work of the robot arm R and the human H does not interfere with each other, the productivity does not decrease. Further, even if the robot arm R and the human H are close to each other and there is a possibility of contact between the robot arm R and the human H, the robot arm R continues to move while avoiding the human H, so that the robot arm R continues to move. Productivity can be maintained by eliminating the return operation after the stop.

Further, in the avoidance motion of the robot arm R, the trajectory of the robot arm R is corrected in the direction of connecting to another motion while avoiding the human H. For example, the robot arm R changes the destination from the current target to another target. Since the trajectory is corrected so that the avoidance motion by the robot arm R becomes a partial motion of another work, the motion of the avoidance motion is not wasted, and the productivity can be further improved.

Further, as shown in FIG. 5, the robot system 1 (see FIG. 1) may be provided with a learning function such as a random forest. In this case, the computer 17 (see FIG. 1) may learn the behavior pattern of the human H by accumulating the distance images and predict the movement of the human H. For example, when a distance image is input from the imaging device 15 (see FIG. 1), the point cloud data of the distance image is distributed to three-dimensional box cells, and the voxels including the point cloud data of human H are marked. These voxels are converted into one-dimensional data and stored in the database DB for each behavior pattern of human H.

Then, the movement of the human H is predicted depending on whether or not the one-dimensional data showing the current movement of the human H is similar to the behavior pattern accumulated in the database DB. This makes it possible to predict the work of the human H at an early stage and switch the work of the robot arm R before the robot arm R and the human H approach each other. For example, the target of the robot arm R can be switched from the target that the human H wants to access. In this way, by predicting the target of the human H at an early stage and switching the target of the robot arm R, the work of the human H and the robot arm R does not interfere with each other, and the productivity can be further improved.

Next, a control method of the robot system will be described with reference to FIG. FIG. 6 is a flowchart showing a control method of the robot system of the present embodiment. In the description of FIG. 6, the reference numerals of FIGS. 1 and 3 will be used as appropriate.

As shown in FIG. 6, the image pickup device 15 first images the work space on the work table 30 to generate a distance image, and the image pickup device 15 outputs the distance image to the computer 17 (step S01). Next, the computer 17 groups the point cloud data of the distance image (step S02). In this case, the objects on the work table 30 are grouped as parts 37, and the objects in the space above the work table 30 are grouped as human H with respect to the upper surface of the work table 30. The human H, which is an uncontrolled object, is recognized for the first time by grouping, but the robot arm R, which is a controlled object, is always recognized.

Next, attention point _{P H} of the point of interest _{P R} and human H of the robot arm R is set by the computer 17 (step S03). In this case, set the point of interest P _R is the tip portion of the robot arm R, the point of interest P _H of the human H is set to the closest point distance from the attention point P _R. Next, the moving direction and the moving speed of the point of interest P _H of the human H is calculated from the temporal change of the distance image by the computer 17 (step S04). Note that the target point P _R of the robot arm R of the controlled object, the moving direction and the moving speed is always grasped by the computer 17.

Next, the relative velocity of the target point P _H of the point of interest P _R and human H is uncontrolled robot arm R to be controlled is calculated (step S05). In this case, since the relative speed on the straight line L connecting the target point of the robot arm R and the human H P _R, the P _H at the shortest distance is determined, the point of interest P _R, the straight line L is the relative moving direction of P _H The upper relative velocity becomes smaller. Next, it is determined whether or not the robot arm R and the human H come into contact with each other (step S06). Current target point P _R, the contact between the robot arm R and a human H at a relative speed and the shortest distance between P _H is predicted (Yes in step S06), the motion of the robot arm R is course correction (step S07).

On the other hand, the current target point P _R, when it is predicted that there is no contact between the robot arm R and a human H at a relative speed and the shortest distance between P _H (No in step S06), the motion of the robot arm R is on track The operation is maintained without being done. Next, it is determined whether or not the robot system 1 is stopped (step S08), and the processes from step S01 to step S07 are repeated until the robot system 1 is stopped.

As described above, in the robot system 1 of the present embodiment, since the movement of the robot arm R is corrected based on the prediction result of the movement of the human H, the robot arm R, the human H, and the human H are in the same space. There is no interference even when performing separate operations. Further, since the movement of the robot arm R is corrected in the direction of avoiding the human H and the movement is maintained, the robot arm R does not stop during the operation. Therefore, the robot arm R and the human H can be made to work at the same time in the same work space without lowering the productivity in a state where the safety is ensured.

The present invention is not limited to the above embodiment, and can be modified in various ways. In the above embodiment, the size and shape shown in the attached drawings are not limited to this, and can be appropriately changed within the range in which the effects of the present invention are exhibited. In addition, it can be appropriately modified and implemented as long as it does not deviate from the scope of the object of the present invention.

For example, in the above embodiment, the robot system 1 is applied to the upstream side of the production line, but the configuration is not limited to this. As shown in FIG. 7, the robot system 1 may be applied to another production line in which the robot arm R and the human H are alternately arranged. Even with such a configuration, it is possible to make the adjacent robot arms R and the human H collaborate in the same work space.

Further, in the above embodiment, the movement of the human H is predicted from the change over time of the distance image, and the robot arm R is such that the robot controller 16 maintains the movement in the direction of avoiding the human H based on the prediction result. Although it was configured to correct the trajectory of the movement, it is not limited to this configuration. The robot controller 16 may be configured to control the movement of the robot arm R based on the prediction result. For example, the robot arm R may be stopped when the robot arm R approaches the human H.

Further, in the above embodiment, the robot system 1 is applied to a configuration in which the robot arm R and the human H collaborate, but the configuration is not limited to the collaborative work. The robot system 1 can be applied to a configuration in which the robot arm R and the human H operate in the same space, and may be applied to a configuration in which the robot arm R and the human H perform unrelated work in the same space.

Further, in the above embodiment, the robot system 1 has a configuration in which the human H is not controlled, but the robot system 1 is not limited to this configuration. The robot system 1 may, for example, make a robot belonging to another system an uncontrolled target.

Further, in the above embodiment, the control target is an articulated robot arm R, but the control target is not limited to this configuration. The control target may be a humanoid robot, an autonomous flight robot, or an autonomous traveling robot, as long as it can be controlled by the robot system 1 to perform a predetermined operation.

Further, in the above embodiment, the robot system 1 has one robot arm R as a control target and one human H as a non-control target, but is not limited to this configuration. The robot system 1 may have a plurality of controlled objects and a plurality of non-controlled objects work in the same space.

Further, in the above embodiment, the trajectory of the robot arm R is corrected in a direction that connects the movement of the robot arm R to another movement while avoiding the human H. However, the movement of the robot arm R is corrected in the direction of avoiding the human H. For example, it does not have to be connected to another operation.

Further, in the above-described embodiment, to set the front end portion of the robot arm R to the attention point P _R, was set from the point of interest P _R distance closest point to the target point P _H of the human H, this structure Not limited to. For example, attention points may be set for each joint of the robot arm R, and attention points may be set for the robot arm R and the human H so that the distance from the attention points of each of these joints to the human H is the shortest. ..

The feature points in the above-described embodiment are summarized below.
The robot system described in the above embodiment is a robot system that causes a controlled object to perform a predetermined operation in the same space as the non-controlled object, and recognizes recognition data in three dimensions of the non-controlled object in chronological order. It includes a recognition unit that outputs, a prediction unit that predicts the movement of the non-control target from changes over time of recognition data, and a control unit that controls the movement of the control target based on the prediction result of the prediction unit. It is characterized by that.

The robot system control method described in the above embodiment is a robot system control method in which a control target performs a predetermined operation in the same space as the non-control target, and recognition data for recognizing the non-control target in three dimensions. Has a step of outputting the motion of the non-controlled object in a time series, a step of predicting the movement of the non-controlled object from a change over time of the recognition data, and a step of controlling the motion of the controlled object based on the prediction result. It is a feature.

According to these configurations, the movement of the controlled object is controlled based on the prediction result of the motion of the uncontrolled object. Therefore, the controlled object and the uncontrolled object may perform different operations in the same space. However, the non-controlled object and the controlled object do not interfere with each other. Therefore, it is possible to have the controlled object and the non-controlled object work at the same time in the same space while ensuring safety.

Further, in the robot system described in the above embodiment, the control unit activates and corrects the movement of the control target based on the prediction result of the prediction unit so as to maintain the operation in the direction of avoiding the non-control target. According to this configuration, the movement of the controlled object is corrected based on the prediction result of the movement of the uncontrolled object, so that the controlled object and the non-controlled object may perform different operations in the same space. However, the non-controlled object and the controlled object do not interfere with each other. Further, since the movement of the controlled object is corrected in the direction of avoiding the non-controlled object and the operation is maintained, the controlled object does not stop during the operation. Therefore, it is possible to work the controlled object and the non-controlled object at the same time in the same space without lowering the productivity while ensuring the safety.

Further, in the robot system described in the above embodiment, the control unit corrects the trajectory of the control target in a direction leading to another operation while avoiding the non-control target based on the prediction result of the prediction unit. According to this configuration, since the trajectory is corrected so that the avoidance motion by the controlled object becomes a partial motion of another work, the motion of the avoidance motion is not wasted and the productivity can be further improved. ..

Further, in the robot system described in the above embodiment, the prediction unit determines a first prediction space according to the movement direction and movement speed of the control target, and determines the movement direction and movement speed of the non-control target. The second prediction space corresponding to the control is determined, and the control unit controls the control so that the first prediction space around the control target does not overlap with the second prediction space around the non-control target. Correct the trajectory of the target's movement. According to this configuration, since the movement of the controlled object is corrected by predicting the contact between the controlled object and the non-controlled object, the contact between the controlled object and the non-controlled object can be suppressed.

Further, in the robot system according to the above embodiment, the first prediction space has directivity in the moving direction of the controlled object and has an area corresponding to the moving speed of the controlled object, and the second predicted space. The predicted space of is directional in the moving direction of the uncontrolled object, and has an area corresponding to the moving speed of the uncontrolled object. According to this configuration, even if the controlled object and the non-controlled object are close to each other, the controlled object does not perform the avoidance operation unless there is a possibility of contact between the controlled object and the non-controlled object. Therefore, the work of the controlled object and the non-controlled object does not interfere with each other, and the productivity does not decrease.

Further, in the robot system described in the above embodiment, the prediction unit sets the attention point of the non-control target at a position closest to the predetermined attention point of the control target, and the attention point of the control target is set. The first prediction space around the first prediction space is determined, and the second prediction space around the point of interest of the uncontrolled object is determined. According to this configuration, the point of interest of the non-controlled object is set at the point where the distance from the predetermined point of interest of the controlled object to the uncontrolled object is the shortest, so that the point where the controlled object and the uncontrolled object are closest to each other is set. Contact can be avoided.

Further, in the robot system described in the above embodiment, the predetermined point of interest of the controlled object is the tip portion of the robot arm. According to this configuration, it is possible to avoid contact between the tip portion of the robot arm and the uncontrolled object.

Further, in the robot system described in the above embodiment, the prediction unit learns the behavior pattern of the non-control target by accumulating recognition data and predicts the movement of the non-control target. According to this configuration, the work of the non-controlled target can be predicted at an early stage, and the controlled target can be made to perform a work different from the current work.

The program described in the above embodiment is a program for causing a controlled object of a robot system to perform a predetermined operation in the same space as the non-controlled object, and recognizes recognition data in three dimensions of the non-controlled object in chronological order. The robot system is made to execute a step of predicting the movement of the non-controlled object from a change over time of the recognition data, and a step of controlling the movement of the controlled object based on the prediction result. According to this configuration, by installing a program in the robot system, it is possible to add a control function of a controlled object that ensures safety without reducing productivity to the robot system.

As described above, the present invention has an effect that safety can be ensured without lowering productivity when the controlled object and the non-controlled object work in the same space, and particularly with a robot. It is useful for robot systems where humans work on the same production line.

1 Robot system 15 Imaging device (recognition unit)
16 Robot controller (control unit)
17 Computer (Prediction Department)
H human (uncontrolled target)
R robot arm (controlled object)
P _H human attention point P _R target point of the robot arm S _H first prediction space S _R second prediction space

Claims (8)

A robot system that allows a controlled object to perform a predetermined operation in the same space as an uncontrolled object.
A recognition unit that outputs recognition data that recognizes the uncontrolled object in three dimensions in chronological order.
A prediction unit that predicts the movement of the uncontrolled object from changes over time in the recognition data,
A control unit that controls the movement of the controlled object based on the prediction result of the prediction unit is provided .
From the first mode in which the control target moves the control target toward the first target to perform the first operation, the control unit avoids the non-control target based on the prediction result of the prediction unit. A robot system characterized in that the movement of the controlled object is corrected so as to move the controlled object toward a second target and change the mode to a second mode in which the second operation is performed . The prediction unit determines a first prediction space according to the moving direction and moving speed of the controlled object, and determines a second prediction space according to the moving direction and moving speed of the non-controlled object.
The control unit is characterized in that the movement of the controlled object is corrected so that the first predicted space around the controlled object does not overlap with the second predicted space around the non-controlled object. The robot system according to claim 1 . The first prediction space has directivity in the moving direction of the controlled object and has an area corresponding to the moving speed of the controlled object.
The robot system according to claim 2 , wherein the second prediction space has directivity in the moving direction of the uncontrolled object and has an area corresponding to the moving speed of the uncontrolled object. When the prediction unit sets a predetermined target point of the non-controlled object position whose distance is short from the target point of the controlled object, to determine the first prediction space around the target point of the controlled The robot system according to claim 2 or 3 , both of which determine the second prediction space around the point of interest of the uncontrolled object. The robot system according to claim 4, wherein the predetermined point of interest of the controlled object is a tip end portion of the robot arm. The robot system according to any one of claims 1 to 5 , wherein the prediction unit learns an action pattern of the uncontrolled object by accumulating recognition data and predicts the movement of the uncontrolled object. .. A control method for a robot system that causes a controlled object to perform a predetermined operation in the same space as a non-controlled object.
A step of outputting recognition data for recognizing the non-controlled object in three dimensions in chronological order, and
The step of predicting the movement of the uncontrolled object from the change over time of the recognition data,
Possess and controlling the movement of the controlled object based on a prediction result,
In the control step, the non-control target is avoided from the first mode in which the control target is moved toward the first target to perform the first operation, based on the prediction result of the predicted step. However, the robot system is characterized in that the movement of the controlled object is corrected so as to move the controlled object toward the second target and change to the second mode in which the second operation is performed. Control method. A program that causes a controlled object of a robot system to perform a predetermined operation in the same space as an uncontrolled object.
A step of outputting recognition data for recognizing the non-controlled object in three dimensions in chronological order, and
The step of predicting the movement of the uncontrolled object from the change over time of the recognition data,
The robot system is made to execute a step of controlling the movement of the controlled object based on the prediction result .
In the control step, the non-control target is avoided based on the prediction result of the predicted step from the first mode in which the control target is moved toward the first target to perform the first operation. However, the program is characterized in that the movement of the controlled object is corrected so as to move the controlled object toward the second target and change to the second mode in which the second operation is performed .

Images