CN114055470A - Mechanical arm work task control method, device, equipment, system and storage medium - Google Patents
Mechanical arm work task control method, device, equipment, system and storage medium Download PDFInfo
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- CN114055470A CN114055470A CN202111374594.9A CN202111374594A CN114055470A CN 114055470 A CN114055470 A CN 114055470A CN 202111374594 A CN202111374594 A CN 202111374594A CN 114055470 A CN114055470 A CN 114055470A
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B25—HAND TOOLS; PORTABLE POWER-DRIVEN TOOLS; MANIPULATORS
- B25J—MANIPULATORS; CHAMBERS PROVIDED WITH MANIPULATION DEVICES
- B25J9/00—Programme-controlled manipulators
- B25J9/16—Programme controls
- B25J9/1656—Programme controls characterised by programming, planning systems for manipulators
- B25J9/1661—Programme controls characterised by programming, planning systems for manipulators characterised by task planning, object-oriented languages
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B25—HAND TOOLS; PORTABLE POWER-DRIVEN TOOLS; MANIPULATORS
- B25J—MANIPULATORS; CHAMBERS PROVIDED WITH MANIPULATION DEVICES
- B25J9/00—Programme-controlled manipulators
- B25J9/16—Programme controls
- B25J9/1602—Programme controls characterised by the control system, structure, architecture
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Abstract
The disclosure provides a method, a device, equipment, a system and a storage medium for establishing a work task of a mechanical arm. The mechanical arm work task making method comprises the following steps: acquiring a task request in a task queue, wherein the task request comprises a machine station identifier and a task type; determining a target initial position corresponding to each task request based on the machine station identification and the task type; determining the priority of each task request based on the current task end point position of the mechanical arm working end and the target initial position corresponding to each task request, wherein the current task end point position is the position of the mechanical arm working end when the current task is completed; and formulating the next task of the mechanical arm based on the task request with the highest priority. By adopting the scheme provided by the embodiment of the disclosure, the next task of the mechanical arm is formulated by selecting the task request with the highest priority, so that the idle time of the test machine is reduced, and the production beat is accelerated.
Description
Technical Field
The disclosure relates to the technical field of mechanical arm control, in particular to a method, a device, equipment, a system and a storage medium for controlling a work task of a mechanical arm.
Background
In order to realize the efficient use of the mechanical arm, an automatic production line can adopt one mechanical arm to execute the material loading and unloading tasks of a plurality of machines. In the related art, in order to avoid task conflicts, a computer device controlling the operation of the mechanical arm creates and maintains a task queue of first-in first-out, and task requests sent to the computer device by each machine are cached in the task queue maintained by the computer device. After receiving a task completion signal that the mechanical arm completes the current work task, the computer equipment acquires a task request with the longest waiting time from the task queue, formulates a mechanical arm control instruction based on the task request, and controls the mechanical arm to execute the next work task. However, the aforementioned method does not consider the travel time consumption of the robot arm, resulting in a long idle time of the machine.
Disclosure of Invention
In order to solve the technical problems described above or at least partially solve the technical problems, the present disclosure provides a method, an apparatus, a device, a system, and a storage medium for establishing a work task of a robot arm.
On one hand, the embodiment of the disclosure provides a method for making a work task of a mechanical arm, which is characterized by comprising the following steps:
acquiring a task request in a task queue, wherein the task request comprises a machine station identifier and a task type;
determining a target starting position corresponding to each task request based on the machine station identification and the task type;
determining the priority of each task request based on the current task end point position of the mechanical arm working end and the target starting position corresponding to each task request, wherein the current task end point position is the position of the mechanical arm working end when the current task is completed;
and formulating the next task of the mechanical arm based on the task request with the highest priority.
Optionally, the determining the priority of each task request based on the current task end position of the mechanical arm working end and the target start position corresponding to each task request includes:
determining a travel distance or a travel time for the mechanical arm working end to move to the target starting position corresponding to each task request based on the current task end position and the target starting position corresponding to each task request;
determining a priority for each of the task requests based on the travel distance or the travel time.
Optionally, the task request further comprises a generation timestamp;
the determining the priority of each task request based on the current task end position of the mechanical arm working end and the target starting position corresponding to each task request comprises the following steps:
and determining the priority of each task request based on the current task end position, the target starting position corresponding to each task request and the generation timestamp.
Optionally, the determining the priority of each task request based on the current task end position, the target start position corresponding to each task request, and the generation timestamp includes:
determining a travel distance of the mechanical arm working end to move to the target starting position based on the current task end position and the target starting position corresponding to each task request;
determining a travel characteristic weight of each task request based on the travel distance;
calculating the waiting time of each task request based on the time stamp, and determining the time characteristic weight of each task request based on the waiting time;
determining a priority for each of the task requests based on the travel characteristic weight and the time characteristic weight.
Optionally, the determining a temporal feature weight of each task request based on the waiting time includes: using a ═ eα×t/MWTCalculating the time characteristic weight of each task request, wherein a is the time characteristic weight, alpha is a time weighting coefficient, and t is the waiting timeIn between, the MWT is the longest waiting time of the task request in the task queue;
the determining the travel characteristic weight of each task request based on the travel distance comprises: calculating a stroke characteristic weight of each task request by using b ═ β × (D-D)/D, wherein b is the stroke characteristic weight, β is a stroke weighting coefficient, D is a working diameter of the mechanical arm, and D is the stroke distance;
the determining the priority of each task request based on the travel characteristic weight and the time characteristic weight comprises: and adding the time characteristic weight a and the travel characteristic weight b to obtain a priority score, and determining the priority of each task request based on the priority score.
Optionally, the determining the priority of each task request based on the current task end position of the mechanical arm working end and the target start position corresponding to each task request includes:
and determining the priority of each task request based on the current task end position, the target starting position corresponding to each task request and the task type.
On the other hand, the embodiment of the present disclosure provides a robot arm job task making device, including:
the task request acquisition unit is used for acquiring task requests in a task queue, and the task requests comprise machine station identifiers and task types;
a target starting position determining unit, configured to determine a target starting position corresponding to each task request based on the machine identifier and the task type;
the priority determining unit is used for determining the priority of each task request based on the current task end point position of the mechanical arm working end and the target starting position corresponding to each task request, wherein the current task end point position is the position of the mechanical arm working end when the current task is completed;
and the task formulating unit is used for formulating the next working task of the mechanical arm based on the task request with the highest priority.
In yet another aspect, an embodiment of the present disclosure provides a computer device, including: a memory and a processor, wherein the memory has stored therein a computer program which, when executed by the processor, implements the robotic arm work task formulating method as described above.
In another aspect, an embodiment of the present disclosure provides an automated production system, including a robot arm, at least two stations for executing a main production task, and a computer device; the machine station generates a task request based on the state of executing the main production task and sends the task request to the computer equipment; the computer equipment caches the task request into a task queue, and executes the mechanical arm work task formulation method to formulate a task for controlling the mechanical arm action.
In yet another aspect, embodiments of the present disclosure provide a computer-readable storage medium, where the storage medium stores computer instructions for causing a computer to execute the foregoing method for preparing a work task of a robot arm.
Compared with the prior art, the technical scheme provided by the embodiment of the disclosure has the following advantages:
the embodiment of the disclosure provides a technical scheme that a target starting position corresponding to each task request is determined according to the type and the machine station identification of each task request in a task queue, then the priority of each task request is determined based on the current task end position of a working end of a mechanical arm and the target starting position corresponding to each task request, and the next task of the mechanical arm is made based on the task request with the highest priority. The priority of each task is determined based on the current task end position of the mechanical arm working end and the target starting position corresponding to each task request, the travel time required by the current task end position of the mechanical arm working end and the target starting position corresponding to each task request is reflected, the higher the priority is, the shorter the travel time corresponding to the higher the priority is, the smaller the idle time of the corresponding machine table is. By adopting the scheme provided by the embodiment of the disclosure, the next task of the mechanical arm is formulated by selecting the task request with the highest priority, so that the idle time of the test machine is reduced, and the production beat is accelerated.
Drawings
The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the present disclosure and together with the description, serve to explain the principles of the disclosure.
In order to more clearly illustrate the embodiments of the present disclosure or the technical solutions in the prior art, the drawings used in the description of the embodiments or the prior art will be briefly described below. It will be apparent to those skilled in the art that other drawings can be obtained from these drawings without inventive exercise, wherein:
FIG. 1 is a schematic diagram of an automated production system provided by embodiments of the present disclosure;
FIG. 2 is a flowchart of a method for creating a work task for a robotic arm according to an embodiment of the present disclosure;
FIG. 3 is a schematic diagram illustrating the structure of a robotic arm work task formulating device according to some embodiments of the present disclosure;
fig. 4 is a schematic structural diagram of a computer device provided in an embodiment of the present disclosure.
Detailed Description
Embodiments of the present disclosure will be described in more detail below with reference to the accompanying drawings. While certain embodiments of the present disclosure are shown in the drawings, it is to be understood that the present disclosure may be embodied in various forms and should not be construed as limited to the embodiments set forth herein, but rather are provided for a more thorough and complete understanding of the present disclosure. It should be understood that the drawings and embodiments of the disclosure are for illustration purposes only and are not intended to limit the scope of the disclosure.
The embodiment of the disclosure provides a method for making a work task of a mechanical arm, which is used for determining the priority of each task request based on the task requests in a task queue and the current task end position of a working end of the mechanical arm, and selecting the task request with the highest priority to make the next work task of the mechanical arm.
The mechanical arm disclosed by the embodiment of the disclosure is a mechanical arm which is matched with a machine table to complete an auxiliary task, wherein the auxiliary task can be a feeding task and a discharging task of the machine table or a task of moving materials on the machine table and the like.
The method for formulating the work task of the mechanical arm provided by the embodiment of the disclosure is executed by computer equipment. The computer device may be an upper computer for controlling the operation of the robot arm, or may be a remote server communicatively connected to the upper computer for controlling the operation of the robot arm, and the embodiment of the present disclosure is not limited thereto.
In order to more clearly understand the method for formulating the work task of the mechanical arm provided by the embodiment of the present disclosure, before the method for formulating the work task of the mechanical arm provided by the embodiment of the present disclosure is introduced, an automated production system capable of using the method of the embodiment of the present disclosure is introduced first. The automatic production system provided by the embodiment of the disclosure is an automatic detection system for realizing automatic detection of a printed circuit board. Of course, the automatic generation system provided by the embodiment of the present disclosure may also be an automatic system for assembling and producing products such as printed circuit boards.
Fig. 1 is a schematic diagram of an automated production system provided by an embodiment of the present disclosure. As shown in fig. 1, the automatic detection system provided by the embodiment of the present disclosure includes an incoming material conveying line 11, a mechanical arm 12, and at least two detection stations 13. In addition, the automated inspection system provided by the present disclosure further includes a return flow line and a computer device (the return flow line and the computer device are not shown in the figure).
The incoming material conveying line 11 is used for conveying the printed circuit board assembled at the upstream to the vicinity of the detection machine 13. In the embodiment of the present disclosure, a blocking device 14, a material feeding detection device (not shown in fig. 1) and a turning device 15 may be disposed on the material feeding transmission line 11.
The damming device 14 is used to damming the pcb that is transported upstream via the incoming transport line 11 such that the pcb slows down and stays on the incoming side of the damming device 14. In a particular embodiment, the arresting means 14 may be an arresting rail.
The incoming material detection device is arranged on the upstream side of the blocking device 14 and is used for detecting whether the incoming material conveying line 11 has a printed circuit board or not. After detecting that the incoming material conveying line 11 conveys the printed circuit board, the incoming material detecting device generates a detection signal and sends the detection signal to the computer device so as to trigger the computer device to control the mechanical arm 12 to grab the printed circuit board. In a specific implementation, the incoming material detection device may be an opposite-emitting photoelectric sensor, a proximity sensor, or the like.
The turnover device 15 is used for turning over the printed circuit board placed thereon and detected by the detection machine 13 to the downstream side of the blocking device 14, so that the turned-over printed circuit board is transmitted to the downstream side through the incoming material transmission line 11.
The incoming material conveying line 11 in the embodiment of the present disclosure is provided with the aforementioned incoming material detecting device, intercepting device, and turning device 15. In other embodiments of the present disclosure, the incoming material conveying line 11 may not be provided with any one of the incoming material detecting device, the intercepting device, and the turning device 15.
The reflow line is used to convey the printed circuit board (i.e. the failed circuit board) that is not detected by the detection platform 13 to the upstream, so that the failed circuit board can be subjected to repair soldering and other operations in the upstream production process.
The mechanical arm 12 is used for transferring the printed circuit board between the incoming conveying line 11 and the detection bench 13, or transferring the printed circuit board between the detection bench 13 and the return conveying line. When the inspection station at the inspection station 13 has no printed circuit board and the inspection station 13 is in the inspection preparation state, the mechanical arm 12 picks up the printed circuit board from the feeding line 11 and places the printed circuit board on the inspection station of the inspection station 13, so that the inspection station 13 starts the inspection work of the printed circuit board. After the detection machine 13 finishes the detection of the printed circuit board and determines that the printed circuit board passes the detection, the mechanical arm 12 takes the printed circuit board off from the detection station and places the printed circuit board on the turnover device 15 of the incoming material production line. After the detection machine 13 finishes the detection of the printed circuit board and determines that the printed circuit board does not pass the detection, the arm 12 of the mechanical arm takes the printed circuit board off the detection station and places the printed circuit board on a reflow transmission line.
In the disclosed embodiment, in order to grasp and transfer the printed circuit, the working end of the robot arm 12 is provided with a gripping jaw. In addition, in order to realize the accurate positioning of the printed circuit board and then accurately grab and place the printed circuit board, the working end of the mechanical arm 12 is further provided with a shooting camera for shooting the printed circuit board on the incoming material conveying line 11 or the detection station. The shooting camera may be a depth camera or a plane camera, and the embodiment of the present disclosure is not particularly limited. After the shooting camera shoots the printed circuit board to form a shot image, the shot image is sent to the computer device, so that the computer device determines the pose of the printed circuit board based on the shot image and the pose of the mechanical arm 12, and the mechanical arm 12 is set and controlled according to the pose of the printed circuit board.
In the embodiment of the present disclosure, the photographing camera is disposed at the working end of the robot arm 12. In other embodiments, the camera may also be disposed at other locations of the robotic arm 12, or disposed independently of the robotic arm 12. For example, in other embodiments, the shooting cameras may be disposed on both the upper side of the incoming material conveying line 11 and the detection machine 13.
The inspection machine 13 is configured to perform an inspection task on the assembled printed circuit board, and is configured to determine whether the printed circuit board passes the inspection (in the embodiment of the present disclosure, the inspection task on the printed circuit board is a main task). In addition, the detection machine 13 determines whether to generate a task request according to a detection signal generated by a state sensor on the detection station. For example, when the state sensor on the detection station determines that the detection station is in a position state and there is no printed circuit board to be detected on the detection station, the detection machine 13 generates a task request for requesting feeding; after the state sensor on the detection station determines that the detection station has the printed circuit board and finishes detecting the printed circuit board, the detection machine 13 generates a task request for requesting blanking.
In the case that the detection machine station 13 is generating a task request, the detection machine station 13 sends the task request to the computer device, so that the computer device formulates the task of the mechanical arm 12 based on the task request.
As before, the computer apparatus controls the robot arm 12 to perform the pick and transfer operations of the printed circuit board. In the embodiment of the present disclosure, the computer device executes the method for formulating the work task of the mechanical arm provided by the embodiment of the present disclosure, formulates the work task of the mechanical arm 12, and determines the control instruction of the mechanical arm 12 according to the task.
As before, the automated inspection system in the embodiments of the present disclosure includes the incoming material conveying line 11 and the return flow conveying line. In other embodiments of the present disclosure, the automated inspection system may also have no incoming material transfer line 11 and no return transfer line, but rather a material placement station. The mechanical arm 12 transfers the printed circuit board between the material placing station and the detection machine 13 to complete the tasks of feeding, blanking and the like.
Fig. 2 is a flowchart of a method for making a work task of a mechanical arm according to an embodiment of the present disclosure. As shown in fig. 2, the method provided by the embodiment of the present disclosure includes steps S201 to S204.
Step S201: and acquiring a task request in the task queue, wherein the task request comprises a machine station identifier and a task type.
In the embodiment of the disclosure, after acquiring the task request sent by the detection machine, the computer device caches the task request in the task queue.
The task request includes a machine identification and a task type. The machine identification is used for identifying which detection machine generates and sends the task request to the computer equipment. The task type is used for identifying the type of a task requested by the machine station, and the task type can be a loading task or a blanking task.
Step S202: and determining a target initial position corresponding to each task request based on the machine station identification and the task type.
In the embodiment of the disclosure, the computer device may read the task request in the task queue according to a set rule, and determine a target start position corresponding to the task request. The target start position is a position of the robot arm when gripping the printed circuit board, or a position where the robot arm is ready when gripping the printed circuit board.
In the embodiment of the disclosure, the computer device determines a target starting position corresponding to the task request according to the machine identifier and the task type in the task request. For example, when the task type is a loading task, the target initial position is predetermined, and the initial position of the working end of the mechanical arm is suspended on the upper side of the incoming material production line. For another example, in a task type blanking task, the target starting position is the position of the detection station corresponding to the machine station identifier.
Step S203: and determining the priority of each task request based on the current task end position of the mechanical arm working end and the target initial position corresponding to each task request.
The current task end point position is the position of the mechanical arm when the current task is completed. For example, when the current task is to transfer a printed circuit board on a certain machine to a turnover device of an incoming material conveying line, the current task end point position of the working end of the mechanical arm may be a position corresponding to the turnover device. When the current task is to transfer a printed circuit board on a certain machine to a reflow transmission line, the current task end point position of the working end of the mechanical arm may be a position corresponding to the reflow transmission line. When the current task is to load a certain machine, the current task end point position of the working end of the mechanical arm may be a position corresponding to the specific machine.
In some embodiments of the present disclosure, the determining, by the computer device, the priority of each task request based on the current task end position of the working end of the robot arm and the target start position corresponding to each task request may include steps S2031-S2032.
Step S2031; and determining the travel distance of the mechanical arm working end moving to the target starting position corresponding to each task request based on the current task end position of the mechanical arm working end and the target starting position corresponding to each task request.
In some embodiments of the present disclosure, the computer device may calculate a corresponding linear distance by using the coordinates of the current task end position and the coordinates of the target start position corresponding to each task request, and use the corresponding linear distance as the travel distance corresponding to the task request.
In some other embodiments of the present disclosure, the computer device may calculate a planned path in space when the mechanical arm working end moves from the current task end position to the target start position based on the coordinates of the current task end position and the coordinates of the target start position corresponding to each task request, and adopt the length of the planned path as the travel distance.
Step S2032: the priority of each task request is determined based on the travel distance.
In some embodiments of the present disclosure, the computer device determines the priority of each task request based on the travel distance, may perform sorting according to the travel distance corresponding to each task request, and determines the priority of each task request based on the sorted travel distance. Specifically, the computer device may assign the task request corresponding to the shortest travel distance to the highest priority, and assign the task request corresponding to the longest travel distance to the lowest priority.
According to the working characteristics of the mechanical arm, the longer the travel distance of the working end of the mechanical arm is, the longer the time for the working end of the mechanical arm to move from the current task end position to the target initial position is, so that the sequencing of the travel time corresponding to each working task request can be determined according to the priority of the travel distance, wherein the travel time is the time required by the whole travel when the working end of the mechanical arm moves from the current task end position to the target initial position
In some embodiments of the present disclosure, the determining, by the computer device, the priority of each task request based on the current task end position of the working end of the mechanical arm and the target start position corresponding to each task request may include steps S2033 to S2034.
Step S2033; and determining the travel time of the mechanical arm working end moving to the target initial position corresponding to each task request based on the current task end position of the mechanical arm working end and the target initial position corresponding to each task request.
In the embodiment of the disclosure, the travel time is the time required by the whole travel when the working end of the mechanical arm moves from the current task end position to the target start position. The travel time is determined by the computer device based on the current task end position, the target start position, and the mechanical arm operating characteristics.
Step S2034: the priority of each task request is determined based on the travel distance.
In some embodiments of the present disclosure, the computer device determines the priority of each task request based on the travel time, may perform sorting according to the travel time corresponding to each task request, and determines the priority of each task request based on the sorted travel time. Specifically, the task request corresponding to the shortest travel time may be assigned the highest priority, and the task request corresponding to the longest travel time may be assigned the lowest priority.
Step S204: and formulating the next task of the mechanical arm based on the task request with the highest priority.
In the embodiment of the disclosure, after determining the priority corresponding to each task request, the computer device selects the task request with the highest priority as the task request of the next response, and formulates the next task of the mechanical arm based on the task request.
It should be noted that the computer device may execute the aforementioned steps S201 to S204 to determine the next task when the working end of the robot arm has not moved to the current task end position, or may execute the aforementioned steps S201 to S204 to determine the next task when the working end of the robot arm completes the current task and moves to the current task end position. Preferably, the computer device may determine the next task by using the foregoing steps S201 to S204 when the working end of the robot arm has not moved to the current task end position.
By adopting the method for formulating the work task of the mechanical arm provided by the embodiment of the disclosure, the computer equipment determines the target initial position corresponding to each task request according to the type and the machine station identification of each task request in the task queue, then determines the priority of each task request based on the current task end position of the mechanical arm work end and the target initial position corresponding to each task request, and formulates the next task of the mechanical arm based on the task request with the highest priority. The priority is determined based on the current task end position of the mechanical arm working end and the target starting position corresponding to each task request, the travel time required by the current task end position of the mechanical arm working end and the target starting position corresponding to each task request is reflected, and the travel time corresponding to the higher the priority is shorter. By adopting the method for formulating the work tasks of the mechanical arm, the travel time consumption of the mechanical arm is considered through the priority, the task request with the highest priority is selected to formulate the next task of the mechanical arm, the probability is that the task request with the lowest travel time consumption of the mechanical arm is selected to formulate the next task, the idle time of a test machine is reduced, and the production beat is accelerated.
In some embodiments of the present disclosure, the task request sent by each detection machine to the computer device may include generating a timestamp in addition to the machine identification and the task type. The generation timestamp characterizes a generation time of the task request.
In the case where the task request includes a generation timestamp, step S203 may include step S2035 in some embodiments of the present disclosure.
Step S2035: and determining the priority of each task request based on the current task end position, the target starting position corresponding to each task request and the generation time stamp.
In the embodiment of the present disclosure, step S2035 may specifically include steps S20351 to S20354.
Step S20351: and determining the travel distance of the mechanical arm working end moving to the target starting position based on the current task end position and the target starting position corresponding to each task request.
The method for determining the travel distance in the embodiment of the present disclosure is the same as that in the previous embodiment, and the corresponding contents can be referred to the foregoing description, and will not be repeated here.
Step 20352: and determining the travel characteristic weight of each task request based on the travel distance.
In some embodiments of the present disclosure, determining the travel characteristic weight of each task request based on the travel distance may be to sort the travel distance or the travel time of each task request, and determine the travel characteristic weight of each task request according to a sorting result.
In some embodiments of the present disclosure, a stroke characteristic weight of each task request may be calculated by using b ═ β × (D-D)/D, where b is the stroke characteristic weight, β is a stroke weighting coefficient, D is a working diameter of the robot arm, and D is the stroke distance.
Step S20353: calculating the waiting time of each task request based on the time stamp, and determining the time characteristic weight of each task request based on the waiting time.
In some embodiments of the present disclosure, determining the time characteristic weight of each task request based on the waiting time may be sorting the waiting times, and determining the time characteristic weight based on a sorting result, where the time characteristic weight of the task request with the longest waiting time is the largest.
In some other embodiments of the present disclosure, a ═ e is usedα×t/MWTAnd calculating the time characteristic weight of each task request, wherein a is the time characteristic weight, alpha is a time weighting coefficient, t is the waiting time, and MWT is the longest waiting time of the task request in the task queue.
Step S20354: and determining the priority of each task request based on the travel characteristic weight and the time characteristic weight.
In some embodiments of the present disclosure, after obtaining the travel characteristic weight and the time characteristic weight, the travel characteristic weight a and the time characteristic weight b may be added to obtain a priority _ score corresponding to each task request. Subsequently, the priority of each task request is determined based on the priority score priority _ score of the task request.
For example, in some embodiments, the priority score priority _ score is a eα×t/MWT+b＝β×(D-d)/D。
In some embodiments of the disclosure, in order to enable the machine to achieve the optimal working efficiency through the work task formulated by the work task formulation method for the mechanical arm, the aforementioned time weighting coefficient α and the aforementioned travel weighting coefficient β need to be set reasonably.
In order to obtain a reasonable time weighting coefficient α and a reasonable travel weighting coefficient β, in the embodiment of the disclosure, a plurality of test data sets may be set empirically, each data set includes a test time weighting coefficient αTestingAnd the test run weighting factor betaTestingAnd performing production test based on multiple test data sets to determine the working yield N of the workbench when each test data set is adoptedTesting. Finally, based on each test data set and the corresponding work output NTestingAnd performing parameter fitting, and determining a time weighting coefficient and a travel weighting coefficient corresponding to the maximum working yield as an actually used time weighting coefficient alpha and a travel weighting coefficient beta. In particular embodiments, a multi-layered perceptual function network may be employed, based on a plurality of sets of test data and corresponding work outputs NTestingAnd performing parameter fitting to obtain the optimal time weighting coefficient alpha and the optimal travel weighting coefficient beta.
By adopting the method provided by the embodiment of the disclosure, the priority of each task request is determined based on the target starting position and the generation timestamp corresponding to each task request, and the task request with the earlier generation timestamp can have higher priority, so that the task request generated earlier is processed earlier.
In some other embodiments of the present disclosure, step S203 of the method for making a work task of a robot arm may include step S2036.
Step S2036: and determining the priority of each task request based on the current task end position, and the target starting position, the task type and the machine station identification corresponding to each task request.
In some embodiments of the disclosure, different task types cause the detection machine to be idle for different lengths of time. In order to reduce the length of idle time of the detection machine as much as possible, in the embodiment of the present disclosure, the priority of each task request is determined based on the task type of each task request, in addition to the priority of each task request being determined based on the current task end position and the target start position corresponding to each task request.
In some embodiments of the present disclosure, step S2036 may specifically include steps S20361-S20364.
Step S20361: and determining the travel distance or the travel time for the mechanical arm working end to move to the target starting position based on the current task end position and each target starting position.
Step S20362: and calculating the corresponding travel characteristic weight of each task request based on the travel distance or the travel time.
In an embodiment, the foregoing steps S20361 and S20362 are the same as those in the foregoing embodiment, and will not be repeated here.
Step S20363: based on the task type, a type weight of each task request is determined.
In the embodiment of the present disclosure, the type weight of each task request is determined based on the task type, and may be determined by searching a preset type weight lookup table based on the task type.
Step S20364: and determining the priority of each task request based on the travel characteristic weight and the type weight.
In some embodiments of the present disclosure, after obtaining the travel characteristic weight and the type weight, the travel characteristic weight and the type weight may be added to obtain a weight sum corresponding to each task request. And then, determining the priority of each task request based on the weight sum corresponding to each task weight. In particular embodiments, the priority of the task request with the largest sum of weights is set to be highest, while the priority of the task request with the smallest sum of weights is set to be smallest.
In some embodiments of the present disclosure, different inspection stations may have different inspection processing rates for printed circuit boards. In order to speed up the production cycle and improve the production efficiency, the task requests generated by the inspection machines with higher inspection processing rate should be processed as preferentially as possible. In order to achieve the foregoing object, the foregoing step S203 may further include step S2037.
Step S2037: and determining the priority of each task request based on the current task end position, the target initial position corresponding to each task request and the identification of the machine.
In some embodiments of the present disclosure, step S2037 may specifically include steps S20371-S20374.
Step S20371: and determining the travel distance or the travel time for the mechanical arm working end to move to the target starting position based on the current task end position and each target starting position.
Step S20372: and calculating the corresponding travel characteristic weight of each task request based on the travel distance or the travel time.
In an embodiment, steps S20371 and S20372 are the same as those in the previous embodiment, and will not be repeated here.
Step S20373: and determining the machine weight of each task request based on the machine identification.
In the embodiment of the present disclosure, the machine weight of each task request is determined based on the machine identifier, and the set love weight of each task request may be determined by searching a preset machine weight lookup table based on the set love identifier.
Step S20374: and determining the priority of each task request based on the travel characteristic weight and the machine weight.
In some embodiments of the present disclosure, after obtaining the trip feature weight and the machine weight, the trip feature weight and the machine weight may be added to obtain a weight sum corresponding to each task request. And then, determining the priority of each task request based on the weight sum corresponding to each task weight. In particular embodiments, the priority of the task request with the largest sum of weights is set to be highest, while the priority of the task request with the smallest sum of weights is set to be smallest.
In addition to determining the priority of each task request by using the foregoing method, in some embodiments of the present disclosure, the priority of each task request may also be determined based on the current task end position, the target start position corresponding to each task request, the generation timestamp, the machine identifier, and the task type. Specifically, the corresponding travel feature weight may be calculated based on the current task end position and the target start position, the time weight may be calculated based on the generation timestamp, the machine weight may be calculated based on the machine identifier, and the type weight may be calculated based on the task type. And then adding the travel characteristic weight, the time weight, the machine weight and the type weight to obtain a weight sum. And finally, determining the priority of each task request according to the weight sum.
In a specific application of the embodiment of the present disclosure, in order to implement the method for making a work task of a mechanical arm, the mechanical arm is controlled to execute a corresponding work task, and an instantiated application program may be deployed in the computer device. The application program may include a task listening thread and a main thread. The task monitoring thread is used for monitoring task requests sent by all detection machines and writing the task requests into the task queue. The main thread is used for executing the mechanical arm work task making method; in specific implementation, both the task listening thread and the main thread can read the memory space where the task queue is located, so as to add the task request to the task queue or take the task request out of the task request. In practical application, in order to avoid that the task listening thread and the main thread operate the memory space where the task queue is located at the same time, when any one of the task listening thread and the main thread operates the memory space where the task queue is located, the mutual exclusion lock is added to the memory space to prevent the other thread from operating the task queue at the same time.
In addition to providing the aforementioned method for formulating a work task of a robot arm, the embodiment of the present disclosure further provides a device 300 for formulating a work task of a robot arm, which is used for formulating a work task for controlling the robot arm. Fig. 3 is a schematic structural diagram of a robotic arm work task formulating device 300 according to some embodiments of the present disclosure. The robot arm work task formulating device 300 provided by the embodiment of the present disclosure is a functional module which can be the aforementioned computer device.
As shown in fig. 3, the robot arm work task formulating device 300 provided by the embodiment of the present disclosure includes a task request acquiring unit 301, a target start position determining unit 302, a priority determining unit 303, and a task formulating unit 304.
The task request obtaining unit 301 is configured to obtain a task request in a task queue, where the task request includes a machine identifier and a task type. The target start position determining unit 302 is configured to determine a target start position corresponding to each task request based on the machine identifier and the task type. The priority determining unit 303 is configured to determine the priority of each task request based on a current task end position of the mechanical arm working end and a target start position corresponding to each task request, where the current task end position is a position of the mechanical arm working end when the current task is completed. The task formulation unit 304 is configured to formulate a next work task of the robot arm based on the task request with the highest priority.
In some embodiments of the present disclosure, the priority determining unit 303 first determines a travel distance or a travel time for the robot arm working end to move to the target start position corresponding to each task request based on the current task end position of the robot arm working end and the target start position corresponding to each task request, and then determines the priority of each task request based on the travel distance or the travel time.
In some embodiments of the present disclosure, the task request further comprises generating a timestamp. Correspondingly, the priority determining unit 303 determines the priority of each task request based on the current task end position, the target start position corresponding to each task request and the generation timestamp.
In some embodiments of the present disclosure, the priority determining unit 303 determines the priority of each task request based on the current task end position, the target start position corresponding to each task request, and the generation timestamp.
In some embodiments of the present disclosure, the priority determining unit 303 determines the priority of each task request based on the current task end position, and the target start position and the task type corresponding to each task request.
The embodiment of the present disclosure further provides a computer device, which includes a processor and a memory, where the memory stores a computer program, and when the computer program is executed by the processor, the method for making a work task of a mechanical arm according to any of the above embodiments may be implemented.
Referring now in particular to fig. 4, there is shown a schematic block diagram of a computer device 400 suitable for use in implementing embodiments of the present disclosure. The computer device shown in fig. 4 is only an example and should not bring any limitation to the function and scope of use of the embodiments of the present disclosure.
As shown in fig. 4, the computer device 400 may include a processing means (e.g., a central processing unit, a graphics processor, etc.) 401 that may perform various appropriate actions and processes in accordance with a program stored in a read only memory ROM402 or a program loaded from a storage means 408 into a random access memory RAM 403. In the RAM403, various programs and data necessary for the operation of the computer apparatus 400 are also stored. The processing device 401, the ROM402, and the RAM403 are connected to each other via a bus 404. An input/output I/O interface 405 is also connected to bus 404.
Generally, the following devices may be connected to the I/O interface 405: input devices 406 including, for example, a touch screen, touch pad, keyboard, mouse, camera, microphone, accelerometer, gyroscope, etc.; an output device 407 including, for example, a Liquid Crystal Display (LCD), a speaker, a vibrator, and the like; storage 408 including, for example, tape, hard disk, etc.; and a communication device 409. The communication means 409 may allow the computer device 400 to communicate with other devices, either wirelessly or by wire, to exchange data. While fig. 4 illustrates a computer device 400 having various means, it is to be understood that not all illustrated means are required to be implemented or provided. More or fewer devices may alternatively be implemented or provided.
In particular, according to an embodiment of the present disclosure, the processes described above with reference to the flowcharts may be implemented as computer software programs. For example, embodiments of the present disclosure include a computer program product comprising a computer program carried on a non-transitory computer readable medium, the computer program containing program code for performing the method illustrated by the flow chart. In such an embodiment, the computer program may be downloaded and installed from a network via the communication device 409, or from the storage device 408, or from the ROM 402. The computer program performs the above-described functions defined in the methods of the embodiments of the present disclosure when executed by the processing device 401.
It should be noted that the computer readable medium in the present disclosure can be a computer readable signal medium or a computer readable storage medium or any combination of the two. A computer readable storage medium may be, for example, but not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any combination of the foregoing. More specific examples of the computer readable storage medium may include, but are not limited to: an electrical connection having one or more wires, a portable computer diskette, a hard disk, a Random Access Memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing. In the present disclosure, a computer readable storage medium may be any tangible medium that can contain, or store a program for use by or in connection with an instruction execution system, apparatus, or device. In contrast, in the present disclosure, a computer readable signal medium may comprise a propagated data signal with computer readable program code embodied therein, either in baseband or as part of a carrier wave. Such a propagated data signal may take many forms, including, but not limited to, electro-magnetic, optical, or any suitable combination thereof. A computer readable signal medium may also be any computer readable medium that is not a computer readable storage medium and that can communicate, propagate, or transport a program for use by or in connection with an instruction execution system, apparatus, or device. Program code embodied on a computer readable medium may be transmitted using any appropriate medium, including but not limited to: electrical wires, optical cables, RF (radio frequency), etc., or any suitable combination of the foregoing.
In some embodiments, the client, computer device may communicate using any currently known or future developed network Protocol, such as HTTP (HyperText Transfer Protocol), and may be interconnected with any form or medium of digital data communication (e.g., a communications network). Examples of communication networks include a local area network ("LAN"), a wide area network ("WAN"), the Internet (e.g., the Internet), and peer-to-peer networks (e.g., ad hoc peer-to-peer networks), as well as any currently known or future developed network.
The computer readable medium may be embodied in the computer device; or may exist separately and not be incorporated into the computer device.
The computer readable medium carries one or more programs which, when executed by the computing device, cause the computing device to: acquiring a task request in a task queue, wherein the task request comprises a machine station identifier and a task type; determining a target initial position corresponding to each task request based on the machine station identification and the task type; determining the priority of each task request based on the current task end point position of the mechanical arm working end and the target initial position corresponding to each task request, wherein the current task end point position is the position of the mechanical arm working end when the current task is completed; and formulating the next task of the mechanical arm based on the task request with the highest priority.
Computer program code for carrying out operations for the present disclosure may be written in any combination of one or more programming languages, including but not limited to an object oriented programming language such as Java, Smalltalk, C + +, and conventional procedural programming languages, such as the "C" programming language or similar programming languages. The program code may execute entirely on the user's computer, partly on the user's computer, as a stand-alone software package, partly on the user's computer and partly on a remote computer or entirely on the remote computer or computer device. In the case of a remote computer, the remote computer may be connected to the user's computer through any type of network, including a Local Area Network (LAN) or a Wide Area Network (WAN), or the connection may be made to an external computer (for example, through the Internet using an Internet service provider).
The flowchart and block diagrams in the figures illustrate the architecture, functionality, and operation of possible implementations of systems, methods and computer program products according to various embodiments of the present disclosure. In this regard, each block in the flowchart or block diagrams may represent a module, segment, or portion of code, which comprises one or more executable instructions for implementing the specified logical function(s). It should also be noted that, in some alternative implementations, the functions noted in the block may occur out of the order noted in the figures. For example, two blocks shown in succession may, in fact, be executed substantially concurrently, or the blocks may sometimes be executed in the reverse order, depending upon the functionality involved. It will also be noted that each block of the block diagrams and/or flowchart illustration, and combinations of blocks in the block diagrams and/or flowchart illustration, can be implemented by special purpose hardware-based systems that perform the specified functions or acts, or combinations of special purpose hardware and computer instructions.
The units described in the embodiments of the present disclosure may be implemented by software or hardware. Where the name of an element does not in some cases constitute a limitation on the element itself.
The functions described herein above may be performed, at least in part, by one or more hardware logic components. For example, without limitation, exemplary types of hardware logic components that may be used include: field Programmable Gate Arrays (FPGAs), Application Specific Integrated Circuits (ASICs), Application Specific Standard Products (ASSPs), systems on a chip (SOCs), Complex Programmable Logic Devices (CPLDs), and the like.
In the context of this disclosure, a machine-readable medium may be a tangible medium that can contain, or store a program for use by or in connection with an instruction execution system, apparatus, or device. The machine-readable medium may be a machine-readable signal medium or a machine-readable storage medium. A machine-readable medium may include, but is not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any suitable combination of the foregoing. More specific examples of a machine-readable storage medium would include an electrical connection according to one or more wires, a portable computer diskette, a hard disk, a Random Access Memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing.
The embodiments of the present disclosure also provide a computer-readable storage medium, where a computer program is stored in the storage medium, and when the computer program is executed by a processor, the method of any of the above method embodiments can be implemented, and the execution manner and the beneficial effect are similar, and are not described herein again.
It is noted that, in this document, relational terms such as "first" and "second," and the like, may be used solely to distinguish one entity or action from another entity or action without necessarily requiring or implying any actual such relationship or order between such entities or actions. Also, the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus. Without further limitation, an element defined by the phrase "comprising an … …" does not exclude the presence of other identical elements in a process, method, article, or apparatus that comprises the element.
The foregoing are merely exemplary embodiments of the present disclosure, which enable those skilled in the art to understand or practice the present disclosure. Various modifications to these embodiments will be readily apparent to those skilled in the art, and the generic principles defined herein may be applied to other embodiments without departing from the spirit or scope of the disclosure. Thus, the present disclosure is not intended to be limited to the embodiments shown herein but is to be accorded the widest scope consistent with the principles and novel features disclosed herein.
Claims (10)
1. A method for formulating a working task of a mechanical arm is characterized by comprising the following steps:
acquiring a task request in a task queue, wherein the task request comprises a machine station identifier and a task type;
determining a target starting position corresponding to each task request based on the machine station identification and the task type;
determining the priority of each task request based on the current task end point position of the mechanical arm working end and the target starting position corresponding to each task request, wherein the current task end point position is the position of the mechanical arm working end when the current task is completed;
and formulating the next task of the mechanical arm based on the task request with the highest priority.
2. The method of claim 1, wherein the determining the priority of each task request based on a current task end position of the working end of the robotic arm and the target start position corresponding to each task request comprises:
determining a travel distance or a travel time for the mechanical arm working end to move to the target starting position corresponding to each task request based on the current task end position and the target starting position corresponding to each task request;
determining a priority for each of the task requests based on the travel distance or the travel time.
3. The method of claim 1, wherein the task request further comprises generating a timestamp;
the determining the priority of each task request based on the current task end position of the mechanical arm working end and the target starting position corresponding to each task request comprises the following steps:
and determining the priority of each task request based on the current task end position, the target starting position corresponding to each task request and the generation timestamp.
4. The method of claim 3, wherein determining the priority of each task request based on the current task end position, the target start position corresponding to each task request, and the generation timestamp comprises:
determining a travel distance of the mechanical arm working end to move to the target starting position based on the current task end position and the target starting position corresponding to each task request;
determining a travel characteristic weight of each task request based on the travel distance;
calculating the waiting time of each task request based on the time stamp, and determining the time characteristic weight of each task request based on the waiting time;
determining a priority for each of the task requests based on the travel characteristic weight and the time characteristic weight.
5. The method of claim 4,
the determining a temporal feature weight for each of the task requests based on the latency includes: using a ═ eα×t/MWTCalculating a time characteristic weight of each task request, wherein a is the time characteristic weight, alpha is a time weighting coefficient, t is the waiting time, and MWT is the longest waiting time of the task request in the task queue;
the determining the travel characteristic weight of each task request based on the travel distance comprises: calculating a stroke characteristic weight of each task request by using b ═ β × (D-D)/D, wherein b is the stroke characteristic weight, β is a stroke weighting coefficient, D is a working diameter of the mechanical arm, and D is the stroke distance;
the determining the priority of each task request based on the travel characteristic weight and the time characteristic weight comprises: and adding the time characteristic weight a and the travel characteristic weight b to obtain a priority score priority _ score, and determining the priority of each task request based on the priority score.
6. The method of claim 1, wherein the determining the priority of each task request based on a current task end position of the working end of the robotic arm and the target start position corresponding to each task request comprises:
and determining the priority of each task request based on the current task end position, the target starting position corresponding to each task request and the task type.
7. A mechanical arm work task formulating device is characterized by comprising:
the task request acquisition unit is used for acquiring task requests in a task queue, and the task requests comprise machine station identifiers and task types;
a target starting position determining unit, configured to determine a target starting position corresponding to each task request based on the machine identifier and the task type;
the priority determining unit is used for determining the priority of each task request based on the current task end point position of the mechanical arm working end and the target starting position corresponding to each task request, wherein the current task end point position is the position of the mechanical arm working end when the current task is completed;
and the task formulating unit is used for formulating the next working task of the mechanical arm based on the task request with the highest priority.
8. A computer device, comprising: memory and a processor, wherein the memory has stored therein a computer program which, when executed by the processor, implements a method of task-making a robotic arm according to any one of claims 1 to 6.
9. An automatic production system is characterized by comprising a mechanical arm, at least two machine stations for executing a main task and computer equipment;
the machine station generates a task request based on the state of executing the main task and sends the task request to the computer equipment;
the computer device buffers the task requests into a task queue, and performs the method of formulating a task for controlling the actions of the robot arm according to any of claims 1-6.
10. A computer-readable storage medium, wherein the storage medium has stored thereon computer instructions for causing the computer to perform the robotic arm work task formulation method of any of claims 1-6.
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