CN-120921408-B - Multi-robot cooperative control method based on new energy street lamp production line data

CN120921408BCN 120921408 BCN120921408 BCN 120921408BCN-120921408-B

Abstract

The invention relates to the technical field of electric digital data processing, and particularly discloses a multi-robot cooperative control method based on new energy street lamp production line data, which comprises the following steps: and after receiving the new energy street lamp assembly total task, the central control port carries out task decomposition to obtain each functional domain task to be assembled, and sends a preparation calling signal to each assembly robot in the production line. After the robot receives the signals, acquiring real-time execution data of the robot to judge a real-time load evaluation value, and feeding back load state data to the central control port. And the central control port performs cooperative adjustment of the task of the functional domain to be assembled on the assembly robot according to the data. Meanwhile, the task execution condition and the execution state of the robot are monitored in real time, and smooth production process is ensured. The process realizes the accurate control of the assembly robot and the efficient allocation of tasks, and improves the automation degree and the production efficiency of the new energy street lamp production line.

Inventors

LIU LIMING
WANG TAIGUANG
HU XIAOGUO

Assignees

贵州伊尔软件有限公司
贵州水利水电职业技术学院

Dates

Publication Date: 20260508
Application Date: 20251014

Claims (8)

1. The multi-robot cooperative control method based on the new energy street lamp production line data is characterized by comprising the following steps of: the central control port receives the assembly total task of the street lamp of the production line, carries out task decomposition to obtain tasks of each functional domain to be assembled, and generates a preparation calling signal to the signal receiving port of each assembly robot in the production line; After the signal receiving port receives the preliminary call signal, acquiring real-time execution data of each assembly robot, judging real-time load evaluation values of each assembly robot, feeding back real-time load state data of each assembly robot to the central control port, and judging whether to carry out cooperative adjustment of the assembly robots; according to the real-time load state data, the cooperative adjustment of the tasks of the functional domain to be assembled is carried out on each assembly robot through a central control port; monitoring the current task execution condition of each assembly robot in real time, and feeding back the execution state of each assembly robot; the judging whether the cooperative adjustment of the assembly robot is carried out or not comprises the following specific judging process: Comparing the real-time load evaluation value of each assembly robot with a predefined load evaluation permission threshold, if the real-time load evaluation value of a certain assembly robot is smaller than or equal to the load evaluation permission threshold, marking the assembly robot as a unemployed unit, and feeding back unemployed unit execution state data to a central control port without cooperative adjustment of the assembly robot; If the real-time load evaluation value of a certain assembly robot is larger than the load evaluation permission threshold, the assembly robot needs to be cooperatively adjusted, the assembly robot is marked as a high-load unit, the execution state data of the high-load unit is fed back to a central control port, meanwhile, the real-time load evaluation value of the assembly robot and the load evaluation permission threshold are subjected to difference processing to obtain the load deviation of the assembly robot, the overflow load state of the assembly robot is judged, and the cooperative adjustment is carried out; The overflow load state of the assembly robot is judged, cooperative adjustment is carried out, and the specific judging process is as follows: Comparing the load deviation of the assembly robot with a predefined load deviation threshold, if the load deviation of the assembly robot is smaller than or equal to the load deviation threshold, judging that the overflow load state of the assembly robot is a heavy load, and preferentially triggering the next round of cooperative allocation to maintain the current task accumulation queue of the assembly robot; If the load deviation of the assembly robot is larger than the load deviation threshold, judging that the overflow load state of the assembly robot is overload, starting master-slave cooperative adjustment, automatically upgrading a high-load unit into a master robot, acquiring task scheduling rights, simultaneously extracting real-time load evaluation values of unemployed units in the same attribute operation domain, taking unemployed units with the minimum real-time load evaluation values as slave robots, and broadcasting master-slave relation change instructions to the slave robots by a central control port; and the main robot distributes the auxiliary robot operation according to the task scheduling weight.
2. The multi-robot cooperative control method based on the new energy street lamp production line data, which is disclosed in claim 1, is characterized in that the task decomposition is carried out, and the specific analysis process is as follows: the task decomposition comprises a first-level decomposition and a second-level decomposition; dividing a street lamp assembly total task into a plurality of production functional domains according to functional characteristics, wherein the production functional domains comprise a lamp assembly functional domain, an electric control system assembly functional domain, a solar module installation functional domain and a complete machine assembly functional domain, and each functional domain corresponds to an independent robot operation unit; The two-level decomposition is specifically that tasks of the functional domains to be assembled are arranged according to an execution sequence, so that the tasks of the functional domains to be assembled meet a preset task relation dependency matrix, sub-task queues with time sequence labels are generated, production functional domains are distributed according to space positions, and sub-task queues with space labels are generated.
3. The method for collaborative control of multiple robots based on new energy street lamp production line data according to claim 1, wherein the real-time load evaluation value of each assembly robot is determined by the following specific determination process: the real-time execution data of each assembly robot comprises the real-time motor running load of each assembly robot, the real-time production beat lag deviation of each assembly robot, the real-time task queue accumulation amount of each assembly robot and the real-time end effector occupancy rate of each assembly robot; And respectively carrying out normalization processing on the real-time motor running load of each assembly robot, the real-time production beat lag deviation of each assembly robot, the real-time task queue accumulation amount of each assembly robot and the real-time end effector occupancy rate of each assembly robot, and sequentially carrying out weighted aggregation on normalization processing results to obtain the real-time load evaluation value of each assembly robot.
4. The multi-robot cooperative control method based on the new energy street lamp production line data, as set forth in claim 1, is characterized in that the main robot distributes auxiliary robot operations, and the specific analysis process is as follows: Dividing a task accumulation queue of the main robot into sub accumulation tasks, acquiring waiting time of each sub accumulation task, and recording a plurality of sub accumulation tasks with waiting time longer than preset waiting defining time as migration tasks; The auxiliary robot takes over the migration task, obtains the number of the migration task, adds with the current task queue number of the auxiliary robot to obtain the actual execution task number of the auxiliary robot, compares with the predefined parallel task permission number of the auxiliary robot, confirms to take over the migration task if the actual execution task of the auxiliary robot is smaller than or equal to the parallel task permission number of the auxiliary robot, maintains the operation of the auxiliary robot, and keeps the next unemployed unit in the same attribute operation domain along if the actual execution task of the auxiliary robot is larger than the parallel task permission number of the auxiliary robot, marks the next unemployed unit as a second auxiliary robot to carry out operation, wherein the task execution number of the second auxiliary robot is the difference between the actual execution task of the auxiliary robot and the parallel task permission number of the auxiliary robot; The method comprises the steps that a main robot monitors the state of an auxiliary robot in real time, the rotating speed of a real-time motor of the auxiliary robot is obtained, the accumulated time length, in which the rotating speed of the real-time motor of the auxiliary robot is smaller than the reference rotating speed of a preset motor, of the auxiliary robot is counted, the accumulated time length is compared with a predefined accumulated limiting time length, if the accumulated time length is smaller than or equal to the accumulated limiting time length, the main robot continuously monitors the auxiliary robot, and if the accumulated time length is longer than the accumulated limiting time length, the main robot issues a compensation instruction.
5. The multi-robot cooperative control method based on the new energy street lamp production line data, as set forth in claim 1, wherein the central control port performs cooperative adjustment of tasks of functional domains to be assembled on each assembling robot, and the specific analysis process is as follows: According to the task relation dependency matrix, acquiring a load state of an assembly robot corresponding to a current functional domain task to be assembled, marking the load state as the load state of the current assembly robot, if the load state of the current assembly robot is a high load unit, dividing the current functional domain task into a main task queue and a slave task queue according to the task relation dependency matrix, marking the slave task queue as a migration task, taking over the migration task by the auxiliary robot, automatically merging the main task queue into the task queue of the main robot to form master-slave cooperation, simultaneously extracting a real-time load evaluation value of the main robot, mapping to obtain an adaptive production takt of the main robot, and up-regulating the real-time production takt of the main robot to the adaptive production takt of the main robot; If the load state of the current assembly robot is unemployed units, the current assembly robot executes the task of the functional domain to be assembled; repeating the execution process of the functional domain tasks to be assembled until the cooperative adjustment of all the functional domain tasks is completed; After the task execution of the functional domain to be assembled is completed, the assembly robot feeds back task execution data to the central control port, judges the execution quality index of the assembly robot and feeds back the execution state of the current assembly robot.
6. The multi-robot cooperative control method based on the new energy street lamp production line data, as set forth in claim 5, wherein the feedback of the execution state of the current assembly robot comprises the following specific analysis processes: Comparing the execution quality index of the assembly robot with a predefined execution quality reference index, if the execution quality index of the assembly robot is greater than or equal to the execution quality reference index, maintaining cooperative adjustment, and feeding back the execution state of the assembly robot to be normal execution; If the execution quality index of the assembly robot is smaller than the execution quality reference index, feeding back that the execution state of the current assembly robot is abnormal execution, triggering a robot self-calibration program, recalibrating a joint zero point through a laser positioning landmark, performing difference processing on the execution quality index of the assembly robot and the execution quality reference index to obtain the execution quality deviation of the assembly robot, mapping to obtain the adaptive scanning frequency of the laser sensor, and configuring the robot self-calibration program according to the adaptive scanning frequency of the laser sensor.
7. The multi-robot cooperative control method based on the new energy street lamp production line data, as set forth in claim 5, wherein the determining the execution quality index of the assembly robot comprises the following specific analysis processes: Extracting task execution data of the assembly robot, wherein the task execution data comprise the motion track overlap ratio of an end effector of the assembly robot, the moment fluctuation variance of the assembly robot and the standard deviation of the acceleration of each joint of the assembly robot; Capturing optical mark points on the end effector in real time through a high-precision visual positioning device to generate an actual track point space coordinate set, comparing the actual track point space coordinate set with a preset track point space coordinate set one by one, counting the actual track point space coordinate set through a distance formula three-dimensional Euclidean distance formula between two points in space, carrying out average value processing on the actual track point space coordinate set and each distance of the preset track point space coordinate set, and carrying out reciprocal processing to obtain the moving track coincidence degree of the end effector of the assembly robot; And respectively carrying out normalization processing on the movement track coincidence degree of the end effector of the assembly robot, the moment fluctuation variance of the assembly robot and the standard deviation of the acceleration of each joint of the assembly robot, and sequentially carrying out weighted aggregation on normalization processing results to obtain the execution quality index of the assembly robot.
8. The multi-robot cooperative control method based on the new energy street lamp production line data, as set forth in claim 4, wherein the main robot distributes the auxiliary robot operation, further comprising: The method comprises the steps of obtaining a real-time task energy consumption value of an auxiliary robot, comparing the real-time task energy consumption value of the auxiliary robot with a predefined task energy consumption standard threshold, if the real-time task energy consumption value of the auxiliary robot is smaller than or equal to the task energy consumption standard threshold, executing a main robot to distribute auxiliary robot operation, and if the real-time task energy consumption value of the auxiliary robot is larger than the task energy consumption standard threshold, performing difference processing on the real-time task energy consumption value of the auxiliary robot and the task energy consumption standard threshold to obtain a real-time task energy consumption deviation of the auxiliary robot; And comparing the real-time task energy consumption deviation of the auxiliary robot with the predefined task energy consumption adaptation deviation, if the real-time task energy consumption deviation of the auxiliary robot is smaller than or equal to the task energy consumption adaptation deviation, executing the main robot to allocate the auxiliary robot to operate, and if the real-time task energy consumption deviation of the auxiliary robot is larger than the task energy consumption adaptation deviation, invoking the standby robot to execute the migration task together with the auxiliary robot, and forming parallel cooperation with the main robot.

Description

Multi-robot cooperative control method based on new energy street lamp production line data Technical Field The invention relates to the technical field of robot cooperative control, in particular to a multi-robot cooperative control method based on new energy street lamp production line data. Background At present, the multi-robot control of the street lamp production line mainly relies on pre-programming and fixed logic to coordinate the actions of robots, task allocation is based on the initial programming of production tasks, the robots execute the tasks according to preset sequences and tracks, and less dynamic adjustment is achieved or fine adjustment is achieved only according to simple sensor feedback. In the production of complex new energy street lamps, the traditional mode is difficult to adapt to the rapid switching of street lamps of different types due to the problems of unreasonable task allocation, insufficient real-time adjustment, low efficiency of resource utilization and the like, so that the production efficiency and the product quality are reduced. Therefore, development of a new energy street lamp production line with high automation and flexibility is needed, and the collaborative operation of multiple robots can be realized, so that the production efficiency and the product quality are improved. For example, the invention patent with publication number CN118394009B discloses a production and assembly control method for medium-light intensity obstruction lights, which relates to the field of automation control, and comprises the steps of obtaining Q node configuration information; extracting target assembly quantity, inquiring a history assembly control scheme to obtain a plurality of history assembly control schemes, calculating the adaptability, taking a stage history assembly control scheme corresponding to the maximum adaptability as an adjustment target, adjusting the rest plurality of history assembly control schemes, restricting an adjustment process by using Q node transfer capacity and Q node assembly efficiency adjustable spaces to obtain a plurality of updated history assembly control schemes, adjusting and optimizing again to generate the target assembly control scheme, and controlling Q assembly nodes. For example, the invention patent with publication number CN116339260A discloses a production time adjustment analysis method and system for flexible manufacturing of a black lamp factory, and relates to the field of process control. The method comprises the steps of obtaining the number of machines and the circulation time of the machines of a flexible production line, obtaining the production index of a preset product, each process flow and the production time of each process flow, obtaining the takt time of the product according to the production index and the circulation time of the machines, improving each process flow, and observing and recording the production time of each improved process flow. According to the technical scheme, the existing production line control technology is found, static process splitting and single process constraint are mostly carried out on the basis of existing historical data to control the production line, and due to the process complexity and diversity of the street lamp production line, multiple robots are needed to cooperate on the production line, the existing technology lacks of flexible control of real-time data of the production line, the problems of mismatching of task allocation and low cooperation rate of the multiple robots are easy to occur, and the efficiency and quality of the production line are greatly reduced. Disclosure of Invention Aiming at the defects of the prior art, the invention provides a multi-robot cooperative control method based on new energy street lamp production line data, which can effectively solve the problems related to the background art. The multi-robot cooperative control method based on the new energy street lamp production line data comprises the following steps of enabling a central control port to receive a street lamp assembly total task of a production line, performing task decomposition to obtain functional domain tasks to be assembled, generating a preparation calling signal to a signal receiving port of each assembly robot in the production line, enabling the signal receiving port to receive the preparation calling signal, acquiring real-time execution data of each assembly robot, judging real-time load evaluation values of each assembly robot, feeding back real-time load state data of each assembly robot to the central control port, judging whether cooperative adjustment of the assembly robots is performed or not, performing cooperative adjustment of the functional domain tasks to be assembled on each assembly robot through the central control port according to the real-time load state data, monitoring current task execution conditions of each assembly robot in real time, and feeding back