Multi-robot cooperation path anti-collision method and system

Abstract

The invention discloses a multi-robot cooperative path anti-collision method and system, and relates to the technical field of robot path control. The multi-robot cooperative path anti-collision method comprises the following steps of data acquisition, time anti-collision measure taking and space anti-collision measure taking. Time data and space data are obtained through a data acquisition method, a time window overlapping degree coefficient is obtained based on the time data, whether corresponding time anti-collision measures are taken or not is judged according to the time window overlapping degree coefficient and a time threshold value, and a space distance evaluation coefficient is obtained according to the space data. And whether corresponding space anti-collision measures are taken or not is judged based on the space distance evaluation coefficient and the distance threshold value, so that the effect of improving the anti-collision accuracy in the multi-robot cooperation process is achieved, and the problem of inaccurate anti-collision in the multi-robot cooperation process in the prior art is solved.

Description

Technical Field

[0001] The present invention relates to the technical field of robot path control, and in particular to a multi-robot collaborative path anti-collision method and system. Background Art

[0002] With the development of Industry 4.0, the demand for multiple robots in automated production lines and intelligent warehousing systems has increased significantly. However, when multiple robots are working at the same time, how to effectively plan their paths, avoid collisions, optimize efficiency, and reduce energy consumption is a technical challenge. The traditional path planning method of a single robot can no longer meet the complex needs of multiple robots working together. Through optimization algorithms, real-time data processing and perception technology, the multi-robot operation path generation system can assign the optimal path to each robot in a dynamic environment to achieve an efficient and conflict-free operation process. This technology has broad application prospects in scenarios such as smart factories, unmanned warehousing and automated distribution.

[0003] Existing technologies mainly focus on path planning algorithms, collaborative control and obstacle avoidance technologies. Common methods include A-Star Algorithm, Dijkstra's Algorithm, ant colony algorithm, genetic algorithm, etc. These algorithms generate paths for single or multiple robots by calculating the shortest path, global optimization, etc. In addition, two main architectures, distributed control system and central control system, are used to achieve collaboration among multiple robots and ensure the coordination of task allocation and execution. Obstacle avoidance technology usually relies on lidar, infrared sensors or vision systems to perceive environmental changes and dynamically adjust the path.

[0004] For example, the invention patent with announcement number: CN112415997B announces a path planning method and system for multi-robot collaboration, including: system initialization, obtaining the initial position, target position and path set of each robot, and establishing a global two-dimensional grid map of the robot's operating environment; each robot uses visual sensors, ultrasonic sensors, infrared sensors, lidar and other devices to detect the environment to perceive the surrounding environment, and sends the local position information and perceived environmental information to the path planning server; the path planning server locks the decision area for the robot, and selects the initial predicted position and optimized predicted position for each robot during the movement process through the multi-robot collaborative path planning method, thereby realizing multi-robot collaborative path planning.

[0005] For example, the path generation method and generation device, intelligent robot and storage medium announced in the invention patent with announcement number: CN110928320B include: acquiring continuous multi-frame point cloud data; identifying curb point cloud data in the multi-frame point cloud data, the curb point cloud data is the point cloud data corresponding to the points on the curb of the road; and generating a moving path according to the curb point cloud data and controlling the intelligent robot to move along the moving path.

[0006] However, in the process of implementing the technical solution of the invention in the embodiments of the present application, the present application found that the above technology has at least the following technical problems: In the existing technology, in actual production environments, dynamic obstacles (such as other robots, workers or mobile equipment) often appear due to various emergencies, such as in addition to static obstacles. Although robots are uniformly equipped with dynamic obstacle avoidance capabilities, it is still a difficult problem to accurately predict and respond to these rapidly changing dynamic obstacles in real-time complex environments, and there is a problem of inaccurate collision prevention during multi-robot collaboration. Summary of the invention

[0007] The embodiments of the present application solve the problem of inaccurate collision prevention in the multi-robot collaboration process in the prior art by providing a multi-robot collaboration path collision prevention method and system, thereby improving the accuracy of collision prevention in the multi-robot collaboration process.

[0008] An embodiment of the present application provides a multi-robot collaborative path collision avoidance method, comprising the following steps: obtaining time data and space data through a data acquisition method; obtaining a time window overlap coefficient based on the time data, and judging whether to take corresponding time collision avoidance measures according to the time window overlap coefficient and a time threshold obtained from a preset database, wherein the time window overlap coefficient is used to quantify the degree of overlap of the time operation windows of each robot's collaborative operation; obtaining a space distance evaluation coefficient according to the space data, and judging whether to take corresponding space collision avoidance measures based on the space distance evaluation coefficient and a distance threshold obtained from a preset database, wherein the space distance evaluation coefficient is used to quantify the possibility of collision between each robot.

[0009] Furthermore, the acquisition process of the time data is as follows: obtain collaborative work characteristic data and robot execution characteristic data; the collaborative work characteristic data includes the length of the conveyor line path and the start time of the operation; the robot execution characteristic data includes the robot running speed, bottle grabbing time, bottle inserting time, bottle placing time, operation adjustment time, sensor update frequency and sensor lag time, and the sensor update frequency is normalized; the operation path duration is obtained based on the length of the conveyor line path and the robot running speed; the time data includes the start time of the operation, the operation path duration, the bottle grabbing time, the bottle inserting time, the bottle placing time and the operation adjustment time Duration; the steps for acquiring the spatial data are: acquiring the relative position of each robot and the bottle position on the conveyor line through a visual sensor; scanning the working space through a laser ranging sensor to detect the distance between the robot and the conveyor line and its corresponding environment; sending ultrasonic signals through an ultrasonic sensor and receiving reflected signals to measure the distance to objects in the environment, and acquiring the spatial position coordinates of each robot according to the established environmental map; acquiring the work shop area through the environmental map and de-unitizing the work shop area, and acquiring the number of conveyor lines by searching for collaborative work requirements; the spatial data includes spatial position coordinates, work shop area and the number of conveyor lines.

[0010] Furthermore, the acquisition process of the time window overlap coefficient is as follows: number each robot, establish a corresponding time operation window based on the time data of each robot, and obtain the corresponding start time and end time based on the established time operation window; establish the corresponding time vector coordinates according to the start time and the end time, and obtain the corresponding time vector set through the time vector coordinates of each robot; input two different time vector coordinates, sensor update frequency and sensor lag time into the time window overlap calculation model to obtain the time window overlap coefficient, and the specific restriction expression is: ; ; In the formula, Indicates the number of each robot, , N represents the total number of robots, represents the start time of the time operation window of the nth robot, Indicates the end time of the time operation window of the nth robot, Indicates the duration of the operation path of the nth robot, It indicates the bottle grabbing time of the nth robot. It indicates the time it takes for the nth robot to insert the bottle. It indicates the time it takes for the nth robot to place the bottle. Indicates the operation adjustment duration of the nth robot. represents the start time of the time operation window of the ith robot, represents the end time of the time operation window of the ith robot, represents the start time of the time operation window of the jth robot, represents the end time of the time operation window of the jth robot, represents the sensor update frequency of the nth robot, represents the sensor lag time of the nth robot, represents the time window overlap coefficient of the i-th robot and the j-th robot, , j ,and , e represents a natural constant.

[0011] Furthermore, the specific process of judging whether to take corresponding time collision avoidance measures according to the time window overlap coefficient and the time threshold obtained from the preset database is as follows: if the time window overlap coefficient is less than the time threshold, a zero intervention time window measure is taken; if the time window overlap coefficient is not less than the time threshold, a time staggered measure is taken; the specific steps of the time staggered measure are as follows: step one, judging whether the conveyor lines of each robot are consistent, if the conveyor lines are inconsistent, a parallel execution strategy is adopted, the parallel execution strategy means that each robot works collaboratively on different conveyor lines at the same time, otherwise step two is executed; step two, judging the preset priority of each robot Whether they are consistent: If the preset priorities are consistent, the time operation window of one of the robots with a smaller number will be adjusted to a staggered time operation window, where the staggered time operation window is the sum of the time operation window and the staggered time interval, and the staggered time interval is used to delay the time interval duration of the operation start time of each robot; if the preset priorities are inconsistent, the time operation window of each robot will be adjusted to a buffer time operation window, where the buffer time operation window is the sum of the time operation window and the dynamic buffer duration, and the dynamic buffer duration is represented by the extended collaborative operation duration of each robot; the time anti-collision measures include time staggered measures and zero intervention time window measures.

[0012] Furthermore, the process of obtaining the spatial distance evaluation coefficient is as follows: establishing corresponding two-dimensional space vector coordinates based on the spatial position coordinates of each robot, and obtaining a spatial vector set by integrating the two-dimensional space vector coordinates of each robot; obtaining the horizontal coordinates and vertical coordinates of two different two-dimensional space vector coordinates in the spatial vector set, and obtaining the square difference of the horizontal coordinate according to the horizontal coordinates of the two different two-dimensional space vector coordinates, and obtaining the square difference of the vertical coordinate according to the vertical coordinates of the two different two-dimensional space vector coordinates; inputting the square difference of the horizontal coordinate and the square difference of the vertical coordinate as well as the obtained work shop area and the number of conveyor lines into the spatial distance evaluation calculation model to obtain the spatial distance evaluation coefficient.

[0013] An embodiment of the present application provides a multi-robot collaborative path collision avoidance system, comprising a data acquisition module, a time collision avoidance module and a space collision avoidance module; wherein the data acquisition module is used to obtain time data and space data through a data acquisition method; the time collision avoidance module is used to obtain a time window overlap coefficient based on time data, and judge whether to take corresponding time collision avoidance measures according to the time window overlap coefficient and a time threshold obtained from a preset database, wherein the time window overlap coefficient represents the degree of overlap of time operation windows for quantifying the collaborative operation of each robot; the space collision avoidance module is used to derive a space distance evaluation coefficient according to space data, and judge whether to take corresponding space collision avoidance measures based on the space distance evaluation coefficient and a distance threshold obtained from a preset database, wherein the space distance evaluation coefficient is used to quantify the possibility of collision between each robot.

[0014] One or more technical solutions provided in the embodiments of the present application have at least the following technical effects or advantages: 1. Whether to take corresponding time anti-collision measures is determined by the obtained time window overlap coefficient and the time threshold obtained from the preset database, and whether to take corresponding space anti-collision measures is determined based on the obtained space distance evaluation coefficient and the distance threshold obtained from the preset database, thereby reducing the possibility of collision between robots, thereby achieving improved accuracy of anti-collision in the process of multi-robot collaboration, and effectively solving the problem of inaccurate anti-collision in the process of multi-robot collaboration in the prior art.

[0015] 2. By numbering each robot and establishing a corresponding time operation window based on the time data of each robot, and obtaining the corresponding start time and end time based on the established time operation window, the corresponding time vector coordinates are established according to the start time and the end time, and the corresponding time vector set is obtained through the time vector coordinates of each robot. Two different time vector coordinates are input into the time window overlap calculation model to obtain the time window overlap coefficient, so that each robot is staggered in time when performing collaborative work, thereby reducing the possibility of collision between robots in time.

[0016] 3. A spatial vector set is obtained by integrating the two-dimensional spatial vector coordinates of each robot, and then the horizontal and vertical coordinates of two different two-dimensional spatial vector coordinates in the spatial vector set are obtained, and the square difference of the horizontal coordinate and the square difference of the vertical coordinate are obtained accordingly. Finally, the square difference of the horizontal coordinate and the square difference of the vertical coordinate are input into the spatial distance evaluation calculation model to obtain the spatial distance evaluation coefficient, thereby reducing the possibility of collision between each robot when performing collaborative work, thereby reducing the collision incidence rate of each robot during collaborative work. BRIEF DESCRIPTION OF THE DRAWINGS

[0017] Figure 1A flowchart of a multi-robot collaborative path collision avoidance method provided in an embodiment of the present application; Figure 2 A schematic diagram of the spatial distance evaluation coefficient provided in an embodiment of the present application changing with the square difference of the horizontal coordinate; Figure 3 A schematic diagram of the spatial distance evaluation coefficient provided in an embodiment of the present application changing with the square difference of the ordinate; Figure 4 A schematic diagram of the structure of a multi-robot collaborative path collision avoidance system provided in an embodiment of the present application. DETAILED DESCRIPTION

[0018] The embodiment of the present application solves the problem of inaccurate collision avoidance in the multi-robot collaboration process in the prior art by providing a multi-robot collaboration path collision avoidance method and system. Time data and space data are obtained through a data acquisition method, and a time window overlap coefficient is obtained based on the time data. It is determined whether to take corresponding time collision avoidance measures according to the time window overlap coefficient and a time threshold obtained from a preset database, and a space distance evaluation coefficient is obtained according to the space data. It is determined whether to take corresponding space collision avoidance measures based on the space distance evaluation coefficient and the distance threshold obtained from the preset database, thereby improving the accuracy of collision avoidance in the multi-robot collaboration process.

[0019] The technical solution in the embodiment of the present application is to solve the problem of inaccurate anti-collision in the above-mentioned multi-robot collaboration process, and the overall idea is as follows: Whether to take corresponding time anti-collision measures is determined by combining the obtained time window overlap coefficient with the time threshold obtained from the preset database, and whether to take corresponding space anti-collision measures is determined based on the obtained space distance evaluation coefficient and the distance threshold obtained from the preset database, thereby achieving the effect of improving the accuracy of anti-collision in the multi-robot collaboration process.

[0020] In order to better understand the above technical solution, the above technical solution will be described in detail below in conjunction with the accompanying drawings and specific implementation methods.

[0021] like Figure 1As shown, it is a flow chart of a multi-robot collaborative path anti-collision method provided by an embodiment of the present application, the method comprising the following steps: obtaining time data and space data through a data acquisition method, the data acquisition method comprising searching for collaborative operation requirements, searching for robot operation specifications and obtaining positioning sensor data, the time data is used to describe the time arrangement of each robot for collaborative operation, the collaborative operation represents that a preset number of robots jointly complete the non-collision bottle insertion and bottle placement operation on the conveyor line, and the positioning sensor is used to form the spatial position coordinates of each robot during collaborative operation; obtaining a time window overlap coefficient based on the time data, judging whether to take corresponding time anti-collision measures according to the time window overlap coefficient and the time threshold obtained from the preset database, the time window overlap coefficient is used to quantify the degree of overlap of the time operation windows of each robot collaborative operation, and the time threshold represents the maximum limit of the time window overlap coefficient specified in the multi-robot collaborative path anti-collision method; obtaining a space distance evaluation coefficient based on the space data, judging whether to take corresponding space anti-collision measures based on the space distance evaluation coefficient and the distance threshold obtained from the preset database, the space distance evaluation coefficient is used to quantify the possibility of collision between each robot, and the distance threshold represents the minimum limit of the space distance evaluation coefficient specified in the multi-robot collaborative path anti-collision method.

[0022] In this embodiment, the collaborative work requirements include the task objectives set for each robot (such as inserting bottles, placing bottles, etc.), the work sequence, and the time requirements and space requirements (such as the operation time between robots cannot overlap to avoid interference); the robot operation specifications include the operation process (such as grabbing bottles, inserting bottles, placing bottles, etc.) and action constraints (such as running speed, action operation time, etc.). In addition, the positioning sensor exchanges information through communication interfaces and protocols. The communication interface includes wired interfaces and wireless interfaces. The wired interfaces are such as USB (Universal Serial Bus), RS232 (Recommended Standard232), RS485 (Recommended Standard 485), and the wireless interfaces are such as Wi-Fi (Wireless Fidelity), Bluetooth, Zigbee, and LoRa (Long Range). The protocols that can be used by the positioning sensor are NMEA (NationalMarine Electronics Association, used for GPS), MODBUS (Originally derived from "Modicon Bus", used for industrial automation), TCP / IP (Transmission Control Protocol / InternetProtocol) etc.; through the method provided in the embodiment of the present application, anti-collision management in time and space is realized, ensuring that no collision occurs between robots during the collaboration process, thereby improving the accuracy of anti-collision of collaborative tasks.

[0023] Furthermore, the process of acquiring time data is as follows: acquiring collaborative work characteristic data by searching for collaborative work requirements, acquiring robot execution characteristic data by searching for robot operation specifications, the collaborative work characteristic data includes the length of the conveyor line path and the start time of the operation, the robot execution characteristic data includes the robot operation speed, bottle grabbing time, bottle insertion time, bottle placement time, operation adjustment time, sensor update frequency and sensor lag time, and the sensor update frequency is normalized; the operation path duration is obtained based on the length of the conveyor line path and the robot operation speed; the time data includes the start time of the operation, the operation path duration, the bottle grabbing time, the bottle insertion time, the bottle placement time and the operation adjustment time; the steps for acquiring spatial data The method is as follows: the relative position of each robot and the position of the bottle on the conveyor line are obtained through the visual sensor; the distance between the robot and the conveyor line and its corresponding environment is detected by scanning the working space through the laser ranging sensor; the distance to the objects in the environment is measured by sending ultrasonic signals and receiving reflected signals through the ultrasonic sensor, and the spatial position coordinates of each robot are obtained according to the established environmental map. The environmental map is established through the SLAM technology, and the positioning sensors include visual sensors, laser ranging sensors and ultrasonic sensors; the area of ​​the work shop is obtained through the environmental map and the work shop area is de-unitized, and the number of conveyor lines is obtained by searching for collaborative work requirements; the spatial data includes spatial position coordinates, the area of ​​the work shop and the number of conveyor lines.

[0024] In this embodiment, SLAM (Simultaneous Localization and Mapping) technology is a technology used for robots or unmanned driving systems. The system needs to locate its own position in real time in an unknown environment through sensors (such as lidar, ultrasound, etc.), and at the same time build a map of the surrounding environment; and the visual sensor is deployed at the front center point of each robot, the laser ranging sensor is deployed at the top center point of each robot, and the ultrasonic sensor is deployed at the side center point of each robot; by combining the visual sensor, laser ranging sensor and ultrasonic sensor, the position coordinates of each robot and bottle can be accurately obtained, ensuring accurate position recognition during collaborative operation, performing accurate spatial and temporal data calculations, ensuring that the robot can efficiently complete operations such as grabbing bottles, inserting bottles, and placing bottles, reducing waiting time and unnecessary operation adjustments, and improving overall work efficiency.

[0025] Specifically, the normalization process is performed using the following formula: ; It is important to understand that Represents the original data, Represents the minimum data in a set of data. Represents the maximum data in a set of data. Represents the normalized data.

[0026] Specifically, the de-unitization process is performed using the following formula: ; It is important to understand that Represents the original data, Represents unit area, It represents the data after de-unitization, and the unit area means per square meter.

[0027] Furthermore, time data and space data are obtained, and then the operating status information of each robot is obtained; the specific steps for obtaining the operating status information of each robot are: obtaining the preset priority corresponding to each robot, the preset priority represents the order of collaborative work of each robot determined according to the importance of each robot's task; obtaining the operating status information of each robot through the communication interface of each robot, the operating status information includes movement direction, operating status, position update frequency and remaining power, the operating status includes operating failure and normal operation, and the communication interface is used to obtain the operating status information of the robot.

[0028] In this embodiment, the preset operator allocates the corresponding bottle production volume to each conveyor line according to the production requirements, uses the quick sorting method to sort the bottle production volumes corresponding to all conveyor lines in ascending order, and sets different preset priorities for each robot performing the corresponding conveyor line collaborative operation in accordance with the sorting order. The robots performing the conveyor lines with large bottle production volumes have high preset priorities, while the robots performing the conveyor lines with small bottle production volumes have low preset priorities. The operation status information of each robot is obtained through the communication interface, so that real-time status monitoring of each robot is realized, and operation faults can be identified and processed in time to ensure the stability and safety of the operation of each robot. The robots are dispatched by monitoring the remaining power to avoid task interruption caused by insufficient power.

[0029] Furthermore, the process of obtaining the time window overlap coefficient is as follows: number each robot, establish a corresponding time operation window based on the time data of each robot, and obtain the corresponding start time and end time based on the established time operation window; establish the corresponding time vector coordinates according to the start time and end time, and obtain the corresponding time vector set through the time vector coordinates of each robot; input two different time vector coordinates, sensor update frequency and sensor lag time into the time window overlap calculation model to obtain the time window overlap coefficient. The specific restriction expression is: ; ; In the formula, Indicates the number of each robot, , N represents the total number of robots, represents the start time of the time operation window of the nth robot, Indicates the end time of the time operation window of the nth robot, Indicates the duration of the operation path of the nth robot, It indicates the bottle grabbing time of the nth robot. It indicates the time it takes for the nth robot to insert the bottle. It indicates the time it takes for the nth robot to place the bottle. Indicates the operation adjustment duration of the nth robot. represents the start time of the time operation window of the ith robot, represents the end time of the time operation window of the ith robot, represents the start time of the time operation window of the jth robot, represents the end time of the time operation window of the jth robot, represents the sensor update frequency of the nth robot, represents the sensor lag time of the nth robot, represents the time window overlap coefficient of the i-th robot and the j-th robot, , j ,and , e represents a natural constant.

[0030] In this embodiment, the algorithm combines the start time, the operation path length, the bottle grabbing time, the bottle inserting time, the bottle releasing time, the operation adjustment time, the sensor update frequency and the sensor lag time for comprehensive analysis to obtain the time window overlap coefficient, and the end time is obtained by the start time, the operation path length, the bottle grabbing time, the bottle inserting time, the bottle releasing time and the operation adjustment time. In the time window overlap calculation model, the independent variables are the start time and the end time. When the difference between the start time and the end time of the two robots is smaller, the time window overlap coefficient is larger, indicating that the higher the degree of overlap of the time windows of the two robots, the greater the possibility of collision when performing collaborative work. When the sensor update frequency is smaller and the sensor lag time is larger, the risk of collision of each robot is increased in time. Therefore, by evaluating the degree of overlap of the time windows through the time window overlap coefficient, it is possible to effectively evaluate the possibility of collision caused by each robot being at the same conveyor line position at the same time during collaborative work.

[0031] Specifically, when the influence of sensor update frequency and sensor lag time on the time window overlap coefficient is not considered, the time window overlap coefficient change table is obtained by combining the start time, operation path duration, bottle grabbing duration, bottle inserting duration, bottle placing duration and operation adjustment duration, as shown in Table 1: Table 1 Time window overlap coefficient change table

[0032] It can be seen from Table 1 that when the difference between the start time and the end time of the two robots is smaller, the time window overlap coefficient is larger. For example, the two rows of data with robot numbers 1 and 2 have the same start time and a difference of 5 minutes in the end time. The time operation windows of the two robots overlap for 14 minutes, and the corresponding time window overlap coefficient is 0.76. The two rows of data with robot numbers 5 and 6 have a difference of 5 minutes in the start time and a difference of 3 minutes in the end time. The time operation windows of the two robots overlap for 11 minutes, and the corresponding time window overlap coefficient is 0.60. It can be obtained that when the difference between the start time and the end time is smaller, the overlap duration of the time operation window is longer, thereby making the time window overlap coefficient larger. Therefore, regulating the start time and end time of each robot through time dislocation measures can effectively reduce the probability of sending collisions between robots.

[0033] Furthermore, the specific process of judging whether to take the corresponding time anti-collision measures according to the time window overlap coefficient and the time threshold obtained from the preset database is as follows: if the time window overlap coefficient is less than the time threshold, the zero intervention time window measure is taken; if the time window overlap coefficient is not less than the time threshold, the time staggered measure is taken; the specific steps of the time staggered measure are as follows: step one, judging whether the conveyor lines of each robot are consistent, if the conveyor lines are inconsistent, adopting a parallel execution strategy, which means that each robot works collaboratively on different conveyor lines at the same time, otherwise executing step two; step two, judging the preset priority of each robot Whether the priorities are consistent: If the preset priorities are consistent, the time operation window of one of the robots with a smaller number will be adjusted to a staggered time operation window. The staggered time operation window is the sum of the time operation window and the staggered time interval. The staggered time interval is used to delay the time interval duration of the operation start time of each robot; if the preset priorities are inconsistent, the time operation window of each robot will be adjusted to a buffer time operation window. The buffer time operation window is the sum of the time operation window and the dynamic buffer duration. The dynamic buffer duration is expressed as the extended collaborative operation duration of each robot; time collision avoidance measures include time staggered measures and zero intervention time window measures.

[0034] In this embodiment, the staggered time interval is usually a preset fixed time interval, such as one minute, three minutes or five minutes. In a specific embodiment, the staggered time interval can be set to the average of the bottle grabbing time, bottle inserting time, bottle placing time and operation adjustment time; by judging the time window overlap coefficient and the time threshold, it can effectively avoid collisions between robots in the same or similar time periods, ensure the smoothness of the operation, and improve the automation level and operation smoothness of the multi-robot collaborative path collision avoidance method.

[0035] Specifically, the time threshold is obtained from a preset database. In a specific embodiment, the time threshold is the maximum limit of the time window overlap coefficient specified by the multi-robot collaborative path anti-collision method. The maximum limit is tested by scene simulation to obtain the minimum value of the time window overlap coefficient that enables each robot to perform collaborative work on the same conveyor line at the same time in the application environment. The scene simulation test means performing a simulation test according to the specific environment and task of each robot's collaborative work. During the simulation test, the time operation window of each robot is changed and it is observed whether each robot performs collaborative work on the same conveyor line at the same time. For example, if the scene simulation test shows that the minimum value of the time window overlap coefficient that enables each robot to perform collaborative work on the same conveyor line at the same time in the application environment is 0.6, then 0.6 is the time threshold.

[0036] Furthermore, the steps for determining the dynamic buffer duration are as follows: S1, the completion time of the collaborative tasks of each robot with different preset priorities is counted through historical data to obtain the average completion time corresponding to the preset priority, and the average completion time is calculated using the following formula: ; In the formula, Indicates the number of each robot, , N represents the total number of robots, Indicates the time it takes to complete the first robot's collaborative work. Indicates the time it takes for the second robot to complete the collaborative task. Indicates the completion time of the collaborative work of the Nth robot. Indicates the average completion time.

[0037] S2, count the completion time percentiles of each robot with the corresponding preset priority, and construct a percentile mapping set of completion time percentiles and dynamic buffer time. Obtain the dynamic buffer time of each robot with the corresponding preset priority through the percentile mapping set. If the dynamic buffer time between each robot is different, adjust the time operation window of each robot to the buffer time operation window, otherwise execute S3.

[0038] S3, construct a mapping set of completion time standard deviation and dynamic buffer duration, and obtain the dynamic buffer duration corresponding to each robot based on the mapping set of completion time standard deviation and dynamic buffer duration. If the dynamic buffer durations of the robots are different, adjust the time operation window of each robot to the buffer time operation window, otherwise execute S4, the completion time standard deviation is obtained according to the collaborative operation completion time of each robot with preset priority in the historical data and the corresponding average completion time, and the completion time standard deviation is calculated using the following formula: ; In the formula, Indicates the number of each robot, , N represents the total number of robots, Indicates the completion time of the collaborative work of the nth robot. represents the average completion time, represents the standard deviation of completion time.

[0039] S4, compare the standard deviation of the completion time corresponding to each robot of the preset priority with the average completion time to obtain the dynamic buffer time. If the dynamic buffer time between the robots is different, adjust the time operation window of each robot to the buffer time operation window, otherwise execute S5.

[0040] S5, insert the dynamic buffer duration obtained by S2 after the end time of the time operation window of the robot with a higher preset priority among the two robots, and insert the dynamic buffer duration obtained by S2 and the staggered time interval after the end time of the time operation window of the robot with a lower preset priority.

[0041] In this embodiment, according to the differences in priority and completion time of each robot, the time operation window is flexibly adjusted and the buffer time is dynamically inserted to avoid different robots from working together on the same conveyor line at the same time, thereby improving the collaboration efficiency. When the robots have different preset priorities, the time window of the robot with a high preset priority is adjusted to ensure that the task with a high priority is completed first, and at the same time, the task with a low preset priority is allocated with a suitable dynamic buffer time and staggered time interval. This effectively reduces the overlap of the time operation windows of each robot, prevents task collisions, and improves the smoothness of collaborative work.

[0042] Furthermore, the process of obtaining the spatial distance evaluation coefficient is as follows: based on the spatial position coordinates of each robot, the corresponding two-dimensional space vector coordinates are established, and the spatial vector set is obtained by integrating the two-dimensional space vector coordinates of each robot; the horizontal coordinates and vertical coordinates of two different two-dimensional space vector coordinates in the spatial vector set are obtained, and the horizontal coordinate square difference is obtained according to the horizontal coordinates of the two different two-dimensional space vector coordinates, and the vertical coordinate square difference is obtained according to the vertical coordinates of the two different two-dimensional space vector coordinates; the horizontal coordinate square difference and the vertical coordinate square difference as well as the obtained workshop area and the number of conveyor lines are input into the spatial distance evaluation calculation model to obtain the spatial distance evaluation coefficient. The spatial distance evaluation calculation model is used to obtain the spatial distance evaluation coefficient. The specific restriction expression is: ; ; ; In the formula, Indicates the number of each robot, , N represents the total number of robots, represents the horizontal coordinate of the nth robot, represents the horizontal coordinate of the first robot, represents the horizontal coordinate of the second robot, represents the horizontal coordinate of the Nth robot, represents the ordinate of the nth robot, Indicates the vertical coordinate of the first robot, represents the ordinate of the second robot, represents the ordinate of the Nth robot, represents the two-dimensional space vector coordinates of the nth robot, represents the two-dimensional space vector coordinates of the first robot, represents the two-dimensional space vector coordinates of the second robot, represents the two-dimensional space vector coordinates of the Nth robot, represents the horizontal coordinate of the jth robot, represents the horizontal coordinate of the ith robot, represents the ordinate of the jth robot, represents the ordinate of the ith robot, Indicates the area of ​​the work shop, Indicates the number of conveyor lines. represents the spatial distance evaluation coefficient between the i-th robot and the j-th robot, , j ,and , e represents a natural constant.

[0043] In this embodiment, the algorithm combines the square difference of the horizontal coordinate, the square difference of the vertical coordinate, the area of ​​the work shop and the number of conveyor lines for comprehensive analysis to obtain the spatial distance evaluation coefficient, and the square difference of the horizontal coordinate, the square difference of the vertical coordinate, the area of ​​the work shop and the number of conveyor lines are positively correlated with the spatial distance evaluation coefficient. By combining the square difference of the horizontal coordinate and the square difference of the vertical coordinate, a schematic diagram of the change of the spatial distance evaluation coefficient is obtained, as shown in detail. Figure 2 and Figure 3 As shown in the image, it can be seen that with the increase of the square difference of the horizontal coordinate and the square difference of the vertical coordinate, the spatial distance evaluation coefficient also increases, and the image shows an upward trend, which further proves that the square difference of the horizontal coordinate and the square difference of the vertical coordinate are positively correlated with the spatial distance evaluation coefficient. The larger the spatial distance evaluation coefficient, the greater the spatial distance between the robots, which makes the possibility of collision smaller; the spatial distance evaluation coefficient quantitatively evaluates the possibility of collision between robots, thereby reducing the possibility of collision between robots.

[0044] Furthermore, the specific content of judging whether to take corresponding spatial collision avoidance measures based on the spatial distance evaluation coefficient and the distance threshold obtained from the preset database is as follows: if the spatial distance evaluation coefficient is not less than the distance threshold, zero-intervention spatial position measures are taken; if the spatial distance evaluation coefficient is less than the distance threshold, coordinate deduplication measures are taken, and the deduplication robot is determined by the deduplication judgment condition, and a command instruction is sent to the preset operator. The deduplication robot represents a robot whose spatial position coordinates are deleted, and the command instruction is used to obtain the preset operator's new work task instructions for the deduplication robot; spatial collision avoidance measures include coordinate deduplication measures and zero-intervention spatial position measures.

[0045] In this embodiment, when the distance between each robot exceeds the safe distance, coordinate deduplication measures are used to avoid spatial overlap. When the deduplicated robot is determined by itself, the deduplicated robot operation task instructions are submitted to the preset operator for confirmation and adjustment, thereby realizing the combination of automation and manual intervention and improving the flexibility and safety of the system.

[0046] Specifically, the distance threshold is obtained from a preset database. In a specific embodiment, the distance threshold is the minimum limit of the spatial distance evaluation coefficient specified by the multi-robot collaborative path collision avoidance method. The minimum limit is tested by scene simulation to find the maximum value of the spatial distance evaluation coefficient that causes each robot to collide in the application environment. The scene simulation test means performing a simulation test according to the specific environment and task of each robot's collaborative operation. During the simulation test, the spatial position coordinates of each robot are changed and whether each robot collides is observed. For example, if the scene simulation test finds that the maximum value of the spatial distance evaluation coefficient that causes each robot to collide in the application environment is 0.3, then 0.3 is the distance threshold.

[0047] Furthermore, the specific steps of determining the deduplicated robots through deduplication judgment conditions are as follows: A1, determine whether the movement directions of the robots are consistent. If the movement directions of the robots are inconsistent, execute zero-intervention spatial position measures, otherwise execute A2; A2, determine whether the operating conditions of the robots are all operating failures. If the operating conditions of the robots are all operating failures, an alarm is issued to the preset operator, otherwise the robots with operating conditions of operating failures are recorded as deduplicated robots, and the spatial position coordinates of the deduplicated robots are sent to the preset operator to request maintenance, otherwise execute A3; A3, determine the preset priority of each robot Whether they are consistent, if the preset priorities of the robots are inconsistent, then the robots with low preset priorities will be recorded as deduplicated robots, otherwise execute A4; A4, determine whether the position update frequencies of the robots are consistent, if the position update frequencies of the robots are inconsistent, then the robots with low position update frequencies will be recorded as deduplicated robots, otherwise execute A5; A5, determine whether the remaining power of the robots is consistent, if the remaining power of the robots is inconsistent, then the robots with low remaining power will be recorded as deduplicated robots, otherwise send a selection instruction to the preset operator, and the selection instruction is used to determine the deduplicated robot according to the selection of the preset operator.

[0048] In this embodiment, the deduplicated robots are screened out in sequence according to the direction of movement, operating status, preset priority, position update frequency, and remaining power. When a robot fails, the faulty robot can be automatically identified, and the operator can be notified to request maintenance, thereby ensuring that the position of the faulty robot is deduplicated, while avoiding interference with other robots operating normally. When encountering multiple robot conflicts, robots with low preset priorities will be deduplicated to ensure the normal operation of robots with high preset priorities, ensuring that tasks are completed in order of importance. And when the deduplicated robots cannot be clearly identified through automatic judgment, the final selection right will be given to the preset operator, so that the system can operate autonomously and allow manual intervention, thereby enhancing the system's resilience and flexibility, effectively avoiding spatial collisions between robots, ensuring the smooth completion of collaborative operations, and avoiding waste of resources and task delays.

[0049] like Figure 4As shown, it is a structural schematic diagram of a multi-robot collaborative path collision avoidance system provided in an embodiment of the present application. A multi-robot collaborative path collision avoidance system provided in an embodiment of the present application includes: a data acquisition module, a time collision avoidance module and a space collision avoidance module; wherein the data acquisition module obtains time data and space data through a data acquisition method, and the data acquisition method includes searching for collaborative operation requirements, searching for robot operation specifications and obtaining positioning sensor data, and the time data is used to describe the time arrangement of each robot for collaborative operation, and the collaborative operation indicates that a preset number of robots jointly complete the collision-free bottle insertion and bottle placement operation on the conveyor line, and the positioning sensor is used to form the spatial position coordinates of each robot during collaborative operation; the time collision avoidance module obtains time data and space data based on the time data To the time window overlap coefficient, determine whether to take corresponding time collision avoidance measures based on the time window overlap coefficient and the time threshold obtained from the preset database, the time window overlap coefficient represents the degree of overlap of the time operation windows used to quantify the collaborative operation of each robot, and the time threshold represents the maximum limit of the time window overlap coefficient specified by the multi-robot collaborative path collision avoidance method; the space collision avoidance module derives the space distance evaluation coefficient according to the space data, and determines whether to take corresponding space collision avoidance measures based on the space distance evaluation coefficient and the distance threshold obtained from the preset database, the space distance evaluation coefficient is used to quantify the possibility of collision between each robot, and the distance threshold represents the minimum limit of the space distance evaluation coefficient specified by the multi-robot collaborative path collision avoidance method.

[0050] In this embodiment, by combining time data and space data, the system can comprehensively evaluate the collision risk of each robot's collaborative operation, perform anti-collision management from both time and space dimensions, and ensure the safety and efficiency of multi-robot collaboration.

[0051] To summarize, the embodiments of the present application determine whether to take corresponding time anti-collision measures based on the obtained time window overlap coefficient and the time threshold obtained from the preset database, and determine whether to take corresponding space anti-collision measures based on the obtained space distance evaluation coefficient and the distance threshold obtained from the preset database, thereby reducing the possibility of collision between robots, thereby achieving improved accuracy in anti-collision during multi-robot collaboration, and effectively solving the problem of inaccurate anti-collision during multi-robot collaboration in the prior art.

[0052] It will be appreciated by those skilled in the art that embodiments of the present invention may be provided as methods, systems, or computer program products. Therefore, the present invention may take the form of a complete hardware embodiment, a complete software embodiment, or an embodiment combining software and hardware. Furthermore, the present invention may take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0053] The present invention is described with reference to flowcharts and / or block diagrams of methods, devices (systems), and computer program products according to embodiments of the present invention. It should be understood that each process and / or block in the flowchart and / or block diagram, as well as the combination of processes and / or blocks in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to produce a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowchart and / or block diagram. Figure 1 A process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0054] These computer program instructions may also be stored in a computer-readable memory capable of directing a computer or other programmable data processing device to operate in a specific manner, so that the instructions stored in the computer-readable memory produce an article of manufacture comprising an instruction device, which implements the process Figure 1 A process or multiple processes and / or boxes Figure 1 A function specified in one or more boxes.

[0055] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operating steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing instructions for implementing the process in the computer or other programmable device. Figure 1 A process or multiple processes and / or boxes Figure 1 The steps for the functions specified in one or more boxes.

[0056] Although the preferred embodiments of the present invention have been described, those skilled in the art may make other changes and modifications to these embodiments once they have learned the basic creative concept. Therefore, the appended claims are intended to be interpreted as including the preferred embodiments and all changes and modifications that fall within the scope of the present invention.

[0057] Obviously, those skilled in the art can make various changes and modifications to the present invention without departing from the spirit and scope of the present invention. Thus, if these modifications and variations of the present invention fall within the scope of the claims of the present invention and their equivalents, the present invention is also intended to include these modifications and variations.

Claims

1. A multi-robot collaborative path collision avoidance method, characterized in that: The following steps are involved: The temporal and spatial data are obtained through data collection methods; Based on the time data, a time window overlap coefficient is obtained, and according to the time window overlap coefficient and the time threshold obtained from the preset database, it is determined whether to take corresponding time collision avoidance measures. The time window overlap coefficient is used to quantify the degree of overlap of the time operation windows of each robot collaborative operation; A spatial distance evaluation coefficient is obtained according to the spatial data, and whether to take corresponding spatial collision avoidance measures is determined based on the spatial distance evaluation coefficient and a distance threshold obtained from a preset database. The spatial distance evaluation coefficient is used to quantify the possibility of collision between robots.

2. A multi-robot collaborative path collision avoidance method as claimed in claim 1, characterized in that: The process of obtaining the time data is as follows: Acquire collaborative work feature data and robot execution feature data; The collaborative operation characteristic data includes the length of the conveyor line path and the operation start time; The robot execution characteristic data includes the robot running speed, bottle grabbing time, bottle inserting time, bottle placing time, operation adjustment time, sensor update frequency and sensor lag time, and the sensor update frequency is normalized; The operation path duration is obtained based on the length of the conveyor line path and the robot running speed; The time data includes the operation start time, operation path duration, bottle grabbing duration, bottle inserting duration, bottle placing duration and operation adjustment duration; The steps for obtaining the spatial data are: The relative position of each robot and the position of the bottles on the conveyor line are acquired through visual sensors; The laser ranging sensor is used to scan the working space to detect the distance between the robot and the conveyor line and its corresponding environment; The ultrasonic sensor sends ultrasonic signals and receives reflected signals to measure the distance to objects in the environment, and obtains the spatial position coordinates of each robot based on the established environment map; Obtain the area of ​​the work shop through the environmental map and de-unitize the area of ​​the work shop, and obtain the number of conveyor lines by searching for collaborative work requirements; The spatial data includes spatial position coordinates, workshop area and the number of conveyor lines.

3. A multi-robot collaborative path collision avoidance method as claimed in claim 1, characterized in that: The step of obtaining the time data and the space data further includes obtaining the operation status information of each robot; The specific steps of obtaining the running status information of each robot are: Obtaining a preset priority corresponding to each robot, wherein the preset priority indicates the order in which each robot performs collaborative work; The operation status information of each robot is obtained through the communication interface of each robot, and the operation status information includes movement direction, operation status, position update frequency and remaining power, and the operation status includes operation failure and normal operation.

4. A multi-robot collaborative path collision avoidance method as claimed in claim 2, characterized in that: The process of obtaining the time window overlap coefficient is as follows: Number each robot, establish a corresponding time operation window based on the time data of each robot, and obtain the corresponding start time and end time based on the established time operation window; Establish corresponding time vector coordinates according to the start time and the end time, and obtain the corresponding time vector set through the time vector coordinates of each robot; The two different time vector coordinates, sensor update frequency and sensor lag time are input into the time window overlap calculation model to obtain the time window overlap coefficient. The specific restriction expression is: ； ； In the formula, Indicates the number of each robot, , N represents the total number of robots, represents the start time of the time operation window of the nth robot, Indicates the end time of the time operation window of the nth robot, Indicates the duration of the operation path of the nth robot, It indicates the bottle grabbing time of the nth robot. It indicates the time it takes for the nth robot to insert the bottle. It indicates the time it takes for the nth robot to place the bottle. Indicates the operation adjustment duration of the nth robot. represents the start time of the time operation window of the ith robot, represents the end time of the time operation window of the ith robot, represents the start time of the time operation window of the jth robot, represents the end time of the time operation window of the jth robot, represents the sensor update frequency of the nth robot, represents the sensor lag time of the nth robot, represents the time window overlap coefficient of the i-th robot and the j-th robot, , j ,and , e represents a natural constant.

5. A multi-robot collaborative path collision avoidance method as claimed in claim 4, characterized in that: The specific process of judging whether to take corresponding time anti-collision measures according to the time window overlap coefficient and the time threshold obtained from the preset database is as follows: If the time window overlap coefficient is less than the time threshold, a zero intervention time window measure is adopted; If the time window overlap coefficient is not less than the time threshold, time dislocation measures are taken; The specific steps of the time dislocation measure are as follows: Step 1: determine whether the conveyor lines of each robot are consistent. If the conveyor lines are inconsistent, a parallel execution strategy is adopted, which means that each robot works collaboratively on different conveyor lines at the same time. Otherwise, step 2 is executed. Step 2: Determine whether the preset priorities of each robot are consistent: If the preset priorities are consistent, the time operation window of one of the robots with a smaller number is adjusted to a staggered time operation window, where the staggered time operation window is the sum of the time operation window and the staggered time interval, and the staggered time interval is used to delay the time interval length of the operation start time of each robot; If the preset priorities are inconsistent, the time operation window of each robot is adjusted to a buffer time operation window, where the buffer time operation window is the sum of the time operation window and the dynamic buffer duration, where the dynamic buffer duration is represented by the extended collaborative operation duration of each robot; The time anti-collision measures include time dislocation measures and zero intervention time window measures.

6. A multi-robot collaborative path collision avoidance method as claimed in claim 5, characterized in that: The steps for determining the dynamic buffering duration are as follows: S1, using historical data to count the completion time of collaborative tasks of each robot with different preset priorities, to obtain the average completion time of the corresponding preset priority; S2, counting the completion time percentiles of each robot of the corresponding preset priority, and constructing a percentile mapping set of the completion time percentiles and the dynamic buffer duration, and obtaining the dynamic buffer duration of each robot of the corresponding preset priority through the percentile mapping set. If the dynamic buffer durations of the robots are different, the time operation window of each robot is adjusted to the buffer time operation window, otherwise, executing S3; S3, construct a mapping set of completion time standard deviation and dynamic buffer duration, and obtain the dynamic buffer duration corresponding to each robot based on the mapping set of completion time standard deviation and dynamic buffer duration. If the dynamic buffer durations of the robots are different, adjust the time operation window of each robot to the buffer time operation window, otherwise execute S4; S4, comparing the standard deviation of the completion time corresponding to each robot of the preset priority with the average completion time to obtain the dynamic buffer time. If the dynamic buffer time between the robots is different, the time operation window of each robot is adjusted to the buffer time operation window, otherwise, S5 is executed; S5, insert the dynamic buffer duration obtained by S2 after the end time of the time operation window of the robot with a higher preset priority among the two robots, and insert the dynamic buffer duration obtained by S2 and the staggered time interval after the end time of the time operation window of the robot with a lower preset priority.

7. A multi-robot collaborative path collision avoidance method as claimed in claim 2, characterized in that: The process of obtaining the spatial distance evaluation coefficient is as follows: The corresponding two-dimensional space vector coordinates are established based on the spatial position coordinates of each robot, and the space vector set is obtained by integrating the two-dimensional space vector coordinates of each robot; Obtaining the abscissa and ordinate of two different two-dimensional space vector coordinates in the space vector set, obtaining the abscissa square difference according to the abscissas of the two different two-dimensional space vector coordinates, and obtaining the ordinate square difference according to the ordinates of the two different two-dimensional space vector coordinates; The square difference of the horizontal coordinate and the square difference of the vertical coordinate as well as the obtained work shop area and the number of conveyor lines are input into the spatial distance evaluation calculation model to obtain the spatial distance evaluation coefficient.

8. A multi-robot collaborative path collision avoidance method as claimed in claim 7, characterized in that: The specific content of judging whether to take corresponding spatial anti-collision measures based on the spatial distance evaluation coefficient and the distance threshold obtained from the preset database is as follows: If the spatial distance assessment coefficient is not less than the distance threshold, a zero intervention spatial location measure is adopted; If the spatial distance evaluation coefficient is less than the distance threshold, coordinate deduplication measures are taken, and the deduplication robot is determined by the deduplication judgment condition, and a command instruction is sent to the preset operator. The deduplication robot represents the robot whose spatial position coordinates are deleted; The spatial anti-collision measures include coordinate deduplication measures and zero-intervention spatial position measures.

9. A multi-robot collaborative path collision avoidance method as claimed in claim 8, characterized in that: The specific steps of determining the deduplication robot according to the deduplication judgment condition are as follows: A1, determine whether the movement directions of the robots are consistent. If the movement directions of the robots are inconsistent, execute the zero-intervention spatial position measure, otherwise execute A2; A2, judging whether the operation status of each robot is an operation fault, if the operation status of each robot is an operation fault, an alarm is issued to the preset operator, otherwise each robot with an operation fault is recorded as a deduplicated robot, and the spatial position coordinates of the deduplicated robot are sent to the preset operator to request maintenance, otherwise A3 is executed; A3, determining whether the preset priorities of the robots are consistent. If the preset priorities of the robots are inconsistent, the robots with lower preset priorities are recorded as deduplicated robots. Otherwise, execute A4; A4, determine whether the position update frequencies of the robots are consistent. If the position update frequencies of the robots are inconsistent, the robots with low position update frequencies are recorded as deduplicated robots. Otherwise, execute A5; A5, determine whether the remaining power of each robot is consistent. If the remaining power of each robot is inconsistent, each robot with low remaining power is recorded as a deduplicated robot, otherwise a selection instruction is sent to a preset operator.

10. A multi-robot collaborative path collision avoidance system, characterized in that: It includes data acquisition module, time anti-collision module and space anti-collision module; Wherein, the data acquisition module is used to obtain time data and space data through a data acquisition method; The time anti-collision module is used to obtain a time window overlap coefficient based on time data, and determine whether to take corresponding time anti-collision measures according to the time window overlap coefficient and the time threshold obtained from a preset database, wherein the time window overlap coefficient represents the degree of overlap of the time operation windows used to quantify the collaborative operation of each robot; The spatial collision avoidance module is used to obtain a spatial distance evaluation coefficient based on spatial data, and to determine whether to take corresponding spatial collision avoidance measures based on the spatial distance evaluation coefficient and a distance threshold obtained from a preset database. The spatial distance evaluation coefficient is used to quantify the possibility of collision between robots.

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