Coffee beverage robot three-mechanical-arm operation section time-sharing control method and equipment

Abstract

The invention provides a coffee beverage robot three-mechanical-arm operation sectionalized time-sharing control method and device, and relates to the technical field of cooperative control. The method comprises the steps that mechanical arm task time sequence analysis is carried out according to a task directed acyclic graph to obtain a three-mechanical-arm function activation time sequence; performing operation task sectioning processing to output a plurality of collaborative operation sectors; task trajectory conflict compensation is conducted according to the multiple sets of mechanical arm activation functions in the multiple collaborative operation sections, multiple sets of collaborative control parameters are output to conduct mechanical arm collaborative control over the coffee beverage robot, and coffee order making is executed. The technical problems that in the prior art, due to the fact that a robot is loose in mechanical arm collaborative scheduling logic, coffee making efficiency is low, resource preemption conflicts occur frequently in the making process, the mechanical arm collision risk is increased sharply, and the coffee order process is delayed are solved. The technical effects that efficient parallel operation of multiple mechanical arms, resource conflict avoidance and accurate synchronization of actions are achieved, and the coffee making efficiency and order response real-time performance are remarkably improved are achieved.

Description

Technical Field

[0001] The present invention relates to the field of collaborative control technology, and in particular to a method and device for controlling the segmented time-sharing operation of three robotic arms of a coffee beverage robot. Background Art

[0002] As a key component of smart catering equipment, coffee beverage robots are increasingly being adopted in commercial settings. However, with the increasing demand for personalized coffee production (e.g., customized coffee strength and milk foam thickness), traditional single-arm robotic systems or fixed process control solutions are no longer able to meet the time-sensitive demands of complex production tasks.

[0003] In the existing technology, the collaborative control of multiple robotic arms mostly relies on static task allocation and simple time-series queuing mechanisms, resulting in loose movement connections between robotic arms and frequent resource preemption.

[0004] For example, when making cappuccino, while the extraction robot occupies the brewing head, the raw material processing robot may collide because the path planning does not anticipate spatial conflicts, or the milk foam processing robot is forced to wait for key equipment to be released, causing process delays.

[0005] Furthermore, in scenarios with dynamic order surges, existing scheduling algorithms lack the ability to globally optimize task dependencies and spatiotemporal resources, making it difficult to achieve real-time collaborative obstacle avoidance and efficient parallel operations for multiple robotic arms. This ultimately leads to low production efficiency, poor system stability, and a degraded user experience. These shortcomings severely restrict the large-scale application of coffee beverage robots in high-frequency, multi-category commercial scenarios. Summary of the Invention

[0006] The present invention provides a segmented time-sharing control method and equipment for the three-arm operation of a coffee beverage robot, which is used to solve the technical problems in the prior art of coffee beverage robots, such as low coffee making efficiency and frequent resource preemption conflicts in the production process due to loose collaborative scheduling logic of the robotic arms, resulting in a surge in the risk of robotic arm collisions and delays in the coffee order process.

[0007] In view of the above problems, the present invention provides a method and equipment for segmented time-sharing control of the three-arm operation of a coffee beverage robot.

[0008] In a first aspect, the present invention provides a method for controlling the operation of a coffee beverage robot with three robotic arms in a segmented and time-sharing manner, the method comprising:

[0009] After receiving a real-time coffee order, the task chain is parsed according to the coffee type of the real-time coffee order, and a task directed acyclic graph is output; the robot arm task timing analysis is performed based on the task directed acyclic graph, and the A-arm function activation timing, B-arm function activation timing, and C-arm function activation timing corresponding to the A-arm, B-arm, and C-arm functions are obtained; after time-aligning the A-arm function activation timing, B-arm function activation timing, and C-arm function activation timing, the operation task is segmented and a plurality of collaborative operation segments are output; task trajectory conflict compensation is performed according to the plurality of groups of robot arm activation functions in the plurality of collaborative operation segments, and a plurality of groups of collaborative control parameters are output; within the plurality of collaborative operation segments, the robot arms of the coffee beverage robot are collaboratively controlled according to the plurality of groups of collaborative control parameters, and the production process of the real-time coffee order is executed.

[0010] In one embodiment, after receiving a real-time coffee order, a task chain is parsed based on the coffee type of the real-time coffee order, a task directed acyclic graph is output, and the following processing is performed:

[0011] According to the coffee type of the real-time coffee order, a standard production process is matched from a process rule library; the standard production process is split into atomic tasks to obtain multiple process task units, wherein the multiple process task units are identified with multiple predecessor task dependencies; according to the multiple standard execution times of the multiple process task units and the multiple predecessor task dependencies, multiple task execution time windows are calculated and output; based on the multiple task execution time windows and the multiple task dependencies, the task directed acyclic graph is constructed.

[0012] In one embodiment, a robotic arm task timing analysis is performed based on the task directed acyclic graph to obtain the function activation timing of arm A, arm B, and arm C corresponding to the robotic arm A, arm B, and arm C, and the following processing is further performed:

[0013] According to the task directed acyclic graph, function groups are assigned to the A robot arm, the B robot arm and the C robot arm through a dynamic scheduling algorithm to obtain the A task function group, the B task function group and the C task function group; according to the task execution time and task dependency of the task directed acyclic graph, the A task function group, the B task function group and the C task function group are time-sequentially decomposed to obtain the A arm function activation timing, the B arm function activation timing and the C arm function activation timing.

[0014] In one embodiment, according to the task directed acyclic graph, a dynamic scheduling algorithm is used to assign function groups to the A robot arm, the B robot arm, and the C robot arm to obtain the A task function group, the B task function group, and the C task function group. The following processing is also performed:

[0015] Interactively obtain the robotic arm function group configuration of the coffee beverage robot, wherein the robotic arm function group configuration includes the A initial function group, B initial function group and C initial function group corresponding to the A robotic arm, B robotic arm and C robotic arm; according to the resource requirement attributes of the multiple process task units, map the multiple process task units to the A initial function group, B initial function group and C initial function group to perform function screening to obtain the A candidate function group, B candidate function group and C candidate function group; according to the task timing characteristics in the task directed acyclic graph, perform timing optimization sorting of the A candidate function group, B candidate function group and C candidate function group, and output the A task function group, B task function group and C task function group.

[0016] In one embodiment, task trajectory conflict compensation is performed based on multiple sets of robot arm activation functions in the multiple collaborative operation sections, multiple sets of collaborative control parameters are output, and the following processing is also performed:

[0017] According to the first group of robot arm activation functions in the first collaborative operation section, a single-segment collision-free trajectory is fitted, and a first group of collaborative control parameters are output; according to the connection relationship between the first collaborative operation section and the second collaborative operation section, with the end posture of the first section as the starting point, a single-segment collision-free trajectory is fitted according to the second group of robot arm activation functions, and a second group of collaborative control parameters are output; and so on, according to the multiple groups of robot arm activation functions in the multiple collaborative operation sections, task trajectory conflict compensation is performed section by section, and the multiple groups of collaborative control parameters are output.

[0018] In one embodiment, the task function group A includes raw material processing tasks, the task function group B includes liquid operation tasks, and the task function group C includes dairy product processing tasks.

[0019] In one embodiment, a single-segment collision-free trajectory is fitted based on the first set of robot arm activation functions in the first collaborative operation segment, a first set of collaborative control parameters is output, and the following processing is further performed:

[0020] If the first collaborative operation section is a single-arm section, the single-arm collision-free trajectory is directly fitted according to the obstacle map and the first group of robotic arm activation functions; if the first collaborative operation section is a multi-arm section, collaborative motion planning and spatiotemporal conflict detection are performed according to the first group of robotic arm activation functions, and a joint collision-free trajectory is output; joint state parameters are matched according to the single-arm collision-free trajectory fitting or the joint collision-free trajectory, and the first group of collaborative control parameters is output.

[0021] The second aspect of the present invention provides a segmented time-sharing control device for the three-arm operation of a coffee beverage robot, the device comprising: a task parsing unit, for performing task chain parsing according to the coffee type of the real-time coffee order after receiving a real-time coffee order, and outputting a task directed acyclic graph; a task allocation unit, for performing robot arm task timing analysis based on the task directed acyclic graph, and obtaining the A-arm function activation timing, B-arm function activation timing, and C-arm function activation timing corresponding to the A-arm, B-arm, and C-arm functions; a segment processing unit, for performing segmented operation task processing after time-aligning the A-arm function activation timing, B-arm function activation timing, and C-arm function activation timing, and outputting multiple collaborative operation segments; a trajectory fitting unit, for performing task trajectory conflict compensation according to multiple groups of robot arm activation functions in the multiple collaborative operation segments, and outputting multiple groups of collaborative control parameters; a time-sharing control unit, for performing collaborative control of the robot arms of the coffee beverage robot according to the multiple groups of collaborative control parameters within the multiple collaborative operation segments, and executing the real-time coffee order production process.

[0022] One or more technical solutions provided in the present invention have at least the following technical effects or advantages:

[0023] The method provided by an embodiment of the present invention receives a real-time coffee order, performs task chain parsing based on the coffee type of the real-time coffee order, and outputs a directed acyclic graph of tasks. Based on the directed acyclic graph of tasks, it performs robotic arm task timing analysis to obtain the function activation timing of arm A, arm B, and arm C corresponding to robotic arms A, B, and C. After time-aligning the function activation timings of arm A, arm B, and arm C, it performs task segmentation processing and outputs multiple collaborative operation segments. It then performs task trajectory conflict compensation based on multiple sets of robotic arm activation functions in the multiple collaborative operation segments and outputs multiple sets of collaborative control parameters. Within the multiple collaborative operation segments, the robotic arms of the coffee beverage robot are collaboratively controlled based on the multiple sets of collaborative control parameters to execute the real-time coffee order production process. This method achieves efficient parallel operation of multiple robotic arms, avoids resource conflicts, and precisely synchronizes actions, significantly improving coffee production efficiency, the reliability of robotic arm collaborative operation, and the real-time response to orders. BRIEF DESCRIPTION OF THE DRAWINGS

[0024] Figure 1 A schematic flow chart of the time-sharing control method for the three-arm operation section of a coffee beverage robot provided by the present invention is shown;

[0025] Figure 2 A structural schematic diagram of the three-arm operation section time-sharing control device of the coffee beverage robot provided by the present invention is shown.

[0026] Description of the accompanying symbols: task analysis unit 1, task allocation unit 2, segment processing unit 3, trajectory fitting unit 4, time-sharing control unit 5. DETAILED DESCRIPTION

[0027] The present invention provides a segmented time-sharing control method and equipment for the three-arm operation of a coffee beverage robot, which is used to solve the technical problems in the prior art of coffee beverage robots, such as low coffee making efficiency and frequent resource preemption conflicts in the production process due to loose collaborative scheduling logic of the robotic arms, resulting in a surge in the risk of robotic arm collisions and delays in the coffee order process.

[0028] Below, the technical solutions of the present invention will be clearly and completely described with reference to the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present invention, rather than all the embodiments of the present invention. It should be understood that the present invention is not limited to the example embodiments described herein. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative work are within the scope of protection of the present invention. It should also be noted that, for the convenience of description, only the parts related to the present invention, rather than all, are shown in the accompanying drawings.

[0029] Example 1, a flow chart of the time-sharing control method for the three-arm operation of the coffee beverage robot provided by the embodiment of the present invention, see Figure 1 , the method comprising:

[0030] Step S100: After receiving a real-time coffee order, perform task chain parsing according to the coffee type of the real-time coffee order and output a task directed acyclic graph.

[0031] In one embodiment, after receiving a real-time coffee order, task chain parsing is performed based on the coffee type of the real-time coffee order, and a task directed acyclic graph is output. Step S100 of the method provided by the present invention includes:

[0032] Step S110: According to the coffee type of the real-time coffee order, a standard production process is matched from the process rule library.

[0033] Step S120: performing atomic task splitting on the standard production process to obtain a plurality of process task units, wherein the plurality of process task units are identified with a plurality of predecessor task dependencies.

[0034] Step S130: Calculate and output multiple task execution time windows based on the multiple standard execution times of the multiple process task units and the multiple predecessor task dependencies.

[0035] Step S140: Constructing the task directed acyclic graph according to the multiple task execution time windows and the multiple task dependencies.

[0036] Specifically, the process rule library stores standardized steps for making different types of coffee. For example, a latte requires extracting coffee and then adding steamed milk, while a cappuccino requires additional frothing. Upon receiving a real-time coffee order, the process rule library is searched based on the coffee type, quickly locating the corresponding process template and outputting it as the standard production process.

[0037] Atomic splitting refers to breaking down complex processes into indivisible independent operations. For example, splitting "making espresso" into three task units: "grinding coffee beans", "pressing powder", and "extraction". It is clear that "pressing powder" must be performed after "grinding" is completed, and "extraction" depends on "pressing powder" to be completed.

[0038] Based on this, this embodiment performs atomic task splitting on the standard production process to obtain multiple process task units, wherein the multiple process task units are identified with multiple predecessor task dependencies.

[0039] Based on the preset execution time of each task unit (e.g., grinding takes 30 seconds, extraction takes 25 seconds) and the dependencies between the preceding tasks, the earliest start time and the latest end time of each task unit are determined, and multiple task execution time windows are output. For example, if "pressing" needs to start after "grinding" is completed, the time window is within 5 seconds after the grinding is completed.

[0040] By integrating the multiple task execution time windows and the multiple task dependencies, the task directed acyclic graph including nodes (tasks), edges (dependencies) and time attributes is generated.

[0041] This embodiment achieves the technical effect of providing structured input for subsequent robotic arm scheduling of the coffee beverage robot.

[0042] Step S200: Performing a timing analysis of the robotic arm tasks based on the task directed acyclic graph to obtain the function activation timing of arm A, arm B, and arm C corresponding to the robotic arm A, arm B, and arm C.

[0043] In one embodiment, a robotic arm task timing analysis is performed based on the task directed acyclic graph to obtain the function activation timing of arm A, arm B, and arm C corresponding to the robotic arm A, arm B, and arm C. Step S200 of the method provided by the present invention includes:

[0044] Step S210: According to the task directed acyclic graph, functional groups are assigned to the A robot arm, the B robot arm and the C robot arm through a dynamic scheduling algorithm to obtain the A task functional group, the B task functional group and the C task functional group.

[0045] In one embodiment, the task function group A includes raw material processing tasks, the task function group B includes liquid operation tasks, and the task function group C includes dairy product processing tasks.

[0046] Step S220: According to the task execution time and task dependency of the task directed acyclic graph, the A task function group, B task function group and C task function group are decomposed in time sequence to obtain the A arm function activation timing, B arm function activation timing and C arm function activation timing.

[0047] In one embodiment, according to the task directed acyclic graph, a dynamic scheduling algorithm is used to assign function groups to the A robot arm, the B robot arm, and the C robot arm to obtain the A task function group, the B task function group, and the C task function group. Step S210 of the method provided by the present invention includes:

[0048] Step S211: Interactively obtain the robotic arm function group configuration of the coffee beverage robot, wherein the robotic arm function group configuration includes the A initial function group, the B initial function group and the C initial function group corresponding to the A robotic arm, the B robotic arm and the C robotic arm.

[0049] Step S212: Mapping the multiple process task units to the A initial function group, B initial function group and C initial function group according to the resource requirement attributes of the multiple process task units to perform function screening to obtain A candidate function group, B candidate function group and C candidate function group.

[0050] Step S213: performing timing optimization sorting of the candidate function group A, candidate function group B, and candidate function group C according to the task timing characteristics in the task directed acyclic graph, and outputting the task function group A, task function group B, and task function group C.

[0051] Specifically, this embodiment obtains the initial functional configuration of the coffee beverage robot's robotic arms and defines the basic capability range of each robotic arm (A, B, and C). For example, the initial functional group of robotic arm A might include gripping, moving, and applying pressure, the initial functional group of robotic arm B might support precise water injection and temperature control, and the initial functional group of robotic arm C might cover milk frothing and container tilting. These configurations are determined by the coffee beverage robot's robotic arms' sensors, actuators, and load capacity.

[0052] Matching function groups are selected based on the resource requirements of the multiple process task units. For example, the "espresso extraction" task requires high-temperature water control capabilities, and only the liquid manipulation function group of Robot B meets this requirement. Therefore, this task is mapped to Robot B's candidate function group. The "milk frothing" task requires steam wand operation permissions, so it is mapped to Robot C's candidate function group.

[0053] Based on this, the multiple process task units are mapped to the A initial function group, B initial function group and C initial function group to perform function screening to obtain A candidate function group, B candidate function group and C candidate function group.

[0054] The function execution order of the candidate function group A, the candidate function group B and the candidate function group C is optimized and sorted according to the task timing characteristics in the task directed acyclic graph, and the task function group A, the task function group B and the task function group C are output.

[0055] According to the multiple predecessor task dependencies and multiple task execution time windows corresponding to the multiple nodes in the task directed acyclic graph, the tasks in the functional group are decomposed into specific startup sequences to obtain the A-arm function activation sequence, the B-arm function activation sequence and the C-arm function activation sequence.

[0056] This embodiment analyzes the task timing of the robotic arms based on the task directed acyclic graph, generates the function activation timing of each robotic arm, and converts the logical dependencies in the task directed acyclic graph into the specific action time schedule of the robotic arms, achieving the technical effect of efficient and conflict-free overall process when multiple robotic arms execute tasks sequentially or in parallel.

[0057] Step S300: After time-aligning the A-arm function activation sequence, the B-arm function activation sequence, and the C-arm function activation sequence, the operation task is segmented and a plurality of collaborative operation segments are output.

[0058] Specifically, after time-aligning the A-arm function activation sequence, the B-arm function activation sequence, and the C-arm function activation sequence, this embodiment divides the timeline into non-interfering or partially overlapping work task segments based on several start and end times of each robotic arm task and combined with spatial resource occupancy rules (such as brewing head exclusivity), and outputs the multiple collaborative work segments.

[0059] For example, grinding and preheating milk are divided into parallel sections, while the extraction stage is divided into mutually exclusive sections to avoid collisions between robotic arms. Each section defines the activation tasks, resource usage, and time and space constraints of the participating robotic arms, forming a structured collaborative operation section.

[0060] Step S400: Perform task trajectory conflict compensation according to the activation functions of multiple groups of robotic arms in the multiple collaborative operation sections, and output multiple groups of collaborative control parameters.

[0061] In a real-time manner, task trajectory conflict compensation is performed based on the activation functions of multiple sets of robotic arms in the multiple collaborative operation sections, and multiple sets of collaborative control parameters are output. The method step S400 provided by the present invention includes:

[0062] Step S410: Perform single-segment collision-free trajectory fitting according to the first set of robot arm activation functions in the first collaborative operation section, and output a first set of collaborative control parameters.

[0063] Step S420: Based on the connection relationship between the first collaborative operation section and the second collaborative operation section, taking the end posture of the first section as the starting point, a single-section collision-free trajectory fitting is performed according to the second set of robot arm activation functions, and a second set of collaborative control parameters is output.

[0064] Step S430: Similarly, according to the multiple groups of robot arm activation functions in the multiple collaborative operation sections, task trajectory conflict compensation is performed section by section, and the multiple groups of collaborative control parameters are output.

[0065] In one embodiment, a single-segment collision-free trajectory is fitted based on the activation functions of the first group of manipulators in the first collaborative operation section, and a first group of collaborative control parameters is output. Step S410 of the method provided by the present invention includes:

[0066] Step S411: If the first collaborative operation section is a single robotic arm section, a single-arm collision-free trajectory fitting is directly performed based on the obstacle map and the activation function of the first group of robotic arms.

[0067] Step S412: If the first collaborative operation section is a multi-robotic arm section, collaborative motion planning and spatiotemporal conflict detection are performed according to the activation function of the first group of robotic arms, and a joint collision-free trajectory is output.

[0068] Step S413: performing joint state parameter matching according to the single-arm collision-free trajectory fitting or the combined collision-free trajectory, and outputting the first set of collaborative control parameters.

[0069] This embodiment first processes trajectory planning for the first collaborative operation section. Specifically, if the section involves only a single robotic arm (e.g., arm A independently grinding coffee beans), an independent collision-free path is directly generated for that arm. If multiple robotic arms are involved (e.g., arm A tamping powder while arm C preheats milk simultaneously), a collaborative path is planned and conflicts are detected. For example, when robotic arms A and C operate in parallel, their paths must be isolated, ensuring collision-free operation through spatial segmentation or staggered movement.

[0070] Specifically, if the first collaborative operation section is a single-arm section, a single-arm collision-free trajectory is directly fitted based on the obstacle map and the activation function of the first group of robotic arms. For example, when robotic arm B performs the extraction task alone, a straight line path from the brewing head to the coffee cup is generated based on the environmental obstacle map, avoiding fixed obstacles (such as the grinder), and outputting a single-arm collision-free trajectory.

[0071] If the first collaborative operation section involves multiple robotic arms, joint trajectory planning and collision detection are performed for each of the multiple robotic arms. For example, when robotic arm A is transferring the powder basket to the brewing group while robotic arm C is simultaneously pouring milk, their paths may intersect. Therefore, an S-shaped detour trajectory must be generated or speeds must be adjusted to stagger time windows to ensure spatial overlap. Finally, a joint collision-free trajectory is output.

[0072] The joint state parameters are matched based on the single-arm collision-free trajectory fitting or the combined collision-free trajectory to convert the trajectory into robot arm joint parameters and output the first set of coordinated control parameters. For example, the movement path of the end effector of robot arm A is reverse-solved into a sequence of angle changes of each joint, including position, velocity, and torque values, to form control instructions (control parameters) that can directly drive the hardware.

[0073] When planning the trajectory of the subsequent segment based on the end state of the robot arm in the previous segment, in order to ensure the spatiotemporal consistency of the action, specifically, after the task of the previous segment is completed, the position, posture and motion state (such as speed and acceleration) of the end effector of the robot arm will be used as the initial conditions for the trajectory planning of the subsequent segment. For example, if robot arm A has transferred the powder bowl to the brewing head and maintained a specific posture at the end of segment 1, when robot arm B takes the powder bowl from this position in segment 2, it needs to use the end coordinates of robot arm A as the starting point and move to the next target point along a collision-free path. The space or resources that may still be occupied by the preceding robot arm must be considered simultaneously during the planning process. For example, when robot arm A stays near the brewing head, the path of robot arm B needs to bypass the area or wait for it to completely evacuate to avoid the risk of collision caused by instantaneous spatial overlap. This connection mechanism ensures the smooth transition of cross-segment tasks and the collaborative safety between robots.

[0074] Based on this, this embodiment performs single-segment collision-free trajectory fitting based on the connection relationship between the first collaborative operation section and the second collaborative operation section, takes the end posture of the first section as the starting point, and outputs the second set of collaborative control parameters according to the second set of robot arm activation functions.

[0075] By analogy, when processing each section, it is necessary to dynamically detect and reversely correct global trajectory conflicts. Specifically, when the tasks of the subsequent sections depend on the resources or space of the previous section (such as the mixing table occupied by the robot B in section 2 is needed for robot C to pour milk in section 3), if a trajectory conflict is detected, the parameters of the previous section are adjusted in reverse to eliminate the contradiction. For example, if robot C finds that the mixing table has been occupied by robot B at the end of section 2 during section 3 planning, it may shorten the task time window of robot B in section 2, release the mixing table in advance, or adjust its path so that robot B leaves the area in advance. This global backtracking optimization iteratively corrects the trajectory parameters of each section (such as path curvature and speed distribution) to ensure that the robot movements in the entire process are strictly coordinated in time and space, avoid systematic conflicts caused by the isolation of local planning, and ultimately generate multiple sets of collaborative control parameters that are temporally coherent and spatially isolated.

[0076] This embodiment achieves the technical effect of efficient collaborative operation of robotic arms, avoiding collisions, ensuring timing consistency, and improving reliability and overall efficiency through multi-segment trajectory planning and global conflict correction.

[0077] Step S500: Within the multiple collaborative operation sections, the robotic arms of the coffee beverage robot are collaboratively controlled according to the multiple sets of collaborative control parameters to execute the real-time coffee order production process.

[0078] This embodiment uses collaborative control parameters generated by each collaborative operation section to drive the coffee beverage robot's multiple robotic arms to execute tasks within each operation section according to the planned timing and path. Specifically, by synchronously executing joint motion instructions (such as position, speed, and torque parameters) within each operation section, the robotic arms' movements in each operation section strictly follow the preset trajectory, achieving seamless connection and collaborative operation in time and space. For example, after robotic arm A completes powder compacting, robotic arm B immediately initiates extraction, while robotic arm C simultaneously begins frothing milk, ultimately completing the entire coffee production process in a coherent manner and achieving efficient and accurate order execution.

[0079] This embodiment achieves efficient parallel operation of multiple robotic arms, resource conflict avoidance, and precise synchronization of movements through dynamic task decomposition, time scheduling, segmented collaboration, and trajectory optimization, significantly improving the technical effects of coffee production efficiency, reliability of collaborative operation of robotic arms, and real-time order response.

[0080] The second embodiment is based on the same inventive concept as the method for controlling the three-arm operation of the coffee beverage robot in the aforementioned embodiment. Figure 2 As shown, the present invention provides a time-sharing control device for the three-arm operation of a coffee beverage robot, wherein the device includes:

[0081] The task parsing unit 1 is used to receive a real-time coffee order, perform task chain parsing according to the coffee type of the real-time coffee order, and output a task directed acyclic graph.

[0082] The task allocation unit 2 is used to perform a timing analysis of the robot arm tasks based on the task directed acyclic graph to obtain the A arm function activation timing, B arm function activation timing, and C arm function activation timing corresponding to the A robot arm, B robot arm, and C robot arm.

[0083] The segment processing unit 3 is used to perform segment processing of the operation task after time alignment of the A-arm function activation timing, the B-arm function activation timing and the C-arm function activation timing, and output a plurality of collaborative operation segments.

[0084] The trajectory fitting unit 4 is used to perform task trajectory conflict compensation according to the multiple sets of robot arm activation functions in the multiple collaborative operation sections, and output multiple sets of collaborative control parameters.

[0085] The time-sharing control unit 5 is used to perform collaborative control of the robotic arms of the coffee beverage robot within the multiple collaborative operation sections according to the multiple sets of collaborative control parameters, and execute the real-time coffee order production process.

[0086] In one embodiment, the task parsing unit 1 is further configured to:

[0087] According to the coffee type of the real-time coffee order, a standard production process is matched from a process rule library; the standard production process is split into atomic tasks to obtain multiple process task units, wherein the multiple process task units are identified with multiple predecessor task dependencies; according to the multiple standard execution times of the multiple process task units and the multiple predecessor task dependencies, multiple task execution time windows are calculated and output; based on the multiple task execution time windows and the multiple task dependencies, the task directed acyclic graph is constructed.

[0088] In one embodiment, the task allocation unit 2 is further configured to:

[0089] According to the task directed acyclic graph, function groups are assigned to the A robot arm, the B robot arm and the C robot arm through a dynamic scheduling algorithm to obtain the A task function group, the B task function group and the C task function group; according to the task execution time and task dependency of the task directed acyclic graph, the A task function group, the B task function group and the C task function group are time-sequentially decomposed to obtain the A arm function activation timing, the B arm function activation timing and the C arm function activation timing.

[0090] In one embodiment, the task allocation unit 2 is further configured to:

[0091] Interactively obtain the robotic arm function group configuration of the coffee beverage robot, wherein the robotic arm function group configuration includes the A initial function group, B initial function group and C initial function group corresponding to the A robotic arm, B robotic arm and C robotic arm; according to the resource requirement attributes of the multiple process task units, map the multiple process task units to the A initial function group, B initial function group and C initial function group to perform function screening to obtain the A candidate function group, B candidate function group and C candidate function group; according to the task timing characteristics in the task directed acyclic graph, perform timing optimization sorting of the A candidate function group, B candidate function group and C candidate function group, and output the A task function group, B task function group and C task function group.

[0092] In one embodiment, the trajectory fitting unit 4 is further configured to:

[0093] According to the first group of robot arm activation functions in the first collaborative operation section, a single-segment collision-free trajectory is fitted, and a first group of collaborative control parameters are output; according to the connection relationship between the first collaborative operation section and the second collaborative operation section, with the end posture of the first section as the starting point, a single-segment collision-free trajectory is fitted according to the second group of robot arm activation functions, and a second group of collaborative control parameters are output; and so on, according to the multiple groups of robot arm activation functions in the multiple collaborative operation sections, task trajectory conflict compensation is performed section by section, and the multiple groups of collaborative control parameters are output.

[0094] In one embodiment, the task allocation unit 2 is further configured to:

[0095] The task function group A includes raw material processing tasks, the task function group B includes liquid operation tasks, and the task function group C includes dairy product processing tasks.

[0096] In one embodiment, the trajectory fitting unit 4 is further configured to:

[0097] If the first collaborative operation section is a single-arm section, the single-arm collision-free trajectory is directly fitted according to the obstacle map and the first group of robotic arm activation functions; if the first collaborative operation section is a multi-arm section, collaborative motion planning and spatiotemporal conflict detection are performed according to the first group of robotic arm activation functions, and a joint collision-free trajectory is output; joint state parameters are matched according to the single-arm collision-free trajectory fitting or the joint collision-free trajectory, and the first group of collaborative control parameters is output.

[0098] The above description is merely a specific embodiment of the present invention, but the scope of protection of the present invention is not limited thereto. Any modifications or substitutions that can be easily conceived by a person skilled in the art within the technical scope disclosed in the present invention should be included within the scope of protection of the present invention. Therefore, the scope of protection of the present invention should be based on the scope of protection of the claims.

Claims

1. A time-sharing control method for the three-arm operation of a coffee beverage robot, characterized in that: include: After receiving a real-time coffee order, perform task chain parsing according to the coffee type of the real-time coffee order and output a task directed acyclic graph; Performing a robotic arm task timing analysis based on the task directed acyclic graph to obtain an arm A function activation timing, an arm B function activation timing, and an arm C function activation timing corresponding to the robotic arm A, the robotic arm B, and the robotic arm C; After time alignment of the A-arm function activation sequence, the B-arm function activation sequence, and the C-arm function activation sequence, segmenting the operation tasks and outputting a plurality of collaborative operation segments; Perform task trajectory conflict compensation according to the activation functions of multiple sets of robotic arms in the multiple collaborative operation sections, and output multiple sets of collaborative control parameters; In the multiple collaborative operation sections, the robotic arms of the coffee beverage robot are collaboratively controlled according to the multiple sets of collaborative control parameters to execute the real-time coffee order production process.

2. The method for controlling the three-arm operation of a coffee beverage robot in a segmented and time-sharing manner as claimed in claim 1, wherein: After receiving a real-time coffee order, the task chain is parsed according to the coffee type of the real-time coffee order, and a task directed acyclic graph is output, including: According to the coffee type of the real-time coffee order, a standard production process is matched from a process rule library; Performing atomic task splitting on the standard production process to obtain a plurality of process task units, wherein the plurality of process task units are identified with a plurality of predecessor task dependency relationships; Calculating and outputting a plurality of task execution time windows according to a plurality of standard execution times of the plurality of process task units and the plurality of predecessor task dependencies; The task directed acyclic graph is constructed according to the multiple task execution time windows and the multiple task dependencies.

3. The method for controlling the three-arm operation of a coffee beverage robot in a segmented and time-sharing manner as claimed in claim 2, wherein: Performing a robotic arm task timing analysis based on the task directed acyclic graph to obtain the function activation timing of arm A, arm B, and arm C corresponding to the robotic arm A, arm B, and arm C, including: According to the task directed acyclic graph, a function group is assigned to the A robot arm, the B robot arm, and the C robot arm by a dynamic scheduling algorithm to obtain the A task function group, the B task function group, and the C task function group; According to the task execution time and task dependency of the task directed acyclic graph, the A task function group, B task function group and C task function group are decomposed in time sequence to obtain the A arm function activation timing, the B arm function activation timing and the C arm function activation timing.

4. The method for controlling the three-arm operation of a coffee beverage robot in a segmented and time-sharing manner as claimed in claim 3, wherein: According to the task directed acyclic graph, function groups are assigned to the A robot arm, the B robot arm, and the C robot arm through a dynamic scheduling algorithm to obtain the A task function group, the B task function group, and the C task function group, including: Interactively obtaining a robotic arm function group configuration of the coffee beverage robot, wherein the robotic arm function group configuration includes an A initial function group, a B initial function group, and a C initial function group corresponding to the A robotic arm, the B robotic arm, and the C robotic arm; According to the resource requirement attributes of the multiple process task units, the multiple process task units are mapped to the initial function group A, the initial function group B, and the initial function group C to perform function screening to obtain the candidate function group A, the candidate function group B, and the candidate function group C; The A candidate function group, B candidate function group and C candidate function group are sorted in a timing optimized manner according to the task timing characteristics in the task directed acyclic graph, and the A task function group, B task function group and C task function group are output.

5. The method for controlling the three-arm operation of a coffee beverage robot in a segmented and time-sharing manner as claimed in claim 1, wherein: Perform task trajectory conflict compensation according to the activation functions of multiple sets of robotic arms in the multiple collaborative operation sections, and output multiple sets of collaborative control parameters, including: Perform single-segment collision-free trajectory fitting based on the first set of robot arm activation functions in the first collaborative operation section, and output a first set of collaborative control parameters; Based on the connection relationship between the first collaborative operation section and the second collaborative operation section, taking the end posture of the first section as the starting point, a single-section collision-free trajectory fitting is performed according to the second set of robot arm activation functions, and a second set of collaborative control parameters is output; Similarly, task trajectory conflict compensation is performed section by section according to the multiple groups of robot arm activation functions in the multiple collaborative operation sections, and the multiple groups of collaborative control parameters are output.

6. The method for controlling the three-arm operation of a coffee beverage robot in a segmented and time-sharing manner as claimed in claim 3, wherein: The task function group A includes raw material processing tasks, the task function group B includes liquid operation tasks, and the task function group C includes dairy product processing tasks.

7. The method for controlling the three-arm operation of a coffee beverage robot in a segmented and time-sharing manner as claimed in claim 5, wherein: According to the activation function of the first group of manipulators in the first collaborative operation section, a single-segment collision-free trajectory is fitted, and the first group of collaborative control parameters is output, including: If the first collaborative operation section is a single-arm section, directly performing single-arm collision-free trajectory fitting based on the obstacle map and the activation functions of the first group of manipulators; If the first collaborative operation section is a multi-manipulator section, performing collaborative motion planning and spatiotemporal conflict detection according to the activation functions of the first group of manipulators, and outputting a joint collision-free trajectory; Joint state parameters are matched according to the single-arm collision-free trajectory fitting or the combined collision-free trajectory, and the first set of collaborative control parameters is output.

8. The three-arm operation section time-sharing control equipment of the coffee beverage robot is characterized by: The steps for implementing the method according to any one of claims 1 to 7 include: A task parsing unit, configured to, after receiving a real-time coffee order, parse a task chain according to the coffee type of the real-time coffee order and output a task directed acyclic graph; A task allocation unit is used to perform a timing analysis of the robot arm tasks according to the task directed acyclic graph to obtain the function activation timing of arm A, arm B, and arm C corresponding to the robot arm A, the robot arm B, and the robot arm C; a segment processing unit, configured to perform segment processing of the operation task after time alignment of the A-arm function activation timing, the B-arm function activation timing, and the C-arm function activation timing, and output a plurality of collaborative operation segments; a trajectory fitting unit, configured to perform task trajectory conflict compensation according to multiple sets of robot arm activation functions in the multiple collaborative operation sections, and output multiple sets of collaborative control parameters; The time-sharing control unit is used to perform collaborative control of the robotic arms of the coffee beverage robot within the multiple collaborative operation sections according to the multiple sets of collaborative control parameters, and execute the real-time coffee order production process.

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