Three-mechanical-arm cooperative control method and system of coffee beverage machine combined with energy consumption analysis

Abstract

The application provides a three-mechanical-arm cooperative control method and system of a coffee beverage machine combined with energy consumption analysis, and relates to the technical field of mechanical arm energy consumption optimization. The method comprises the following steps: decomposing real-time order information to obtain a double-state component demand driving process mechanical arm and a substrate carrying sub-arm of a rotating base double-arm to pre-engage double-state process raw materials; adopting a double-arm energy consumption balanced track to cooperatively control the process mechanical arm and the substrate carrying sub-arm to displace the double-state process raw materials to a process docking coordinate to perform space-time synchronous processing to obtain an order coffee beverage. The technical problem of high mechanical arm energy consumption in the process of making coffee by a coffee beverage machine in the prior art, which indirectly leads to the increase of production cost, is solved. The technical effect of reducing the liquid spatter risk in the coffee cup clamping displacement process while reducing the mechanical arm operation energy consumption and compressing the cost in the coffee making process is achieved.

Description

Technical Field

[0001] This invention relates to the field of robotic arm energy consumption optimization technology, and in particular to a collaborative control method and system for three robotic arms in a coffee beverage machine that incorporates energy consumption analysis. Background Technology

[0002] The automation of traditional coffee and beverage machines generally relies on robotic arms to perform tasks such as raw material transportation, processing, and delivery, but this faces significant challenges in terms of energy efficiency and process stability.

[0003] In existing technologies, the robotic arms of coffee beverage machines mostly adopt single-target trajectory planning, which leads to frequent start-stop of the joint motors and torque peaks. Especially during the transportation of liquid raw materials, the motion parameters need to be repeatedly adjusted to suppress liquid sloshing, which further aggravates energy loss.

[0004] In summary, existing technologies have the technical problem of high energy consumption of the robotic arm during the coffee-making process of coffee beverage machines, which indirectly leads to increased production costs. Summary of the Invention

[0005] This invention provides a collaborative control method and system for three robotic arms of a coffee beverage machine that incorporates energy consumption analysis, in order to address the technical problem of high energy consumption of robotic arms during the coffee making process in existing coffee beverage machines, which indirectly leads to increased production costs.

[0006] In view of the above problems, the present invention provides a collaborative control method and system for three robotic arms of a coffee beverage machine that incorporates energy consumption analysis.

[0007] A first aspect of the present invention provides a collaborative control method for three robotic arms of a coffee beverage machine that incorporates energy consumption analysis, the method comprising:

[0008] After receiving a new real-time order, the coffee beverage machine analyzes the order process characteristics of the real-time order information to locate the process docking coordinates. The coffee beverage machine includes a rotary duplex robotic arm and a process robotic arm. The real-time order information is decomposed to obtain dual-state component requirements, and based on these requirements, the process robotic arm and the rotary duplex robotic arm's substrate transport sub-arm pre-accept the dual-state process raw materials. Based on the process docking coordinates, docking control energy consumption balance analysis is performed, and a dual-arm energy consumption balance trajectory is output. Using the dual-arm energy consumption balance trajectory, the process robotic arm and the substrate transport sub-arm are coordinated to move the dual-state process raw materials to the process docking coordinates for spatiotemporal synchronous processing, resulting in the ordered coffee beverage. By flipping the rotatable main body, the cap-closing robotic arm is aligned with the ordered coffee beverage to perform a cap-closing operation. The rotary duplex robotic arm integrates the cap-closing robotic arm and the substrate transport arm through the rotatable main body.

[0009] In one implementation, the real-time order information is decomposed to obtain dual-state component requirements, and the substrate transport sub-arm of the process robot arm and the spin-based duplex robot arm is driven to pre-accept dual-state process raw materials based on the dual-state component requirements. The following processing is also performed:

[0010] The real-time order information is decomposed to obtain liquid component requirements and non-liquid component requirements, constituting the dual-state component requirements. The liquid component requirements and non-liquid component requirements are sent to the fluid filling station and the conditioning preparation station, respectively, to drive the pre-preparation of the dual-state process raw materials, wherein the dual-state process raw materials include fluid base material and conditioning auxiliary material. The substrate carrier arm is controlled to hold a coffee cup at the fluid filling station to receive the fluid base material. The process robotic arm is controlled to hold an auxiliary material cup at the conditioning preparation station to receive the conditioning auxiliary material.

[0011] In one implementation, based on the process docking coordinates, a docking control energy consumption balance analysis is performed to output the dual-arm energy consumption balance trajectory, and the following processing is also performed:

[0012] Based on the fluid characteristics of the base material in the coffee cup, an energy consumption balance analysis for docking control is performed between the fluid filling station and the process docking coordinates, and the base material transport balance trajectory is output. Based on the fluid characteristics of the conditioning auxiliary material in the auxiliary material cup, an energy consumption balance analysis for docking control is performed between the conditioning preparation station and the process docking coordinates, and the auxiliary material transport balance trajectory is output. The base material transport balance trajectory and the auxiliary material transport balance trajectory are time-aligned and balanced, and the dual-arm energy consumption balance trajectory is output.

[0013] In one embodiment, based on the fluid characteristics of the fluid base material in the coffee cup, a docking control energy consumption balance analysis is performed between the fluid filling station and the process docking coordinates to output the base material transport balance trajectory, and the following processing is also performed:

[0014] Based on the spatiotemporal reachability constraints of the process docking coordinates, the transport time window is initialized; the sloshing suppression model is called according to the fluid characteristics of the fluid base material in the coffee cup, wherein the sloshing suppression model has a safe tilt angle threshold; in the CFD simulation environment, the multiple rounds of displacement of the base material transport arm clamping the sloshing suppression model between the fluid injection station and the process docking coordinates are simulated to obtain multiple initial candidate trajectories; the safe tilt angle threshold and the transport time window are used to traverse multiple initial fluid tilt angle sequences and multiple control transport durations of the multiple initial candidate trajectories to filter out W candidate control trajectories; the energy consumption balance quantization of the W candidate control trajectories is performed, and the base material transport balance trajectory is selected and located according to the quantization results.

[0015] In one implementation, the energy consumption balancing quantization is performed on the W candidate control trajectories, and the material transport balancing trajectory is selected and located based on the quantization results. The following processing is also performed:

[0016] Torque integrals are performed on the W candidate control trajectories to output W candidate torque integrals; acceleration features of the W candidate control trajectories are extracted to output W candidate acceleration distributions; W control energy consumptions, W candidate torque integrals, and W candidate acceleration distributions of the W candidate control trajectories are weighted and fused to output W quantized docking control energy consumptions; the material transport equilibrium trajectory is extracted from the W candidate control trajectories based on the ranking results of the W quantized docking control energy consumptions.

[0017] In one embodiment, by flipping the rotatable body, the cap-closing robotic arm is aligned with the ordered coffee beverage to perform the cap-closing operation, and the following processing is also performed:

[0018] Based on the real-time user coordinates of the ordering user, an adaptive analysis of the food pickup distance is performed to locate the target receiving tray at the pickup station. Based on the fluid characteristics of the ordered coffee beverage, the energy consumption of the robotic arm displacement is optimized between the process docking coordinates and the target receiving tray, and a single-arm energy consumption balance trajectory is output. Using the single-arm energy consumption balance trajectory, the substrate transport sub-arm is controlled to move the ordered coffee beverage to the target receiving tray, and then the rotatable main body is flipped to drive the cap-closing robotic arm to align with the ordered coffee beverage and perform a semi-sealed cap-closing.

[0019] In one implementation, an adaptive analysis of the food pickup distance is performed based on the real-time user coordinates of the ordering user to locate the target receiving tray at the pickup station, and the following processing is also performed:

[0020] The system locally calls multiple cup-receiving coordinate points of multiple sunken circular receiving trays pre-stamped on the food dispensing station; calculates multiple spatial distance features between the real-time user coordinates and the multiple cup-receiving coordinate points, and locates P candidate receiving coordinate points; performs food dispensing obstacle verification on the P candidate receiving coordinate points according to the boundary structure of the coffee beverage machine, and locates the target receiving tray.

[0021] A second aspect of the present invention provides a three-robotic arm collaborative control system for a coffee beverage machine incorporating energy consumption analysis. The system includes: a docking and positioning unit, used to locate the process docking coordinates by parsing the order process characteristics of the real-time order information after the coffee beverage machine receives a new real-time order; wherein the coffee beverage machine includes a spin-based duplex robotic arm and a process robotic arm; a demand-driven unit, used to decompose the real-time order information to obtain dual-state component requirements, and drive the substrate transport sub-arms of the process robotic arm and the spin-based duplex robotic arm to pre-accept dual-state process raw materials based on the dual-state component requirements; and an energy consumption balancing unit. The analysis unit is used to perform docking control energy consumption balance analysis based on the process docking coordinates and output the dual-arm energy consumption balance trajectory; the collaborative processing unit is used to use the dual-arm energy consumption balance trajectory to collaboratively control the process robot arm and the substrate transport sub-arm to move the dual-state process raw material to the process docking coordinates to perform spatiotemporal synchronous processing to obtain the ordered coffee beverage; the cap-closing execution unit is used to align the cap-closing robot sub-arm with the ordered coffee beverage by flipping the rotatable main body to perform the cap-closing operation, wherein the rotating base duplex robot arm integrates the cap-closing robot sub-arm and the substrate transport arm through the rotatable main body.

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

[0023] The method provided in this invention, after receiving a new real-time order in a coffee beverage machine, locates the process docking coordinates by analyzing the order process characteristics of the real-time order information. The coffee beverage machine includes a rotary duplex robotic arm and a process robotic arm. The real-time order information is decomposed to obtain dual-state component requirements, and the substrate transport sub-arms of the process robotic arm and the rotary duplex robotic arm are driven to pre-accept the dual-state process raw materials based on these requirements. A docking control energy consumption balance analysis is performed based on the process docking coordinates, outputting a dual-arm energy consumption balance trajectory. Using this trajectory, the process robotic arm and the substrate transport sub-arm are coordinated to move the dual-state process raw materials to the process docking coordinates for spatiotemporal synchronous processing, resulting in the ordered coffee beverage. The lid-closing robotic arm is aligned with the ordered coffee beverage by flipping the rotatable main body to perform a lid-closing operation. The rotary duplex robotic arm integrates the lid-closing robotic arm and the substrate transport arm through the rotatable main body. This achieves the technical effect of reducing the energy consumption and cost of robotic arm operation during coffee making while simultaneously reducing the risk of liquid spillage during the coffee cup handling and displacement process. Attached Figure Description

[0024] Figure 1 This invention provides a schematic flowchart of a collaborative control method for a coffee beverage machine using three robotic arms, incorporating energy consumption analysis.

[0025] Figure 2A schematic diagram of the three robotic arms collaborative control system for a coffee beverage machine, which incorporates energy consumption analysis, is shown in this invention.

[0026] Explanation of reference numerals in the attached diagram: 1. Docking and positioning unit; 2. Demand-driven unit; 3. Energy consumption balance analysis unit; 4. Collaborative processing unit; 5. Covering execution unit. Detailed Implementation

[0027] This invention provides a collaborative control method and system for three robotic arms of a coffee beverage machine that incorporates energy consumption analysis, in order to address the technical problem of high energy consumption of robotic arms during the coffee making process in existing coffee beverage machines, which indirectly leads to increased production costs.

[0028] The technical solutions of the present invention will now be clearly and completely described with reference to the accompanying drawings. Obviously, the described embodiments are only a part of the embodiments of the present invention, and not all of them. It should be understood that the present invention is not limited to the exemplary embodiments described herein. All other embodiments obtained by those skilled in the art based on the embodiments of the present invention without creative effort are within the scope of protection of the present invention. It should also be noted that, for ease of description, only the parts related to the present invention are shown in the accompanying drawings, not all of them.

[0029] Example 1: A flowchart of the three-robotic arm collaborative control method for a coffee beverage machine combined with energy consumption analysis provided in this embodiment of the invention. (See attached diagram) Figure 1 The method includes:

[0030] Step A100: After receiving a new real-time order, the coffee and beverage machine locates the process docking coordinates by parsing the order process characteristics of the real-time order information. The coffee and beverage machine includes a rotary duplex robotic arm and a process robotic arm.

[0031] First, it should be understood that the three-arm robotic system of the coffee beverage machine involved in this embodiment consists of a rotating duplex robotic arm and a process robotic arm. The rotating duplex robotic arm has a main body that can rotate 360°, and its front end integrates two functional sub-arms: a substrate transport sub-arm (responsible for holding the coffee cup and transporting raw materials such as milk and coffee liquid) and a lid-closing robotic arm (equipped with an electromagnetic chuck or sensor for precise lid pressing). The process robotic arm is independently deployed in the side working area, and its end is equipped with tools such as a milk frother and latte art needle, specifically for performing delicate processes such as milk frothing and latte art.

[0032] Specifically, when the coffee beverage machine receives a new real-time order (such as a cappuccino that requires latte art), it will analyze the process requirements in the order, such as "milk frothing" and "latte art pattern", and determine the precise position of the robotic arm operation (i.e. process docking coordinates) based on these features.

[0033] For example, milk frothing requires a process robotic arm to move to the milk frothing station, while the coffee cup needs to be delivered to the latte art station by a substrate transport sub-arm. The rotating base duplex robotic arm and the process robotic arm will work together according to these coordinates to ensure that the raw materials and tools are accurately aligned, avoiding liquid spillage or process conflicts caused by positional deviations.

[0034] Step A200: Decompose the real-time order information to obtain the dual-state component requirements, and drive the substrate transport sub-arm of the process robot arm and the spin-based duplex robot arm to pre-accept the dual-state process raw materials according to the dual-state component requirements.

[0035] In one embodiment, the real-time order information is decomposed to obtain dual-state component requirements, and the substrate transport sub-arm of the process robot arm and the spin-based duplex robot arm is driven to pre-accept dual-state process raw materials based on the dual-state component requirements. The method step A200 provided by the present invention includes:

[0036] Step A210: Decompose the real-time order information to obtain liquid component demand and non-liquid component demand, thus forming the dual-state component demand.

[0037] Step A220: Send the liquid component requirements and non-liquid component requirements to the fluid filling station and the conditioning preparation station respectively to drive the pre-preparation of the dual-state process raw materials, wherein the dual-state process raw materials include fluid base materials and conditioning auxiliary materials.

[0038] Step A230: Control the substrate carrier arm to hold the coffee cup and receive the fluid base material at the fluid filling station.

[0039] Step A240: Control the process robotic arm to hold the auxiliary material cup and receive the conditioning auxiliary material at the conditioning preparation station.

[0040] Specifically, when the coffee beverage machine (robot) receives an order, it analyzes the required liquid and non-liquid components of the beverage, forming the dual-state component requirement. For example, if a user orders an iced latte, the liquid requirement includes milk and espresso, while the non-liquid requirement is ice. This classification is based on the differences in the physical form of the raw materials—liquid materials require pumping and dispensing, while non-liquid materials (such as ice or milk foam) require grasping or shaping processes. This decomposition lays the foundation for subsequent parallel processing, ensuring that the substrate transport arm and the process robotic arm each perform their respective functions, avoiding resource competition.

[0041] Liquid component requirements are allocated to fluid filling stations (such as metered pump stations for milk and coffee), while non-liquid component requirements are sent to conditioning preparation stations (such as milk frothers or auxiliary material bins). For example, the caramel sauce in a caramel macchiato needs to be heated and melted at the conditioning preparation station, while the milk foam needs to be generated by a dedicated frothing device. This step achieves parallel preprocessing of raw materials through station division of labor. The substrate carrier arm is already holding an empty cup at the fluid station, waiting to receive coffee, while the process robotic arm goes to the auxiliary material bin to grab the caramel sauce container, shortening the overall preparation time.

[0042] The substrate carrier arm grips the coffee cup and moves it to the fluid filling station to precisely collect the liquid raw material (fluid base). For example, when making a cup of hot chocolate, the carrier arm positions the cup below the chocolate sauce outlet, and the injection volume is controlled by a flow sensor (error ±1.5ml). During this process, the robotic arm must maintain a stable posture to avoid liquid spillage, and dynamically adjust the lifting speed according to the cup's capacity—decelerating for small cups to prevent overflow and accelerating for large cups to improve efficiency.

[0043] After acquiring non-liquid raw materials (conditioning additives) at the conditioning preparation station, the robotic arm needs to transport them to the collaborative processing area. For example, when making matcha smoothie coffee, the robotic arm picks up the mixed smoothie base from the smoothie machine, while the base material carrier arm has already poured milk into the cup. The two meet at the latte art station, where the robotic arm evenly spreads the smoothie on the surface of the milk, while the carrier arm simultaneously fine-tunes the cup angle (e.g., tilting it 20°) to match the pouring trajectory. This spatiotemporal collaboration of the two robotic arms avoids uneven mixing of raw materials and reduces energy consumption from idling.

[0044] This embodiment utilizes the composition of raw materials in a coffee order to divide the work of the robotic arm and coordinate task execution, thereby achieving the technical effect of shortening the coffee order production time.

[0045] Step A300: Perform docking control energy consumption balance analysis based on the process docking coordinates, and output the dual-arm energy consumption balance trajectory.

[0046] In one embodiment, docking control energy consumption balance analysis is performed based on the process docking coordinates, and the dual-arm energy consumption balance trajectory is output. The method step A300 provided by the present invention includes:

[0047] Step A310: Based on the fluid characteristics of the fluid base material in the coffee cup, perform docking control energy consumption balance analysis between the fluid filling station and the process docking coordinates, and output the base material transport balance trajectory.

[0048] Step A320: Based on the fluid characteristics of the conditioning excipients in the excipient cup, perform docking control energy consumption balance analysis between the conditioning preparation station and the process docking coordinates, and output the excipient transport balance trajectory.

[0049] Step A330: Perform time-series alignment and balancing on the base material transport balancing trajectory and the auxiliary material transport balancing trajectory, and output the dual-arm energy consumption balancing trajectory.

[0050] In one embodiment, based on the fluid characteristics of the fluid base material in the coffee cup, a docking control energy consumption balance analysis is performed between the fluid filling station and the process docking coordinates to output the base material transport balance trajectory. Step A310 of the method provided by this invention includes:

[0051] Step A311: Initialize the transport time window based on the spatiotemporal reachability constraints of the process docking coordinates.

[0052] Step A312: Match and invoke the sloshing suppression model according to the fluid characteristics of the fluid base in the coffee cup, wherein the sloshing suppression model has a safe tilt angle threshold identifier.

[0053] Step A313: In the CFD simulation environment, simulate the multiple rounds of displacement of the substrate carrier arm clamping the sway suppression model between the fluid injection station and the process docking coordinates to obtain multiple initial candidate trajectories.

[0054] Step A314: Using the safety tilt angle threshold and the carrying time window, traverse the multiple initial fluid tilt angle sequences and multiple control carrying times of the multiple initial candidate trajectories to filter out W candidate control trajectories.

[0055] Step A315: Perform energy consumption balance quantization on the W candidate control trajectories, and select and locate the material transport balance trajectory based on the quantization results.

[0056] In one embodiment, energy consumption balancing quantization is performed on the W candidate control trajectories, and the material transport balancing trajectory is selected and located based on the quantization results. Step A315 of the method provided by the present invention includes:

[0057] Step A315a: Perform torque integration on the W candidate control trajectories and output W candidate torque integrals.

[0058] Step A315b: Extract the acceleration features of the W candidate control trajectories and output the W candidate acceleration distributions.

[0059] Step A315c: Weighted fusion of the W control energy consumptions of the W candidate control trajectories, the W candidate torque integrals, and the W candidate acceleration distributions to output W quantized docking control energy consumptions.

[0060] Step A315d: Based on the ranking results of the W quantified docking control energy consumption, extract the base material transport equilibrium trajectory from the W candidate control trajectories.

[0061] Specifically, the spatiotemporal accessibility constraint refers to the spatial location of the process docking coordinates and the movement capability of the robotic arm (such as joint angle limitations). In this embodiment, the allowable transport time range is initialized based on the spatiotemporal accessibility constraint to obtain the transport time window.

[0062] For example, if the latte art station is far from the milk filling station, a maximum allowable time window of 8 seconds will be set to ensure that the coffee liquid is transported at the optimal temperature. At the same time, the physical limitations of the robotic arm joints (such as the pitch angle range of -15° to 75°) are considered, eliminating path options that exceed its movement capabilities. This spatiotemporal accessibility constraint avoids the problem of invalid paths caused by the robotic arm's inability to reach the target location, such as choosing a detour path instead of forcibly moving in a straight line within a narrow work area.

[0063] The model is matched to the fluid properties (such as viscosity and density) of the fluid base material. For example, when transporting an iced Americano containing ice, the model will set a safe tilt angle threshold of ≤15° and force a path curvature radius of ≥150mm to prevent ice from hitting the cup wall or liquid from spilling.

[0064] In a CFD simulation environment, the movement of a coffee cup held by a substrate carrier arm from the fluid filling station to the process docking coordinates is simulated. For example, 10 different paths (such as straight lines, arcs, and zigzags) are generated in the CFD simulation environment to simulate the liquid sloshing under different accelerations and tilt angles in a coffee cup sloshing suppression model. By analyzing the simulation results, several initial candidate trajectories with liquid sloshing amplitude <0.5mm are selected. During the simulation, the cup tilt angle sequence and movement duration of each initial candidate trajectory are recorded to provide data support for subsequent selection.

[0065] The safety tilt angle threshold and transport time window are used to traverse multiple initial fluid tilt angle sequences and multiple control transport durations of the multiple initial candidate trajectories to filter out W candidate control trajectories. Energy consumption quantification analysis is performed on the W candidate control trajectories. For example, the joint torque integral (reflecting motor energy consumption) and acceleration fluctuation frequency (reflecting stability) of each path are calculated, and a comprehensive score is generated through weighted fusion. A certain path, although having the shortest transport time, has a torque integral as high as 120J due to frequent starts and stops, while another path with a slightly longer transport time has a torque integral of only 85J and less acceleration fluctuation due to smooth movement. Finally, the path with the highest total score is selected as the material transport equilibrium trajectory based on the score ranking. For example, a path with a comprehensive energy consumption of 95J and a sway amplitude of 0.3mm is selected as the optimal solution, reducing energy consumption by 35% compared to the traditional scheme.

[0066] The specific method for determining the balanced trajectory of the base material transport is as follows:

[0067] Torque integrals are performed on the W candidate control trajectories to output W candidate torque integrals. Acceleration features of the W candidate control trajectories are extracted to output W candidate acceleration distributions. Preset weights are used to weightedly fuse the W control energy consumptions, W candidate torque integrals, and W candidate acceleration distributions of the W candidate control trajectories, outputting W quantized docking control energy consumptions. Then, based on the ranking of the W quantized docking control energy consumptions, the base material transport equilibrium trajectory is extracted from the W candidate control trajectories.

[0068] Similarly, using the same method, based on the fluid characteristics of the conditioning excipients in the excipient cup, an energy consumption balance analysis of docking control is performed between the conditioning preparation station and the process docking coordinates, and the excipient transport balance trajectory is output.

[0069] Aligning the base material transport equilibrium trajectory and the auxiliary material transport equilibrium trajectory in time and space eliminates conflicts and optimizes overall efficiency, resulting in the output dual-arm energy consumption equilibrium trajectory. For example, if milk foam addition needs to be initiated within 0.5 seconds after the coffee cup arrives at the latte art station, the path delay of the process robotic arm will be adjusted to ensure seamless connection between the two at the target position.

[0070] This embodiment achieves the technical effect of reducing total energy consumption while avoiding efficiency loss due to waiting or collisions by generating a dual-arm energy consumption balance trajectory based on the final energy consumption balance.

[0071] This embodiment performs a comprehensive optimization analysis of the energy consumption and stability of the robotic arm's motion trajectory based on the process docking coordinates, achieving the generation of a dual-arm energy-balanced trajectory that balances efficiency and safety. This provides technical effects for the subsequent low-energy coffee order production by providing robotic arm control parameters.

[0072] Step A400: Using the dual-arm energy consumption balancing trajectory, the process robotic arm and the substrate transport sub-arm are coordinated to move the dual-state process raw material to the process docking coordinates to perform spatiotemporal synchronous processing, thereby obtaining the ordered coffee beverage.

[0073] Specifically, this embodiment uses an energy-optimized dual-arm collaborative trajectory (base material transport balance trajectory and auxiliary material transport balance trajectory) to control the process robotic arm and the base material transport sub-arm to accurately transport liquid base materials (such as milk, coffee liquid) and conditioning auxiliary materials (such as milk foam, ice cubes) to the process docking coordinates (such as latte art station or mixing station) and perform processing operations synchronously in time and space.

[0074] For example, while the substrate carrier arm delivers the coffee cup to the latte art station, the process robotic arm simultaneously injects the frothed milk. The two processes are aligned via a time window (error < 0.2 seconds) to ensure the milk foam and coffee are fully blended, preventing liquid separation or overflow due to timing misalignment. During the process, the robotic arm's motion trajectory is optimized based on B-spline curves to reduce torque fluctuations from sudden stops and starts. Simultaneously, a gravity compensation algorithm counteracts the additional torque when the cup is tilted, ultimately completing the preparation of the ordered beverage.

[0075] Step A500: By flipping the rotatable main body, the cap-closing robotic arm is aligned with the ordered coffee beverage to perform the cap-closing operation, wherein the rotating base duplex robotic arm integrates the cap-closing robotic arm and the substrate transport arm through the rotatable main body.

[0076] In one embodiment, by flipping the rotatable main body, the cap-closing robotic arm is aligned with the ordered coffee beverage to perform the cap-closing operation. The method step A500 provided by this invention includes:

[0077] Step A510: Perform a pick-up distance adaptability analysis based on the real-time user coordinates of the ordering user to locate the target receiving tray at the pick-up station.

[0078] Step A520: Based on the fluid characteristics of the ordered coffee beverage, optimize the displacement energy consumption of the robotic arm between the process docking coordinates and the target receiving plate, and output a single-arm energy consumption balanced trajectory.

[0079] Step A530: Using the single-arm energy consumption balancing trajectory, control the substrate transport sub-arm to move the ordered coffee beverage to the target receiving tray, then flip the rotatable main body to drive the cap-closing mechanical sub-arm to align with the ordered coffee beverage and perform a semi-sealed cap-closing.

[0080] In one implementation, an adaptive analysis of the food pickup distance is performed based on the real-time user coordinates of the ordering user to locate the target receiving tray at the pickup station. Step A510 of the method provided by this invention includes:

[0081] Step A511: Locally call the coordinate points of multiple cup receiving cups on the multiple sunken circular receiving trays pre-stamped on the food pick-up station.

[0082] Step A512: Calculate the spatial distance features between the real-time user coordinates and the multiple cup-body receiving coordinate points, and locate P candidate receiving coordinate points.

[0083] Step A513: Based on the boundary structure of the coffee beverage machine, perform food collection obstacle verification on the P candidate receiving coordinate points, and locate the target receiving tray.

[0084] It should be understood that after the beverage is prepared in this embodiment, the rotating main body flipping spindle robotic arm is used to align the lid-closing robotic arm with the top of the coffee cup to perform the lid-closing operation.

[0085] Before closing the lid, this embodiment locates the optimal target receiving tray among multiple sunken circular receiving trays on the food pick-up station based on the user's real-time location (obtained via APP positioning or geofencing). The method for determining the target receiving tray is as follows:

[0086] Multiple sunken circular receiving trays are pre-set on the food serving table. The center coordinates of each tray have been pre-marked and stored in the local database. Based on this, the local database calls the multiple cup receiving coordinates (center coordinates of the receiving trays) of the multiple sunken circular receiving trays pre-stamped on the food serving table.

[0087] Calculate multiple spatial distance features (spatial distances) between the real-time user coordinates and the multiple cup-bearing coordinates to filter out P candidate bearing coordinates that meet a preset distance threshold.

[0088] Based on the physical structure of the coffee machine (such as the radius of motion of the robotic arm and the location of obstacles at the edge of the serving table) and P alternative receiving coordinate points, the collision risk of the alternative tray positions is checked. For example, if tray position 5 is too close to the rotation axis of the robotic arm (<30 cm), it may cause the robotic arm to interfere with the serving table support during transfer. Therefore, it is marked as a high-risk tray position and eliminated. Finally, the unobstructed tray position 7 is selected as the target receiving tray.

[0089] Based on the fluid characteristics of the ordered beverage (such as whether it contains ice or the density of milk foam), the energy-efficient single-arm energy-balancing trajectory is planned between the process docking coordinates (such as the latte art station) and the target receiving tray. The technology for obtaining the single-arm energy-balancing trajectory is similar to that for the double-arm energy-balancing trajectory, and will not be elaborated here.

[0090] Using the single-arm energy consumption balancing trajectory, the substrate transport sub-arm is controlled to move the ordered coffee beverage to the target receiving tray, and then the rotatable main body is flipped to drive the cap-closing mechanical sub-arm to align with the ordered coffee beverage and perform a semi-sealed capping.

[0091] This embodiment achieves the technical effect of reducing the energy consumption of the robotic arm during the coffee making process while reducing the risk of liquid spillage during the coffee cup clamping and displacement process.

[0092] Example 2, based on the same inventive concept as the three-robotic arm collaborative control method for a coffee beverage machine combined with energy consumption analysis in the aforementioned examples, such as... Figure 2 As shown, this invention provides a three-robotic arm collaborative control system for a coffee beverage machine that incorporates energy consumption analysis, wherein the system includes:

[0093] The docking and positioning unit 1 is used to locate the process docking coordinates by parsing the order process characteristics of the real-time order information after the coffee and beverage machine receives a new real-time order. The coffee and beverage machine includes a rotary duplex robotic arm and a process robotic arm.

[0094] Demand-driven unit 2 is used to decompose the real-time order information to obtain dual-state component requirements, and drive the substrate transport sub-arm of the process robot arm and the spin-based duplex robot arm to pre-accept dual-state process raw materials according to the dual-state component requirements.

[0095] Energy consumption balance analysis unit 3 is used to perform docking control energy consumption balance analysis based on the process docking coordinates and output the dual-arm energy consumption balance trajectory.

[0096] The collaborative processing unit 4 is used to coordinate the control of the process robotic arm and the substrate transport sub-arm to move the dual-state process raw material to the process docking coordinate to perform spatiotemporal synchronous processing to obtain the ordered coffee beverage by adopting the dual-arm energy consumption balance trajectory.

[0097] The cap-closing execution unit 5 is used to align the cap-closing robotic arm with the ordered coffee beverage by flipping the rotatable main body to perform the cap-closing operation. The rotating base duplex robotic arm integrates the cap-closing robotic arm and the substrate transport arm through the rotatable main body.

[0098] In one embodiment, the demand-driven unit 2 is further configured to:

[0099] The real-time order information is decomposed to obtain liquid component requirements and non-liquid component requirements, constituting the dual-state component requirements. The liquid component requirements and non-liquid component requirements are sent to the fluid filling station and the conditioning preparation station, respectively, to drive the pre-preparation of the dual-state process raw materials, wherein the dual-state process raw materials include fluid base material and conditioning auxiliary material. The substrate carrier arm is controlled to hold a coffee cup at the fluid filling station to receive the fluid base material. The process robotic arm is controlled to hold an auxiliary material cup at the conditioning preparation station to receive the conditioning auxiliary material.

[0100] In one embodiment, the energy consumption balance analysis unit 3 is further configured to:

[0101] Based on the fluid characteristics of the base material in the coffee cup, an energy consumption balance analysis for docking control is performed between the fluid filling station and the process docking coordinates, and the base material transport balance trajectory is output. Based on the fluid characteristics of the conditioning auxiliary material in the auxiliary material cup, an energy consumption balance analysis for docking control is performed between the conditioning preparation station and the process docking coordinates, and the auxiliary material transport balance trajectory is output. The base material transport balance trajectory and the auxiliary material transport balance trajectory are time-aligned and balanced, and the dual-arm energy consumption balance trajectory is output.

[0102] In one embodiment, the energy consumption balance analysis unit 3 is further configured to:

[0103] Based on the spatiotemporal reachability constraints of the process docking coordinates, the transport time window is initialized; the sloshing suppression model is called according to the fluid characteristics of the fluid base material in the coffee cup, wherein the sloshing suppression model has a safe tilt angle threshold; in the CFD simulation environment, the multiple rounds of displacement of the base material transport arm clamping the sloshing suppression model between the fluid injection station and the process docking coordinates are simulated to obtain multiple initial candidate trajectories; the safe tilt angle threshold and the transport time window are used to traverse multiple initial fluid tilt angle sequences and multiple control transport durations of the multiple initial candidate trajectories to filter out W candidate control trajectories; the energy consumption balance quantization of the W candidate control trajectories is performed, and the base material transport balance trajectory is selected and located according to the quantization results.

[0104] In one embodiment, the energy consumption balance analysis unit 3 is further configured to:

[0105] Torque integrals are performed on the W candidate control trajectories to output W candidate torque integrals; acceleration features of the W candidate control trajectories are extracted to output W candidate acceleration distributions; W control energy consumptions, W candidate torque integrals, and W candidate acceleration distributions of the W candidate control trajectories are weighted and fused to output W quantized docking control energy consumptions; the material transport equilibrium trajectory is extracted from the W candidate control trajectories based on the ranking results of the W quantized docking control energy consumptions.

[0106] In one embodiment, the cover-fastening unit 5 is further configured to:

[0107] Based on the real-time user coordinates of the ordering user, an adaptive analysis of the food pickup distance is performed to locate the target receiving tray at the pickup station. Based on the fluid characteristics of the ordered coffee beverage, the energy consumption of the robotic arm displacement is optimized between the process docking coordinates and the target receiving tray, and a single-arm energy consumption balance trajectory is output. Using the single-arm energy consumption balance trajectory, the substrate transport sub-arm is controlled to move the ordered coffee beverage to the target receiving tray, and then the rotatable main body is flipped to drive the cap-closing robotic arm to align with the ordered coffee beverage and perform a semi-sealed cap-closing.

[0108] In one embodiment, the cover-fastening unit 5 is further configured to:

[0109] The system locally calls multiple cup-receiving coordinate points of multiple sunken circular receiving trays pre-stamped on the food dispensing station; calculates multiple spatial distance features between the real-time user coordinates and the multiple cup-receiving coordinate points, and locates P candidate receiving coordinate points; performs food dispensing obstacle verification on the P candidate receiving coordinate points according to the boundary structure of the coffee beverage machine, and locates the target receiving tray.

[0110] 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 variations or substitutions that can be easily conceived by those 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 determined by the scope of the claims.

Claims

1. A collaborative control method for three robotic arms in a coffee beverage machine based on energy consumption analysis, characterized in that: include: After receiving a new real-time order, the coffee and beverage machine locates the process docking coordinates by parsing the order process characteristics of the real-time order information. The coffee and beverage machine includes a rotary duplex robotic arm and a process robotic arm. The real-time order information is decomposed to obtain the dual-state component requirements, and the substrate transport sub-arm of the process robot arm and the spin-based duplex robot arm is driven to pre-accept the dual-state process raw materials based on the dual-state component requirements. Based on the process docking coordinates, a docking control energy consumption balance analysis is performed, and the dual-arm energy consumption balance trajectory is output. Using the dual-arm energy consumption balancing trajectory, the process robotic arm and the substrate transport sub-arm are coordinated to move the dual-state process raw material to the process docking coordinates to perform spatiotemporal synchronous processing, thereby obtaining the ordered coffee beverage. By flipping the rotatable main body, the cap-closing robotic arm is aligned with the ordered coffee beverage to perform the cap-closing operation. The rotating base duplex robotic arm integrates the cap-closing robotic arm and the substrate transport arm through the rotatable main body. The real-time order information is decomposed to obtain dual-state component requirements, and the substrate transport sub-arm of the process robot arm and the rotary duplex robot arm is driven to pre-accept dual-state process raw materials based on the dual-state component requirements, including: The real-time order information is decomposed to obtain liquid component demand and non-liquid component demand, which constitute the dual-state component demand; The liquid component requirements and non-liquid component requirements are sent to the fluid filling station and the conditioning preparation station, respectively, to drive the pre-preparation of the dual-state process raw materials, wherein the dual-state process raw materials include fluid base materials and conditioning auxiliary materials; The substrate carrier arm is controlled to hold a coffee cup and receive the fluid base material at the fluid filling station; The process robotic arm is controlled to hold the auxiliary material cup and receive the prepared auxiliary material at the prepared preparation station; Based on the aforementioned process docking coordinates, a docking control energy consumption balance analysis is performed, and the dual-arm energy consumption balance trajectory is output, including: Based on the fluid characteristics of the fluid base material in the coffee cup, an energy consumption balance analysis of docking control is performed between the fluid filling station and the process docking coordinates, and the base material transport balance trajectory is output. Based on the fluid characteristics of the conditioned excipients in the excipient cup, an energy consumption balance analysis of docking control is performed between the conditioned preparation station and the process docking coordinates, and the excipient transport balance trajectory is output. Perform time-series alignment and equalization on the base material transport balance trajectory and the auxiliary material transport balance trajectory, and output the dual-arm energy consumption balance trajectory. Based on the fluid characteristics of the fluid base material in the coffee cup, an energy consumption balance analysis for docking control is performed between the fluid filling station and the process docking coordinates, outputting the base material transport balance trajectory, including: Initialize the launch time window based on the spatiotemporal reachability constraints of the process docking coordinates; The sloshing suppression model is invoked based on the fluid characteristics of the fluid base material in the coffee cup, wherein the sloshing suppression model has a safe tilt angle threshold identifier; In the CFD simulation environment, the multiple rounds of displacement of the substrate carrier arm clamping the sway suppression model between the fluid injection station and the process docking coordinates are simulated to obtain multiple initial candidate trajectories. The safety tilt angle threshold and the carrying time window are used to traverse multiple initial fluid tilt angle sequences and multiple control carrying durations of the multiple initial candidate trajectories in order to filter out W candidate control trajectories; The energy consumption balance quantization is performed on the W candidate control trajectories, and the material transport balance trajectory is selected and located based on the quantization results; The energy consumption balance quantization is performed on the W candidate control trajectories, and the material transport balance trajectory is selected and located based on the quantization results, including: Perform torque integration on the W candidate control trajectories and output W candidate torque integrals; Extract the acceleration features of the W candidate control trajectories and output the W candidate acceleration distributions; The W control energy consumptions of the W candidate control trajectories, the W candidate torque integrals, and the W candidate acceleration distributions are weighted and fused to output W quantized docking control energy consumptions; Based on the ranking results of the W quantified docking control energy consumption, the base material transport equilibrium trajectory is extracted from the W candidate control trajectories.

2. The three-robotic arm collaborative control method for a coffee beverage machine combining energy consumption analysis as described in claim 1, characterized in that, By flipping the rotatable main body, the cap-closing robotic arm is aligned with the ordered coffee beverage to perform the cap-closing operation, including: Based on the real-time user coordinates of the ordering user, an adaptive analysis of the food pickup distance is performed to locate the target receiving tray at the food pickup station; Based on the fluid characteristics of the ordered coffee beverage, the displacement energy consumption of the robotic arm is optimized between the process docking coordinates and the target receiving plate, and a single-arm energy consumption balanced trajectory is output. Using the single-arm energy consumption balancing trajectory, the substrate transport sub-arm is controlled to move the ordered coffee beverage to the target receiving tray, and then the rotatable main body is flipped to drive the cap-closing mechanical sub-arm to align with the ordered coffee beverage and perform a semi-sealed capping.

3. The three-robotic arm collaborative control method for a coffee beverage machine combined with energy consumption analysis as described in claim 2, characterized in that, Based on the real-time user coordinates of the ordering user, an adaptive analysis of the food pickup distance is performed to locate the target receiving tray at the pickup station, including: The local system calls the coordinates of multiple cup-receiving points of the multiple sunken circular receiving trays pre-stamped on the food pick-up station. Calculate the spatial distance features between the real-time user coordinates and the multiple cup-bearing coordinate points, and locate P candidate cup-bearing coordinate points; Based on the boundary structure of the coffee beverage machine, the P candidate receiving coordinate points are checked for obstacles to food retrieval, and the target receiving tray is located.

4. A collaborative control system for three robotic arms in a coffee beverage machine, incorporating energy consumption analysis, is characterized in that: The steps for implementing the method according to any one of claims 1 to 3 include: The docking and positioning unit is used by the coffee and beverage machine to locate the process docking coordinates by parsing the order process characteristics of the real-time order information after receiving a new real-time order. The coffee and beverage machine includes a rotary duplex robotic arm and a process robotic arm. The demand-driven unit is used to decompose the real-time order information to obtain the dual-state component demand, and drive the substrate transport sub-arm of the process robot arm and the spin-based duplex robot arm to pre-accept the dual-state process raw materials according to the dual-state component demand. The energy consumption balance analysis unit is used to perform docking control energy consumption balance analysis based on the process docking coordinates and output the dual-arm energy consumption balance trajectory. The collaborative processing unit is used to coordinate the control of the process robotic arm and the substrate transport sub-arm to move the dual-state process raw material to the process docking coordinate to perform spatiotemporal synchronous processing to obtain the ordered coffee beverage by adopting the dual-arm energy consumption balance trajectory. The cap-closing execution unit is used to align the cap-closing robotic arm with the ordered coffee beverage by flipping the rotatable main body to perform the cap-closing operation. The rotating base duplex robotic arm integrates the cap-closing robotic arm and the substrate transport arm through the rotatable main body.

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