Mechanical arm meal taking interaction control method, system and equipment and medium

Abstract

The invention provides a mechanical arm meal taking interaction control method, system and device and a medium. The method comprises the steps that force in any direction is obtained based on mechanical arm force sensing, force change is obtained based on the sensed force in any direction, a clamping jaw of a mechanical arm is controlled to be loosened based on the force change, and mechanical arm meal taking interaction control is achieved.

Description

Technical Field

[0001] This invention relates to the field of human-machine interaction technology for robotic arms, specifically to a method, system, device, and medium for interactive control of robotic arm food retrieval. Background Technology

[0002] In the field of food service automation, existing technologies for robotic arm food retrieval and interaction control typically employ a preset program control method. Specifically, the robotic arm moves to the food retrieval position according to a pre-set motion trajectory, grips the food with a fixed clamping force using its grippers, and then remains stationary, waiting for the user to retrieve the food.

[0003] Throughout the entire food retrieval process, the robotic arm's gripper release action relies entirely on user-inputted commands: when a user retrieves their food, they must send a release signal to the robotic arm by triggering a preset button, touch sensor, or voice command. Only after receiving this signal will the robotic arm control the gripper to release. This control logic, which depends on active user input, results in significant operational redundancy in the food retrieval process. Users must perform additional command input operations outside of the food retrieval action, increasing the complexity of the process and potentially causing interruptions or delayed gripper release due to input delays or operational errors, thus impacting efficiency and user experience. Summary of the Invention

[0004] To address the shortcomings of existing technologies, the purpose of this invention is to provide a robotic arm food retrieval interactive control method, system, device, and medium.

[0005] According to the present invention, a robotic arm food retrieval interactive control method includes: obtaining force in any direction based on the robotic arm's force sensing, obtaining force changes based on the sensed force in any direction, and controlling the gripper of the robotic arm to release based on the force changes, thereby realizing robotic arm food retrieval interactive control.

[0006] Preferably, the step of acquiring force in any direction based on the force sensor of the robotic arm, acquiring force changes based on the sensed force in any direction, and controlling the gripper of the robotic arm to release based on the force changes to achieve interactive control of the robotic arm picking up food includes:

[0007] Step S1: Control the robotic arm holding the skewered bamboo sticks to reach the preset position and clear the force sensing of the robotic arm.

[0008] Step S2: When the force sensing of the robotic arm changes, control the gripper of the robotic arm to loosen by a certain width;

[0009] Step S3: When the human hand is removed, control the robotic arm to return to the preset position.

[0010] Preferably, step S1 includes: obtaining the force of each mechanical joint based on the torque sensor integrated in each joint of the robotic arm; and obtaining the end-effector force by back-calculating the obtained force of each mechanical joint through a dynamic model.

[0011] Preferably, step S3 includes: setting up a detection device in a preset food collection area to detect whether a hand enters; when a hand is detected, triggering an image acquisition device; acquiring image information of the food collection area in real time through the image acquisition device; performing hand recognition based on the image information; when no hand information is detected in the image information, and the robotic arm gripper releases a certain width of preset time, it is considered that the hand has been removed, and the robotic arm is controlled to return to the preset position.

[0012] A robotic arm food-fetching interactive control system according to the present invention includes:

[0013] The change sensing module is used to obtain force in any direction based on the force sensing of the robotic arm, and to obtain the change in force based on the sensed force in any direction.

[0014] The control module is used to control the gripper of the robotic arm to release based on force changes, so as to realize the interactive control of the robotic arm to pick up food.

[0015] Preferably, the system includes:

[0016] Module M1: Controls the robotic arm holding the skewered bamboo sticks to reach the preset position and resets the force sensing of the robotic arm to zero.

[0017] Module M2: When the force sensing of the robotic arm changes, it controls the gripper of the robotic arm to loosen by a certain width;

[0018] Module M3: When the human hand is removed, the robotic arm is controlled to return to the preset position.

[0019] Preferably, the module M1 includes: obtaining the force of each mechanical joint based on the torque sensor integrated in each joint of the robotic arm; and obtaining the end force by back-calculating the obtained force of each mechanical joint through a dynamic model.

[0020] Preferably, the module M3 includes: setting a detection device in a preset food pick-up area to detect whether a hand enters; when a hand is detected, triggering an image acquisition device; acquiring image information of the food pick-up area in real time through the image acquisition device; performing hand recognition based on the image information; when no hand information is detected in the image information, and the robotic arm gripper releases a certain width of preset time, it is considered that the hand has been removed, and the robotic arm is controlled to return to the preset position.

[0021] According to an electronic device provided by the present invention, the electronic device includes a memory and at least one processor, wherein the memory stores instructions;

[0022] The at least one processor invokes the instructions in the memory to cause the electronic device to execute the various steps of the robotic arm food retrieval interaction control method as described above.

[0023] According to a computer-readable storage medium provided by the present invention, the computer-readable storage medium stores instructions, which, when executed by a processor, implement the various steps of the robotic arm food-picking interactive control method described above.

[0024] Compared with the prior art, the present invention has the following beneficial effects:

[0025] 1. This invention achieves a safe and stable human-computer interaction process for food retrieval by employing precise force control sensing of a robotic arm and real-time width feedback of the end gripper.

[0026] 2. This invention utilizes the force sensing capability of the robotic arm, eliminating the need for users to input additional commands. The release of the gripper is triggered simply by the force change generated when a person picks up a bamboo skewer, thus eliminating the need for users to actively operate the command input device. This simplifies the food retrieval process, making food retrieval more natural and efficient for users, and reducing the inconvenience caused by redundant operations.

[0027] 3. The robotic arm integrates torque sensors in each joint, and uses a dynamic model to back-calculate the force and torque of the end effector TCP. After reaching the food retrieval position, the force is reset to zero. It can accurately sense changes in force in any direction, ensuring that the gripper releases in time when the hand comes into contact with it, avoiding squeezing or scratching the hand due to continuous gripping by the gripper, and reducing safety risks during the interaction process.

[0028] 4. Combining the detection device and image acquisition device of the preset food pick-up area, the image acquisition is triggered when a hand is detected entering. The image recognition technology monitors in real time whether the hand has been removed. At the same time, the preset time condition after the gripper releases a certain width ensures the accuracy of the hand removal judgment. This avoids the problem of the robotic arm removing too early or too late due to relying solely on a fixed time delay. It not only prevents interference with the user's food pick-up, but also improves the working efficiency of the robotic arm. Attached Figure Description

[0029] Other features, objects, and advantages of the present invention will become more apparent from the following detailed description of non-limiting embodiments with reference to the accompanying drawings:

[0030] Figure 1 This is a flowchart of the interactive control method for a robotic arm to pick up food.

[0031] Figure 2 This is a flowchart of an automated threading method based on dual-arm collaborative control and force sensing feedback.

[0032] Figure 3 This is a flowchart of an automatic threading control method for a robotic arm based on machine vision and real-time communication. Detailed Implementation

[0033] The present invention will now be described in detail with reference to specific embodiments. These embodiments will help those skilled in the art to further understand the present invention, but do not limit the invention in any way. It should be noted that those skilled in the art can make several changes and improvements without departing from the concept of the present invention. These all fall within the scope of protection of the present invention.

[0034] Example 1

[0035] According to the present invention, a robotic arm food retrieval interactive control method is provided, such as... Figure 1 As shown, it includes: obtaining force in any direction based on the force sensing of the robotic arm, obtaining force changes based on the sensed force in any direction, and controlling the gripper of the robotic arm to release based on the force changes, thereby realizing interactive control of the robotic arm to pick up food.

[0036] Specifically, the method of acquiring force in any direction based on the force sensing of the robotic arm, obtaining force changes based on the sensed force in any direction, and controlling the release of the gripper of the robotic arm based on the force changes to achieve interactive control of the robotic arm for food retrieval includes:

[0037] Step S1: Control the robotic arm holding the skewered bamboo sticks to reach the preset position and clear the force sensing of the robotic arm.

[0038] Step S2: When the force sensing of the robotic arm changes, control the gripper of the robotic arm to loosen by a certain width;

[0039] Step S3: When the human hand is removed, control the robotic arm to return to the preset position.

[0040] Specifically, step S1 includes: obtaining the force of each mechanical joint based on the torque sensor integrated in each joint of the robotic arm; and obtaining the end force by back-calculating the force of each mechanical joint through a dynamic model.

[0041] Specifically, step S3 includes: setting up a detection device in a preset food collection area to detect whether a hand enters; when a hand is detected, triggering an image acquisition device; acquiring image information of the food collection area in real time through the image acquisition device; performing hand recognition based on the image information; when no hand information is detected in the image information, and the robotic arm gripper releases a certain width of preset time, it is considered that the hand has been removed, and the robotic arm is controlled to return to the preset position.

[0042] The present invention also provides a robotic arm food retrieval interaction control system, which can be implemented by executing the process steps of the robotic arm food retrieval interaction control method. That is, those skilled in the art can understand the robotic arm food retrieval interaction control method as a preferred embodiment of the robotic arm food retrieval interaction control system.

[0043] Example 2

[0044] Example 2 is a preferred example of Example 1.

[0045] An automated threading method based on dual-robotic arm collaborative control and force sensing feedback is provided by the present invention, such as... Figure 2 As shown, it includes:

[0046] Step 201: The first robotic arm grabs the bamboo skewers, and the second robotic arm grabs the raw materials;

[0047] Step 202: Perform basic positioning of the first robotic arm for grasping bamboo skewers and the second robotic arm for grasping raw materials to meet preset requirements; under the basic positioning of the first robotic arm for grasping bamboo skewers and the second robotic arm for grasping raw materials to meet preset requirements, identify the position information of bamboo skewers; wherein, the spatial position of the tip of the bamboo skewer and the angle information between the target bamboo skewer and the horizontal line;

[0048] Step 203: Calculate the alignment points of the first robotic arm and the second robotic arm based on the identified bamboo skewer position information;

[0049] Step 204: Based on the alignment of the first and second robotic arms at the threading points, the robotic arms perform threading, and determine whether the threading is successful through force control sensing to achieve closed-loop stable threading;

[0050] Step 205: Control the robotic arm holding the skewered bamboo sticks to reach the preset position and reset the force sensing of the robotic arm to zero.

[0051] Step 206: When the force sensing of the robotic arm changes, control the gripper of the robotic arm to loosen by a certain width;

[0052] Step 207: When the human hand is removed, control the robotic arm to return to the preset position.

[0053] Specifically, step 201 includes:

[0054] Step 2011: Obtain the fixed position information of the target bamboo stick, control the gripper of the first robotic arm to grab the target bamboo stick based on the fixed position information of the target bamboo stick, and determine whether the target bamboo stick has been successfully grabbed by force control sensing of the gripper and real-time feedback of the gripping width.

[0055] Step 2012: Identify the center location of the target raw material and the distance between the target raw material and adjacent raw material locations using AI;

[0056] Step 2013: Use the identified center position of the target material as the center position for the gripper of the second robotic arm; obtain the gripping posture of the second robotic arm gripper based on the distance between the original position of the target and the adjacent material positions, so that the second robotic arm can avoid interference between the gripper and the material to the greatest extent.

[0057] Step 2014: Based on the gripping posture of the second robotic arm gripper, and combined with the width of the target material, obtain the opening width of the second robotic arm gripper;

[0058] Step 2015: Grasp the target raw material based on the gripping posture and opening width of the second robotic arm's gripper.

[0059] Specifically, step 202 includes:

[0060] Step 2021: Move the first robotic arm that grabs bamboo skewers and the second robotic arm that grabs raw materials to a preset range directly above the raw material cooking pot, and make the center point of the raw material located on the central axis of the bamboo skewers, thus completing the basic positioning of the first robotic arm that grabs bamboo skewers and the second robotic arm that grabs raw materials to meet the preset requirements.

[0061] Step 2022: Use AI to identify the spatial position of the tip of the bamboo skewer grasped by the first robotic arm and the angle between the bamboo skewer and the horizontal line.

[0062] Specifically, step 203 includes:

[0063] Step 2031: In the Cartesian coordinate system of the first robotic arm, the spatial position of the tip of the bamboo skewer is obtained by AI recognition, and the starting point of stringing is obtained based on the spatial position of the tip of the bamboo skewer.

[0064] Step 2032: Calculate the skewering end point by recognizing the tilt angle of the bamboo skewers and the order of the meatballs to be skewered using AI.

[0065] Specifically, step 204 includes:

[0066] The first robotic arm that is currently grasping bamboo skewers and the second robotic arm that is grasping raw materials move relative to each other along the central axis of the bamboo skewers based on the starting point and ending point of skewering to implement the skewering of the robotic arms;

[0067] During the process from the start point to the end point of the stringing process, the second robotic arm that grabs the raw materials obtains the sensing force through the force control sensor of the first robotic arm. When the sensing force is always less than or equal to the preset value, it is determined that the current stringing has failed; when the sensing force is greater than the preset value, it is determined that the current stringing has been completed.

[0068] Specifically, step 205 includes: obtaining the force of each mechanical joint based on the torque sensor integrated in each joint of the robotic arm; and obtaining the end force by back-calculating the force of the end effector based on the obtained force of each mechanical joint through a dynamic model.

[0069] Specifically, step 207 includes: setting up a detection device in a preset food collection area to detect whether a hand enters; when a hand is detected, triggering an image acquisition device; acquiring image information of the food collection area in real time through the image acquisition device; performing hand recognition based on the image information; when no hand information is detected in the image information, and the robotic arm gripper releases a certain width of preset time, it is considered that the hand has been removed, and the robotic arm is controlled to return to the preset position.

[0070] The present invention also provides an automated threading system based on dual-arm collaborative control and force sensing feedback. The automated threading system based on dual-arm collaborative control and force sensing feedback can be implemented by executing the process steps of the automated threading method based on dual-arm collaborative control and force sensing feedback. That is, those skilled in the art can understand the automated threading method based on dual-arm collaborative control and force sensing feedback as a preferred embodiment of the automated threading system based on dual-arm collaborative control and force sensing feedback.

[0071] Example 3

[0072] Example 3 is a preferred example of Example 2.

[0073] The present invention provides an automatic threading control method for a robotic arm based on machine vision and real-time communication, such as... Figure 3 As shown, it includes:

[0074] Step 301: The overall scheduling module controls the image acquisition module to acquire food images and bamboo skewer images, and then the recognition module is used to identify the target food information and target bamboo skewer information;

[0075] Step 302: Based on the real-time communication between the overall scheduling module and the robotic arm, dynamically acquire the motion state of the robotic arm;

[0076] Step 303: Based on the identified target ingredient information and target bamboo skewer information, as well as the dynamically acquired motion state of the robotic arm, control the robotic arm to perform preset actions according to the preset execution process, thereby realizing automatic skewering by the robotic arm.

[0077] Specifically, during the real-time communication between the overall scheduling module and the robotic arm, the hardware information of the robotic arm is dynamically acquired. Based on the dynamically acquired hardware information, the status of the robotic arm is monitored. When the status of the robotic arm is abnormal, an abnormal warning is issued. The hardware information includes whether there is an emergency stop and whether there is an error message.

[0078] The real-time communication between the overall scheduling module and the robotic arm includes: the overall scheduling module communicating with the robotic arm in real time via the ModbusTCP protocol.

[0079] Specifically, step 301 includes:

[0080] Step 3011: When the main scheduling module receives the automatic stringing instruction, it controls the filter lifting module to rise until the liquid level sensor module determines that the filter lifting module is above the liquid level.

[0081] Step 3012: Control the image acquisition module through the overall scheduling module to acquire the food images and bamboo skewer images in the target area of ​​the current filter lifting module;

[0082] Step 3013: Based on the food image and bamboo skewer image, the AI ​​algorithm in the recognition module identifies the target food information and target bamboo skewer information; the target food includes: the food with the highest similarity to the food requested by the user; the target food information includes: the target food coordinates, the length, width, and angle of the target food; the target bamboo skewer information includes: the bamboo skewer at the target location within the target area; the target bamboo skewer information includes: the target bamboo skewer coordinates, length, and angle information. Based on the target food information and target bamboo skewer information, the first and second robotic arms in the robotic arm are controlled to grip the target food and target bamboo skewer respectively.

[0083] Specifically, step 3011 includes: the main scheduling module establishing communication with the filter lifting module and the liquid level sensor module through the USB to RS485 module; controlling the filter lifting module to rise and fall through the main scheduling module, and determining whether the filter lifting module is above or below the liquid level through the liquid level sensor module; and ensuring the stability and safety of the equipment operation through the liquid level sensor module.

[0084] Specifically, the method further includes: storing basic information of ingredients and bamboo skewers in a Redis database; updating the basic information of ingredients and bamboo skewers in the Redis database when the robotic arm automatically completes the skewering; storing basic information of meatballs in real time and accurately controlling inventory deduction, effectively improving data processing efficiency and accuracy;

[0085] The basic information about the ingredients includes: the remaining quantity of different ingredients, the location information of the remaining bamboo skewers, and the remaining quantity of bamboo skewers.

[0086] The remaining quantity of different ingredients is displayed through the display module.

[0087] Specifically, the method further includes: controlling the cooking equipment through the overall scheduling module, obtaining the status information of the cooking equipment in real time, and pushing it to the client through the WebSocket communication protocol.

[0088] In this embodiment, during each cycle of the threading process, the overall control module communicates in real time with the robotic arm, image acquisition module, and hardware devices to precisely schedule the execution of each module at each key node, ensuring that each link performs its own function, does not interfere with each other, and operates in a coordinated and efficient manner.

[0089] Specifically, step 303 includes:

[0090] Step 3031: The left robotic arm grabs the bamboo skewer, and the right robotic arm grabs the raw material;

[0091] Specifically, step 3031 includes:

[0092] Step 30311: Obtain the fixed position information of the target bamboo stick, and control the gripper of the left robotic arm to grasp the target bamboo stick based on the fixed position information of the target bamboo stick. In this embodiment, the left robotic arm can grasp the bamboo stick based on its fixed position. Then, determine whether the target bamboo stick has been successfully grasped by the force control sensing of the gripper and the real-time feedback of the gripping width.

[0093] Step 30312: Identify the center location of the target raw material and the distance between the target raw material and adjacent raw material locations using AI;

[0094] Step 30313: Use the identified center position of the target material as the center position for gripping by the right robotic arm's gripper; obtain the gripping posture of the right robotic arm's gripper based on the distance between the original position of the target and the adjacent material positions, so that the right robotic arm can avoid interference between the gripper and the material to the greatest extent.

[0095] Step 30314: Based on the gripping posture of the right robotic arm gripper, and combined with the width of the target material, obtain the opening width of the right robotic arm gripper to achieve precise gripping and avoidance of interference with the material.

[0096] Step 30315: Grasp the target raw material based on the gripping posture and opening width of the right robotic arm's gripper.

[0097] Step 3032: Perform basic positioning of the left robotic arm for grasping bamboo skewers and the right robotic arm for grasping raw materials to meet preset requirements; under the basic positioning of the left robotic arm for grasping bamboo skewers and the right robotic arm for grasping raw materials to meet preset requirements, identify the position information of bamboo skewers; wherein, the spatial position of the tip of the bamboo skewer and the angle information between the target bamboo skewer and the horizontal line.

[0098] Specifically, step 3032 includes:

[0099] Step 30321: Move the left robotic arm that grabs the bamboo skewer and the right robotic arm that grabs the raw material to the preset range directly above the raw material cooking pot, and make the center point of the raw material located on the central axis of the bamboo skewer, thus completing the basic positioning of the left robotic arm that grabs the bamboo skewer and the right robotic arm that grabs the raw material to meet the preset requirements.

[0100] Step 30322: Use AI to identify the spatial position of the tip of the bamboo skewer grasped by the left robotic arm and the angle between the bamboo skewer and the horizontal line.

[0101] Step 3033: Calculate the alignment points for the left and right robotic arms based on the identified bamboo skewer position information;

[0102] Specifically, step 3033 includes:

[0103] Step 30331: Under the Cartesian coordinate system of the left robotic arm, the spatial position of the tip of the bamboo skewer is obtained through AI recognition, and the starting point of stringing is obtained based on the spatial position of the tip of the bamboo skewer.

[0104] Step 30332: Calculate the skewering end point by recognizing the tilt angle of the bamboo skewers and the order of the meatballs to be skewered using AI.

[0105] Step 3034: Based on the alignment of the left and right robotic arms at the threading points, the robotic arms perform threading, and determine whether the threading is successful through force control sensing to achieve closed-loop stable threading.

[0106] Specifically, step 3034 includes: controlling the left robotic arm currently gripping the bamboo skewer and the right robotic arm gripping the raw material to move relative to each other along the central axis of the bamboo skewer based on the starting point and ending point of the stringing process to implement the stringing process.

[0107] During the process from the start point to the end point of the stringing process, the second robotic arm that grabs the raw materials obtains the sensing force through the force control sensor of the first robotic arm. When the sensing force is always less than or equal to the preset value, it is determined that the current stringing has failed; when the sensing force is greater than the preset value, it is determined that the current stringing has been completed.

[0108] The present invention also provides an automatic threading control system for a robotic arm based on machine vision and real-time communication. The automatic threading control system for a robotic arm based on machine vision and real-time communication can be implemented by executing the process steps of the automatic threading control method for a robotic arm based on machine vision and real-time communication. That is, those skilled in the art can understand the automatic threading control method for a robotic arm based on machine vision and real-time communication as a preferred embodiment of the automatic threading control system for a robotic arm based on machine vision and real-time communication.

[0109] Those skilled in the art will understand that, in addition to implementing the system, apparatus, and their modules provided by this invention in purely computer-readable program code, the same program can be implemented in the form of logic gates, switches, application-specific integrated circuits, programmable logic controllers, and embedded microcontrollers by logically programming the method steps. Therefore, the system, apparatus, and their modules provided by this invention can be considered a hardware component, and the modules included therein for implementing various programs can also be considered structures within the hardware component; alternatively, modules for implementing various functions can be considered both software programs implementing the method and structures within the hardware component.

[0110] Specific embodiments of the present invention have been described above. It should be understood that the present invention is not limited to the specific embodiments described above, and those skilled in the art can make various changes or modifications within the scope of the claims, which do not affect the essence of the present invention. Unless otherwise specified, the embodiments and features described in this application can be arbitrarily combined with each other.

Claims

1. A robotic arm food retrieval interactive control method, characterized in that, include: The robotic arm uses force sensing to acquire force in any direction, and uses the force changes to control the release of the gripper based on the force changes, thus realizing interactive control of the robotic arm for food retrieval.

2. The robotic arm food-fetching interactive control method according to claim 1, characterized in that, The method involves acquiring force in any direction based on the robotic arm's force sensing, obtaining force changes based on the sensed force in any direction, and controlling the release of the robotic arm's gripper based on the force changes to achieve interactive control of the robotic arm for food retrieval, including: Step S1: Control the robotic arm holding the skewered bamboo sticks to reach the preset position and clear the force sensing of the robotic arm. Step S2: When the force sensing of the robotic arm changes, control the gripper of the robotic arm to loosen by a certain width; Step S3: When the human hand is removed, control the robotic arm to return to the preset position.

3. The robotic arm food-fetching interactive control method according to claim 2, characterized in that, Step S1 includes: obtaining the force of each mechanical joint based on the torque sensor integrated in each joint of the robotic arm; and obtaining the end force by back-calculating the force of the end effector based on the obtained force of each mechanical joint through a dynamic model.

4. The robotic arm food-fetching interactive control method according to claim 2, characterized in that, Step S3 includes: setting up a detection device in a preset food collection area to detect whether a hand enters; when a hand is detected, triggering an image acquisition device; acquiring image information of the food collection area in real time through the image acquisition device; performing hand recognition based on the image information; when no hand information is detected in the image information, and the robotic arm gripper releases a certain width of preset time, it is considered that the hand has been removed, and the robotic arm is controlled to return to the preset position.

5. A robotic arm food-fetching interactive control system, characterized in that, include: The change sensing module is used to obtain force in any direction based on the force sensing of the robotic arm, and to obtain the change in force based on the sensed force in any direction. The control module is used to control the gripper of the robotic arm to release based on force changes, so as to realize the interactive control of the robotic arm to pick up food.

6. The robotic arm food-fetching interactive control method according to claim 1, characterized in that, The system includes: Module M1: Controls the robotic arm holding the skewered bamboo sticks to reach the preset position and resets the force sensing of the robotic arm to zero. Module M2: When the force sensing of the robotic arm changes, it controls the gripper of the robotic arm to loosen by a certain width; Module M3: When the human hand is removed, the robotic arm is controlled to return to the preset position.

7. The robotic arm food-fetching interactive control system according to claim 6, characterized in that, The module M1 includes: obtaining the force of each mechanical joint based on the torque sensor integrated in each joint of the robotic arm; and obtaining the end force by back-calculating the force of each mechanical joint through a dynamic model.

8. The robotic arm food-fetching interactive control system according to claim 6, characterized in that, The module M3 includes: setting a detection device in a preset food pick-up area to detect whether a hand enters; when a hand is detected, triggering an image acquisition device; acquiring image information of the food pick-up area in real time through the image acquisition device; performing hand recognition based on the image information; when no hand information is detected in the image information, and the robotic arm gripper releases a certain width of preset time, it is considered that the hand has been removed, and the robotic arm is controlled to return to the preset position.

9. An electronic device comprising a memory and at least one processor, wherein the memory stores instructions; The at least one processor invokes the instructions in the memory to cause the electronic device to perform the steps of the robotic arm food-fetching interactive control method as described in any one of claims 1-4.

10. A computer-readable storage medium storing instructions thereon, characterized in that, When the instructions are executed by the processor, they implement the various steps of the robotic arm food-fetching interactive control method as described in any one of claims 1-4.

Images