Automatic detection grabbing system of earphone assembly line

Abstract

The invention relates to the technical field of assembly line detection, in particular to an earphone assembly line automatic detection grabbing system which comprises an assembly line conveying module, a real-time detection module, an image recognition and processing module, a mechanical arm control module and a grabbing execution module. Wherein the assembly line conveying module is used for continuously conveying earphone parts; the real-time detection module is integrated with a plurality of sensors for rapid screening; the image recognition and processing module is used for recognizing features of earphone parts based on an image processing technology; the mechanical arm control module dynamically generates a motion path of the mechanical arm through linkage with the image recognition and processing module; the grabbing execution module selects the optimal grabbing mode, and stable grabbing is conducted on the premise that it is guaranteed that the parts are not damaged. The method can adapt to grabbing tasks in various complex scenes, the production efficiency of an assembly line is remarkably improved, and the requirement for human intervention is reduced.

Description

Technical Field

[0001] The invention relates to the technical field of assembly line detection, and in particular to an automatic detection and grasping system for an earphone assembly line. Background Art

[0002] In the modern headphone manufacturing process, with the continuous development of automation technology, the efficiency of the production line has been significantly improved. However, the detection and grasping of headphone parts still face many challenges. The components of headphones are of various shapes and high precision. Existing automated grasping equipment often has difficulty in handling parts of different materials, shapes and sizes, resulting in insufficient grasping accuracy or damage to parts. Most existing assembly line grasping equipment lacks flexibility, and grasping tools can usually only handle specific types of parts. When encountering complex or varied headphone parts, they cannot complete the task efficiently.

[0003] In addition, existing detection systems are mostly limited to a single type of sensor or fixed-position detection equipment, which cannot fully cope with the diversity of component shapes and random placement in headphone production, resulting in inaccurate detection results. Summary of the invention

[0004] The invention provides an automatic detection and grabbing system for an earphone production line.

[0005] An automatic detection and grasping system for an earphone assembly line includes an assembly line conveying module, a real-time detection module, an image recognition and processing module, a mechanical arm control module, and a grasping execution module; wherein: The assembly line conveying module is used for continuous conveying of earphone parts, including a conveyor belt structure with adjustable speed, which adjusts the conveying speed and direction according to the different forms of the parts to ensure that each part accurately reaches the detection and grasping position; The real-time detection module is used to perform preliminary appearance and size detection on the earphone parts. The real-time detection module integrates multiple sensors, can quickly screen according to the material, shape, and color information of the parts, and send the detection data to the image recognition and processing module; The image recognition and processing module is based on image processing technology and combines the images acquired in real time by the industrial camera to identify the features of the headphone parts, including the shape, size, and defect location of the parts; The robot control module dynamically generates the motion path of the robot by linking with the image recognition and processing module. The path is adjusted according to the actual position of the parts to ensure the grasping accuracy and speed. The grasping execution module includes a multifunctional gripper and a vacuum suction cup, and selects the optimal grasping method according to the specific shape and material of the earphone parts to ensure stable grasping without damaging the parts.

[0006] Optionally, the real-time detection module integrates an infrared sensor, an optical sensor, an ultrasonic sensor, and a color sensor, and the sensors work together to detect the material, shape, and color information of the earphone components, wherein: Infrared sensors are used to detect the material of components and quickly distinguish different headphone shell materials, such as plastic, metal or composite materials, by analyzing the heat reflection characteristics of the components. Optical sensors combined with industrial cameras are used to detect the shape of parts and identify the geometric features, size and surface integrity of the headphone shell; Ultrasonic sensors are used to detect the thickness and surface flatness of parts and components, and to identify whether there are uneven surfaces or processing defects on the headphone parts. The color sensor is used to quickly screen the appearance color of headphone components. By comparing with the preset color standards, it can determine whether the color of the components meets the production requirements and avoid color difference problems.

[0007] Optionally, the image recognition and processing module performs feature recognition on earphone components by using the following image processing technology: Edge detection technology: Based on the images acquired in real time by industrial cameras, edge detection is first used to extract the contours of the headphone components and identify the shape and external contour features of the components; Shape matching technology: Analyze the shape of parts through template matching and calculate the similarity between them and standard templates to determine whether the shape of headphone parts meets the production standards. It is suitable for the identification of headphone shells and components of different models. Dimension measurement technology: Combined with a calibrated industrial camera, the mapping relationship between pixels and actual physical dimensions is used to measure the key dimensions of headphone components to ensure that the dimensional error is within the allowable range of production, and the dimensional changes during the production process can be monitored in real time.

[0008] Optionally, the robot arm control module dynamically generates a motion path of the robot arm by linkage with the image recognition and processing module, specifically including: Position data acquisition: The image recognition and processing module determines the actual position, posture and moving direction of the headphone components relative to the conveyor belt based on the images collected in real time by the industrial camera, and transmits the position information to the robot arm control module; Path planning: The robot control module uses the inverse kinematics algorithm to generate the optimal grasping path in real time based on the position information of the headphone components. The path not only takes into account the spatial coordinates of the components, but also comprehensively analyzes the relative positions between the robot and other devices to ensure that the robot can efficiently grasp the components without colliding with other objects.

[0009] Optionally, the robotic arm control module further includes: Dynamic adjustment: When the headphone parts move or deflect slightly on the conveyor belt, the image recognition and processing module can instantly update the position information, and the robot control module dynamically adjusts the grasping path according to the latest position information to ensure that the robot arm can always quickly and accurately approach and grasp the target parts; Speed ​​optimization: After the grasping path is generated, the robot control module optimizes the movement speed of the robot through acceleration and deceleration control based on the shape and material of the headset components. The inverse kinematics algorithm generates the optimal grasping path in real time, specifically including: Obtaining the target position and posture: The image recognition and processing module provides the three-dimensional position information and relative posture of the headphone components in real time. This process is based on the detection results of industrial cameras and sensors to ensure accurate target position and angle. The position information is generally expressed in Cartesian coordinates, including displacement and angle information of the X, Y, and Z axes (such as the tilt angle of the gripping tool, etc.); Determine motion constraints: Before generating the path, the robot control module understands the motion constraints of the robot, including the range of motion of each joint, maximum speed, acceleration, and degrees of freedom of the joints; Using the inverse kinematics algorithm, the angles and motion trajectories of each joint of the robotic arm are calculated in real time based on the target position and posture. The geometric structure of the robotic arm is analyzed by the geometric method, and the angles of each joint are directly calculated. After obtaining the joint angles, the robotic arm control module will use the motion planning algorithm to generate an optimal path from the current state to the target state.

[0010] Optionally, after obtaining the angles of each joint, the robot arm control module will use a motion planning algorithm to generate an optimal path from the current state to the target state. The path planning includes: Time optimization: ensure that the robot reaches the target position at the fastest speed while meeting the robot's motion constraints; Collision detection: During path planning, ensure that the robot arm does not collide with surrounding equipment, conveyor belts or other mechanical devices during movement; Energy optimization: The optimal path should complete the grasping task with the minimum energy consumption of the robot movement, avoiding unnecessary rotation and joint movement.

[0011] Optionally, the grasping execution module intelligently selects to use a multifunctional gripper or a vacuum suction cup according to the acquired component characteristic information through the control unit, and the selection process is based on the following rules: Vacuum suction cup: suitable for parts with smooth and flat surfaces. The vacuum suction cup fixes the parts through suction and is suitable for processing large-area smooth objects; Multifunctional gripper: For parts with irregular shapes, bumps or depressions on the surface, and parts that are not easy to fix by adsorption, choose a multifunctional gripper. The multifunctional gripper uses mechanical grasping to automatically adjust the clamping point and force according to the shape of the part to ensure stable grasping.

[0012] Beneficial effects of the present invention: The present invention solves the problems of low detection accuracy and single grasping method in the prior art. By integrating multiple sensors, image recognition technology and multifunctional grasping devices, the system can flexibly respond to changes in the shape, size and material of headphone parts, and achieve efficient automatic detection and stable grasping. The system adjusts the grasping force in real time through force control sensors to avoid damage to delicate parts while ensuring the stability of the grasping process. In addition, the intelligent switching function of the vacuum suction cup and the multifunctional clamp enables the system to adapt to grasping tasks in a variety of complex scenarios, significantly improving the production efficiency of the assembly line and reducing the need for human intervention. BRIEF DESCRIPTION OF THE DRAWINGS

[0013] In order to more clearly illustrate the technical solutions in the present invention or the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings in the following description are only for the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0014] Figure 1 Schematic diagram of functional modules of a grabbing system according to an embodiment of the present invention. DETAILED DESCRIPTION

[0015] The present invention is described in detail below in conjunction with the accompanying drawings and specific embodiments. At the same time, it is explained here that in order to make the embodiments more detailed, the following embodiments are the best and preferred embodiments, and those skilled in the art may also adopt other alternatives to implement some known technologies; and the accompanying drawings are only for more specific description of the embodiments, and are not intended to specifically limit the present invention.

[0016] It should be noted that the references to "one embodiment", "embodiment", "exemplary embodiments", "some embodiments" and the like in the specification indicate that the embodiments described may include specific features, structures or characteristics, but not every embodiment may include the specific features, structures or characteristics. In addition, when a specific feature, structure or characteristic is described in conjunction with an embodiment, it should be within the knowledge of a person skilled in the art to implement such feature, structure or characteristic in conjunction with other embodiments (whether or not explicitly described).

[0017] In general, a term can be understood, at least in part, from its use in context. For example, depending, at least in part, on the context, the term "one or more" as used herein can be used to describe any feature, structure, or characteristic in the singular sense, or can be used to describe a combination of features, structures, or characteristics in the plural sense. Additionally, the term "based on" can be understood as not necessarily intended to convey an exclusive set of factors, but can instead, depending, at least in part, on the context, allow for the presence of other factors that are not necessarily explicitly described.

[0018] like Figure 1 As shown, an automatic detection and grasping system for an earphone assembly line includes an assembly line conveying module, a real-time detection module, an image recognition and processing module, a robotic arm control module, and a grasping execution module; wherein: The assembly line conveying module is used for the continuous conveying of earphone parts, including a conveyor belt structure with adjustable speed. The conveying speed and direction are adjusted according to the different forms of the parts to ensure that each part reaches the detection and grasping position accurately. The real-time detection module is used to perform preliminary appearance and size detection on earphone parts. The real-time detection module integrates multiple sensors, can quickly screen parts according to their material, shape, and color information, and send the detection data to the image recognition and processing module; The image recognition and processing module uses image processing technology and real-time images acquired by industrial cameras to identify the features of headphone components, including the shape, size, and defect location of the components. The robot control module dynamically generates the movement path of the robot arm by linking with the image recognition and processing module. The path is adjusted according to the actual position of the parts to ensure the grasping accuracy and speed. The grasping execution module includes a multi-functional gripper and a vacuum suction cup. It selects the optimal grasping method according to the specific shape and material of the headphone components to ensure stable grasping without damaging the components.

[0019] The real-time detection module integrates infrared sensors, optical sensors, ultrasonic sensors, and color sensors. The sensors work together to detect the material, shape, and color information of the headphone components. Infrared sensors are used to detect the material of components and quickly distinguish different headphone shell materials, such as plastic, metal or composite materials, by analyzing the heat reflection characteristics of the components. Optical sensors combined with industrial cameras are used to detect the shape of parts and identify the geometric features, size and surface integrity of the headphone shell; Ultrasonic sensors are used to detect the thickness and surface flatness of parts and components, and to identify whether there are uneven surfaces or processing defects on the headphone parts. The color sensor is used to quickly screen the appearance color of headphone components. By comparing with the preset color standards, it can determine whether the color of the components meets the production requirements and avoid color difference problems.

[0020] The image recognition and processing module uses the following image processing technologies to identify the features of headphone components: Edge detection technology: Based on the images acquired in real time by industrial cameras, edge detection is first used to extract the contours of the headphone components and identify the shape and external contour features of the components; Shape matching technology: Analyze the shape of parts through template matching and calculate the similarity between them and standard templates to determine whether the shape of headphone parts meets the production standards. It is suitable for the identification of headphone shells and components of different models. Dimension measurement technology: Combined with a calibrated industrial camera, the mapping relationship between pixels and actual physical dimensions is used to measure the key dimensions of headphone components to ensure that the dimensional error is within the allowable range of production, and the dimensional changes during the production process can be monitored in real time; Defect detection technology: Through high-precision image differential algorithm, it can identify whether there are scratches, dents, cracks and other appearance defects on the surface of headphone components. This module can automatically mark the defect location and generate a defect report for reference and optimization of subsequent production processes.

[0021] The robot control module dynamically generates the motion path of the robot arm by linking with the image recognition and processing module, including: Position data acquisition: The image recognition and processing module determines the actual position, posture and moving direction of the headphone components relative to the conveyor belt based on the images collected in real time by the industrial camera, and transmits the position information to the robot arm control module; Path planning: The robot control module uses the inverse kinematics algorithm to generate the optimal grasping path in real time based on the position information of the headphone components. The path not only takes into account the spatial coordinates of the components, but also comprehensively analyzes the relative positions between the robot and other devices to ensure that the robot can efficiently grasp the components without colliding with other objects.

[0022] The robot control module also includes: Dynamic adjustment: When the headphone parts move or deflect slightly on the conveyor belt, the image recognition and processing module can instantly update the position information, and the robot control module dynamically adjusts the grasping path according to the latest position information to ensure that the robot arm can always quickly and accurately approach and grasp the target parts; Speed ​​optimization: After the grasping path is generated, the robot arm control module combines the shape and material of the headphone components to optimize the movement speed of the robot arm through acceleration and deceleration control. For vulnerable parts or delicate parts, the system will automatically reduce the grasping speed to avoid damage; for stable parts, the robot arm can adopt high-speed grasping mode to improve production efficiency.

[0023] The core of the inverse kinematics problem is to solve the angle of each joint of the robot arm when the desired position and posture of the end effector are known (usually three-dimensional coordinates and the direction of grasping). The movement of the robot arm is controlled by multiple joints, and each joint has its range of motion and degree of freedom. Inverse kinematics calculates the angle changes of these joints to achieve the end effector reaching the target position; input the target position and posture of the end effector, and output the rotation angle or position of each joint of the robot arm. The inverse kinematics algorithm generates the optimal grasping path in real time, specifically including: Obtaining the target position and posture: The image recognition and processing module provides the three-dimensional position information and relative posture of the headphone components in real time. This process is based on the detection results of industrial cameras and sensors to ensure accurate target position and angle. The position information is generally expressed in Cartesian coordinates, including displacement and angle information of the X, Y, and Z axes (such as the tilt angle of the gripping tool, etc.); Determine motion constraints: Before generating a path, the robot control module understands the motion constraints of the robot, including the range of motion of each joint, maximum speed, acceleration, and degrees of freedom of the joints. This information determines the motion mode that the robot can perform and avoids the generation of a path that exceeds the physical limits of the robot. Using the inverse kinematics algorithm, the angles and motion trajectories of each joint of the robotic arm are calculated in real time based on the target position and posture. The geometric structure of the robotic arm is analyzed by the geometric method, and the angles of each joint are directly calculated. After obtaining the joint angles, the robotic arm control module will use the motion planning algorithm to generate an optimal path from the current state to the target state.

[0024] After obtaining the angles of each joint, the robot control module will use the motion planning algorithm to generate an optimal path from the current state to the target state. Path planning includes: Time optimization: ensure that the robot reaches the target position at the fastest speed while meeting the robot's motion constraints; Collision detection: During path planning, ensure that the robot arm does not collide with surrounding equipment, conveyor belts or other mechanical devices during movement; Energy optimization: The optimal path should complete the grasping task with the minimum energy consumption of the robot movement, avoiding unnecessary rotation and joint movement.

[0025] The gripping execution module uses the control unit to intelligently select the multi-function gripper or vacuum suction cup based on the acquired component characteristic information. The selection process is based on the following rules: Vacuum suction cup: suitable for parts with smooth and flat surfaces. The vacuum suction cup fixes the parts through suction, which is suitable for handling large-area smooth objects and can avoid surface damage that may be caused by using mechanical grippers. The suction cup can adjust the suction force according to the surface material and air tightness of the parts to ensure a stable grasp without damaging the parts; Multifunctional gripper: For parts with irregular shapes, bumps or depressions on the surface, and parts that are not easy to fix by adsorption, choose a multifunctional gripper. The multifunctional gripper automatically adjusts the gripping point and force according to the shape of the part through mechanical grasping to ensure stable grasping. The gripper is usually covered with flexible material to prevent excessive pressure from causing physical damage to the part.

[0026] The present invention covers any substitution, modification, equivalent method and scheme made on the essence and scope of the present invention. In order to make the public have a thorough understanding of the present invention, specific details are described in detail in the following preferred embodiments of the present invention, but those skilled in the art can fully understand the present invention without the description of these details. In addition, in order to avoid unnecessary confusion about the essence of the present invention, well-known methods, processes, procedures, components and circuits are not described in detail.

[0027] The above is only a preferred embodiment of the present invention. It should be pointed out that for ordinary technicians in this technical field, several improvements and modifications can be made without departing from the principle of the present invention. These improvements and modifications should also be regarded as the scope of protection of the present invention.

Claims

1. An automatic detection and grabbing system for a headphone production line, characterized in that: It includes assembly line conveying module, real-time detection module, image recognition and processing module, robotic arm control module, and grasping execution module; among which: The assembly line conveying module is used for continuous conveying of earphone parts, including a conveyor belt structure with adjustable speed, which adjusts the conveying speed and direction according to the different forms of the parts to ensure that each part accurately reaches the detection and grasping position; The real-time detection module is used to perform preliminary appearance and size detection on the earphone parts. The real-time detection module integrates multiple sensors, can quickly screen according to the material, shape, and color information of the parts, and send the detection data to the image recognition and processing module; The image recognition and processing module is based on image processing technology and combines the images acquired in real time by the industrial camera to identify the features of the headphone parts, including the shape, size, and defect location of the parts; The robot control module dynamically generates the motion path of the robot by linking with the image recognition and processing module. The path is adjusted according to the actual position of the parts to ensure the grasping accuracy and speed. The grasping execution module includes a multifunctional gripper and a vacuum suction cup, and selects the optimal grasping method according to the specific shape and material of the earphone parts to ensure stable grasping without damaging the parts.

2. The automatic detection and grabbing system for earphone production line according to claim 1, characterized in that: The real-time detection module integrates infrared sensors, optical sensors, ultrasonic sensors and color sensors, which work together to detect the material, shape and color information of the earphone parts, wherein: Infrared sensors are used to detect the material of components and quickly distinguish headphone shells of different materials by analyzing the heat reflection characteristics of the components; Optical sensors combined with industrial cameras are used to detect the shape of parts and identify the geometric features, size and surface integrity of the headphone shell; Ultrasonic sensors are used to detect the thickness and surface flatness of parts and components, and to identify whether there are uneven surfaces or processing defects on the headphone parts. The color sensor is used to quickly screen the appearance color of headphone components. By comparing with the preset color standards, it can determine whether the color of the components meets the production requirements and avoid color difference problems.

3. The automatic detection and grabbing system for earphone production line according to claim 1, characterized in that: The image recognition and processing module performs feature recognition on the earphone components through the following image processing technologies: Edge detection technology: Based on the images acquired in real time by industrial cameras, edge detection is first used to extract the contours of the headphone components and identify the shape and external contour features of the components; Shape matching technology: Analyze the shape of parts through template matching, calculate the similarity between them and the standard template, and thus determine whether the shape of the headphone parts meets the production standards; Dimension measurement technology: Combined with a calibrated industrial camera, the mapping relationship between pixels and actual physical dimensions is used to measure the key dimensions of headphone components to ensure that the dimensional error is within the allowable range of production.

4. The automatic detection and grasping system for earphone production line according to claim 1, characterized in that: The robot arm control module dynamically generates the motion path of the robot arm by linking with the image recognition and processing module, specifically including: Position data acquisition: The image recognition and processing module determines the actual position, posture and moving direction of the headphone components relative to the conveyor belt based on the images collected in real time by the industrial camera, and transmits the position information to the robot arm control module; Path planning: The robot control module uses the inverse kinematics algorithm to generate the optimal grasping path in real time based on the position information of the headphone components. The path not only takes into account the spatial coordinates of the components, but also comprehensively analyzes the relative positions between the robot and other devices to ensure that the robot can efficiently grasp the components without colliding with other objects.

5. The automatic detection and grabbing system for earphone production line according to claim 4, characterized in that: The robotic arm control module also includes: Dynamic adjustment: When the headphone parts move or deflect slightly on the conveyor belt, the image recognition and processing module can instantly update the position information, and the robotic arm control module dynamically adjusts the grasping path according to the latest position information to ensure that the robotic arm always grasps the target parts; Speed ​​optimization: After the grasping path is generated, the robot arm control module combines the shape and material of the earphone components to optimize the robot arm movement speed through acceleration and deceleration control.

6. The automatic detection and grabbing system for earphone production line according to claim 4, characterized in that: The inverse kinematics algorithm generates the optimal grasping path in real time, specifically including: Obtaining target position and posture: The image recognition and processing module provides the three-dimensional position information and relative posture of the headphone components in real time; Determine motion constraints: Before generating the path, the robot control module understands the motion constraints of the robot, including the range of motion of each joint, maximum speed, acceleration, and degrees of freedom of the joints; Using the inverse kinematics algorithm, the angles and motion trajectories of each joint of the robotic arm are calculated in real time based on the target position and posture. The geometric structure of the robotic arm is analyzed by the geometric method, and the angles of each joint are directly calculated. After obtaining the joint angles, the robotic arm control module will use the motion planning algorithm to generate an optimal path from the current state to the target state.

7. The automatic detection and grabbing system for earphone production line according to claim 6, characterized in that: After obtaining the angles of each joint, the robot control module will use the motion planning algorithm to generate an optimal path from the current state to the target state. The path planning includes: Time optimization: ensure that the robot reaches the target position at the fastest speed while meeting the robot's motion constraints; Collision detection: During path planning, ensure that the robot arm does not collide with surrounding equipment, conveyor belts or other mechanical devices during movement; Energy optimization: The optimal path should complete the grasping task with the minimum energy consumption of the robot movement, avoiding unnecessary rotation and joint movement.

8. The automatic detection and grasping system for earphone production line according to claim 1, characterized in that: The grasping execution module intelligently selects to use a multifunctional gripper or a vacuum suction cup according to the acquired component characteristic information through the control unit, and the selection process is based on the following rules: Vacuum suction cup: suitable for parts with smooth and flat surfaces. The vacuum suction cup fixes the parts through suction and is suitable for processing large-area smooth objects; Multifunctional gripper: For parts with irregular shapes, bumps or depressions on the surface, and parts that are not easy to fix by adsorption, choose a multifunctional gripper. The multifunctional gripper uses mechanical grasping to automatically adjust the clamping point and force according to the shape of the part to ensure stable grasping.

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