Negative pressure type fruit picking mechanical arm and control system thereof

Abstract

The invention relates to the technical field of intelligent agriculture, and provides a negative pressure type fruit picking mechanical arm and a control system thereof.The negative pressure type fruit picking mechanical arm comprises a connecting chassis, a plurality of wheels are rotationally connected to the outer side wall of the connecting chassis, a storage groove is fixedly connected to the outer side wall of the top end of the connecting chassis, and a picking mechanism is arranged at the top end of the connecting chassis; the picking mechanism comprises a connecting frame which is mounted at the top end of the connecting chassis; by integrating an advanced mechanical arm and a visual recognition technology, the robot can accurately recognize and quickly pick crops, the picking efficiency is greatly improved, the robot is particularly suitable for large-scale agricultural production, the crop quality is improved, crop maturity judgment is conducted through deep learning models such as YOLOv5, immature crops are prevented from being picked by mistake, and the crop quality is improved. The quality of picked crops is guaranteed, the market value of agricultural products is improved, the labor cost is reduced, full-process automatic operation is achieved, the labor demand is reduced, the labor cost of agricultural production is reduced, and meanwhile the labor intensity of farmers is relieved.

Description

Technical Field

[0001] The invention relates to the technical field of intelligent agriculture, and in particular to a negative pressure fruit picking mechanical arm and a control system thereof. Background Art

[0002] With the continuous development of modern agricultural technology, smart agriculture has become an important way to improve agricultural production efficiency and quality. In the field of fruit and vegetable picking, traditional manual picking methods have problems such as high labor intensity, low efficiency, and high cost, which makes it difficult to meet the large-scale and refined production needs of modern agriculture. Therefore, the development of intelligent picking robots has become an important means to solve these problems.

[0003] However, the current harvesting robot technology on the market still has many limitations. Especially for small farmers, most of the existing harvesting robots are complex in design and expensive, making them difficult to popularize. At the same time, these robots still need to be improved in terms of crop recognition accuracy, picking efficiency and intelligence. For example, some robots have difficulty accurately identifying crops in complex farmland environments, resulting in low picking efficiency; some robots lack maturity judgment functions and are prone to mistakenly picking immature fruits and vegetables, affecting crop quality; and some robots lack autonomous cruising capabilities and require frequent manual intervention, which increases the difficulty and cost of use.

[0004] To this end, those skilled in the art have proposed a negative pressure fruit picking robot arm and a control system thereof to solve the problems raised by the background technology. Summary of the invention

[0005] In order to solve the above technical problems, the present invention provides a negative pressure fruit picking robot arm and its control system, which integrates advanced mechanical structure design, electronic control technology, visual processing algorithm and autonomous navigation strategy, aiming to realize the full automation of crop recognition and harvesting. By using deep learning models (such as YOLOv5) for target detection and crop maturity judgment, and using ORB-SLAM3 algorithm to realize autonomous navigation and path planning, the system can significantly improve the picking efficiency and crop quality, reduce labor costs, and enhance the intelligent level of agricultural production.

[0006] A negative pressure fruit picking mechanical arm comprises a connecting chassis, the outer side wall of the connecting chassis is rotatably connected to a plurality of wheels, the outer side wall at the top of the connecting chassis is fixedly connected to a storage tank, and the top of the connecting chassis is provided with a picking mechanism;

[0007] The picking mechanism includes a connecting frame, which is installed on the top of the connecting chassis. The top of the connecting frame is rotatably connected to a mechanical arm body. A connecting air pipe is installed on the outer wall of the mechanical arm body. A control pipe is also installed on the outer wall of the mechanical arm body. A control head is fixedly connected to the outer wall of the mechanical arm body, and an adsorption mechanism is provided at the bottom end of the control head.

[0008] Preferably, the adsorption mechanism includes a connecting head, which is fixedly connected to the outer wall of the control head in multiple parts, and the inner wall of the connecting head is also provided with an air injection groove, which is installed together with the connecting air pipe, and the air injection groove and the connecting air pipe are interconnected, and the bottom end of the connecting head is fixedly connected with a flexible clamp, and the outer wall of the flexible clamp is installed with an adjustment plate.

[0009] Preferably, the connecting air pipe supplies air to the flexible clamping jaw and the adjusting plate through the air injection groove, and the outer side wall of the flexible clamping jaw is fixedly connected with a plurality of suction cups.

[0010] Preferably, the robot arm body and the end effector module are equipped with at least one robot arm body driven by a multi-degree-of-freedom, high-precision servo motor. A flexible clamp is installed at the end of the robot arm body. The flexible clamp has adaptive adjustment capability and can automatically adjust the clamping force according to the size and shape of fruits and vegetables to reduce damage to fruits and vegetables. Suction cups are provided on both sides of the flexible clamp to adsorb fruits and vegetables to enhance picking stability. In addition, a vibration soil removal device is integrated to improve picking efficiency.

[0011] Preferably, the recognition camera is installed on the outer wall of the control head and is used to take pictures of fruits. The inner wall of the recognition camera is installed with an image preprocessing module, and the image preprocessing module is used to process the pictures taken by the recognition camera. The outer wall of the recognition camera is installed with a crop type recognition module. The pictures processed by the image preprocessing module are transmitted to the crop type recognition module, so that the crop type recognition module recognizes the pictures processed by the image preprocessing module. The crop type recognition module also has a maturity judgment function and can self-identify. The outer wall of the recognition camera is also installed with a pest and disease detection module, and the pest and disease detection module judges the pest and disease based on the judgment of the crop type recognition module. The information of the crop type recognition module and the pest and disease detection module are respectively transmitted to the positions of the output and feedback module and the data storage and analysis module.

[0012] Preferably, a data acquisition module is installed on the top of the connecting chassis, and the data acquisition module is used to collect temperature and humidity, light intensity, and air temperature information. The data acquisition module also includes a data preprocessing module and a data storage module. The information collected by the data acquisition module is processed by the data preprocessing module and then stored by the data storage module. A continuous monitoring module is installed on the outer wall of the data acquisition module, and the continuous monitoring module can continuously monitor the information collected by the data acquisition module.

[0013] Preferably, an environmental perception module is installed at the bottom end of the connecting chassis, and a positioning and navigation module is also installed at the bottom end of the connecting chassis. The information collected by the environmental perception module and the positioning and navigation module is transmitted to the path planning and navigation module. The path planning and navigation module is installed at the bottom end of the connecting chassis for planning the overall navigation. A four-wheel drive module is installed at the bottom end of the connecting chassis for driving the wheels. A safety detection module is also installed at the bottom end of the connecting chassis. The safety detection module is used to monitor the information at the bottom end of the connecting chassis. An alarm module is installed at the bottom end of the safety detection module. When an abnormality occurs in the safety detection module, an alarm can be issued through the alarm module.

[0014] A negative pressure fruit picking robot arm control system, including an intelligent control center, integrated with a high-performance processor and a large-capacity storage device, running an advanced operating system and picking control software, processing image data from a visual subsystem in real time, planning an optimal picking path, and controlling the coordinated movement of the robot arm, the end effector and the mobile chassis, while supporting remote monitoring and fault diagnosis functions;

[0015] In visual SLAM, pose estimation is usually based on minimizing the reprojection error:

[0016] minξ∑i=1Nρ(∥f(K,ξ,Pi)-zi∥22)

[0017] in ξ is the camera pose (usually expressed in Lie algebra), K is the camera intrinsic parameter matrix, P i is a point in 3D space, zi is the corresponding 2D observation (pixel coordinate), f is the projection function, and ρ is the robust kernel function;

[0018] The user interaction and data management terminal provides an intuitive user interface and convenient operation methods. It supports touch screen operation, voice control and mobile phone APP remote control. It displays the picking progress, fruit and vegetable quality analysis report and map location information in real time. At the same time, it has a built-in big data analysis module to conduct in-depth mining of picking data and provide users with planting suggestions and market forecasts.

[0019] The safety protection and emergency response mechanism is equipped with an emergency stop button, collision sensor and anti-fall protection device to ensure that all power sources can be quickly cut off in an emergency to prevent accidental injuries. At the same time, it has a built-in battery management system to ensure the safe use of the battery and extend the robot's endurance.

[0020] Preferably, the robotic arm and the end effector module are also equipped with high-precision force feedback sensors, which can monitor the force changes during the picking process in real time to avoid damage to fruits and vegetables caused by excessive clamping.

[0021] Preferably, the mobile chassis and drive system support automatic charging function, and when the power is lower than a preset threshold, the robot can autonomously return to the charging station for charging without manual intervention;

[0022] In robot path planning, multiple optimization objectives may need to be considered simultaneously, such as path length, obstacle avoidance, energy consumption, etc. This can be expressed as a multi-objective optimization problem:

[0023] min(x,y,θ)(w1·L(x,y)+w2·C(x,y,θ)+w3·E(x,y,θ))

[0024] in:

[0025] L(x,y) is the path length function;

[0026] C(x,y,θ) is the obstacle avoidance cost function;

[0027] E(x,y,θ) is the energy consumption function;

[0028] w1,w2,w3 are the weights of each target.

[0029] Compared with the prior art, the present invention has the following beneficial effects:

[0030] 1. Improve picking efficiency: By integrating advanced robotic arms and visual recognition technology, the robot can accurately identify and quickly pick crops, greatly improving picking efficiency, which is especially suitable for large-scale agricultural production.

[0031] 2. Improve crop quality: Use deep learning models such as YOLOv5 to judge crop maturity, avoid mistakenly picking immature crops, ensure the quality of picked crops, and increase the market value of agricultural products.

[0032] 3. Reduce labor costs: realize full automation operation, reduce manpower demand, reduce labor costs of agricultural production, and reduce the labor intensity of farmers.

[0033] 4. Enhanced intelligence: Combined with the ORB-SLAM3 algorithm to achieve autonomous navigation and path planning, the robot can respond flexibly in complex farmland environments without frequent human intervention, thus improving the intelligence level of operations.

[0034] 5. Expanded application scenarios: The harvesting robot designed by the present invention is not only suitable for harvesting small fruits and vegetables such as peppers, but can also adjust the mechanical structure and algorithm parameters according to demand and expand to the harvesting application of other crops, thereby improving the versatility and flexibility of the system. BRIEF DESCRIPTION OF THE DRAWINGS

[0035] Figure 1 It is one of the three-dimensional structural schematic diagrams of the present invention;

[0036] Figure 2 This is the second schematic diagram of the three-dimensional structure of the present invention;

[0037] Figure 3 For the present invention Figure 2 Schematic diagram of the structure of the adsorption mechanism;

[0038] Figure 4 For the present invention Figure 1 Schematic diagram of the structure of the adsorption mechanism;

[0039] Figure 5 It is a flow chart of the control system in the present invention;

[0040] Figure 6 It is a structural schematic diagram of the identification module in the present invention;

[0041] Figure 7 It is a structural schematic diagram of the data acquisition module in the present invention;

[0042] Figure 8 It is a structural schematic diagram of the positioning module in the present invention.

[0043] In the figure: 1. Connecting chassis; 11. Wheels; 12. Storage tank; 2. Connecting frame; 21. Robot arm body; 22. Connecting air pipe; 23. Control pipe; 24. Control head; 25. Connecting head; 26. Air injection tank; 27. Adjustment plate; 28. Suction cup; 29. ​​Flexible gripper; 3. Recognition camera; 31. Image preprocessing module; 32. Crop type recognition module; 33. Pest and disease detection module; 34. Output and feedback module; 35. Data storage and analysis module; 5. Data acquisition module; 51. Data preprocessing module; 52. Data storage module; 53. Continuous monitoring module; 6. Environmental perception module; 61. Positioning and navigation module; 62. Path planning and navigation module; 63. Four-wheel drive module; 64. Safety detection module; 65. Alarm module. DETAILED DESCRIPTION

[0044] The following is a further detailed description of the embodiments of the present invention in conjunction with the accompanying drawings and examples. The following examples are used to illustrate the present invention but are not intended to limit the scope of the present invention.

[0045] As attached Figure 1 To Attachment Figure 8 As shown:

[0046] Embodiment 1: The present invention provides a negative pressure fruit picking mechanical arm, comprising a connecting chassis 1, the outer side wall of the connecting chassis 1 is rotatably connected to a plurality of wheels 11, the outer side wall of the top of the connecting chassis 1 is fixedly connected to a storage tank 12, and the top of the connecting chassis 1 is provided with a picking mechanism;

[0047] The picking mechanism includes a connecting frame 2, which is installed on the top of the connecting chassis 1. The top of the connecting frame 2 is rotatably connected to a mechanical arm body 21, and the outer wall of the mechanical arm body 21 is installed with a connecting air pipe 22. The outer wall of the mechanical arm body 21 is also installed with a control pipe 23. The outer wall of the mechanical arm body 21 is fixedly connected with a control head 24. The bottom end of the control head 24 is provided with an adsorption mechanism. The adsorption mechanism includes a connecting head 25, and the connecting head 25 is fixedly connected to the outer wall of the mechanical arm body 21. The outer wall of the control head 24 and the inner wall of the connecting head 25 are also provided with an air injection groove 26, and the air injection groove 26 is installed together with the connecting air pipe 22, and the air injection groove 26 and the connecting air pipe 22 are interconnected. A flexible clamp 29 is fixedly connected to the bottom end of the connecting head 25, and an adjustment plate 27 is installed on the outer wall of the flexible clamp 29. The connecting air pipe 22 supplies air to the flexible clamp 29 and the adjustment plate 27 through the air injection groove 26, and a plurality of suction cups 28 are fixedly connected to the outer wall of the flexible clamp 29.

[0048] Specifically, by controlling the flexible jaws 29 and the suction cup 28 through the connecting air pipe 22, the connecting air pipe 22 can control the air in the flexible jaws 29 and the suction cup 28 through the air injection groove 26, so that the flexible jaws 29 and the suction cup 28 can fit the fruit to be picked. The flexible jaws 29 can achieve the grasping effect, and the suction cup 28 can easily fit the fruit, increase the force area, and facilitate picking.

[0049] The robot arm body 21 and the end effector module are equipped with at least one multi-degree-of-freedom, high-precision servo motor-driven robot arm body 21. A flexible clamp 29 is installed at the end of the robot arm body 21. The flexible clamp 29 has adaptive adjustment capabilities and can automatically adjust the clamping force according to the size and shape of fruits and vegetables to reduce damage to fruits and vegetables. Suction cups 28 are arranged on both sides of the flexible clamp 29 to adsorb fruits and vegetables to enhance picking stability. In addition, a vibration soil removal device is integrated to improve picking efficiency. The recognition camera 3 is installed on the outer wall of the control head 24 for taking pictures of fruits. The inner wall of the recognition camera 3 is installed with an image preprocessing module 31, which is used to process the recognition camera 3, a crop type recognition module 32 is installed on the outer wall of the recognition camera 3, the photos processed by the image preprocessing module 31 are transmitted to the crop type recognition module 32, so that the crop type recognition module 32 recognizes the photos processed by the image preprocessing module 31, the crop type recognition module 32 also has a maturity judgment function and can self-recognize, and a pest and disease detection module 33 is also installed on the outer wall of the recognition camera 3, the pest and disease detection module 33 judges the pest and disease based on the judgment of the crop type recognition module 32, and the information of the crop type recognition module 32 and the pest and disease detection module 33 are respectively transmitted to the positions of the output and feedback module 34 and the data storage and analysis module 35.

[0050] Specifically, the negative pressure fruit picking robot arm and its control system are started. During the system startup process, the environment sensing unit is first initialized. The unit integrates temperature and humidity sensors (such as DHT11), light intensity sensors, etc., for real-time monitoring of farmland environmental parameters.

[0051] A data acquisition module 5 is installed at the top of the connection chassis 1. The data acquisition module 5 is used to collect temperature and humidity, light intensity, and air temperature information. The data acquisition module 5 also includes a data preprocessing module 51 and a data storage module 52. The information collected by the data acquisition module 5 is processed by the data preprocessing module 51 and then stored by the data storage module 52. A continuous monitoring module 53 is installed on the outer wall of the data acquisition module 5. The continuous monitoring module 53 can continuously monitor the information collected by the data acquisition module 5. An environmental perception module 6 is installed at the bottom of the connection chassis 1. The bottom of the connection chassis 1 is also installed There is a positioning navigation module 61, and the information collected by the environmental perception module 6 and the positioning navigation module 61 is transmitted to the path planning navigation module 62. The path planning navigation module 62 is installed at the bottom of the connecting chassis 1 for planning the overall navigation. The bottom of the connecting chassis 1 is installed with a four-wheel drive module 63 for driving the wheels 11. The bottom of the connecting chassis 1 is also installed with a safety detection module 64, and the safety detection module 64 is used to monitor the information at the bottom of the connecting chassis 1. The bottom of the safety detection module 64 is installed with an alarm module 65. When an abnormality occurs in the safety detection module 64, an alarm can be issued through the alarm module 65.

[0052] Specifically, the safety detection module 64 performs a self-check on the four-wheel independent drive motor to ensure that the motor can start and operate normally, checks the status of the anti-skid tires to confirm that the tire pressure is sufficient and the degree of wear is within an acceptable range, performs a self-check on the intelligent suspension system to ensure that it can adjust the vehicle body height and posture as needed, tests the functions of the environmental perception module 6 and the positioning and navigation module 61 to confirm that they can receive satellite signals and stably output position, speed and posture information.

[0053] A negative pressure fruit picking robot arm control system, including a visual subsystem, integrated with a high-definition RGB camera, a depth camera and an infrared sensor, for real-time collection of multi-dimensional image information of fruits and vegetables, and identification of the location, type, maturity and pests and diseases of fruits and vegetables through image processing and deep learning algorithms, while supporting stable operation at night or in low-light environments;

[0054] Camera intrinsic calibration is usually performed by minimizing the reprojection error. The formula is similar to BA, but focuses on optimizing the camera intrinsic parameter matrix K and distortion coefficients:

[0055] minK,dist∑i=1N∑j=1Mi∥f(K,dist,Pj,ξi)-zij∥2

[0056] Where dist represents the distortion coefficient;

[0057] The robot arm body 21 and the end effector module are equipped with at least one multi-degree-of-freedom, high-precision servo motor-driven robot arm body 21. A flexible clamp 29 is installed at the end of the robot arm body 21. The flexible clamp 29 has adaptive adjustment capability and can automatically adjust the clamping force according to the size and shape of fruits and vegetables to reduce damage to fruits and vegetables. Suction cups 28 are arranged on both sides of the flexible clamp 29 to adsorb fruits and vegetables to enhance picking stability. In addition, a vibration soil removal device is integrated to improve picking efficiency.

[0058] Connect chassis 1 to the drive system, adopt a four-wheel independent drive design, equipped with anti-skid tires and an intelligent suspension system to ensure the robot's stable driving and obstacle-crossing capabilities in various complex farmland terrains. Built-in high-precision GPS and inertial navigation systems to achieve precise positioning and autonomous navigation;

[0059] The intelligent control center integrates high-performance processors and large-capacity storage devices, runs advanced operating systems and picking control software, processes image data from the visual subsystem in real time, plans the optimal picking path, and controls the coordinated movement of the robotic arm, end effector, and mobile chassis, while supporting remote monitoring and fault diagnosis functions;

[0060] In visual SLAM, pose estimation is usually based on minimizing the reprojection error:

[0061] minξ ∑i=1N ρ(∥f(K,ξ,Pi)-zi∥22)

[0062] in ξ is the camera pose (usually expressed in Lie algebra), K is the camera intrinsic parameter matrix, Pi is a point in 3D space, zi is the corresponding 2D observation (pixel coordinate), f is the projection function, and ρ is the robust kernel function;

[0063] The user interaction and data management terminal provides an intuitive user interface and convenient operation methods. It supports touch screen operation, voice control and mobile phone APP remote control. It displays the picking progress, fruit and vegetable quality analysis report and map location information in real time. At the same time, it has a built-in big data analysis module to conduct in-depth mining of picking data and provide users with planting suggestions and market forecasts.

[0064] Specifically, the YOLOv5 model is used to perform real-time target detection on the RGB images captured by the Intel RealSense D4 data storage and analysis module (35)i camera to identify the crop type and location.

[0065] By converting RGB images to HSV color space, the average HSV value of the crops is calculated, and then the maturity of the crops is determined and thresholds for different maturity levels are set;

[0066] The ORB-SLAM3 algorithm is used to process the depth image acquired by the camera, build an environmental map, and output the three-dimensional coordinates of the crop in the camera coordinate system in real time.

[0067] The STM32 microcontroller receives the three-dimensional coordinate information from the host computer, controls the robotic arm and the gimbal servo to rotate to the target position, and enables the flexible shear module to accurately align with the crop stem.

[0068] Safety protection and emergency response mechanism, equipped with emergency stop button, collision sensor and anti-fall protection device, to ensure that all power sources can be quickly cut off in an emergency to prevent accidental injuries. At the same time, it has a built-in battery management system to ensure the safe use of batteries and extend the robot's endurance.

[0069] The visual subsystem also includes an environmental perception unit that can monitor the environmental parameters of temperature, humidity, and light intensity of the farmland in real time, providing data support for fruit and vegetable growth status analysis and precision agricultural management;

[0070] The robotic arm and end effector module are also equipped with high-precision force feedback sensors, which can monitor the force changes during the picking process in real time to avoid damage to fruits and vegetables caused by excessive clamping;

[0071] The mobile chassis and drive system support automatic charging function. When the power level is lower than the preset threshold, the robot can return to the charging station to charge autonomously without human intervention.

[0072] In robot path planning, multiple optimization objectives may need to be considered simultaneously, such as path length, obstacle avoidance, energy consumption, etc. This can be expressed as a multi-objective optimization problem:

[0073] min(x,y,θ)(w1·L(x,y)+w2·C(x,y,θ)+w3·E(x,y,θ))

[0074] in:

[0075] L(x,y) is the path length function;

[0076] C(x,y,θ) is the obstacle avoidance cost function;

[0077] E(x,y,θ) is the energy consumption function;

[0078] w1, w2, w3 are the weights of each target;

[0079] Specifically, the robot's autonomous navigation and path planning are realized based on the ORB-SLAM3 algorithm, ensuring that the robot can perform picking operations according to a preset path or an autonomously planned path without human intervention.

[0080] Combining IMU data and visual data can improve the robustness and positioning accuracy of the system and avoid tracking loss due to visual occlusion or lighting changes.

[0081] The intelligent control center also has the ability of autonomous learning, and can continuously optimize the picking strategy and algorithm model according to historical picking data and user feedback to improve picking efficiency and accuracy;

[0082] The user interaction and data management terminal supports a variety of data export formats and interface protocols, making it convenient for users to connect and share data with other agricultural management systems or third-party software;

[0083] The safety protection and emergency response mechanism also includes a remote locking function. When the user confirms that the robot is in a safe state, all moving parts can be locked through remote commands to prevent safety risks caused by unauthorized operations.

[0084] Specifically, the main control unit uses the STM32F407 microcontroller as the main control board, which is responsible for receiving commands from the host computer and controlling the movement of the entire robot. It is equipped with a TMC2209 stepper motor driver and a 42 closed-loop stepper motor to achieve precise position control.

[0085] Sensor module: Integrates ESP8266 WI FI module, DHT11 temperature and humidity sensor, HX711 gravity sensor, SGP30 gas detection module and HC-SR04 ultrasonic ranging module for real-time monitoring of farmland environment and robot status.

[0086] The standard parts used in the present invention can all be purchased from the market, and the special-shaped parts can be customized according to the description and the drawings. The specific connection methods of each part adopt conventional means such as mature bolts, rivets, welding, etc. in the prior art. The machinery, parts and equipment all adopt conventional models in the prior art, and the circuit connection adopts the conventional connection method in the prior art, which will not be described in detail here. The contents not described in detail in this specification belong to the prior art known to professional and technical personnel in this field.

[0087] In the description of the present invention, the terms "first" and "second" are used for descriptive purposes only and should not be understood as indicating or implying relative importance or implicitly indicating the number of the indicated technical features. Therefore, the features defined as "first" and "second" may explicitly or implicitly include one or more of the features. "Multiple" means two or more, unless otherwise clearly and specifically defined.

[0088] In the present invention, unless otherwise clearly specified and limited, the terms "installed", "connected", "connected", "fixed" and the like should be understood in a broad sense, for example, it can be a fixed connection, a detachable connection, or an integral connection; it can be a mechanical connection or an electrical connection; it can be a direct connection or an indirect connection through an intermediate medium, it can be the internal connection of two elements or the interaction relationship between two elements. For ordinary technicians in this field, the specific meanings of the above terms in the present invention can be understood according to specific circumstances.

[0089] In the present invention, unless otherwise clearly specified and limited, a first feature being "above" or "below" a second feature may mean that the first and second features are in direct contact, or the first and second features are in indirect contact through an intermediate medium. Moreover, a first feature being "above", "above" or "above" a second feature may mean that the first feature is directly above or obliquely above the second feature, or simply means that the first feature is higher in level than the second feature. A first feature being "below", "below" or "below" a second feature may mean that the first feature is directly below or obliquely below the second feature, or simply means that the first feature is lower in level than the second feature.

[0090] In the description of this specification, the description with reference to the terms "one embodiment", "some embodiments", "example", "specific example" or "some examples" etc. means that the specific features, structures, materials or characteristics described in conjunction with the embodiment or example are included in at least one embodiment or example of the present invention. In this specification, the schematic expressions of the above terms do not necessarily refer to the same embodiment or example. Moreover, the specific features, structures, materials or characteristics described may be combined in a suitable manner in any one or more embodiments or examples. In addition, those skilled in the art may combine and combine different embodiments or examples and features of different embodiments or examples described in this specification without contradiction.

[0091] In the drawings of the embodiments disclosed in the present invention, only the structures related to the embodiments disclosed in the present invention are involved, and other structures can refer to the general design. In the absence of conflict, the same embodiment and different embodiments of the present invention can be combined with each other.

[0092] Although the present invention has been described in detail with reference to the aforementioned embodiments, it is still possible for those skilled in the art to modify the technical solutions described in the aforementioned embodiments, or to make equivalent substitutions for some of the technical features therein. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the present invention should be included in the protection scope of the present invention.

Claims

1. A negative pressure fruit picking robot arm, Features: It comprises a connecting chassis (1), the outer side wall of the connecting chassis (1) is rotatably connected to a plurality of wheels (11), the outer side wall at the top of the connecting chassis (1) is fixedly connected to a storage tank (12), and the top of the connecting chassis (1) is provided with a picking mechanism; The picking mechanism comprises a connecting frame (2), the connecting frame (2) being mounted on the top of a connecting chassis (1), the top of the connecting frame (2) being rotatably connected to a mechanical arm body (21), the outer side wall of the mechanical arm body (21) being mounted with a connecting air pipe (22), the outer side wall of the mechanical arm body (21) being further mounted with a control pipe (23), the outer side wall of the mechanical arm body (21) being fixedly connected to a control head (24), the bottom end of the control head (24) being provided with an adsorption mechanism.

2. A negative pressure fruit picking robot arm as claimed in claim 1, Features: The adsorption mechanism comprises a connecting head (25), wherein the connecting head (25) is in the form of a plurality of fixedly connected outer side walls of a control head (24), an inner side wall of the connecting head (25) is also provided with an air injection groove (26), the air injection groove (26) is installed together with a connecting air pipe (22), the air injection groove (26) and the connecting air pipe (22) are interconnected, a flexible clamping claw (29) is fixedly connected to the bottom end of the connecting head (25), and an adjustment plate (27) is installed on the outer side wall of the flexible clamping claw (29).

3. A negative pressure fruit picking mechanical arm as claimed in claim 1, Features: The connecting air pipe (22) supplies air to the flexible clamping jaw (29) and the adjusting plate (27) through the air injection groove (26); and a plurality of suction cups (28) are fixedly connected to the outer side wall of the flexible clamping jaw (29).

4. A negative pressure fruit picking mechanical arm as claimed in claim 1, Features: The mechanical arm body (21) and the end effector module are equipped with at least one mechanical arm body (21) driven by a multi-degree-of-freedom, high-precision servo motor. A flexible clamp (29) is installed at the end of the mechanical arm body (21). The flexible clamp (29) has an adaptive adjustment capability and can automatically adjust the clamping force according to the size and shape of fruits and vegetables to reduce damage to the fruits and vegetables. Suction cups (28) are arranged on both sides of the flexible clamp (29) to absorb the fruits and vegetables to enhance the picking stability. In addition, a vibration soil removal device is integrated to improve the picking efficiency.

5. A negative pressure fruit picking mechanical arm as claimed in claim 1, Features: The recognition camera (3) is installed on the outer wall of the control head (24) and is used to take pictures of fruits. The inner wall of the recognition camera (3) is installed with an image preprocessing module (31). The image preprocessing module (31) is used to process the pictures taken by the recognition camera (3). The outer wall of the recognition camera (3) is installed with a crop type recognition module (32). The pictures processed by the image preprocessing module (31) are transmitted to the crop type recognition module (32), so that the crop type recognition module (32) recognizes the pictures processed by the image preprocessing module (31). The crop type recognition module (32) also has a maturity judgment function and can self-recognize. The outer wall of the recognition camera (3) is also installed with a pest and disease detection module (33). The pest and disease detection module (33) judges the pest and disease based on the judgment of the crop type recognition module (32). The information of the crop type recognition module (32) and the pest and disease detection module (33) is transmitted to the positions of the output and feedback module (34) and the data storage and analysis module (35) respectively.

6. A negative pressure fruit picking mechanical arm as claimed in claim 1, Features: A data acquisition module (5) is installed at the top of the connection chassis (1). The data acquisition module (5) is used to collect temperature and humidity, light intensity, and air temperature information. The data acquisition module (5) also includes a data preprocessing module (51) and a data storage module (52). The information collected by the data acquisition module (5) is processed by the data preprocessing module (51) and then stored by the data storage module (52). A continuous monitoring module (53) is installed on the outer wall of the data acquisition module (5). The continuous monitoring module (53) can continuously monitor the information collected by the data acquisition module (5).

7. A negative pressure fruit picking mechanical arm as claimed in claim 1, Features: An environment perception module (6) is installed at the bottom of the connection chassis (1), and a positioning navigation module (61) is also installed at the bottom of the connection chassis (1). Information collected by the environment perception module (6) and the positioning navigation module (61) is transmitted to a path planning navigation module (62). The path planning navigation module (62) is installed at the bottom of the connection chassis (1) and is used to plan overall navigation. A four-wheel drive module (63) is installed at the bottom of the connection chassis (1) and is used to drive the wheels (11). A safety detection module (64) is also installed at the bottom of the connection chassis (1). The safety detection module (64) is used to monitor information at the bottom of the connection chassis (1). An alarm module (65) is installed at the bottom of the safety detection module (64). When an abnormality occurs in the safety detection module (64), an alarm can be issued through the alarm module (65).

8. A negative pressure fruit picking robot arm control system, Features: It includes an intelligent control center, which integrates a high-performance processor and a large-capacity storage device, runs an advanced operating system and picking control software, processes image data from the visual subsystem in real time, plans the optimal picking path, and controls the coordinated movement of the robot arm, end effector and mobile chassis, while supporting remote monitoring and fault diagnosis functions; In visual SLAM, pose estimation is usually based on minimizing the reprojection error: minξ∑i=1Nρ(∥f(K,ξ,Pi)-zi∥22) in ξ is the camera pose (usually expressed in Lie algebra), K is the camera intrinsic parameter matrix, P i is a point in 3D space, zi is the corresponding 2D observation (pixel coordinate), f is the projection function, and ρ is the robust kernel function; The user interaction and data management terminal provides an intuitive user interface and convenient operation methods. It supports touch screen operation, voice control and mobile phone APP remote control. It displays the picking progress, fruit and vegetable quality analysis report and map location information in real time. At the same time, it has a built-in big data analysis module to conduct in-depth mining of picking data and provide users with planting suggestions and market forecasts. The safety protection and emergency response mechanism is equipped with an emergency stop button, collision sensor and anti-fall protection device to ensure that all power sources can be quickly cut off in an emergency to prevent accidental injuries. At the same time, it has a built-in battery management system to ensure the safe use of the battery and extend the robot's endurance.

9. A negative pressure fruit picking robot arm control system as claimed in claim 8, Features: The robotic arm and end effector module are also equipped with high-precision force feedback sensors that can monitor force changes during the picking process in real time to avoid damage to fruits and vegetables caused by excessive clamping.

10. A negative pressure fruit picking robot arm control system as claimed in claim 8, Features: The mobile chassis and drive system support automatic charging function. When the power level is lower than the preset threshold, the robot can return to the charging station to charge autonomously without human intervention. In robot path planning, multiple optimization objectives may need to be considered simultaneously, such as path length, obstacle avoidance, energy consumption, etc. This can be expressed as a multi-objective optimization problem: min(x,y,θ)(w1·L(x,y)+w2·C(x,y,θ)+w3·E(x,y,θ)) in: L(x,y) is the path length function; C(x,y,θ) is the obstacle avoidance cost function; E(x,y,θ) is the energy consumption function; w1,w2,w3 are the weights of each target.

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