8719results about "Manipulator" patented technology

Various systems and methods are described for obtaining compensation for tasks performed by a humanoid robot, where the humanoid robot is associated with a first party. The method includes a first party providing a humanoid robot for use in an operating location. The humanoid robot engaged in performing a plurality of tasks at the operating location. A third party compensates the first party with a specified amount of currency for a pre-determined time interval during which said humanoid robot has engaged in performing the plurality of tasks at the operating location.

The invention relates to the technical field of robot decision making, and provides a robot multi-modal fusion autonomous decision making method and system based on a large language model.The method comprises the steps that a robot obtains multi-modal environment information through a visual sensor, a touch sensor, an auditory sensor and a laser radar which are carried by the robot; performing preliminary filtering and noise reduction processing on the original sensor data, and synchronously recording all the sensor data by timestamps; performing space-time semantic alignment on the preprocessed multi-modal data, mapping pixel coordinates of a target in a visual target coordinate quantization original image to a robot coordinate system, performing uncertainty evaluation on a multi-modal signal through a dynamic Bayesian network, and taking entropy or variance as an uncertainty quantitative evaluation index. According to the method, the information quality is improved from a data fusion source, accurate and reliable basic support is provided for subsequent decision making, and decision making errors caused by data deviation are greatly reduced.

The invention discloses a multi-modal fusion real-time environment monitoring visual robot system, and relates to the technical field of real-time vision. The system comprises a multi-mode sensing module, and is equipped with various sensors such as a binocular stereo camera and a laser radar to collect environment data. The heterogeneous data preprocessing unit cleans and downsamples data such as images and point clouds; the space-time alignment fusion module realizes multi-source data space-time registration and synchronization; the environment semantic understanding engine constructs an environment semantic graph through a multi-branch network in combination with an attention mechanism; the abnormal event detection unit identifies abnormity based on a historical data model; the path planning and decision-making module integrates multiple targets to generate an optimal path; the autonomous movement execution module controls the robot to move and operate; and the cloud cooperative control center supports model updating and remote intervention. According to the invention, through cooperative work of all the modules, full-process intelligentization of environment monitoring data acquisition, processing, analysis and decision making is realized.

The invention discloses a pole climbing robot for a wind power tower pole, which is characterized in that the robot mainly comprises a robot body, 4-8 pole climbing mechanisms, a snake-shaped swing arm and a movable studio, wherein the snake-shaped swing arm and the movable studio are mounted on one side of the robot body; the robot body is an annular body formed by combining two semicircular cambered bodies or three equal cambered bodies; the diameter of an internal ring of the circular body is matched with the diameter of the wind power tower pole; the pole climbing mechanisms mainly comprise upper foot wheels, lower foot wheels, connecting arms, driving gears, thrust screw rods, nut gears and supporting seats; the upper foot wheels are connected with the lower foot wheels by the connecting arms through wheel shafts; the connecting arms are connected with the thrust screw rods by connecting pin shafts on the connecting arms, and form movable hinges; the 4-8 pole climbing mechanisms are distributed in the circular robot body uniformly; the snake-shaped swing arm consists of three swing arm parts, namely a large arm, a middle arm and a small arm; and the movable studio comprises two paralleled linear guide rails, a walk driving device and an operation room.

The invention discloses grinding equipment with a surface self-adaption function for civil aircraft maintenance, and relates to the technical field of grinding equipment, the grinding equipment comprises a grinding mechanism, a self-adaption mechanism and a positioning mechanism, the grinding mechanism is fixedly connected with the self-adaption mechanism, and the self-adaption mechanism is fixedly connected with the positioning mechanism. The grinding mechanism is used for driving a grinding disc to work, and flexible grinding of the surfaces of different areas can be achieved. The self-adaptive mechanism is composed of a self-adaptive assembly, an expanding and contracting assembly and a rotating assembly, the grinding disc has the flexible adjusting capacity when making contact with the surface of a workpiece, the expanding and contracting assembly achieves expanding and contracting, the rotating assembly drives an expanding and contracting block to revolve, and therefore the adaptability of the grinding disc on the complex curved surface is guaranteed. And the positioning mechanism is used for positioning parts needing to be maintained, so that the purposes of adapting to complex curved surfaces, improving the polishing precision and efficiency, avoiding the problem of difficult attachment and ensuring the maintenance quality and the operation safety are achieved.

The invention discloses a visual prediction method for space-time manifold and implicit state deduction of a robot, and relates to the technical field of robot space visual perception. The motion state and the visual image of the robot are collected; calculating carrier pose offset and generating a reverse compensation matrix; modeling an image target into a visual cone probability manifold, and extracting an explicit manifold observation vector; monitoring the confidence coefficient in real time through an observation quality evaluation network, and activating an implicit deduction mode during observation degradation; reading historical time sequence characteristics by using an improved Transform model, and performing prediction and deduction on a future nonlinear motion state of the target; performing coordinate correction and probability field decoding on a prediction result in combination with the reverse compensation matrix, and outputting a three-dimensional prediction trajectory and a spatial covariance ellipsoid; according to the method, the problem that traditional visual tracking fails under the conditions of violent shaking of a carrier and target shielding is solved, and continuous and foresight physical scale positioning and safety decision making of a robot on a dynamic target are achieved.

The invention discloses a self-adaptive control method for operation of a coupler unhooking robot under multiple working conditions, and relates to the technical field of coupler unhooking, and the method comprises the steps: obtaining a target unhooking robot, and collecting and obtaining an operation environment data flow and a coupler state data flow; working condition sensing and coupler recognition are conducted, and the current working condition and coupler feature information are obtained; performing traversal retrieval and adaptive adjustment in the unhooking strategy database, and determining target unhooking strategy parameters; and executing unhooking operation according to the target unhooking strategy parameters, and performing adaptive closed-loop control and abnormal emergency control on the target unhooking robot based on the unhooking operation state data flow. The technical problems that in the prior art, a car coupler unhooking robot is difficult to adapt to complex and various working conditions, and consequently the unhooking operation accuracy, safety and efficiency are poor are solved, accurate sensing of the working conditions of the car coupler unhooking robot is achieved, and the technical effect of improving the unhooking operation accuracy, safety and efficiency is achieved.

The invention discloses a full-size integrated humanoid robot which comprises a trunk mechanism, arm mechanisms arranged on the left side and the right side of the upper end of the trunk mechanism, a hip mechanism arranged at the lower end of the trunk mechanism and leg mechanisms arranged at the left end and the right end of the hip mechanism. The driving modules of the arm mechanisms and the leg mechanisms are mounted in the inner cavities of the corresponding curved-surface metal shells through bolts respectively; the hip mechanism comprises a hip assembly and hip curved surface shells installed on the front side and the rear side of the hip assembly. The hip assembly comprises a hip base connected with an output shaft of a trunk driving module of the trunk mechanism. Hip driving modules are symmetrically arranged at the left end and the right end of an inner cavity of the hip base; a control circuit board of the hip driving module is arranged on the top of the hip base through a fixing plate. On the basis of replacing a traditional shell and a skeleton with the curved metal shell, the size of the hip mechanism is reduced, the assembly steps are simplified, the light weight of the humanoid robot is achieved, and the requirement for structural strength is met.

The invention relates to a robot environment perception method based on single-view three-dimensional scene generation, and the method comprises the steps: collecting a two-dimensional image containing target environment information through employing a monocular camera, generating multi-view information through combining depth estimation, normal prediction and a two-stage semantic guidance diffusion model, and constructing a high-quality three-dimensional scene. And reconstructing three-dimensional point cloud data through the neural radiation field, and performing texture rendering optimization on the point cloud data. A Point Net + + network is used for carrying out semantic analysis on point clouds, a multi-frame time sequence point cloud registration and Kalman filtering tracking method is introduced, modeling is carried out on a dynamic target, and a dynamic semantic map with a motion state is constructed. And finally, structured output environment information is used for robot navigation, path planning and task execution. The problems of high cost, high complexity and insufficient real-time performance and robustness of a three-dimensional scene generation technology in the field of robot environment perception are solved, and the method is high in structuring degree, standard and unified in output format and high in universality and engineering adaptation capacity.

The invention provides a water surface target grabbing system and a control method thereof, and relates to the technical field of marine operation equipment. The system comprises an unmanned ship and a cooperative mechanical arm, the unmanned ship and the cooperative mechanical arm share a processor; the unmanned ship supplies power to the cooperative mechanical arm; the unmanned ship is positioned through an inertial navigation system on the unmanned ship and a scene camera and a depth camera on the cooperative mechanical arm; a scene camera, a depth camera and an integrated sensor on the cooperative mechanical arm transmit data to a processor on the unmanned ship through a local area network, the processor calculates and analyzes the data transmitted by the scene camera and the depth camera, and an action instruction is sent to the cooperative mechanical arm through a CAN bus. According to the water surface target grabbing system, automatic grabbing is achieved, and the grabbing precision, stability and adaptability of the system in the dynamic marine environment are improved.

The invention relates to an underwater cleaning robot positioning and tracking method. Positioning comprises the steps that data of multiple sensors on an underwater cleaning robot are fused through an extended Kalman filter, and coordinates of the underwater cleaning robot on the surface of a ship body are obtained after sensor measurement noise is filtered through a first-order low-pass filtering algorithm. The tracking method comprises the step of realizing the path tracking of the underwater cleaning robot based on the positioning method in combination with an iterative linear quadratic regulator (ILQR). According to the invention, a multi-sensor fusion scheme of the encoder, the IMU and the depth meter is innovatively provided, and the positioning problem of the underwater cleaning robot in a wall attaching state is solved. And double-plane differential treatment is adopted, so that the working state of the robot on the ship wall or the ship bottom is better fitted, and positioning is more accurate. A target point updating mechanism of geometric distance constraint is provided, the nearest neighbor point of the reference trajectory is adjusted in real time, and the problem of tracking lag caused by updating rate mismatch in a traditional method is solved.

The invention discloses a human-computer interaction method and system based on a vision-language-action model, and belongs to the field of human-computer interaction. According to the method, an anchoring ring strategy is adopted to collect human teaching data to finely adjust the VLA model, and then the trained model is applied to an actual human-computer interaction scene. In the data acquisition stage, a first operator guides a master robot to execute task actions, and a slave robot synchronously moves and interacts with a second operator, and returns to a predefined initial position after each interaction; a teaching sample is formed by recording a robot state, an environment image and an instruction text, and a high-quality data set is generated through data enhancement. In the application stage, the real-time robot state, the environment image and the instruction text serve as input, an action instruction is generated through the VLA model, and the robot is driven to complete a cooperation task. According to the method, the data utilization efficiency and the model generalization ability are remarkably improved, the difference between simulation and the real environment is effectively overcome, and efficient, safe and natural man-machine cooperation is achieved.

The invention discloses a dynamic digital twinning system based on 3D Gaussian splashing. The dynamic digital twinning system comprises a flexible electric power inspection robot, a 3DGS dynamic enhancement module and a fusion digital twinning background centralized control system. The flexible electric power inspection robot is used for collecting 2D images and environment point cloud data of substation equipment; the 3DGS dynamic enhancement module is used for carrying out 3DGS dynamic enhancement and generating a 3D Gaussian model; the standard digital twinborn centralized control platform is used for storing and calling data and digital twinborn bodies of the traditional static substation digital model; the model fusion port carries out space alignment and attribute interpolation fusion on the 3D Gaussian model and the static digital twin; and the visual terminal is used for displaying the fused enhanced digital twinborn body and the equipment state evaluation result. According to the invention, the dynamic enhancement of the digital twinborn model of the substation equipment can be realized, and the operation state and change condition of the equipment can be reflected more truly and intuitively.

The invention relates to the technical field of 3D vision, and discloses a manipulator dispensing path optimization method and device based on 3D vision, and the method comprises the steps: carrying out the multi-angle three-dimensional vision scanning of a dispensing workpiece, and obtaining the point cloud data of the dispensing workpiece; performing semantic segmentation on the point cloud data, and decomposing the dispensing workpiece into a plurality of functional parts; according to the semantic identifier and the surface feature of the functional component, identifying a target area to be dispensed and a dispensing path constraint condition; generating an initial dispensing path based on the target area to be dispensed and the dispensing path constraint condition; and performing iterative linear secondary adjustment control on the initial dispensing path to generate a motion control instruction. According to the invention, the self-adaptive optimization adjustment of the dispensing path is realized, the problem that the traditional dispensing system cannot cope with the actual state change of the workpiece is solved, and the adaptability and stability of the dispensing system are greatly improved.

The invention discloses a ship intelligent operation robot based on artificial intelligence, and relates to the technical field of ship equipment. The device comprises a mobile platform, and an operation execution mechanism is arranged at the top of the mobile platform; the operation executing mechanism comprises a driving arm mounted at the top of the movable platform, and a spray gun and a flaw detector which are mounted at the output end of the driving arm. The mobile platform is of a crawler-type structure and is matched with sensing assemblies such as a laser radar and a camera, so that the robot can navigate autonomously and adapt to the complex ship environment, the potential safety hazard that workers enter a dangerous area for operation is avoided, a driving arm in the operation executing mechanism can accurately control the positions of a spray gun and a flaw detector, and the working efficiency is improved. Automatic paint make-up and damage detection are achieved, errors of manual operation are reduced, the rust removal assembly forms a set of complete automatic rust removal system through reciprocating knocking of an impact rod and rotary sweeping of a cleaning roller, and the risk that operators make contact with poisonous and harmful gas and dust is effectively avoided.

The invention discloses a multi-robot task allocation and electric quantity management system for a semi-closed complex environment. The system is composed of a cloud server, an edge computing node and a robot end. The cloud server is used for formulating a global task plan according to the task type and the emergency degree and sending the global task plan to the edge computing node; the edge computing node is used for splitting and distributing a global task according to a real-time state of a robot cluster in the robot end and dynamically dispatching a robot in the robot end, and is internally provided with a computing gateway and a local cache; and the robot end is used for executing the subtasks and autonomously making decisions, and initiating task handover according to electric quantity pre-judgment. According to the method, navigation adaptation and a communication redundancy mechanism are fused, so that a robot system has the continuous operation capability in a complex, dynamic and weak communication tunnel environment, and powerful environment adaptation support is provided for collaborative operation of multiple robots.

The invention provides a water surface target automatic grabbing device and a control method thereof, and relates to the technical field of marine operation equipment. The device comprises a computing platform, a mechanical arm, a hook, a telescopic rod, a binocular camera, a depth camera, an inertial sensor and a self-stabilizing holder, the computing platform is fixedly mounted on the unmanned ship; the self-stabilizing holder is fixed on a deck of the unmanned ship; the mechanical arm is mounted above the self-stabilizing holder; the hook is mounted at a specified position on the unmanned ship; the telescopic rod is mounted at the tail end of the mechanical arm; the binocular camera and the depth camera are installed at preset positions of the tail end of the mechanical arm and connected with the computing platform through high-speed data transmission lines. The inertial sensor is installed in the mechanical arm and connected with the computing platform. According to the automatic grabbing device, the grabbing precision, stability and adaptability of the system in the dynamic marine environment are improved.

A hybrid, redundant, fail-safe architecture provides a unified fail-operational framework for autonomous agents operating across physical and virtual domains. The system employs a multi-modal data source suite, an adaptive hybrid data fusion module, and an intelligent decision-making module. A novel closed-loop interaction enables a health monitoring module that detects an incipient fault in a data source by monitoring ancillary performance metrics. Upon detection, the module generates a fault signature, including a quantitative prognostic estimate of a future failure time, and transmits it to an adaptive data fusion module. The fusion module proactively reconfigures its state estimation algorithm by decreasing reliance on the degrading data source in proportion to the prognostic estimate. This preemptive compensation ensures the system maintains a high-integrity environmental model and achieves true fail-operational continuity. The architecture is applicable to numerous embodiments providing a universal solution for proactive fault management and system resilience.

The invention provides a control method, which is applied to an artificial intelligence experiment system, at least comprises a robot hardware platform, a controller, a wheeled robot chassis and an industrial mechanical arm, and the method comprises the following steps: starting an operation system and executing hardware self-inspection; loading a large language model service and a traditional AI model, wherein the traditional AI model comprises a speech recognition model, a target detection model and a semantic analysis model; a natural language instruction of a user is received, voice is converted into a structured text through a voice recognition model, an instruction intention is analyzed through a large language model and a semantic analysis model, robot control parameters are generated, and a multi-modal interaction control signal is obtained; based on the multi-mode interaction control signal, a camera is called to collect image data, the position and category of a target object to be grabbed by the robot are recognized through a target detection model, the moving path of the robot and the grabbing track of the mechanical arm are calculated in combination with laser radar data, and the wheeled robot chassis and the industrial mechanical arm are controlled to execute coordinated actions.

The invention discloses a multi-modal robot interaction system, and relates to the technical field of robots, the system comprises a robot subsystem and a cloud processing subsystem which are in communication connection with each other, the robot subsystem comprises a multi-modal sensing module and an interaction execution module, and the cloud processing subsystem comprises a cloud processing module. The multi-mode sensing module is used for collecting target data of at least one target user and sending the target data to the cloud processing module, and the target data comprises at least one of touch data, distance data, posture data, position data, action data and voice data; the cloud processing module is used for analyzing the target data, generating an interaction instruction and sending the interaction instruction to the interaction execution module; and the interaction execution module is used for receiving and executing the interaction instruction, so that the higher expectation of the user in the aspects of emotion accompanying and personalized service is effectively met.

The invention relates to the technical field of large-scale structure measurement, and discloses a robot laser vision three-dimensional scanning measurement system for a large-scale structural member. The system comprises a robot motion platform, a laser vision sensing module, an ambient light sensing module, a point cloud processing module and a motion control module, wherein the laser vision sensing module is arranged at the tail end of the robot motion platform. The ambient light sensing module collects ambient light intensity distribution data in real time, and the motion control module combines the data with three-dimensional model data of the large-scale structural member to be measured to generate a multi-view dynamic scanning path instruction. The robot motion platform executes an instruction to drive the laser vision sensing module to move, the module projects laser stripes to the surface of a to-be-measured structural member and synchronously collects an image, the point cloud processing module performs adaptive filtering processing on the image and then generates three-dimensional point cloud data, and the requirement for efficient and accurate measurement of a large structural member in a complex industrial environment can be met.

The invention discloses a six-dimensional force / torque sensor decoupling system and method based on a width neural network, and the method comprises the steps: in a data collection and preprocessing unit, carrying out the null drift correction and normalization processing of a collected voltage signal through a weight type calibration platform and a data collection card, and forming a network model training data set; carrying out model training on the established six-dimensional force / torque sensor decoupling model of the width neural network, and solving a mapping matrix from a hidden layer to an output layer by adopting an importance score-based neuron pruning algorithm and a Moore-Pengos generalized inverse to obtain optimal model parameters; and finally, inputting the voltage signal subjected to data preprocessing to obtain a real-time output vector, and performing reverse normalization processing to obtain a decoupled six-dimensional force / torque vector. According to the method, precise decoupling of the six-dimensional force / torque sensor is achieved, and the inter-dimensional coupling error is remarkably reduced.

The invention discloses a thermal comfort monitoring robot system and method based on multi-modal body language feature recognition and fusion, and aims to realize individual thermal comfort monitoring, regulation and control in a dynamic indoor environment. The intelligent mobile platform carries multiple types of environment sensors and visual acquisition equipment, and performs autonomous navigation and acquires environment parameters and human body image data; the multi-modal feature recognition module performs human body detection, posture recognition and identity maintenance on a video stream frame by frame based on a deep learning network, and extracts multi-modal human body features; the data processing and fusion module realizes cross-frame identity consistency through an algorithm and fuses multi-modal human body features and environmental parameters; the thermal comfort calculation module dynamically adjusts a metabolic rate parameter based on a predicted average voting model, incorporates the metabolic rate parameter into a psychological correction factor and calculates an individual thermal comfort index; the three-dimensional visualization and regulation and control module generates a comfort distribution map, is in butt joint with a building environment automatic control system to achieve dynamic regulation and control, and provides support for intelligent building environment management.

The invention discloses a dynamic leakage fault diagnosis method for a flexible hand for a deep-sea submersible vehicle, and belongs to the technical field of flexible hands for the deep-sea submersible vehicle, and the method comprises the steps: obtaining source domain pressure signals from a plurality of different bending angles, and carrying out the preprocessing of the signals, and obtaining an original multi-source domain data set; a fault diagnosis model is constructed and trained, and in the training stage, the fault diagnosis model is a student network and comprises an adaptive frequency spectrum intervener, a multi-scale feature extractor, an adversarial mask generator, a main classifier and an auxiliary classifier; and inputting a to-be-diagnosed pressure signal into the multi-channel feature extractor and the main classifier in the trained student network, and outputting to obtain a fault diagnosis result. The method has remarkable advantages in the aspects of improving diagnosis precision, enhancing generalization ability, improving weak fault detection, reducing data dependence and the like, is suitable for intelligent diagnosis of hydraulic leakage of the deep-sea submersible flexible hand under dynamic and multi-angle working conditions, and has a good engineering application prospect.

The invention discloses a self-stabilization system of an exterior wall robot, and relates to the technical field of engineering construction robots, and the self-stabilization system comprises a phase reference module, a frequency spectrum coupling module, a playback prediction module, a gap evolution module, a feedforward compensation module and an energy regulation and control module, constructing a millisecond-level phase comb index based on the wind vibration phase reference field, and locking a zero-phase anchor point in the phase comb index to form an initial constraint condition of attitude perception; according to the method, the closed-loop control of the outer wall robot from disturbance sensing to fine control is realized by constructing a six-stage self-stabilization process. The system introduces millisecond-level phase anchor point locking, cross-frequency information fusion, disturbance trend prediction, adhesion gap dynamic mapping, multi-channel compensation control and energy reverse regulation and control mechanisms, and can significantly improve the operation stability, adaptability and safety in a high-rise complex outer wall environment without depending on a mechanical redundant structure.

The invention relates to the technical field of surface spraying, in particular to an intelligent surface spraying method and device based on coating quality and a spraying robot. The intelligent surface spraying method based on the coating quality comprises the steps that the coating actually-measured thicknesses of a plurality of detection points in a spraying width area are monitored in real time, and an actually-measured thickness distribution field is obtained; according to the actually measured thickness distribution field and the target thickness of the coating, a thickness deviation mean value is calculated, and whether the thickness deviation mean value is out of an allowable range or not is judged; if yes, calculating a thickness standard deviation according to the actually measured thickness distribution field; calculating a speed correction amount according to the thickness deviation mean value and the speed correction coefficient; and according to the thickness deviation mean value, the thickness standard deviation and the spraying width correction coefficient, the spraying width correction amount is calculated. According to the intelligent surface spraying method and device based on the coating quality and the spraying robot, the product surface coating spraying effect standard reaching rate is high, the secondary machining number can be greatly reduced, and the productivity is high.

The invention relates to the field of robot additional shafts, in particular to an additional shaft servo motor type selection method for a robot, which comprises the following specific steps of: S1, determining a transmission system structure at a load end of an additional shaft motor; s2, determining a mechanical structure and motion characteristic parameters of the transmission system; s3, importing into a motor library; s4, performing calculation; s5, judging and checking; s6, model selection is completed; for three mainstream transmission systems of a gear rack, a ball screw and a belt at a load end of a robot additional shaft motor, calculation and accurate model selection are performed on parameters of the motor, and the dynamic response characteristic of the motor and the system compatibility of the model selection method are improved; the model selection tool can support a user to import and modify a motor database by himself / herself, and quickly and conveniently recommend an accurate model selection result from the motor database according to the rotation speed, torque, power and load inertia ratio judgment and check conditions of the motor, thereby improving the model selection efficiency of the servo motor and improving the user experience. And resource redundancy and manufacturing cost caused by a traditional empirical selection method are reduced.

The invention provides a multi-scene vision switching intelligent spraying robot, and relates to the technical field of building decoration spraying. The system comprises an intelligent platform, an intelligent spraying manipulator, a processing part, a sealing part and a switching part, the processing part can accurately wind and store the exposed wire harness outside the slot hole of the socket without pulling the wire harness in the slot hole, and can also realize rapid storage of the wire harness; the sealing component provides two plugging schemes of a sealing air bag and a disposable baffle plate, and can automatically seal the socket slot. And the switching component realizes switching and automatic cleaning of the nozzles of multiple specifications, and is adaptive to the requirements of different latex paint types, spraying layer numbers and wall surface roughness. And full-process automation of wire harness protection, socket slot plugging, nozzle switching and spraying operation is realized. The wiring harness pollution and damage during spraying are effectively avoided, the spraying uniformity and the operation efficiency are improved, and the whole robot is made to meet the multi-scene spraying requirement.

The utility model provides a tomato picking robot device which comprises a movable chassis, an installation shell is fixedly arranged on the top face of the movable chassis, a visual picking matching component is installed at the left end of the top face of the installation shell, and an auxiliary picking matching mechanism is installed at the right end of the top face of the installation shell. Two multi-direction picking adjusting mechanisms are arranged on one side of the visual picking matching component, each multi-direction picking adjusting mechanism is installed on an installation shell and used for tomato picking operation, and a picking recycling component is installed on the installation shell. According to the tomato picking machine, through the matching arrangement of all the structures, automatic picking operation on tomatoes is facilitated, operation is easy, picking efficiency is high, and popularization is facilitated.