1058 results about "Collaborative robotics" patented technology

The invention provides a cooperative mechanical arm self-adaptive obstacle avoidance method in a dynamic scene, which comprises the following steps of: 1, setting an initial pose and a target pose according to a work task of a cooperative robot, and performing global path planning in an initial environment; 2, an operator completes an assembly task in an assembly area, and the collaborative robot operates according to a preset route and completes the assembly task in a matched mode; 3, the depth camera obtains a human body skeleton and skeleton node information, and a human body bounding box is generated; 4, whether the distance between the arm bounding box and the robot is smaller than the safety distance or not is judged, and if yes, collision early warning is triggered; 5, a new collision-free track is re-planned based on the self-adaptive obstacle avoidance strategy of the artificial potential field method, and the mechanical arm moves according to the new track to avoid the obstacle; and 6, after the obstacle leaves the safety early warning range, the mechanical arm returns to the global path and finally arrives at the target point.

The invention relates to the technical field of equipment control, and provides a vision-based collaborative robot end control method and related equipment thereof. Multi-modal dynamic anti-interference filtering and semantic fusion are carried out on original visual data to obtain three-dimensional semantic point cloud data, and coordinate system alignment is carried out on the three-dimensional semantic point cloud data according to a robot-based coordinate system to obtain a target pose parameter set; performing dynamic path planning on the target pose parameter set to obtain a joint space motion track, and performing inverse kinematics solution and motor instruction synthesis on the joint space motion track according to robot D-H model parameters to obtain a motor control instruction, and performing closed-loop feedback optimization on the motor control instruction according to the state data of the end effector to obtain a dynamic correction control instruction. According to the method, through full-link optimization from sensing, planning to execution, the operation precision and safety of the collaborative robot in an uncertain environment are remarkably improved.

Provided is a self-adaptive identification method for nonlinear dynamic parameters of a reducer, which belongs to the design field of a reducer. The method includes: modeling a harmonic reducer corresponding to a flexible joint as a concatemer of a rigid reducer and an elastic torsion spring, and carrying out dynamic theoretical modeling and parameter variable independence processing on the concatemer to form a dynamic equation for parameter identification; giving an optimized motion trajectory to each joint of a robot and controlling the robot to act accordingly, acquiring relevant data needed for parameter identification based on a built-in torque sensor and double encoders inside the joint; using an offline identification algorithm to accurately identify a plurality of dynamic parameters of a collaborative robot considering joint flexibility and friction, and obtaining a minimum parameter set.

The invention belongs to the technical field of collaborative robots, and particularly discloses and provides an anti-explosion mechanical arm positive pressure control system and method.The system comprises a mechanical arm motion tracking module, an environment data monitoring module, a configuration adjustment analysis module, a pressure adjustment analysis module, a database and a pressure adjustment execution terminal. The mechanical arm motion tracking module is designed to track the motion state of the mechanical arm and record motion data, a key part pressure sensor is started to monitor pressure data, and the correlation change of motion and pressure can be captured. The environment data monitoring module monitors environment parameters of a working area in real time, and environment changes are comprehensively mastered. The all-dimensional monitoring capability of the system is improved, factors influencing positive pressure control can be obtained more comprehensively, meanwhile, configuration adjustment judgment is carried out in combination with environment, movement and pressure data, adjustment values are dynamically determined, and intelligent decision making and self-adaptive adjustment of mechanical arm positive pressure control are achieved.

The invention discloses an automatic welding method and system based on a collaborative robot, and the method comprises the steps: collecting and preprocessing three-dimensional point cloud data of a to-be-welded steel part and the collaborative robot, and collecting thermal physical property data of to-be-welded steel; based on the three-dimensional point cloud data and the thermophysical property data of the steel, a welding simulation model is constructed through the digital twin technology; constructing a welding quality evaluation model based on a deep learning technology, and performing a virtual welding test by using the welding simulation model and the welding quality evaluation model to obtain an optimal welding route and optimal welding parameters; and based on the optimal welding route and the optimal welding parameters, the collaborative robot is started to conduct automatic welding. The invention relates to the technical field of automatic welding, and solves the technical problem that an existing automatic welding technology lacks welding parameter self-adaptive optimization and welding route intelligent planning through combination of a digital twinning technology and a deep learning technology.

The invention relates to the technical field of robot control, in particular to a time delay double-arm collaborative robot control method based on Udwadia-Kalaaba and a cooperative game theory, and the method mainly comprises the following steps: obtaining the control input of a double-arm collaborative robot system obeying servo constraint according to the uncertainty of the system; a dynamic model is simplified by adopting a time delay estimation method so as to realize time delay estimation and double-mechanical-arm cooperative impedance control, a self-adaptive robust controller is established according to time-varying uncertainty existing in a system in combination with a self-adaptive updating law, and optimal control parameters of the robust controller are obtained through a cooperative game method. By the adoption of the method, control parameters can be optimized, performance maximization is achieved, it is guaranteed that the robot can be effectively balanced among different performance targets, and optimization of the overall control performance of the system is promoted.

The invention relates to a seat cushion robot self-adaptive tightening system and an operation method. The system provided by the invention is composed of an integrated industrial personal computer, an AGV mobile platform, a collaborative robot, a tightening end effector, an industrial camera and accessories thereof. The collaborative robot is installed on the AGV mobile platform, the tightening end effector and the industrial camera are installed at the tail end of the AGV mobile platform, and the whole system is controlled by the integrated industrial personal computer. The accurate position of the center of the to-be-tightened bolt can be obtained through a visual identification method in combination with a designed multi-layer screening method; meanwhile, different feeding modes are set according to different pre-tightening conditions, automatic cap searching is achieved, and it is guaranteed that tightening is in place; in addition, the counter-acting force arm is added to counteract counter-acting force in the tightening process, and robot damage is avoided. The tightening system and the operation method provided by the invention not only have extremely high flexibility, but also can adapt to a complex tightening environment, so that the accuracy of tightening work is ensured, and the working efficiency is also improved.

The invention discloses an automatic stacking control system based on visual positioning. The automatic stacking control system comprises a multi-mode visual positioning module, a model building module, a dynamic path planning module, a mechanical arm execution module, an error correction module and a storage module. The multi-mode visual positioning module comprises an RGB camera, a sensor and a laser radar and is used for obtaining three-dimensional space information of goods and a stacking area in real time. The multi-modal visual positioning module is mounted on one side of the stacking area; the model building module is used for building a stacking area, the cargo position and the position of the mechanical arm in a three-dimensional space, when the system is used, information about the position of the stacking area and information about whether new cargoes can be stacked in the stacking area or not can be obtained, then movement at any position in the space can be achieved through the three-axis cooperation mechanical arm, and the three-axis cooperation mechanical arm can move at any position in the space. The application range of the system is widened, and cargoes can be accurately conveyed to the position of a stacking area through the dynamic path planning module and the error correction module.

New and innovative systems and methods for calibrating and correcting sensors associated with a collaborative robot are disclosed. An example system comprises: at least one robotic arm; a sensor affixed to a location on the robotic arm, wherein the sensor measures force and torque across six degrees of freedom (6DOF); a processor; and memory. The system may receive, from the sensor, sensor input in real-time that indicate a measured force or torque. The system may generate, in real-time, sensor corrections that correspond to offset, linear, and non-linear deviations of the measured force in each sensor axis. The sensor corrections may correspond to offset, linear, and non-linear cross-coupling of the measured force between two or more sensor axes. The sensor corrections may be determined by applying offset, linear, and non nonlinear corrections to each degree of freedom (DOF) from every other DOF.

The invention discloses a satellite flash connection intelligent switching decision-making system and method based on equipment state prediction, and particularly relates to the technical field of satellite flash connection. In order to solve the problem of star-flash network linkage failure caused by multi-mechanical-arm cooperative movement and electromagnetic disturbance coupling in an industrial cooperative robot system, a prediction model fusing space attitude cooperative change characteristics and transient electromagnetic disturbance amplitude gradient characteristics is constructed, and high-sensitivity recognition and risk early warning of the coupling state of a star-flash connection network are achieved. A communication channel and communication parameters are dynamically adjusted through a fuzzy logic decision mechanism, and link stability and interference robustness are effectively improved; and meanwhile, a model adaptive optimization mechanism driven by switching effect feedback is introduced, so that the prediction accuracy and the system self-evolution capability are remarkably improved, and the continuity, the safety and the high reliability of multi-node cooperation in an industrial communication scene are guaranteed.

The invention relates to the technical field of industrial Internet of Things, in particular to an industrial Internet of Things system for collaborative robot monitoring, which comprises the following steps: a sensor calibration module, a running state modeling module, a working performance analysis module, an input parameter analysis module, a movement track detection module and a fault type analysis module. According to the method, the accuracy and reliability of collected data are ensured by calibrating the reading of the sensor, the accuracy of robot state evaluation is optimized, the ideal motion trail of the robot is predicted in real time, the actual position is monitored, the position deviation and the abnormal trail are recognized, and the accuracy of robot state evaluation is improved by combining the calibration of abnormal points and the matching of fault modes. Fault types are quickly identified, fault positions are positioned, fault detection efficiency and accuracy are improved, adaptability of the robot in a complex production environment is improved, operation efficiency and maintenance precision of the robot are enhanced, downtime is shortened, maintenance cost is reduced, and accurate production monitoring and decision support are provided for enterprises.

An autonomous collaborative robotic system for automatically detecting, locating, and mapping underground assets is provided. The collaborative robotic system includes two autonomous robots, each robot including a housing with extendable legs, a camera module, a laser module designed to project a structure light pattern on a pipe interior, a sensor module designed to collect images from the camera module, and a processing module designed to process and stitch data to generate a network of underground assets and identify one or more features within the asset network.

The invention discloses a flexible composite robot system for laboratory automation. The flexible composite robot system comprises a flexible composite robot and a central scheduling and control system, the flexible composite robot comprises an autonomous mobile platform which carries a multi-mode navigation sensor and realizes path planning and obstacle avoidance in a laboratory environment by adopting a synchronous positioning and mapping algorithm; the high-precision cooperative mechanical arm is mounted on the autonomous mobile platform and is integrated with a joint torque sensor; the end effector quick replacement system provides mechanical, electrical and pneumatic standardized interfaces; the central scheduling and control system comprises an intelligent man-machine interaction system for realizing man-machine interaction; the experiment process analyzer is used for decomposing the digital experiment scheme into an executable task sequence; the multi-agent task planning and scheduling engine is used for distributing tasks and planning a moving path; and the anomaly detection and autonomous recovery module is used for detecting an abnormal condition based on machine vision and force sensing data and triggering a recovery strategy.

The invention discloses a flexible joint collaborative robot control method based on self-adaptive jump and application. The control method comprises the following steps: calculating a combined error; calculating a feed-forward compensation item and a feedback control item; adding a feedforward item and a feedback item for control; wherein the combined error comprises first-order to third-order errors; the self-adaptive jump control comprises a PID subitem and an RISE subitem, the RISE subitem comprises a self-adaptive sliding mode gain, and the self-adaptive sliding mode gain is related to a second-order error and a first-order differential of the second-order error. According to the method provided by the invention, the calculation complexity is reduced, and the real-time calculation capability of the system is improved, so that the control system can keep a relatively high response speed under a high-dynamic working condition; due to the self-adaptive jump design, the resistance of the system to uncertainty and external disturbance is improved, and the high-frequency flutter problem caused by the flexible joint is remarkably reduced; and the adjusting process of the control parameters is simplified, and the method is particularly suitable for rapid deployment of the multi-degree-of-freedom collaborative robot.

The invention relates to the field of robot intelligent control and man-machine collaboration, in particular to a multi-sensing collaborative robot control method, which comprises the following steps: synchronously filtering mechanical, tactile, visual and physiological signals to generate a unified observation frame, and calculating power flow and energy in combination with a joint state to form an execution vector; extracting a topological descriptor by using persistent coherence, and outputting an interaction potential field and a human body intention by using the topological descriptor as a conditional driving diffusion model; then, power density is constructed based on the potential field gradient and intention, joint torque and impedance are generated through entropy regular optimal transmission and Jacobian and microoperator kernel mapping, and an energy Lagrange multiplier is updated in real time; and if the consistency error continuously exceeds a threshold value, estimating a Koopman lifting model on line by using a causal weight, completing model prediction control under the energy, conformal security and topology consistency constraint, outputting an update instruction and performing closed-loop feedback. The method improves the cooperation precision and safety, reduces the energy consumption, and is suitable for a high-dynamic man-machine cooperation scene.

The invention relates to the technical field of two-arm robot pipeline butt joint cooperative motion planning and control in a complex environment, in particular to a two-arm cooperative robot pipeline butt joint method based on relative Jacobi. According to the method, a double-arm kinematics equation relative to a Jacobian matrix is constructed, constraint conditions are constructed in combination with pipeline butt joint requirements, pose errors and integral information are introduced to design an anti-noise motion planning scheme, an end effector obstacle avoidance strategy is designed, the anti-noise scheme is converted into a quadratic optimization problem, and the quadratic optimization problem is solved through a numerical algorithm. According to the method, the problems that an existing scheme is insufficient in precision, inaccurate in constraint condition and poor in anti-noise and obstacle avoidance capacity are solved, the uniformity and accuracy of butt joint of the two-arm pipelines are improved, the influence of environmental noise is effectively restrained, butt joint safety is guaranteed, butt joint efficiency and reliability are improved, and the high-precision pipeline butt joint requirement under the complex environment is met.

The present invention relates to a collaborative robot system used in an industrial environment where workers collaborate. The collaborative robot system comprises: a collaborative robot body having a multi-joint structure; a control unit for controlling each joint or auxiliary shaft; one or more sensors for detecting the operational state of the robot in real time; and a status diagnosis and response module for diagnosing the state of the robot on the basis of detected data and controlling the operation of the robot accordingly. Specifically, the system is configured to enable the robot to autonomously perform actions such as deceleration, stopping, and recovery in response to various state changes occurring during work, and to perform self-learning and trajectory optimization on the basis of data accumulated through repetitive tasks. Furthermore, the system includes a graphical user interface (GUI) for intuitive user interaction, which is linked to a digital twin-based virtual simulation environment, enabling presetting and modification of work paths. When multiple collaborative robots are operated together, the system enables task synchronization, path collision avoidance, and sharing of status information among the robots, and may be connected to an external control server or a cloud-based control system to allow integrated management of the entire workflow.

The invention discloses a constraint following control method of a two-arm collaborative robot based on differential homeomorphic mapping, and relates to the field of robot control. According to the method, a nominal dynamical model of a robot is established, and a geometric constraint equation is defined according to a cooperative task; establishing global differential homeomorphic mapping by constructing constraint tracking variables and complementary coordinates, and decoupling a system dynamics model into a constraint tracking subsystem and a complementary subsystem; designing a robust adaptive controller fusing sliding mode control and an adaptive law, and estimating and compensating the uncertainty of the system on line; according to the method, the constraint processing complexity is effectively simplified through differential homeomorphic mapping, the constraint tracking precision and robustness of the system under model uncertainty and external interference are remarkably improved, and high-precision and high-stability cooperative task execution of the two-arm robot in the dynamic environment is achieved.

The invention relates to the technical field of goods stacking, and discloses a goods stacking method and device based on disordered material mixing for a collaborative robot, and the method comprises the steps that based on a stacking area shot by a camera, the space distribution state of the stacking area is updated in real time, and a space capable of being placed is determined; based on the incoming material area shot by the camera, the box size of the target goods is obtained; and according to the box body size of the target goods, in combination with the placement space, optimal matching of the space utilization rate of goods stacking is carried out, and the position of a to-be-stacked box body in the target goods is determined so as to guide the collaborative robot to carry out goods stacking. The method has the effects that the space utilization rate and the taking rate of subsequent boxes are comprehensively considered, the space utilization rate of the collaborative robot during goods stacking is increased, and the goods stacking efficiency is higher.

The present invention discloses a modular joint of a collaborative robot with a compact structure, which is connected in sequence: a joint housing; a joint output flange; a low-speed wire protection tube connected to the joint output flange; a harmonic reducer connected to the joint output flange and the joint housing; a motor assembly, including a stator and a rotor; a motor shaft connected to the motor rotor, one end of which is connected to the input end of the harmonic reducer; a brake assembly, which is a magnetic friction type, locks when the power is off, and opens when the power is on, and is connected to the motor shaft. Compared with the latch-type brake, it is safer to stop in an emergency and will not bend the stop pin; a motor-end encoder assembly; and a joint-end encoder assembly. The encoder code disc at the motor end of the present invention is concentrically arranged with the encoder code disc at the joint end, and the encoder reading head at the motor end is integrated with the encoder reading head at the joint end, so that the axial space of the joint is compact, the integration is high, and the wiring space is large for easy operation. At the same time, the modular joint of the present invention also has the characteristics of high rigidity and large load-to-weight ratio.

The invention discloses a rapid auxiliary assembly collaborative robot suitable for an aircraft cabin door, and belongs to the technical field of aircraft assembly, the rapid auxiliary assembly collaborative robot comprises a main body structure, an adsorption unit, a power system and a control system, the main body structure 1 carries the adsorption unit, the power system and the control system, and the main body structure 1 is matched with the power system and the control system to realize multi-pose follow-up control; the power system provides pneumatic power for the adsorption unit to adsorb cabin door products. The power system provides negative pressure for work of the adsorption unit and provides power for follow-up control of the main body structure. The control system controls adsorption, release and multi-degree-of-freedom free posture adjustment. The device has high degree of freedom, adapts to aircraft cabin doors with different shape and position requirements, can be accurately operated in a narrow assembly space, is flexible in structure, simple and convenient to operate, and rapid and accurate to move and position, greatly shortens the time of loading, unloading and hoisting of the cabin door, and shortens the cabin door assembly time by about 70%.

The invention relates to a robot track synchronization control method. According to the technical scheme, efficient collection and over-distance transmission of neural signals are achieved through the quantum entanglement technology, the brain movement intention is analyzed in combination with a high-sensitivity sensor and an intelligent algorithm, an instruction is transmitted to a robot power driving system through a low-delay communication architecture, and real-time synchronization of man-machine tracks is achieved through a two-way feedback system. Meanwhile, the movement flexibility of the robot is improved by adopting a lightweight design, the problems of high delay, low precision, poor interaction experience and the like in traditional man-machine synchronous control are solved, and the method can be widely applied to the fields of exoskeleton robots, industrial collaborative robots, rehabilitation medical robots and the like. The method has the advantages of being low in delay, high in precision, capable of improving interaction experience and wide in application range.

An autonomous ground vehicle for agricultural plant and soil management operations. According to some embodiments, autonomous ground vehicle includes: a camera unit configured to generate images of agricultural ground soil and plant organisms, a first mechanical arm having an end effector comprising a hoe portion and an electrode portion, a second mechanical arm having an end effector comprising an electrode portion, a high voltage booster electrically connected to the electrode portions, an electronic memory storage medium comprising computer-executable instructions; one or more processors in electronic communication with the electronic memory storage medium, configured to execute the computer-executable instructions stored in an electronic memory storage medium for implementing a plant species control management operation comprising electrical control and mechanical control options.

The invention belongs to the technical field of intelligent and robot operation, and discloses a collaborative robot closed-loop operation method based on scene perception and thinking chain reasoning, which comprises the following steps of: firstly, generating structured semantic representation containing confidence by utilizing a visual language model of LoRA efficient fine tuning and fusing multi-view data, and providing semantic understanding for a robot; secondly, utilizing a three-dimensional diffusion model to generate explicit geometric priori under the condition of no real CAD, and correspondingly completing PnP initial pose estimation in combination with 2D-3D; then, carrying out pose optimization by adopting a tracking-refining strategy, and triggering reinitialization based on geometric prior when a residual error exceeds a threshold value; and finally, decomposing a global task by utilizing a thinking chain reasoning module, and realizing'perception-reasoning-execution 'closed-loop control based on visual servo in cooperation with an execution module. The method realizes effective combination of large model reasoning and physical execution, has strong robustness under dynamic disturbance, and is suitable for intelligent manufacturing and man-machine cooperation scenes.

The invention discloses an in-situ remanufacturing repair system and method based on three-dimensional point cloud.The in-situ remanufacturing repair system comprises an industrial personal computer, a binocular structure light camera and a collaborative robot, the binocular structure light camera and the collaborative robot are connected with the industrial personal computer, and the collaborative robot is provided with a welding gun connected with an intelligent welding machine; the method comprises the following steps of: performing hand-eye calibration on a binocular structured light camera by adopting dual quaternion and a singular value decomposition algorithm; a binocular structured light camera is used for shooting the workpiece, and a complete point cloud of the to-be-repaired area is obtained; performing surface reconstruction on the to-be-repaired area by using a Poisson surface reconstruction algorithm; according to the side wall fusion optimization formula, path planning is conducted on the to-be-repaired area model in Cura software, and filling path coordinates of the to-be-repaired area are obtained. According to the method provided by the invention, the defect of incomplete fusion of the side wall of the workpiece after additive remanufacturing repair can be reduced, and meanwhile, the surface flatness of the weld joint adjacent to the side wall is improved.

The invention discloses a collaborative robot joint external force estimation method, and relates to the technical field of collaborative robot joint external force estimation, and the method comprises the steps: building a joint kinetic model, and obtaining the basic kinetic parameters of a collaborative robot joint; the angular displacement deviation between the input shaft and the output shaft of the speed reducer is obtained, and the compensated torsional angle difference is calculated according to the angular displacement deviation; a joint variable stiffness model is established, multiple sets of calibration data are obtained through experiments, and parameters in the joint variable stiffness model are identified according to the multiple sets of calibration data; based on the basic dynamic model and the joint variable stiffness model after parameter identification, a nonlinear disturbance observer is constructed in combination with introduced auxiliary variables; and system disturbance is observed and compensated through a nonlinear disturbance observer, so that an external torque estimated value acting on the tail end of the joint is calculated and output in real time. According to the method, high-precision and real-time estimation of the external torque can be effectively considered, and meanwhile, the system hardware cost and the structure complexity are greatly reduced.

The invention provides a dynamic adjustment method for robot parameters, electronic equipment and a storage medium, and the method comprises the steps: obtaining the current position of a collaborative robot and the current information of at least one pre-configured safety region corresponding to the collaborative robot, the current information of the security area comprises plane information of the security area and current function information of the security area; according to the current position and the current information of each safety area, a target safety area where the collaborative robot is located currently is determined, the target safety area comprises a working sub-area and a collaborative sub-area, and the collaborative sub-area is pre-configured with corresponding safety parameters; and adjusting the current safety parameter of the collaborative robot to be the safety parameter of the collaborative sub-region in the target safety region, so that the collaborative robot executes collaborative operation according to the safety parameter of the collaborative sub-region. Dynamic adjustment of the safety parameters of the collaborative robot is achieved, and the requirements of different safety areas for the safety parameters can be met.

The present invention provides a machine vision-based anchor rod sorting and intelligent iron removal system for a chute ore-feeding machine, which relates to the field of image data processing and includes: an anchor rod sensing module, which is used to determine whether an anchor rod exists based on an ore-feeding machine image, magnetic field information, sound information and vibration information; a ore-feeding machine control module, which is used to control the ore-feeding machine to stop working after determining that an anchor rod exists; an intelligent iron removal module, which is used to determine anchor rod information based on the ore-feeding machine image, magnetic field information, sound information and vibration information, obtain a target area image, and determine whether an anchor rod exists based on the target area image, and after determining that an anchor rod exists, determine anchor rod sorting working parameters based on the target area image, and a collaborative robot performs anchor rod sorting according to the anchor rod sorting working parameters; the ore-feeding machine control module is also used to control the ore-feeding machine to continue working after determining that an anchor rod does not exist or the collaborative robot completes anchor rod sorting, and has the advantage of realizing automatic removal of anchor rods mixed in ore.

The invention provides a vision-based collaborative robot safety control method, which comprises the following control steps: S1, acquiring scene information of a collaborative robot, and acquiring a target coordinate and a pixel position based on the scene information; and S2, the specific position of an obstacle around the target and a surrounding three-dimensional scene are recorded based on a camera on the collaborative robot, and the three-dimensional scene is modeled and projected on an operation screen, so that the collaborative robot can be ensured to achieve the effects of rapid positioning, moving and grabbing through mutual cooperation of a plurality of modules; meanwhile, a potential field method is adopted for route planning, so that the collaborative robot can be prevented from colliding with an obstacle during planning movement, it is ensured that the whole collaborative robot has good environment sensing and coping capacity, and the overall efficiency in the man-machine collaborative operation process can be effectively guaranteed; and the robot can be applied to any man-machine cooperation production environment without excessive adjustment, so that the development of the field of cooperation robots is promoted.

The invention discloses a dexterous four-foot cooperation robot welding system based on an industrial large model, belongs to the technical field of industrial robot welding, and provides the following scheme that the dexterous four-foot cooperation robot welding system comprises a four-foot robot body and is characterized in that a mounting base is arranged at the upper end of the four-foot robot body, and a mechanical arm body is arranged at the upper end of the mounting base; the arc-shaped guide groove formed in the outer side of the rolling cylinder is matched with the guide rod on one side of the positioning plate, so that the first spray head can flexibly swing left and right, the blowing cleaning range is remarkably expanded, and it is ensured that the periphery of a welding area is subjected to comprehensive and effective dust removal treatment; and meanwhile, the mounting plate and the cleaning brush at one end of the mounting plate are driven to synchronously swing, deep cleaning and removal of impurities on the surface of the iron plate are achieved, the adverse effect of the impurities on the welding quality is effectively avoided, and a solid technical support is provided for efficient and accurate welding operation of the four-foot cooperation robot in a complex environment.