4167results about "Arms" patented technology

The embodiment of the invention provides an unhooking robot control method based on multi-source visual fusion, which is applied to the technical field of robot control and comprises the following steps: acquiring an RGB image, a depth image, an infrared image and IMU data through a multi-source sensing system mounted at the tail end of a robot; carrying out feature fusion identification by adopting a double-branch neural network, and outputting the boundary contour of the lifting hook and the three-dimensional coordinates of the optimal grabbing point; the visual coordinates are unified to a robot base coordinate system through a registration correction mechanism; a Transform prediction model is constructed based on the visual and inertial signals, and future pose changes of the lifting hook are estimated; a feedforward control track is generated to counteract swing of the lifting hook, and track correction is carried out in combination with visual servo feedback; and a joint instruction is generated through path planning and inverse kinematics solution, and the mechanical arm is driven to complete precise unhooking operation. According to the method, the recognition precision, the anti-interference capability and the operation success rate of unhooking operation in complex illumination and dynamic environments are effectively improved.

The disclosure presents a humanoid robot with an upper region (head, torso, arms with forearm assemblies, end effectors), lower region (legs), and connecting central region. Each end effector features index, middle, ring, little finger, and thumb assemblies attached to a housing of said end effector. The housing includes interior wall extents creating spaces for tendon routing, where the first distance between first and second wall extents is less than 45% of the second distance between third and fourth wall extents. Tendons controlling finger movements pass between these wall extents. The robot incorporates a wrist assembly connecting the housing of the end effector to the forearm, actuators housed in the forearm that control the tendons, and a carpal tunnel-like structure that guides tendons from forearm to base of the housing, enabling precise hand movements without requiring actuators in the hand itself.

The invention relates to the technical field of intelligent agricultural equipment, and discloses an automatic agaricus bisporus picking method, device and equipment based on artificial intelligence and a medium. The method comprises the steps that RGB images and three-dimensional point cloud data of the agaricus bisporus growth environment are collected in real time through a binocular vision camera and a depth sensor which are installed at the tail end of a picking robot, and environment illumination parameters and cultivation bed coordinate information are obtained; inputting the RGB image into a pre-trained lightweight convolutional neural network, identifying a pileus contour, a stipe position and a maturity level of the agaricus bisporus, calculating a space coordinate, a height and a growth inclination angle of the agaricus bisporus based on the three-dimensional point cloud data, and constructing an agaricus bisporus target database; a mechanical arm picking path is generated based on the agaricus bisporus target database, and path weight parameters are optimized online through a preset reinforcement learning model; according to the maturity grade and morphological characteristics of the agaricus bisporus, the clamping force and the rotating angle of the end effector are dynamically adjusted, and automatic picking of the agaricus bisporus is completed.

The invention provides a hydraulic generator inner bore inspection robot based on a dynamic behavior tree and an intelligent decision and operation method thereof, and the robot comprises an upper mechanical arm end executor, a six-axis mechanical arm, an intermediate control system, a mobile platform, a multi-physical quantity fusion detection system, and a central control platform. The method is specially designed for the complex dynamic shielding environment of the inner bore of the hydro-generator. According to the method, by constructing a three-level behavior tree architecture composed of a task decision-making layer, a scene adaptation layer and an execution control layer, inspection requirements are decomposed into environment perception, task execution and resource constraint events, and the events are dynamically mapped to preset behavior nodes. Weight factors are adjusted in real time based on a multi-dimensional evaluation system, and functions of autonomous obstacle avoidance, narrow space operation and anomaly detection are realized in combination with hardware characteristics of the robot. The problems that a traditional inspection method is poor in adaptability and low in efficiency in a dynamic shielding environment are solved, and the intelligent level and safety of hydraulic generator inner bore inspection are remarkably improved.

The invention discloses an industrial robot intelligent control system which comprises a master control terminal, the master control terminal is provided with an industrial-grade multi-core processor and is integrated with a motion control subsystem and an environment sensing subsystem, the motion control subsystem is connected with the master control terminal through a first communication interface, and the environment sensing subsystem is connected with the master control terminal through a second communication interface. According to the motion control subsystem, a distributed axis controller array and reinforcement learning strategy switching algorithm is adopted, so that the trajectory tracking precision and the energy consumption efficiency are improved; and the environment sensing subsystem realizes real-time anomaly detection through multi-mode sensor fusion and an LSTM-GAN fault prediction model. The system supports containerized deployment and edge computing collaboration and integrates AR human-computer interaction, and the adaptive capacity and safety of the industrial robot are remarkably improved.

The invention discloses a dredging mechanical arm intelligent control method and system based on DPPO reinforcement learning, and relates to the technical field of dredging engineering equipment intellectualization. The method comprises the steps that hydraulic pressure, vibration spectrum and temperature data of a dredging and desilting mechanical arm of a dredger are collected in real time and preprocessed; the preprocessed data are input into an LSTM-Attention model, feature extraction is carried out based on a long short-term memory network and an attention mechanism, and a predicted value of the remaining service life of the mechanical arm is output; a degradation-efficiency coupling model is established, and the health index and the operation efficiency of the mechanical arm are calculated based on the predicted value of the remaining service life of the mechanical arm; and a DPPO reinforcement learning controller is established, the mechanical arm health index, the operation efficiency, the energy consumption and the mechanical arm joint angle serve as a state space, an action space of a dynamic load adjusting instruction is output, a control strategy is optimized through a reward function, and the load adjusting instruction is subjected to dynamic constraint processing and then drives a mechanical arm hydraulic executing mechanism.

The invention discloses a force / position hybrid control method for a dexterous arm-hand robot, and aims to improve the tracking precision and flexibility of a high-degree-of-freedom robot in a complex interaction task. The method comprises the following steps: constructing a complete kinematics and dynamics model; designing a self-adaptive sliding mode impedance controller, converting an impedance equation into a system taking interaction force as a state, and introducing a sliding mode variable to realize stable tracking of expected force; a preset performance boundary function and a synchronization error are introduced to realize cooperative control and performance constraint; and finally, a force / position hybrid control structure is constructed, the outer ring adjusts the expected trajectory, the inner ring achieves accurate tracking, and therefore smooth interaction between the robot and the complex environment is achieved. The method has good robustness and adaptability, and is suitable for tasks such as grabbing and operation.

The invention discloses an intelligent mechanical arm control system, and relates to the technical field of intelligent mechanical arms, the system comprises a sensor data acquisition module, a multi-modal data fusion module, an environment and target prediction module, an intelligent decision and control module and a control execution and feedback module; through a cooperative working mechanism of the environment and target prediction module and the intelligent decision-making and control module, future state change of a target object can be accurately predicted, possibility is provided for pre-judgment operation of the mechanical arm, then a decision-making optimization algorithm and a multi-target optimization function are applied, an optimal motion strategy is planned for the mechanical arm, and the optimal motion strategy is provided for the mechanical arm. The system further has the real-time feedback and adjustment capacity, it is ensured that the mechanical arm can automatically adapt to changes in the complex dynamic environment, the operation precision and efficiency of the mechanical arm are improved, the capacity of the mechanical arm for adapting to the complex environment and dealing with emergencies is enhanced, and the production efficiency and safety are improved.

The invention relates to the technical field of intelligent mechanical arm control, and discloses a mechanical arm track optimization method and system based on deep learning and a fuzzy algorithm, and the method comprises the steps: building a kinematic model of a mechanical arm, determining the working space of the mechanical arm, carrying out the high-density random sampling, and generating a three-dimensional point cloud picture of a reachable region at the tail end of the mechanical arm; constructing a path planning model, designing a state space and an action space, and constructing a reward function; time-impact double-target optimization is carried out on the tail end path point sequence, a smooth joint trajectory is constructed, and balance between the shortest trajectory execution time and the minimum joint impact is achieved on the premise that speed and acceleration constraints are met; and tracking control is carried out on the trajectory, external disturbance and unmodeled dynamics are estimated and compensated in real time, a parameter adaptive law is designed, and the trajectory tracking precision of the system in a complex environment is improved. The autonomy, the accuracy and the anti-interference capability of the hot-line work mechanical arm in a complex environment are improved.

The invention provides a dynamic obstacle avoidance path planning control method for a redundant mechanical arm, which adopts a self-adaptive artificial potential field dynamic obstacle avoidance algorithm based on a second-order dynamic control barrier function. The problems that a traditional artificial potential field method cannot reach a target, is prone to falling into a local minimum value and cannot effectively deal with a dynamic obstacle are solved. The efficient and safe obstacle avoidance of the mechanical arm in a dynamic complex environment is realized by constructing a self-adaptive velocity repulsion field and a virtual obstacle model, combining a high-order dynamic control barrier function as a safety constraint and utilizing a quadratic programming optimization algorithm. Experimental results show that the method can effectively guide the mechanical arm to escape from the local minimum point, the target point can be reached, meanwhile, the safe distance between the mechanical arm and a dynamic obstacle is guaranteed, the movement efficiency and track quality of the mechanical arm are remarkably improved, and the real-time performance and safety requirements of a dynamic obstacle avoidance task are met.

A method for retrieving an inventory item based on a handling robot, where the handling robot includes: a storage frame; and a material handling device installed on the storage frame, and including a telescopic arm and a manipulator installed to the telescopic arm; and the method for retrieving an inventory item includes: driving, by the telescopic arm, the manipulator to extend to a preset position of warehouse shelf along a preset horizontal reference line; loading, by the manipulator that is remained on the reference line, the inventory item located in the preset position; driving, by the telescopic arm, the manipulator loaded with the inventory item to move to the storage frame along the reference line; and unloading, by the manipulator that is remained on the reference line, the inventory item to the storage frame.

The invention relates to the technical field of transfer robots, in particular to an intelligent warehouse logistics automatic transfer robot. The robot comprises a scraper and a suction cup which are arranged on a robot body, the scraper is provided with specially-designed groove pressing teeth, an arc-shaped groove with a guiding function can be formed in the surface of a box body, and it is ensured that a frost layer effectively falls off along a preset path through the design. The system collects temperature gradient, surface appearance and contact stress data in real time through the integrated multi-mode environment sensing unit, the intelligent decision-making unit establishes a dynamic control model based on the data, and accurate evaluation and self-adaptive processing of the frost layer state are achieved. The whole system constructs a complete closed-loop control chain, the limitation of a traditional defrosting method is overcome, the adsorption stability is kept, meanwhile, the operation efficiency is improved, the system is particularly suitable for the low-temperature storage environment of-25 DEG C and below, and a reliable solution is provided for cold-chain logistics automatic operation.

Various advanced wiring assemblies for a humanoid robot are disclosed. The wiring assembly includes a first actuator printed circuit board (PCB) positioned near a first side of a first actuator and including a first PCB terminal. A second side of the first actuator includes: an output, an actuator cover coupled to the output and having a wire bundle opening formed therein, and an actuator opening formed through an extent of the second side. The wiring assembly includes a wire bundle having: a first end connector coupled to the first PCB terminal, a second end connector coupled to the second PCB terminal, and a plurality of wires that extend between the first end connector and the second end connector, and wherein said plurality of wires extends through the actuator opening of the second side of the first actuator and the wire bundle opening formed in the actuator cover.

The invention relates to the field of robots, and discloses a robot ordering method and system, and the method comprises the steps: obtaining a depth map and a color map of a current scene; obtaining a detection frame of a target object, and cutting out three-dimensional point cloud data of the corresponding object from the depth map according to a detection result; reasoning by taking the three-dimensional point cloud data as input of a reasoning model, and predicting candidate grabbing poses; and according to the predicted candidate grabbing poses, trajectory planning and motion execution are carried out. Reasonable action information can be generated according to information provided by the visual language model in combination with specific task requirements, and therefore control over the mechanical arm is achieved.

Disclosed is a birfield flexible variable-stiffness continuum robot unit and a continuum robot. In the birfield flexible variable-stiffness continuum robot unit, main structural units are interconnected to constitute a continuum manipulator; joint connecting structures connect the two adjacent main structural units; a front-end unit is arranged at a foremost end of the manipulator; and a rear-end unit is arranged at a rearmost end of the manipulator. When in use, birfield joint design is adopted, a single joint has two degrees of freedom, is more flexible and variable, and the adjacent structural units rotate around a center of a sphere, so that modeling is simpler and more convenient; connection design of flexible springs is further adopted, certain stiffness is provided for the manipulator, and thus the manipulator has a variable-stiffness characteristic; and meanwhile, a roll ball structure makes the manipulator have high torsional resistance.

The disclosed humanoid robot is designed to perform diverse, human-like tasks in various environments, from industrial assembly and customer service to every day household chores. These robots possess anthropomorphic features including a head, torso, arms, legs, and hands, enabling complex motions with over 60 degrees of freedom. The upper portion houses over 70% of the DoF, allowing dexterous manipulation, while the central and lower portions are optimized for battery storage and efficient movement. More than 30 electric actuators (mostly rotary) power the humanoid robot, with a strategic arrangement that minimizes mechanical singularities and facilitates tasks such as deep squats and precise reaching. This configuration reduces cost, weight, and maintenance while improving performance and capabilities of said humanoid robot.

The invention belongs to the technical field of mobile mechanical arm grabbing, and provides a mobile mechanical arm grabbing control method and system based on machine vision, and the method comprises the steps: collecting an image in the moving process of a mobile mechanical arm according to a preset grabbing path, recognizing a dynamic obstacle in the image through an RT-DETR algorithm, and generating a prediction track of the dynamic obstacle, collision detection is conducted on a preset grabbing path of the movable mechanical arm, an obstacle avoidance track switching instruction is generated by combining the current time point of the mechanical arm with the predicted collision time point of the dynamic obstacle, trajectory tracking is conducted on the obstacle avoidance track of the mechanical arm, a model reference self-adaptive control algorithm is adopted, a reference model is established, and obstacle avoidance is achieved. According to the method, mechanical arm vibration caused by obstacle avoidance track switching is effectively restrained, interference of vibration on grabbing stability is reduced, and the operation precision and reliability of the mechanical arm in a dynamic obstacle avoidance scene are remarkably improved.

This disclosure sets forth a robotic end effector for acquiring and managing an article, such as an item of luggage. The robotic end effector can include an extendable arm comprising a first support member, a capture device comprising a guide member having a plurality of apertures formed therein with a rod slideably supported in each aperture of the guide member. The capture device can further include a biasing member associated with one or more rods and being configured to bias the one or more rods in a first direction relative to the guide member. The article interface system can include an actuatable article engagement device. The actuatable article engagement device can itself include an article interface surface. The actuatable article engagement device can be operated to interface with an article to facilitate movement of the article toward the capture device.

The invention belongs to the technical field of robot control, and provides a robot self-adaptive task planning and action adjusting method and system, and the method comprises the steps: responding to a task instruction, and calibrating the motion parameters of a mechanical arm of a robot; acquiring a state vector according to a set frequency, determining whether visual abnormality or motion abnormality exists or not according to a continuous change condition of the state vector, and generating an abnormality mark if the visual abnormality or motion abnormality exists; performing action correction in response to the abnormal mark or the task failure mark, performing cross-modal fusion on the current state vector and the semantic vector of the task instruction, generating a candidate action sequence based on the fused feature and task target, and considering the compatibility of the candidate action and the current environment, the residual step number of the action queue and the task failure mark. An optimal action is screened out, and then an action adjusting instruction is generated; and continuously obtaining the state vector and the action correction process until the robot completes the task instruction. The environment adaptability and the execution success rate of the robot in a complex scene can be improved.

The invention relates to the technical field of unmanned aerial vehicle control, in particular to an aerial work six-degree-of-freedom mechanical arm and a self-adaptive anti-interference control method and system.The self-adaptive anti-interference control method comprises the steps that a mechanical arm structure is manufactured through an arm body designed in a carbon fiber topological optimization mode and a joint shell provided with a flow guide groove; constructing a dynamic disturbance observer based on a DDPG algorithm, outputting a dynamic compensation amount through the dynamic disturbance observer, calculating a wind power disturbance value in combination with a disturbance compensation algorithm, and integrating the wind power disturbance value to a control law of the unmanned aerial vehicle; adjusting impedance parameters on line based on a TD3 algorithm; and generating a real-time obstacle avoidance path based on an optimized multi-target PPO path planning algorithm, and executing a path planning task of the corresponding real-time obstacle avoidance path. The unmanned aerial vehicle has the advantages that the wind disturbance resistance is remarkably enhanced, the load sudden change stability is remarkably optimized, the task energy consumption is remarkably reduced, the narrow space adaptability is remarkably improved, and the light weight is achieved.

A snake-arm robot assembly may include a first link and a second link with a joint formed therebetween including first and second contact portions in rolling contact with one another to allow the first and second links to pivot with respect to one another. The first and second contact portions are configured to contact one another at first and second contact points corresponding to a first orientation and third and fourth contact points corresponding to a second orientation. The joint may be configured such that a line of action of a net force acting on the joint is incident with a first reference line extending between the first and second contact points with the links in the first orientation, and the line of action is incident with a second reference line extending between the third and fourth contact points when the links are in the second orientation.

The invention discloses a humanoid robot. The humanoid robot comprises a robot main body, the mechanical arm comprises a connecting support and an arm body, the connecting support is movably installed on the robot body, and the arm body is arranged on the connecting support; the mechanical arm driving structure is arranged on the robot body, connected with the connecting support and used for driving the connecting support to move so as to drive the arm body to move. According to the humanoid robot disclosed by the embodiment of the invention, the mechanical arm comprising the connecting bracket is arranged, and the connecting bracket is movably connected with the robot main body, so that the mechanical arm can move relative to the robot main body through the connecting bracket, the movable freedom degree of the mechanical arm can be increased, and the movement flexibility of the mechanical arm can be improved; and the movable joints of the mechanical arm can be uniformly distributed, so that the shape of the mechanical arm can be more coordinated, and the anthropomorphic effect of the humanoid robot can be improved.

The invention discloses a mechanical arm and a humanoid robot, and relates to the technical field of robots. The mechanical arm comprises a plurality of structural parts which are sequentially connected, the adjacent structural parts rotate relatively through driving parts, and the rotating axes of the adjacent driving parts are perpendicular to each other. The driving part comprises a horizontal driving part and a vertical driving part, the rotating axis of the horizontal driving part is perpendicular to the extending direction of the mechanical arm, and the rotating axis of the vertical driving part is parallel to the extending direction of the mechanical arm. An output shaft of the horizontal driving part drives the adjacent structural parts to rotate through the single cantilever, and a first wire harness fixing structure is arranged at the tail end of the horizontal driving part. An output shaft of the vertical driving piece is connected with a first crossed roller bearing through a connecting inner shaft sleeve, and the first crossed roller bearing is installed on an outer ring of the connecting inner shaft sleeve. After being led out from the first wire harness fixing structure, the wire harness extends along the side wall of the vertical driving piece, penetrates through the inner ring connected with the inner shaft sleeve and then extends to the first wire harness fixing structure of the next horizontal driving piece.

The invention discloses a wheelchair humanoid robot controlled by humanoid mechanical arms. The wheelchair humanoid robot comprises a chassis, a robot trunk, the two mechanical arms and a control calculation unit. The chassis comprises four independent driving wheels; a wheelchair seat is arranged on the robot trunk; the mechanical arm is a seven-axis mechanical arm and comprises three tail end joints and an operation tail end. The control calculation unit is provided with an operation control moving mode; in the operation control movement mode, the control calculation unit senses the operation intention of a user on the operation tail end by collecting data of the joint position sensor and the force feedback sensor, generates a movement command of the chassis through mapping of the operation intention, and converts the movement command into a wheel speed control command of the independent driving wheels. The tail end joint of the mechanical arm serves as a sensing and input device, the independent driving wheel chassis serves as an execution device, and the whole system has the advantages of being high in freedom degree, natural in interaction, safe, smooth and high in space adaptability through cooperation of the two devices.

The invention relates to the technical field of unmanned aerial vehicles and robots, in particular to a lightweight quad-rotor vector unmanned aerial vehicle-mechanical arm system, which realizes effective identification and processing of complex disturbance through cooperative work of a plurality of modules, and improves the working efficiency. The system comprises a sensing module, a state estimation module, a self-adaptive time delay parameter optimization module, a multi-level disturbance decoupling and estimation module, a sliding mode boundary layer self-adaptive regulation and control module, a signal peak value real-time detection and feed-forward compensation module, a multi-module collaborative dynamic fusion module and the like. The modules jointly improve the attitude stability and the tail end positioning precision of the system during execution of fine operation tasks, and the attitude stability and the tail end positioning precision are improved by 70% and 65% respectively. According to the method, through the mode of combining self-adaptive time delay parameter optimization and multi-level disturbance decoupling, the recognition and processing capacity of the system on complex disturbance caused by movement of the mechanical arm is greatly improved, and the system is more stable and accurate when executing a fine operation task.

The multifunctional clamping jaw is installed at the tail end of the mechanical arm through a rotary connecting plate and comprises a clamping jaw body, a first clamping jaw body and a second clamping jaw body, and the clamping jaw body is fixedly connected with the rotary connecting plate and can rotate in the Z-axis direction; the first clamping jaw is arranged on the clamping jaw body and is used for clamping a kit; the second clamping jaw is arranged on the clamping jaw body and used for clamping a magnetic bar sleeve. The utility model provides the multifunctional clamping jaw which is designed according to the magnetic bead purification requirement and can be used for compatibly clamping a kit and a magnetic bar sleeve material, the automatic carrying of the magnetic bead purification material can be realized by mounting the multifunctional clamping jaw at the tail end of a mechanical arm, the automatic carrying and placing of the kit and the magnetic bar sleeve required by the magnetic bead purification can be realized by the multifunctional clamping jaw, and the synchronous carrying can be realized; and meanwhile, materials of multiple specifications are compatible with the same set of robot, and the cost is greatly saved.

The invention discloses a deformation and bearing integrated modular rope-driven flexible mechanical arm and a self-sensing method thereof.The flexible mechanical arm comprises a driving mechanism and a variable-rigidity flexible mechanical arm body, the variable-rigidity flexible mechanical arm body comprises a rope, a corrugated pipe and elastic units, and the multiple elastic units are filled in an inner cavity of the corrugated pipe; the corrugated pipe is provided with a rope guide hole extending in the axial direction of the corrugated pipe, one end of the rope is fixedly connected with the power output end of the driving mechanism, the other end of the rope penetrates through the rope guide hole and is fixedly connected with the corrugated pipe, and when the driving mechanism works, the rope can be driven to move, and then the mechanical arm is pulled to deform. The flexibility of the mechanical arm is improved through fusion of active deformation and a bearing function, additional rigid structure supporting is not needed, and the overall design is simplified; and the bearing capacity and rigidity are adaptively improved through blocking of the elastic units, and the complexity of the driving system is reduced. Meanwhile, the mechanical arm is provided with a self-sensing system, the state of the mechanical arm can be monitored in real time, and the control precision is improved.

The invention discloses a control method and system of a mechanical arm, electronic equipment, a medium and a program product. The control method comprises the steps that the target pose of an end effector under world coordinates and forward kinematics information of the mechanical arm are obtained; according to the first joint angle of the mechanical arm, the forward kinematics information and the first current pose of the end effector, the second current pose of the end effector under the world coordinates is determined; determining a loss function, wherein the loss function comprises a first loss function corresponding to the difference between the target pose and the second current pose; and based on the loss function, the first joint angle is updated through a gradient descent algorithm to control the mechanical arm to move. The mechanical arm is controlled to move without collecting training data in advance, and the calculation cost is reduced.

The invention discloses an unmanned aerial vehicle high-precision spacer dismounting and mounting control method based on tactile feedback, and belongs to the technical field of intelligent operation and maintenance of high-voltage power transmission and distribution lines. According to the method, a multi-mode tactile sensor array and a self-adaptive force control mechanical arm are carried through an unmanned aerial vehicle, three-dimensional force, torque and surface deformation data when the mechanical arm makes contact with a spacer are collected in real time, the action of the mechanical arm is adjusted in combination with a dynamic impedance control algorithm, and high-precision disassembly and assembly operation is achieved. According to the method, the problems of large positioning error and poor operation stability caused by lack of real-time force feedback of a traditional unmanned aerial vehicle disassembling and assembling method are solved, and the operation precision and safety in a complex environment are remarkably improved.