450 results about "Kinematic controller" patented technology

The invention relates to the technical field of large language models, and discloses a voice data interaction feedback control processing method based on a large language model. The method comprises the following steps: acquiring an industrial voice instruction through an AMR main controller, and obtaining a standardized vector through industrial lexicon matching and intention classification; inputting an industrial large language model for reasoning processing, and generating an AMR execution scheme; carrying out distributed coordination and task allocation on the AMR cluster to form a control instruction sequence; and the motion controller executes monitoring, processes exceptions and outputs a feedback strategy. Accurate classification and semantic understanding of complex industrial instructions are achieved, the processing capacity of professional knowledge in the industrial field is improved, and meanwhile high-precision real-time state monitoring is achieved.

The invention discloses a method and a device for dynamically adjusting a focus in laser flight processing. The method comprises the following steps of: 1, acquiring a data stream; 2, according to a laser type matching recognition algorithm, recognizing the data flow to obtain a preliminary result, and filtering to obtain a current position; 3, calculating the deviation between the current position and the reference, judging whether the deviation reaches a preset threshold value or not, and if yes, recording the deviation as a compensation value; step 4, acquiring focus depth and power; the focus depth and the power are optimized according to the compensation value; 5, processing the focus depth and optimizing the power by adopting a track interpolation method to obtain an optimized path; 6, the optimized path is sent to a motion controller, and a correction position is output; 7, judging whether the deviation value between the correction position and the optimal plane is within a threshold range or not, and if yes, completing machining according to the correction position; and if not, the third step to the seventh step are executed again till machining is completed. According to the method, the problem of unstable processing quality caused by focus offset in laser processing can be effectively solved.

The invention discloses a three-dimensional cutting dynamic parameter adjusting system and method based on deep learning, and relates to the technical field of application of three-dimensional five-axis fiber laser cutting machines in the automobile manufacturing industry, and the three-dimensional cutting dynamic parameter adjusting system comprises a multi-mode sensor cluster, an edge calculation unit, a closed-loop control module and an AI model library, the multi-mode sensor cluster collects cutting data, the edge calculation unit receives the multi-mode sensor data and outputs dynamic adjustment parameters, and the closed-loop control module transmits the dynamic parameters to the laser generator and the five-axis motion controller through a high-speed communication bus to form a'sensing-decision-execution 'closed loop. The cutting state and risk are sensed in real time by designing a multi-mode sensor for collaborative decision, the problems that manual experience depends on and dynamic response lags are solved, the reject ratio is reduced, and the response speed is increased.

The invention belongs to the technical field of three-coordinate measurement, and particularly discloses a space parameter measuring system based on a three-coordinate measuring machine, which comprises a measuring platform, a supporting arm, an X-axis driving module, a Y-axis driving module, a Z-axis driving module and a measuring assembly, and is characterized in that a motion controller is arranged at the top of a control box to control each driving module to move. A data acquisition module, a dynamic compensation module, a parameter fusion module and an execution control module are integrated in the box, the data acquisition module acquires multi-source and environmental parameters, the dynamic compensation module outputs a compensation instruction according to the parameters, the parameter fusion module outputs fusion point cloud coordinates, and the execution control module sends the instruction to a motion controller to drive three axes to move according to a preset path. According to the invention, a multi-module collaborative architecture is constructed, contact and non-contact measurement modes are combined, the problem of precision attenuation of a traditional three-coordinate measuring machine is solved, error dynamic correction is realized, and the measurement adaptability to high-precision workpieces is improved.

The embodiment of the invention provides a dexterous hand control method and device, an intelligent agent and a storage medium, and the method comprises the steps: obtaining sensor data, preprocessing the sensor data, obtaining input information which comprises environment information and state information of a dexterous hand, inputting the input information into a cerebellum model, and obtaining a corresponding control instruction, the cerebellum model comprises a trajectory planning model and a motion controller, the trajectory planning model is used for outputting a corresponding trajectory planning result according to the input information, and the motion controller is used for converting the trajectory planning result into a corresponding control instruction; the motion controller is obtained by combining a cerebellum model neural network and a whole body dynamic model based on a model predictive control algorithm, and performs driving control on an execution mechanism module of the dexterous hand according to a control instruction. According to the dexterous hand control method provided by the embodiment of the invention, the control flexibility and accuracy can be improved.

The invention discloses a three-dimensional jitter compensation method and device for laser cutting and a storage medium, and relates to the technical field of lasers, and the method comprises the steps that fast Fourier transform is carried out based on a vibration signal of a to-be-machined thin plate in the Z-axis direction, and a frequency spectrum feature is obtained; according to the frequency spectrum characteristics, combining a preset jitter filtering parameter set to carry out frequency domain filtering processing, and generating a filtering signal; reconstructing the filtering signal into a time domain compensation amount through inverse Fourier transform; based on the time domain compensation quantity, performing weighted fusion by combining the cutting acceleration and the cutting displacement deviation in the current cutting direction, and generating a three-dimensional compensation vector; and superposing the three-dimensional compensation vector to an original cutting path coordinate through a motion controller so as to correct the following state of the cutting head. The technical problem that the thin plate shakes due to nonlinear cutting force caused by interaction between high-speed movement of the cutting head and laser and materials is solved, and the stability of the thin plate during laser cutting is improved.

The invention discloses a radial forging machine chuck rotation oscillation braking electro-hydraulic control system and method, and the control system comprises a position detection encoder installed on a hammer head of a forging main machine, a hydraulic servo motion controller, a high-frequency servo valve, an oscillation braking oil cylinder with the same area as an A cavity and a B cavity, and an oscillation braking device with a worm gear and a worm. The pressure sensor and the displacement sensor are integrated on the oil cylinder to form a closed-loop control loop; the control method comprises the following steps: activating an oscillation braking function and collecting hammer phase, oil cylinder pressure and displacement signals in real time; a sine control signal synchronous with the forging frequency is generated based on the brake phase of 270-360 degrees; a brake oil cylinder is driven to push the worm to axially move, and the rotating speed of the chuck is modulated through the helix angle characteristic; and the amplitude is dynamically adjusted through a displacement-pressure feedback signal, and 25MPa overrun protection is executed. The purposes of reducing the brake response delay rate, the forge piece distortion rate and the equipment impact load are achieved, and 90-620 times / min wide-frequency-domain forging is supported.

The embodiment of the invention provides a dexterous hand control method and device, an intelligent agent and a storage medium, and the method comprises the steps: obtaining sensor data, preprocessing the sensor data, obtaining input information which comprises environment information and state information of a dexterous hand, inputting the input information into a cerebellum model, and obtaining a corresponding control instruction, the cerebellum model comprises a trajectory planning model and a motion controller, the trajectory planning model is used for outputting a corresponding trajectory planning result according to the input information, and the motion controller is used for converting the trajectory planning result into a corresponding control instruction; the motion controller is obtained by combining a cerebellum model neural network and a whole body dynamic model based on a model predictive control algorithm, and performs driving control on an execution mechanism module of the dexterous hand according to a control instruction. According to the dexterous hand control method provided by the embodiment of the invention, the control flexibility and accuracy can be improved.

An adaptive variable-structure duct robot motion control method based on environmental sensing. A duct robot is a dual-swing-arm tracked mechanism, and onboard sensing devices include a depth camera, an IMU, a wheel speed sensor and a TOF module. The method comprises: a depth camera capturing an image of the interior of a duct to perform scenario recognition, segmenting planar and curved surfaces in the image on the basis of scenario recognition results, and extracting edge lines of the duct; using the edge lines to calculate the width of a straight duct, the curvature of a curved duct, the angle of a slope and the height of a step, in order to determine the passability of a robot; designing a path planner and a swing arm planner to generate a reference trajectory and a swing arm angle sequence of the robot, performing smoothing processing, and inputting the smoothed reference trajectory and swing arm angle sequence into an MPC motion controller; using data from the depth camera, an IMU and a wheel speed sensor to estimate the position and state of the robot by means of an ESKF algorithm, and inputting estimation results and a collision warning signal from a TOF module into the MPC motion controller in real time; and finally, outputting control signals for a locomotion electric motor and a swing arm electric motor. Thus, the adaptive variable-structure and autonomous motion of a robot in different scenarios is realized.

The invention provides switchable test equipment, a switchable test method, electronic equipment, a storage medium and a program product, and belongs to the technical field of visual equipment. The switchable test equipment comprises a simulated eyeball, a motion controller, a first driving assembly, a second driving assembly and at least one test device installed on the simulated eyeball. The motion controller is connected with the first motion driving assembly and the second driving assembly, and the first motion driving assembly and the second driving assembly are connected with the simulated eyeball; the motion controller is used for controlling the first motion driving assembly and the second driving assembly according to test requirements so as to drive the simulated eyeball and the test device to rotate synchronously until the target test device is switched to a test position; wherein the target test device is one of the at least one test device. According to the technical scheme, the test device can be rotated to the test position under the condition that eyeball rotation is simulated, and integration of test functions on one device is achieved.

A motion control method for an adaptive self-reconfigurable pipeline robot based on environmental perception includes: acquiring internal images of the pipeline for scene recognition, segmenting planar surfaces and curved surfaces in the images according to recognition results, and extracting boundary lines of the pipeline; calculating a straight-pipe width, a bent-pipe curvature, a slope angle, and a step height to analyze passability of the robot; designing a path planner and a swing-arm planner to generate a reference trajectory and a swing-arm angle sequence of the robot, performing smoothing, and inputting the reference trajectory and the swing-arm angle sequence into a model predictive control (MPC) motion controller; estimating a position and state of the robot through an Error State Kalman Filter (ESKF) algorithm, and inputting estimation results and collision warning signals into the MPC motion controller; and finally outputting a signal for control of a motor and a swing-arm motor.

An unmanned surface vehicle path manipulation control system and method based on a digital twin and a parallel controller. The system comprises: a real unmanned surface vehicle system, a real controller for generating a control input to control the real unmanned surface vehicle system, an unmanned surface vehicle motion digital twin model for generating location information of a virtual unmanned surface vehicle, a kinematics controller for generating an unmanned surface vehicle guidance signal, a dynamics controller for generating a control input on the basis of the guidance signal and speed information of the virtual unmanned surface vehicle at the current moment so as to control a manual system composed of the unmanned surface vehicle motion digital twin model, and a path parameter updating law providing an unmanned surface vehicle path parameter; a parallel controller integrates the constructed virtual unmanned surface vehicle system in an information space into the environment, and drives the virtual unmanned surface vehicle system and the real unmanned surface vehicle system at the same time, thereby realizing mutual mapping and virtual-real interaction between the two systems.

The invention discloses a crane operation parameter self-learning optimization control system oriented to complex working conditions, which is characterized in that a multi-dimensional physical quantity signal is processed through a hierarchical mixed data fusion module, and a working condition feature vector is generated by using a lightweight mode recognition network; the working condition identification and risk assessment module outputs a working condition type identifier and calculates a dynamic safe operation boundary; a physical model enhanced reinforcement learning decision engine is built in the parameter self-learning optimization module, a parameter adjustment instruction is generated through an actor network, and evaluation optimization is carried out through a reviewer network; the optimized parameter adjusting instruction is issued to a self-adaptive fuzzy motion controller to drive an execution mechanism; and after execution, collecting system response data as an empirical sample to be stored and used for periodically updating network parameters. Accurate perception and safety evaluation of complex working conditions are achieved, control parameters can be autonomously optimized through fusion learning and a physical model, and the self-adaptive control capacity, stability and safety of the crane in a changeable environment are improved.

The present disclosure relates to a work space force / acceleration disturbance observer and a robot including the same. The work space force / acceleration disturbance observer is connected to an impedance-based motion controller in a work space. The work space force / acceleration disturbance acquires a disturbance estimate value in consideration of an interactive force and an acceleration applied to an end effector of a robot. The disturbance estimate value is expressed in Equation 1: {circumflex over (D)}=Q(−F′c+Mo{umlaut over (x)}+Fext) wherein {circumflex over (D)} is the disturbance estimate value, “Q” is a “Q” filter, F′c is a control input force, {circumflex over (M)}o is a mass matrix estimate value, {umlaut over (x)} is the acceleration, and Fext is the interactive force.

The invention relates to a control optimization method for a bionic underwater robot, which relates to the field of robot control, and comprises the following steps: collecting neighborhood space image information; species identification is conducted on the neighborhood space image information, a species identification set is obtained, and when sensitive species exist, underwater temperature information and underwater pressure information are collected; according to the underwater temperature information and the underwater pressure information, the escape speed of the sensitive species is optimized, and an escape speed threshold value is obtained; and initializing a motion controller at a speed greater than or equal to an escape speed threshold value by taking a direction far away from the sensitive species as an escape direction, and controlling the bionic underwater robot to perform interference avoidance motion. By identifying the sensitive species and optimizing the escape speed threshold according to the underwater environment parameters, the bionic underwater robot is controlled to avoid in the direction away from the sensitive species, and the technical effects that the task execution efficiency and adaptability of the bionic underwater robot are improved while the underwater sensitive species and the ecological environment are protected are achieved.

The invention relates to a controller, a method and a system for energy source selection. Emission management is provided. A controller for vehicle energy source selection is configured to receive an indication of an emission target for a vehicle. The vehicle includes one or more energy conversion devices. The one or more energy conversion devices are configured to generate mechanical motion from the first energy source and the second energy source. The controller is configured to receive an indication of a first emission output corresponding to the first energy source. The controller is configured to receive a second emission output corresponding to the second energy source. The controller is configured to select a first consumption rate for the first energy source and a second consumption rate for the second energy source based on the emission target, the first emission output, and the second emission output.

The invention provides an intelligent motion control system based on multi-level expansion and multi-type motor compatibility, and aims to solve the technical problems that an existing motion control system is poor in expansibility and weak in motor type compatibility. The system comprises a main controller, a configuration memory and at least one detachable motor control module, the motor control module comprises a motion controller and a motor driver. The core of the method is that when a main controller is initialized, motor type parameters preset for all motor shafts are read from a configuration memory, and differential configuration is executed according to the motor type parameters: when a motor is of a first preset type, a motion controller and a motor driver are cooperatively configured; and when the motor is of the second preset type, only the motion controller is configured to output pulse / direction signals, and the motor driver is disabled. Through software and hardware decoupling, the number of shafts can be flexibly increased or decreased without changing hardware, various motors and encoders are compatible, the expansibility and deployment efficiency of the system are remarkably improved, and the development and maintenance cost is reduced.

The invention discloses a robust trajectory tracking control method for a wheeled mobile robot in finite time, belongs to the technical field of robots, and aims to solve the problems that the wheeled mobile robot is inevitably influenced by model uncertainty and external disturbance in a task execution process due to a complex working environment, and the robot is difficult to track. The design difficulty of a wheeled mobile robot control system is greatly increased due to the factors. The method comprises the following steps: 1, establishing kinematics and dynamics models of a wheeled mobile robot; the invention discloses a wheeled mobile robot finite time robust trajectory tracking control method based on a nonlinear extended state observer, and the method consists of a kinematics controller and a dynamics controller, the kinematics controller can guarantee that the position and attitude tracking error of a wheeled mobile robot is gradually converged to zero, and the kinematics controller can guarantee that the position and attitude tracking error of the wheeled mobile robot is gradually converged to zero. The dynamic controller can ensure that the speed and angular speed tracking errors of the wheeled mobile robot converge to zero within finite time.

A multimodal wheelchair configured to be securely mounted to an aircraft is disclosed. The multimodal wheelchair may include: a first section, including: a processing system contained within a housing of the first section; a movement controller component positioned on a portion of the first section that is connected to the processing system; a plurality of wheels that are controllable by the movement controller; and a set of tracks recessed within a first side of the first section; and a second section, including: a seat portion located on a first side of the second section, the seat portion having an integrated harness; and a connection component, coupled to a second side of the second section, that attaches the second section to the first section via coupling with the set of tracks of the first section. Other aspects are described and claimed.

The invention relates to a self-walking type spot welding robot and a control method thereof, the structure comprises a welding robot main body, a walking device and a control system, the welding robot main body adopts a six-degree-of-freedom industrial robot, and an end effector is a welding gun; the walking device comprises a chassis and crawler wheels arranged on the two sides of the chassis, each crawler wheel comprises a crawler, a guide wheel, a driving wheel and a planet wheel, and the guide wheels, the driving wheels and the planet wheels are arranged in the crawler in a non-equilateral triangle mode. Magnetic sheets which are sequentially arranged in the walking direction are arranged in the crawler belt, and the crawler belt wheels are controlled to walk on the steel structure by sequentially electrifying the magnetic sheets; the control system comprises a demonstrator, and a welding seam tracking system, a welding controller and a motion controller which are in signal connection with the demonstrator; the welding seam tracking system adopts a visual sensor to track a welding seam; the welding controller controls the welding gun to perform spot welding; the motion controller controls on-off of the magnetic sheet. Free walking of the welding robot on the steel structure can be achieved, and remote control is achieved.

The utility model relates to the field of industrial production, in particular to a control system of an extensible IO module. The utility model discloses a control system capable of expanding IO modules, which comprises a motion controller and a plurality of IO modules, and the motion controller and the IO modules are respectively provided with an LVDS (Low Voltage Differential Signaling) interface; the motion controller is connected with the IO module through the LVDS interface; the IO modules are connected through the LVDS interfaces, flexible expansion of the IO modules is achieved, the flexibility of the topological structure of the control system is improved, connection is established through the LVDS interfaces, the communication rate of the motion controller and the IO modules is improved, and therefore the refresh rate of the IO modules is improved.

The invention relates to a control system and method for a seeding and fertilizing integrated seeder, and belongs to the technical field of agricultural machineries, the control system comprises a driving assembly which comprises a seeding motor driver, a seeding motor, a fertilizing motor driver and a fertilizing motor; the seeding motor driver and the seeding motor are mounted on the seeding disc; the fertilization motor driver and the fertilization motor are mounted on the fertilization disc; a sensing assembly; the controller is mounted on the seeder rack; and the Internet of Things cloud platform realizes cooperative control of fertilization operation and seeding operation. The control method comprises the steps that the vehicle-mounted power supply supplies power to the motion controller, and the motion controller determines a speed value; the motion controller adjusts the rotating speeds of the fertilizing motor and the seeding motor according to the speed values, and the two motors are cooperatively controlled; the motion controller sends the data to the Internet of Things cloud platform; the seeder completes seeding. According to the invention, the seeder has intelligent decision-making and remote monitoring capabilities, the seeding precision and efficiency of the seeder in the whole process are improved, and the intelligent degree is improved.

The invention relates to an automatic driving simulation evaluation method and device, and belongs to the technical field of intelligent driving, and the method comprises the steps: constructing a digital twin 3D map; a vehicle simulation model is loaded in the digital twin 3D map, an automatic driving module used for loading an automatic driving algorithm is constructed, and an automatic driving evaluation unit based on traffic regulations is constructed; an automatic driving algorithm to be tested is loaded, the automatic driving module generates a control instruction based on environment data collected by the environment sensing assembly and issues the control instruction to the vehicle motion controller, and the vehicle motion controller controls the vehicle motion model to operate in the digital twin 3D map; the automatic driving evaluation unit collects controlled motion state parameters of the vehicle motion model and intervention degree parameters of the manual controller, and evaluates an automatic driving algorithm. According to the method, the defect that evaluation cannot be carried out according to the traffic regulations in the automatic driving algorithm evaluation process is effectively overcome, meanwhile, advantages and disadvantages of different algorithms can be compared, and the test cost is effectively reduced.

The invention discloses an intelligent vehicle elastic planning and control method based on large language model guidance under network attack, and belongs to the field of vehicle information safety and control, and the method specifically comprises the steps: firstly, building an intelligent vehicle auxiliary decision making and control system, and installing the system on a to-be-detected vehicle; the automatic driving decision-making unit generates an expected driving intention of the current to-be-detected period; the path planning unit generates a corresponding reference trajectory sequence. A vehicle reachable set estimator calculates a maximum allowable motion reachable range. The scene text editor completes scene description of the driving environment in combination with the perception information and converts the scene description into a structured text; the large language model performs comprehensive judgment on an expected driving intention and a planned reference trajectory sequence based on a maximum allowable motion reachable range and structured text description, and gives a final auxiliary decision variable. And based on the reachable set estimation value, constructing a vehicle motion controller based on data driving, and obtaining a control instruction to complete execution. According to the invention, the adaptability and robustness of the real vehicle operation environment are improved.

The present disclosure provides a surgical instrument including an end effector, a drive member movable to effectuate a motion in said end effector, a motor operable to move the drive member to effectuate the motion in the end effector and a bailout assembly operable to perform a mechanical bailout of the surgical instrument in response to a bailout error. The bailout assembly includes a bailout door, a bailout handle accessible through the bailout door. The bailout handle is operable to move the drive member to effectuate a bailout motion in the end effector. A controller includes a memory and a processor coupled to the memory. The processor is configured to detect the bailout error. The processor is programed to stop the motor in response to the detection of the bailout error.

The invention relates to a motor motion control method, a motor motion controller and a storage medium. The method comprises the following steps: acquiring a selected target working mode; the target working mode comprises a speed mode or a displacement mode; acquiring a selected target speed regulation rule; the target speed regulation rule comprises a trapezoidal speed regulation rule and an S-shaped speed regulation rule; acquiring a motion parameter value of the motor; the motion parameter values comprise an initial speed, an acceleration parameter value, a target speed, a deceleration parameter value and a stop speed; and performing motion control on the motor based on the target speed regulation rule and the motion parameter value in the target working mode. By adopting the method, the configuration parameters are simple, the speed regulation algorithm is selectable, and various application scenes can be met.

The invention discloses a mechanical arm tail end dual-light fusion detection data management system and method, and belongs to the technical field of industrial automatic detection. A visible light camera and an infrared camera are integrated at the tail end of a mechanical arm, discrete monitoring points are set according to the motion path of the mechanical arm, and the mechanical arm is based on pose data output by a motion controller; when moving to a preset monitoring point, synchronously triggering dual-light image acquisition, and carrying out space-time alignment on the acquired data; performing semantic segmentation processing on the visible light image, screening out a cable image from the visible light image to construct a cable identification model, obtaining boundary coordinates of a cable, performing feature matching with an infrared image, mapping a cable region to the infrared image, extracting a corresponding temperature data matrix, and calculating a maximum temperature difference value of the surface of the cable; judging an abnormal region in combination with a preset temperature gradient threshold value; and according to the anomaly detection result, the mechanical arm is triggered to dynamically adjust the detection path, the abnormal point is focused for reinspection, and anomaly early warning prompt is carried out according to the reinspection result.

The invention relates to the technical field of robot obstacle avoidance, in particular to a wafer transfer robot-oriented multi-modal real-time obstacle avoidance method and system, and the method comprises the steps: collecting environment data in real time through a multi-modal data collection device, and obtaining multi-modal environment data; performing space-time alignment on the multi-modal environment data, and establishing a workspace map; collecting operation data of the dynamic obstacle, and inputting the operation data into the constructed trajectory prediction model for trajectory prediction to obtain a trajectory prediction result; performing path planning on the wafer transmission robot to generate an optimal obstacle avoidance path; and verifying the optimal obstacle avoidance path, and outputting the optimal obstacle avoidance path to a motion controller for execution. According to the wafer carrying robot, the problem that the obstacle avoidance capability of the wafer carrying robot is insufficient in a dynamic environment is effectively solved, damage caused by collision in the wafer carrying process is effectively avoided, and the operation accuracy and safety of the wafer carrying robot in a complex production environment are improved.

The invention relates to the field of rotary cutter control. The invention relates to a rotary cutter, in particular to a double-machine-head precise rotary cutter and a control system. According to the double-machine-head precise rotary cutter and the control system, the control system adopts the mode of motion controller and bus communication, the precision and speed of the system are improved, and the single-machine-head precise rotary cutter can be compatible with high-speed and high-precision operation.