309 results about "Robotic control" patented technology

The embodiment of the invention provides an optimization method and system for a manipulator control system, and the method comprises the steps: firstly obtaining an operation data set containing a control instruction sequence and corresponding motion state data in a historical operation period of a manipulator, carrying out the feature extraction of the operation data set, and obtaining an associated motion feature set; calling a pre-trained control strategy optimization model to analyze and generate strategy adjustment parameters, adaptively updating the control instruction sequence of the current operation task according to the strategy adjustment parameters to obtain a target control instruction sequence, and finally inputting the target control instruction sequence into a control system to execute operation. And real-time motion state data is collected for subsequent iterative optimization, so that the performance of the manipulator control system can be continuously improved, and the operation precision and efficiency are improved.

The invention provides an industrial robot multi-station intelligent sorting and stacking method based on visual guidance, which relates to the technical field of robot control, and comprises the following steps: determining a target station by acquiring multi-station real-time state information, calculating an optimal grabbing time window by using a graph neural network state predictor, and obtaining a target grabbing time window; and the placement strategy is dynamically adjusted based on the visual image and the force sensing data in the article stacking process. According to the multi-station intelligent stacking system, the sorting efficiency in a multi-station scene can be improved, the grabbing precision of dynamic objects is enhanced, and stable and reliable intelligent stacking operation is achieved.

The invention discloses a robot control system and method based on vision and force sense fusion and a robot, and relates to the technical field of robots. The robot control system based on vision and force sense fusion and the control method thereof analyze visual features in real time through an artificial intelligence processing unit to predict mechanical parameters; and the self-adaptive impedance control unit is combined to dynamically fuse a position instruction and force sense feedback, so that precise adaptation of target object characteristics and compliant regulation and control of an interaction process are realized, real-time sensing and dynamic adjustment capabilities are achieved, assembly damage caused by mechanical mismatching is effectively avoided, and the reliability and efficiency of precise assembly are improved.

The present disclosure provides a method for generating annotation data for robotic training using a hierarchical transformer-based model with multiple layers. The transformer-based model includes Alpha models generating low-level control outputs and Beta models generating high-level control outputs. The method receives multimodal input data comprising visual sensor data and natural language instructions, processes this data through the hierarchical transformer-based model to generate annotations at different abstraction levels, wherein Beta models create semantic annotations describing task objectives and Alpha models generate motor command annotations specifying robotic actions, and stores these annotations with the input data to create annotated training data for robotic control systems.

The invention discloses a continuous feeding manipulator control method which comprises the following steps: constructing a finite element simulation model aiming at each joint of a mechanical arm and a tail end execution structure, acquiring inherent frequency distribution data of the structure under different load states and posture working conditions, and generating a frequency sensitive area parameter set based on the data. The method has the advantages that the track segment exciting the resonance risk can be recognized before the path is executed, the inherent frequency of the structure is effectively avoided through frequency matching and path reconstruction, the dynamic adaptability is improved, and pose offset and structural fatigue caused by resonance are prevented. Meanwhile, the system has the self-adaptive closed-loop optimization capacity, disturbance injection testing and periodic response verification are combined, the structure state can be monitored in real time, path re-optimization can be triggered, the stability and precision of the mechanical arm in continuous high-frequency operation are ensured, and the overall reliability and intelligent level of a production line are improved.

The invention discloses a fault-tolerant reconstruction method for sensing faults of a spatial dexterous hand, and relates to the field of robot control. In order to solve the defects that in the prior art, a dexterous hand on-orbit sensor is weak in fault-tolerant capability, insufficient in model generalization capability and incapable of being adaptive to complex space environment changes, the technical scheme provided by the invention comprises the following steps: constructing a conditional variation auto-encoder model, inputting a joint position and a rope length sequence, and constructing a model; time sequence features are extracted, and a reconstructed joint position mean value and a prediction variance are output; the reconstructed joint position mean value is compared with actual joint data, a dynamic confidence interval is generated, and whether the data breaks down or not is judged; for the data judged to be normal, information entropy is calculated based on the prediction variance, and data samples with the information entropy exceeding a set threshold value are screened and written into a dynamic buffer area; and when the buffer data is fully loaded, incremental learning is triggered, and model parameters are updated by utilizing the buffer data. The method is suitable for real-time detection and fault-tolerant reconstruction of sensor faults in the long-term on-orbit operation process of the space dexterous hand.

The invention discloses a sorting manipulator intelligent control system based on big data, and the system comprises a multi-source data collection module which is used for synchronously collecting the real-time operation parameters of a sorting manipulator, the multi-modal feature data of a to-be-sorted object, and the dynamic environment parameters; the cross-modal fusion module is used for performing space-time alignment on the multi-modal feature data through a dynamic weighting algorithm; the double-domain cooperative training module is used for constructing a mapping relation between a virtual simulation domain and a physical entity domain, migrating initial model parameters trained by the virtual domain to the entity domain based on transfer learning, minimizing double-domain data distribution difference through a domain adaptation loss function, and generating an intelligent decision model adaptive to an entity scene; and the adaptive control module is used for generating a real-time control sequence through a model prediction control algorithm according to the sorting path planning result output by the intelligent decision model. According to the invention, more intelligent sorting manipulator control is realized.

The invention provides a robot control method, system, device and equipment and a medium, and the method comprises the steps: carrying out the visual analysis of a task scene where a robot is located based on a user instruction through a trained target visual language model, so as to obtain a task list needed for achieving the user instruction, the target visual language model is constructed based on a visual encoder, a visual language alignment layer and a large language model; based on the tasks in the task list, a control instruction needed by the robot for executing the task list is obtained; and through diffusion of the control instruction by the diffusion model, determining a mechanical motion track corresponding to the control instruction so as to perform operation control on the robot. The understanding ability of the robot for natural languages is improved, the adaptive capacity of the robot for task scenes is improved, the control precision of the robot is improved, the control flexibility of the robot is improved, and the achievement degree of the robot for user instructions is improved.

A variety of smart inference systems and robotic control devices are disclosed. A device networking system interconnects mobile devices, robotic devices, and others. A robotic controller secures and manipulates a controlled device user interface. A smart device system interprets data based on a plurality of models operating on a plurality of runtimes based on a plurality7 of capabilities. A smart payment processor system assigns payments accounts automatically as a function of a semantic matching between one or more inferred semantic identities. A robotic emulation device captures and analyzes a video signal from a target device and transmits manipulation signals emulating a peripheral input device. A system of carts are physically coupled in a charging configuration. A conveyor is configured to couple with another conveyor and having sensors to detect weight, size, location or other aspects of conveyed items, and implementing semantic analysis for management and augmentation.

The invention provides a system for controlling a manipulator in real time through hand electromyographic signals, which comprises a data acquisition unit, a terminal equipment unit and a tail end execution unit which are in communication connection through serial ports. The data acquisition unit comprises a data acquisition device and a signal acquisition module, and is configured to acquire a multi-channel electromyographic signal of a hand of a user in real time and perform signal conditioning and digitization so as to obtain a digital signal sequence representing a muscle activity intention of the user; the terminal equipment unit comprises a data preprocessing module, a model training module, a gesture recognition module and an instruction generation module; the tail end execution unit comprises a manipulator control unit which is in communication connection with the control output module and is configured to be used for receiving the manipulator control instruction and driving a manipulator to execute corresponding actions; in combination with a control method, the problems of insufficient real-time performance, poor hand action recognition precision and robustness, unstable control instruction, poor user adaptability and the like in the prior art are solved, and the man-machine interaction performance is improved.

The invention discloses an exoskeleton robot fixed time control method based on output constraint and disturbance observation, relates to the field of robot control, constructs a fixed time neural controller (FTNC), and ensures that a system is stable in fixed time by combining a universal obstacle Lyapunov function (UBLF) and a preset performance function (PPF), so as to improve the system stability. The convergence time is irrelevant to the initial state; meanwhile, a radial basis function neural network (RBFNN) and a nonlinear disturbance observer (NDO) are adopted to jointly compensate the uncertainty of the model and the man-machine interaction disturbance; by dynamically adjusting UBLF boundary conditions, joint angle errors are limited, and training safety is guaranteed. According to the method, a fixed time control theory is adopted, fixed time is combined with a preset performance function (PPF) and a universal barrier Lyapunov function (UBLF), and the output of the exoskeleton robot is strictly limited, so that the rapid convergence and transient performance requirements of an exoskeleton system are met at the same time.

The invention provides a method and device for preparing a composite board based on laser remelting and ultrasound, and relates to the technical field of composite board preparation. The method specifically comprises the steps that a molten pool is formed on a first metal plate to be compounded through laser remelting, a fiber laying manipulator control system is started, a fiber laying manipulator is made to lay carbon fibers into the molten pool according to a preset track of a laser remelting head, ultrasonic vibration is started at the same time, and a preformed composite plate is obtained; the molten pool on the preformed composite board is solidified through a temperature control system, ultrasonic vibration is started at the same time, and a metal / carbon fiber mechanical-metallurgical composite interface is formed; and a second metal plate to be compounded is compounded through roller pressure, and the metal / fiber / metal three-layer composite plate is obtained. The device comprises a laser remelting and fiber laying manipulator, a temperature control system and an ultrasonic vibration probe. According to the invention, laser remelting and ultrasonic vibration are combined to form a metal / carbon fiber mechanical-metallurgical composite interface, so that the interface strength of the composite board is enhanced, and the practicability of the composite board is improved.

A system may include a robotic control circuit configured to control one or more robotic functions of a robot. A system may include a plurality of sensors configured to collect data. A system may include a governance analysis circuit configured to analyze the data and select one or more governance frameworks based on the analyzed data. A system may include a governance model circuit configured to generate a model that applies the one or more governance frameworks to determine one or more governance actions, wherein the robotic control circuit is configured to control the one or more robotic functions in accordance with the one or more governance actions, wherein the robotic control circuit, the governance analysis circuit, and the governance model circuit are integrated on a single substrate.

Techniques are disclosed that enable the generation of predicted sequences of terminals using a generator model portion of a prediction model. Various implementations include controlling actuators of a robot based on the predicted sequences of terminals. Additional or alternative implementations include jointly training the generator model portion of the prediction model using a discriminator model portion of the prediction model using, for example, stochastic adversarial based sampling.

The invention belongs to the technical field of medical robots and minimally invasive surgery, and provides a robot control system and method for blue laser vaporization surgery of prostatic hyperplasia. Mapping the nuclear magnetic image volume data to a deformation field under an ultrasonic acquisition coordinate system, and deforming the preoperative nuclear magnetic image to an intra-operative ultrasonic space by using the deformation field to complete image registration; fusing the registered image with a stereoscopic vision system; the spatial depth of the surface of the target tissue is obtained from the endoscopic image so as to supplement navigation information; according to the utility model, the prostate deformation and probe posture change adaptive capacity in an operation is improved, the real-time visual closed-loop regulation and control capacity is improved, and the characteristics of small light spots, shallow heat diffusion, excellent hemostasis and the like of blue laser are combined, so that the vaporization and hemostasis precision in a tiny blood vessel dense area is ensured, and the problems of large tissue trauma and the like are avoided.

A catheter body control system is provided that includes a first and a second robotic module and a manipulator device. The first robotic module is configured to couple with a guide catheter manipulator device to control advancement or angulation of the guide catheter within a heart chamber or to couple with a first control dial of a handle of a TEE probe to control advancement or angulation of a flexible shaft of a TEE probe within an esophagus. The second robotic module is configured to couple with a device catheter angulator to alter an angle of a tip of the device catheter within a heart chamber during a procedure or to couple with a second control dial of a handle of a TEE probe to control advancement or angulation of the flexible shaft of the TEE probe. The manipulator device is configured to advance a tip of the device catheter or TEE probe relative to anatomy of the patient.

The invention discloses an industrial robot unified control architecture system and a universal robot controller, belongs to the technical field of robot control, and relates to a unified control architecture system based on an industrial robot whole machine performance optimization control algorithm. The problems that an existing industrial robot system is high in brand barrier and high in software and hardware coupling performance are solved. The system comprises the following hierarchical structures: a real-time control kernel layer, a system process and thread structure layer, a communication mechanism layer and a basic function module layer. The industrial robot unified control architecture system and the universal robot controller are suitable for integrating six-axis industrial robots of different brands and models into a unified group control system.

A robotic vehicle management system for the control, optimization and distribution of robotic vehicles is presented in which vehicle operational data is recorded and used to model and optimize a vehicle's travel path. A process for receiving data from multiple vehicles is disclosed, wherein the recorded data is used in the optimization of control systems with regards to travel path, fuel savings, safety, and other considerations. The recorded data may be used to improve system operations or operations of individual vehicles. Methods and techniques are also provided for reading data from vehicle sensors, applying analysis techniques to this data, and uploading improved operational processes to one or more vehicles or to a fleet of vehicles. Adaptive controls, learning based controls, navigation system and other capabilities may be included for optimization and distribution by this discloses system and methods.

Robot control systems, methods, control modules, and computer program products are described that utilize one or more large language models (LLMs) in order to achieve at least some degree of autonomy. Robot control parameters, environmental details, and / or instructions may advantageously be specified in a natural language (NL), and communicate with the LLM via NL prompts or queries. NL queries may include requests for one or more work goals from LLM, such as what may do herein- In this way, a proxy form is established by means of which the robotic system can identify the activity to be performed without operator intervention. The LLM may also be queried to translate each work target into a task plan that provides a series of steps that the robotic system may perform to complete the work target. Optionally, the robotic system may communicate with the operator to determine whether to execute the task plan.

The invention provides a double-pneumatic artificial muscle control method and system with overshoot constraint, and relates to the technical field of robot control. Comprising the following steps: defining error signals of a forearm muscle length, an upper arm muscle length, a shoulder joint angle and an elbow joint angle based on a dynamic model of a double-pneumatic artificial muscle system, and constructing an error signal convergence constraint term and an overshoot range constraint term; determining an energy function of the double-pneumatic artificial muscle system; based on a kinetic model and an energy function of the double-pneumatic artificial muscle system, considering the error signal convergence constraint term and the overshoot range constraint term, and designing a controller to control the forearm control input air pressure and the upper arm control input air pressure of the double-pneumatic artificial muscle system. According to the method, the error signal convergence constraint term and the overshoot range constraint term are considered, the overshoot of the system state variable is controlled within the safety constraint range, the overshoot phenomenon is avoided, and the safety performance of the system is improved.

The invention discloses a mechanical arm working area safety protection method and system based on multi-modal sensing, relates to the technical field of mechanical arm control protection, and solves the problem that multi-modal feature fusion lacks dynamic adaptation and space-time correlation modeling capability. In order to solve the technical problems that a risk assessment system is incomplete and a scenarized dynamic adjustment mechanism is lacked, the key security feature expression is accurately enhanced through a dynamic weight distribution mechanism based on a real-time security risk level; a two-dimensional spatial-temporal characteristic incidence matrix is constructed by combining a dynamic time warping algorithm and unified coordinate system mapping, time sequence and spatial correlation information of multi-modal data is fully mined, the defect that characteristic fusion lacks dynamic adaptation and spatial-temporal modeling is overcome, the generated fusion characteristic vector can comprehensively and accurately reflect multi-dimensional safety information, and the safety performance of the system is improved. The index attribute difference and dimension influence are eliminated through attribute-based normalization calibration, and the accuracy of core index quantification is ensured.

A teleoperation system, including a robotic controller configured to translate a plurality of user inputs to a plurality of robotic control signals. A robotic manipulator, configured to operate separately from the robotic controller and to receive robotic control signals from the robotic controller, the robotic manipulator comprising a plurality of first joints and an end effector, wherein the robotic manipulator is configured to assume a plurality of poses, and wherein each respective pose of the plurality of poses corresponds to a respective configuration of the plurality of first joints. A feedback system, operatively coupled to the robotic manipulator, the feedback system configured to generate feedback information and transmit the feedback information to the robotic controller, wherein the feedback information includes information that indicates a current pose of the robotic manipulator, including the respective configuration of the plurality of first joints corresponding to the current pose of the robotic manipulator.

The invention belongs to the technical field of robots, and discloses a teleoperation robot control method and system with self-adaptive admittance and force feedback, and the method comprises the following steps: 1, loading preset parameters, and moving a main arm to an initial calibration pose; 2, reading an original operator acting force vector and an original environment contact force vector to carry out digital filtering; 3, calculating an adaptive parameter matrix in parallel; 4, the expected tail end speed of the main arm in the current period is calculated, safe amplitude limiting processing is conducted on the component, the current actual tail end pose of the main arm is read, the expected speed obtained after amplitude limiting is converted into the target pose of the main arm in the next period, and a target joint angle instruction is obtained through calculation and sent to the main arm; 5, the actual joint angle of the main arm is read in real time and sent to the auxiliary arm. According to the method, the operation intuition, the task adaptability and the man-machine interaction safety of the system are improved.

Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for controlling agents that interact with an environment. In one aspect, a method includes receiving a sequence of natural language text characterizing a task to be performed by the agent in the environment; generating an encoded representation of the natural language text sequence; and at each of a plurality of time steps: obtaining an observation image characterizing a state of the environment at the time step; processing the observation image to generate an encoded representation of the observation image; generating an input lexical element sequence; processing the sequence of input lemma to generate a policy output defining an action to be performed by the agent in response to the observation image; selecting an action to be performed by the agent using the policy output; and causing the agent to perform the selected action.

The invention provides a mechanical arm control system and method, and relates to the technical field of mechanical arms, and the system comprises a motion parameter module which is used for obtaining motion parameters of a mechanical arm; the spraying parameter module is used for acquiring spraying parameters of the nozzle; the environment data module is used for acquiring working environment data; the precision control module is used for determining precision control discrimination parameters according to the ground vibration data; the thickness control module is used for determining spraying layer thickness control judgment parameters according to the spraying parameters, the wind power data, the temperature data, the humidity data and the motion parameters; the motion control module is used for determining motion control discrimination parameters according to the motion parameters; and the control scheme module is used for generating a control scheme according to the precision control discrimination parameter, the spraying layer thickness control discrimination parameter and the motion control discrimination parameter. According to the invention, the timeliness and accuracy of manipulator control can be improved.

Methods, systems, and apparatus, including computer programs encoded on computer storage media, for automatically generating code for contact-rich manipulation tasks by providing action space constraints to a large language model. One of the methods includes obtaining a library of available control methods for a robotic control system to cause a physical robot to move in an operating environment. The method further includes providing an input to an LLM that specifies a manipulation task to be performed using one or more of the available control methods and that specifies one or more action space constraints that constrain the physical movement of the robot in the operating environment according to forces sensed during performance of the manipulation task. Output code can be generated by the LLM, where the output code, when executed by the robotic control system, causes the physical robot to perform the manipulation task.

The invention discloses a brain-computer interface manipulator motion detection system for disturbance of consciousness assessment, which belongs to the technical field of disturbance of consciousness assessment and specifically comprises an electroencephalogram acquisition device for acquiring original electroencephalogram signals when a patient executes motor imagery tasks containing different hand action instructions; the dynamic feature extraction module generates a motor imagery activation map by calculating the energy distribution change of a preset frequency band; the driving instruction generation module calculates the space-time matching degree of the map and a preset action instruction and generates a manipulator driving instruction; the manipulator control module is used for controlling and executing a composite action positively correlated with the instruction strength, and the action is formed by combining basic grasping and multi-joint coordination actions in proportion; the motion capture device records track changes, and the ratio of the number of the joints exceeding the threshold value to the motion duration serves as a consciousness activity index; the disturbance of consciousness grading module determines a grading result according to the fluctuation range of the index in the continuous period; the method provides an objective and accurate quantification means for disturbance of consciousness assessment.

The present disclosure provides a robot control method, system, device, equipment and medium, the method comprises: through the trained target visual language model, based on the task scene where the user instruction is placed to the robot visual analysis is carried out to obtain the task list required to realize the user instruction, wherein the target visual language model is based on visual encoder, visual language alignment layer and large language model is constructed to obtain;Based on the task in the task list, the control instruction required for the robot to execute the task list is obtained;Through the diffusion of the control instruction by the diffusion model, the mechanical motion trajectory corresponding to the control instruction is determined to control the robot. Improve the understanding ability of the robot for natural language, improve the adaptability of the robot for the task scene, improve the control precision of the robot, improve the flexibility of the robot control, improve the robot for the user instruction degree of achievement.

An apparatus is described for robotic control of an ultrasound imaging device. The apparatus comprises a fixed base and a movable platform with an end-effector. A plurality of passive soft links connects the platform to the base. A series of cables connect the platform to a set of motors adjacent the base. When the platform is at rest, the tension in the cables counter-balances the passive soft links pushing the platform away from the base plate. Control electronics move the motors so as to control the location and the orientation of the platform. By increasing or decreasing tension in the cables, the motors smoothly control the location and the orientation of the platform and thus the end effector. Such a robotic apparatus can be used to provide expert handling of an ultrasound imaging device remotely.