204 results about "Robotic control" patented technology

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 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.

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.

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.

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 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.

The invention relates to the technical field of semiconductors, and discloses a wafer loading and unloading device and method.The device comprises an upper computer control system and further comprises a mechanical arm system and a detection table system which communicate with the upper computer control system; the mechanical arm system comprises a mechanical arm controller communicating with the upper computer control system, and further comprises a wafer storage box and a feeding and discharging mechanical arm which communicate with the mechanical arm controller, and the wafer storage box and the feeding and discharging mechanical arm communicate with the upper computer control system. The detection table system comprises a detection table controller communicating with the upper computer control system and a detection table communicating with the detection table controller. The problem that in the prior art, transmission errors are large is solved.

1. Name of the designed product: robot control handle. 2. Use of the designed product: for controlling medical robot. 3. Design points of the designed product: in shape. 4. Picture or photo best indicating the design points: perspective view.

The embodiment of the application provides a robot control method, wherein the method obtains a plurality of sets of acceleration threshold values according to a load state of a robot; determines an acceleration management and control threshold value according to the plurality of sets of acceleration threshold values; determines an output force safety threshold value of a driver according to the acceleration management and control threshold value and the mass of the load; and obtains an acceleration threshold value of the robot according to a maximum acceleration, a minimum acceleration, an acceleration change rate threshold value and motion time in motion data; and controls the acceleration of the robot within the output force safety threshold value, thereby avoiding full-load operation of a servo motor driving the robot to transport and move when the acceleration setting exceeds a design threshold range, and avoiding wear of the robot caused by inertial force exceeding a design threshold value during deceleration, thereby shortening the service life of the robot; and avoiding unsaturated operation of the servo motor when the acceleration setting is less than the design threshold range of the equipment, thereby reducing production efficiency.

A system has a virtual-world (VW) controller and a physical-world (PW) controller. The pairing of a PW element with a VW element establishes them as corresponding physical and virtual twins. The VW controller and / or the PW controller receives measurements from one or more sensors characterizing aspects of the physical world, the VW controller generates the virtual twin, and the VW controller and / or the PW controller generates commands for one or more actuators affecting aspects of the physical world. To coordinate the corresponding virtual and physical twins, (i) the VW controller controls the virtual twin based on the physical twin or (ii) the PW controller controls the physical twin based on the virtual twin. Depending on the operating mode, one of the VW and PW controllers is a master controller, and the other is a slave controller, where the virtual and physical twins are both controlled based on one of VW or PW forces.

The invention relates to the technical field of sampling manipulators, in particular to an intelligent farmland soil detection sampling manipulator device which comprises a following frame, a sampling manipulator is mounted on the following frame on one side of a discharge port of a sample discharger, and a large-diameter sampling container is clamped at the clamping end of the sampling manipulator. The sampling manipulator controls the large-diameter sampling container to receive soil discharged by the sample discharging device and transfer the soil to the position of a detection instrument arranged on the ground, and field detection is completed through manual auxiliary operation; an impurity discharging mechanism and a main driving part for driving the impurity discharging mechanism to rotate are mounted in the following frame; the lower end of the impurity discharging mechanism extends to the lower part of the following frame and is connected with a combined sampler; and a downward drilling device is fixed at the bottom of the combined sampler. Through the operation mode of single-time drilling and multi-depth sampling, repeated disturbance of traditional multi-drilling-hole sampling on a farmland soil structure can be avoided, and meanwhile full-depth-range sampling can be completed without repeated drilling.

The application relates to the technical field of robot control, and particularly discloses a robot control method and system adopting a graphed visual perception feature, the method comprising the following steps: collecting images based on an RGB-D camera; performing target identification on the images, positioning a target frame, performing subject identification on the content of the target frame, and determining subject information; constructing a node corresponding to the robot as a reference node, creating a graph containing the reference node according to the subject information, and synchronously calibrating the attributes of each node in the graph; receiving a demand text, identifying the demand text, and generating a control instruction according to the identification result and the graph. The application acquires a visual image, identifies the visual image, positions a subject, synchronously acquires subject information, constructs a graph, takes the graph as information features, generates a control instruction of the robot based on the graph, and in this process, the graph is taken as numerical information and the source of generation of the control instruction, so that the understanding ability of the robot is greatly improved.

This utility model relates to the field of bearing manufacturing technology, specifically a positioning and adjustment device for a robot control box. It includes a base plate, a robot control box mounted on the base plate, and a positioning and adjustment mechanism mounted on the base plate and acting on the robot control box. The positioning and adjustment mechanism includes an L-shaped support frame, a first sliding rod, and a positioning frame. The L-shaped support frame is located on one side of the base plate. The first sliding rod is mounted on the robot control box and slides in cooperation with the vertical side of the L-shaped support frame. The positioning frame slides vertically on the horizontal side of the L-shaped support frame. The bottom of the robot control box slides in cooperation with the base plate. Symmetrical positioning holes are provided on both the bottom of the robot control box and the base plate. Pushing the first sliding rod until the positioning hole on the robot control box aligns with the positioning hole on the base plate, the positioning rod re-inserts into the positioning hole under the action of a second spring. At this time, both the first and second springs extend, and the positioning rod positions the robot control box on the base plate.

The application discloses a kind of automatic feeding and discharging mechanical hand control method for pad printing machine, comprising the following steps: obtaining feeding point three-dimensional coordinates and material changing point three-dimensional coordinates, wherein machine tool is provided with multiple layers of material tray, and zero point three-dimensional coordinates are set for material tray;Based on feeding point three-dimensional coordinates, material changing point three-dimensional coordinates and zero point three-dimensional coordinates, generate first intermediate position coordinates and second intermediate position coordinates;Control first mechanical hand according to the first intermediate position coordinates generated, carry out machine tool processing;Control second mechanical hand according to the second intermediate position coordinates generated, and remove the processed workpiece of material changing point;Whether the intermediate stroke is greater than the predetermined threshold according to the moving distance, so as to select the first moving speed or the second moving speed to complete the intermediate stroke;The automatic feeding and discharging mechanical hand control method and system for pad printing machine integrate advanced coordinate acquisition, generation, mechanical hand control, speed optimization and fault handling technology, realize efficient, high-precision, automated production.

A software-defined network card hardware function configuration method is disclosed.The application discloses an industrial manipulator grabbing system and method based on FPGA and visual AI.The system integrates an industrial camera, an FPGA heterogeneous computing platform and a manipulator controller.The PS end of the FPGA platform is responsible for image acquisition and communication, and the PL end completes the whole process of image preprocessing, AI target detection and coordinate calculation in parallel through a hardware image preprocessing pipeline, a deep learning processing unit (NPU) IP core and post-processing logic.The application solidifies the complete visual AI processing flow in the FPGA hardware, realizes ultra-low delay and high-deterministic processing performance, effectively solves the problems of high delay and large jitter of the traditional industrial computer scheme, and is particularly suitable for high-speed and high-precision industrial automation grabbing scenes.

The invention discloses a manipulator control method and system for a packaging machine, and the method comprises the steps: obtaining a plurality of abnormal state parameters of a vibration disc of the packaging machine and manipulator motion parameters under each abnormal state parameter, and constructing a vibration disc-manipulator cooperative control model according to the abnormal state parameters and the manipulator motion parameters; real-time material state parameters in the vibration disc are detected, and the vibration disc-manipulator cooperative control model controls the manipulator to conduct dynamic compensation grabbing on materials according to the real-time material state parameters; the moving speed parameter of the carrier tape is detected, the material placing distance is determined according to the moving speed parameter and the weight parameter of the material, and the manipulator is controlled to place the material according to the material placing distance; the material leakage condition of the carrier tape and the slag blocking parameters in the groove are detected through the image analysis technology, the mechanical arm is controlled to carry out material supplementing and discharging and waste cleaning according to the material leakage condition and the slag blocking parameters in the groove, the working efficiency and stability are improved, and the feeding stability and reliability are guaranteed.

The application relates to a mechanical hand control dispensing field, and discloses a feature recognition guide mechanical hand dispensing method, a computing device and a storage medium, the method comprises the following steps: recognizing a fiber coupler part feature according to a camera shooting tool plate image; when the part feature is identified as a taper area, a shearing pipe opening or a glass pipe opening, adjusting a light source according to a preset light adjustment condition corresponding to the taper area, the shearing pipe opening or the glass pipe opening, shooting a part image through the camera, and recognizing pixel coordinates of the taper area, the shearing pipe opening or the glass pipe opening according to the image; calculating dispensing coordinates of a mechanical hand according to the pixel coordinates of the taper area center, the pixel coordinates of the shearing pipe opening and the pixel coordinates of the glass pipe opening; and dispensing at the dispensing coordinate point through the mechanical hand control dispensing machine, the application adjusts the light source and the camera parameter matched with different part features of the coupler based on different part features, accurately recognizes the coordinates of the different part features, calculates the accurate dispensing coordinates of the mechanical hand, and improves the dispensing accuracy and the dispensing efficiency.

This invention discloses a method and apparatus for preventing accidental contact during substrate adsorption in an ion implanter, comprising: a substrate position scanning device for scanning a wafer cassette and acquiring substrate position information; a robotic arm controller connected to the substrate position scanning device; a robotic arm with a substrate adsorption device at its end, the drive unit of the robotic arm being connected to the robotic arm controller; a wafer identification device connected to the robotic arm controller for determining whether the substrate adsorption device has successfully adsorbed the substrate; and an anti-accidental contact detection sensor built into the front end of the robotic arm for real-time acquisition of detection data and transmission to the robotic arm controller; wherein the robotic arm controller is configured to: receive the detection data transmitted by the anti-accidental contact detection sensor; determine in real-time whether there is a risk of accidental contact between the substrate and the robotic arm through a preset algorithm; and immediately control the robotic arm to stop moving when a risk is determined to exist.

The application discloses a kind of based on sEMG signal's bionic manipulator control method, system, equipment and storage medium, belong to the technical field of bionic manipulator, method includes by the multi-modal feature fusion neural network of construction to the multi-modal signal of acquisition is handled, to identify grasping action;Grasping action is identified label by BP neural network and is converted into the control signal of bionic manipulator;Multi-modal feature fusion neural network includes input layer, feature extraction layer, time series modeling layer, feature fusion layer and output layer;Feature extraction layer extracts the local time sequence feature of multi-modal signal, time series modeling layer models the time sequence dependency of grasping action;Feature fusion layer introduces time-based attention mechanism, adaptively adjusts the feature weight of each mode, and then the features of multi-modal are fused into global feature vector.The application can improve the recognition accuracy of grasping action, to improve the control accuracy of bionic manipulator.

Methods, systems, and apparatus, including computer programs encoded on computer storage media, for data-driven robotic control. One of the methods includes maintaining robot experience data; obtaining annotation data; training, on the annotation data, a reward model; generating task-specific training data for the particular task, comprising, for each experience in a second subset of the experiences in the robot experience data: processing the observation in the experience using the trained reward model to generate a reward prediction, and associating the reward prediction with the experience; and training a policy neural network on the task-specific training data for the particular task, wherein the policy neural network is configured to receive a network input comprising an observation and to generate a policy output that defines a control policy for a robot performing the particular task.

Training and / or utilizing a hierarchical reinforcement learning (HRL) model for robotic control. The HRL model can include at least a higher-level policy model and a lower-level policy model. Some implementations relate to technique(s) that enable more efficient off-policy training to be utilized in training of the higher-level policy model and / or the lower-level policy model. Some of those implementations utilize off-policy correction, which re-labels higher-level actions of experience data, generated in the past utilizing a previously trained version of the HRL model, with modified higher-level actions. The modified higher-level actions are then utilized to off-policy train the higher-level policy model. This can enable effective off-policy training despite the lower-level policy model being a different version at training time (relative to the version when the experience data was collected).

Applications of robotics applied to patch-panels and cross-connects to improve operational processes within data centers and communications networks. Systems and architectures to perform frequent, accurate and low-cost reconfigurations and measurements of the physical network are described, thereby eliminating labor and time delays when completing routine tasks such physical network provisioning and reconfiguration.

The present application relates to the technical field of manipulator control, in particular to a visual-guided rotary mold transfer machine positioning control system.The system comprises a joint driving unit, a flexible transmission assembly and a vision module.A master controller first decouples the generalized disturbance torque representing the nonlinear resistance of the flexible assembly from the cross-axis current feedback of the driving unit based on the joint dynamics model;then, the LSTM network is used to learn the mechanical hysteresis loop characteristics of the torque under different rotary motion states, predict the end dynamic position compensation amount covering the system transmission delay time;finally, based on the smooth weight generated by the real-time running speed, the dynamic position compensation amount is fused with the visual positioning coordinates without disturbance.The present application combines physical priori and data driving, effectively overcomes the cumulative error caused by the nonlinear interference of the cable and the signal transmission lag in the non-slip ring rotary operation, and realizes high dynamic precision positioning.