373 results about "Robot controller" patented technology

The invention belongs to the technical field of parallel robot controllers, and discloses a high-performance parallel robot controller based on an arm + fpga architecture, through deep heterogeneous fusion of an ARM and an FPGA, the control period is shortened to be within 10 microseconds, the trajectory tracking error is controlled to be 0.1 mm or below, and the performance bottleneck of a traditional architecture in a high-speed scene is solved; the multi-core ARM undertakes complex tasks such as global trajectory planning and dynamics solution, and realizes parallel processing by means of an NEON instruction set; the FPGA fully releases the hardware parallel characteristic of the FPGA, real-time tasks such as multi-axis motion control and sensor data fusion are synchronously completed through a distributed logic unit, and a complex decision-real-time execution assembly line cooperation mode is formed. Inertial parameters and load changes of the mechanical arm are estimated in real time through an LSTM neural network, and feedforward compensation is carried out on interference such as mechanical vibration and load abrupt change in combination with an extended state observer achieved through FPGA hardware; the innovatively designed double closed-loop control architecture supports seamless switching between a force control mode and a position control mode.

The invention relates to the technical field of industrial automatic welding and discloses an intelligent control method and system for industrial robot welding, and the method comprises the steps that after a welding task is started, an initial welding process parameter model is called based on the current workpiece specification, and a first welding control instruction sequence is generated; according to the first welding control instruction sequence, a welding gun is controlled to execute welding operation, and multi-source sensing data flow in the welding process is synchronously collected; carrying out fusion feature extraction on the real-time sensing data stream to generate a current welding situation feature vector, when situation deviation exists between the current welding situation feature vector and the reference welding situation feature vector, obtaining a self-adaptive welding process parameter model through online incremental learning, and obtaining a self-adaptive welding process parameter model on the basis of the self-adaptive welding process parameter model. And generating an optimized welding control instruction sequence and issuing the optimized welding control instruction sequence to a robot controller and a welding gun so as to execute self-adaptive welding operation. The welding quality stability and the production efficiency can be improved, and the equipment maintenance cost is reduced.

A method of programming an industrial robot (100), with a robot manipulator (110) and robot controller (120), comprises: recording movements of the robot manipulator during a demonstration-based robot programming session, for thereby obtaining a robot trajectory; acquiring a video of the robot programming session; and generating, on the basis of the robot trajectory and the video, a robot program (C) executable by the robot controller, wherein the robot program includes at least one motion command which is expressed in a first reference frame (0 1). The method further comprises capturing operator input data indicating a first object (151) in an image in the video. The generated robot program includes a command to identify a position of an object resembling the first object in a work area (150) of a robot which executes the robot program; and the first reference frame is defined with respect to the identified position of the object resembling the first object.

A robotic controller for controlling a robot according to a sequence of robotic actions. comprises an input interface configured to receive a plurality of multimodal inputs each specifying instructions for performing a task in a different modality including audio, video, and a text modality. The controller also comprises a multimodal large language model, an action sequence decoder, and a controller. The multimodal LLM includes a multimodal LLM encoder and an LLM decoder. The multimodal LLM encoder is trained with machine learning to transform the multimodal instructions into encodings and the LLM decoder is configured to decode the encodings into a sequence of robotic instructions. The action sequence decoder is trained with machine learning to transform the sequence of robotic instructions into a sequence of actions using a library of robotic skills. The controller is configured to control a robot according to the sequence of actions.

The invention provides a servo press control system and method based on a time-sensitive network, and relates to the technical field of intelligent manufacturing and industrial automation control, and the system comprises a time-sensitive network TSN which is used for providing global time synchronization and deterministic data transmission; a main controller of the multi-axis servo control unit is used for issuing a motion control instruction and a feeding and discharging control instruction through a TSN. A robot controller in the robot feeding and discharging unit is used for driving an industrial robot to execute plate taking and placing operation under the action of the feeding and discharging control instruction. The visual monitoring unit comprises an industrial camera accessed to the TSN and is used for collecting images and transmitting image data to the edge computing node through the TSN; the edge computing node is used for processing the image data to generate a compensation instruction and feeding back the compensation instruction through the TSN; and the upper monitoring system is used for subscribing real-time data published by the edge computing nodes, so that the control range of the servo pressure control system is expanded, and the convenience of data transmission and interaction is improved.

The invention discloses a robot multi-mode interaction control method and a related device, and the method comprises the steps that a robot controller obtains user interaction information, and the user interaction information comprises user voice information and / or user action information; analyzing the user interaction information, and determining a shopping guide service type and a target vehicle part; acquiring first component information of the target vehicle component from a preset vehicle knowledge base according to the shopping guide service type; according to the shopping guide service type and the first component information, a target action sequence is determined from a preset action library, the target action sequence comprises joint actions and voice actions, the voice actions are used for outputting voice shopping guide information, and the voice shopping guide information is determined according to the first component information; and sending a first control instruction to the target robot, wherein the first control instruction is used for indicating the target robot to execute the target action sequence. According to the invention, the functionality and intelligence of the humanoid robot as an intelligent shopping guide robot can be improved.

A distributed robot controller is disclosed, comprising a plurality of local controllers, each associated with a corresponding motor included in a plurality of motors comprising a robot; and a robot level controller coupled communicatively with each of the local controllers and configured to determine a plan to operate the plurality of motors to cause the robot to perform a task and send to each of the local controllers included in the plurality of local controllers at least a set of one or more torques associated with the motor with which that local controller is associated.

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 relates to a method for monitoring a robot system comprising a robot arm and a peripheral device, the method comprising the steps of: providing a communicative peripheral connection between the peripheral device and a robot controller; establishing an operation signal history in a digital storage wherein the operation signal history is based on operation representations; executing a robot operation process on the robot controller; establishing a peripheral signal associated with the peripheral connection; recording the peripheral signal to obtain a peripheral signal representation; updating the operation signal history by providing the peripheral signal representation as an operation representation of the operation representations; and tracking operation of the robot system based on the operation signal history. The invention further relates to a robot system.

The application relates to a multi-arm mobile robot control system, which comprises a robot, each joint position of the mechanical arm of which is configured with a joint controller for driving joint movement; a robot controller for realizing the operation of joint motors according to control quantities; a joint position hard analysis unit for calculating the coordinate positions of each joint or mechanical arm in a space coordinate system to output results; and a joint space point position trajectory constraint model for forming a correction quantity of a joint and superimposing the correction quantity on an original control quantity of the joint to become a final control quantity for controlling the joint, the final control quantity being used for output to the joint controller to realize joint movement. The application provides a multi-arm mobile robot control system, which effectively realizes the cooperative control among multi-arm robots, avoids the mutual collision among mechanical arms, improves the avoidance and dynamic response speed of the mechanical arms, and improves the agility of robot actions.

A node-edge symbolic consent kernel (NESCK) provides a computing architecture in which every instruction is gated by a verifiable human-intent signal and an ethical-predicate chain prior to execution. The system integrates a biometric-sensing front-end (EEG / GSR / facial micro-affect), a symbolic arbitration engine that transforms bio-intent data into consent tokens, and a cryptographically bonded node-edge ledger that records execution lineage, revocation, and audit proofs. Each node represents an executable state bound to a human consent fingerprint, while each edge encodes the ethical transition rules authorizing propagation through the network. At runtime, the kernel evaluates symbolic predicates, verifies zero-knowledge proofs of consent, and allows or halts instruction dispatch. The framework operates across devices, edge nodes, and cloud layers, enabling real-time lawful AI behavior, revocable autonomy, and tamper-proof moral audit trails. Embodiments span neuroadaptive wearables, autonomous vehicles, robotics controllers, and sovereign AI systems requiring continuous consent and transparent accountability.

A method and system (200) for determining an elastic characteristic of an industrial robot (100) including a plurality of interconnecting shafts including at least one shaft exhibiting elasticity and at least one joint exhibiting static friction. The method comprises: (S12) clamping an end flange (16) of the industrial robot (100) to the flexible clamping device (1); (S15) determining and loading a program into a robot controller of the industrial robot (100), the program defining a clamping deflection motion that produces deflection of one or more links of the industrial robot (100) based on a force interaction between the robot (100) and the flexible clamping device (1); (S16) controlling the industrial robot (100) to perform a clamping deflection motion while sensing a quantity of the industrial robot (100) and a quantity of the flexible clamping device (1); (S17) determining a reduced data set of the sensing measurements of the industrial robot (100) and the flexible clamping device (1) by excluding data of the sensing measurements that may comprise the influence of static friction; (S18) determining the relative attitude and force / torque between the top plate (2) and the base plate (3) of the flexible clamping device (1); and (S19) determining kinetic friction characteristics of the at least one joint exhibiting static friction and elastic characteristics of the at least one shaft exhibiting elasticity, and (S21) updating one or more of the at least one model of the industrial robot (100) with the determined kinetic friction characteristics and elastic characteristics, wherein the updated one or more in the at least one model provides elastic characteristics of the industrial robot (100) and related dynamics forming a scenario for using the parameters to improve control of the industrial robot (100).

The invention discloses a grabbing and placing task-oriented robot trajectory planning method and device, and the method comprises the steps: obtaining a natural language task instruction, carrying out the path decomposition based on a large language model, and generating a stage sequence containing pre-grabbing, grabbing, lifting, pre-placing, placing and withdrawing, and each stage target and / or constraint; receiving the optimal grabbing pose and / or placing pose provided by the upstream module, and replacing or correcting stage targets related to grabbing and / or placing; generating a trajectory segment according to the corrected stage target and constraint, and carrying out smoothing processing to obtain a trajectory sequence; performing collision detection on the track sequence, and if collision occurs, outputting collision information and executing local repair or replanning until the collision detection is passed or a preset replanning condition is met; and outputting the executable track sequence of the robot controller. According to the scheme, stage decomposition and key pose landing are achieved, and a collision feedback closed loop is formed to obtain an executable track.

The invention discloses a dynamic visual guidance method and system for cooperative assembly of multiple mechanical arms, and belongs to the technical field of industrial robot visual guidance, and the method comprises the steps: synchronously collecting an image sequence through a binocular visual system, synchronously recording the pose sequence of each mechanical arm through a robot controller, and obtaining an observation data set; obtaining a two-dimensional trajectory flow of vehicle body assembly area feature points and instrument body feature points through an optical flow tracking algorithm, and obtaining a hand-eye matrix correction through a nonlinear optimization algorithm; obtaining an updated hand-eye matrix and a local pixel compensation field through a spatial interpolation algorithm based on the re-projection error of each feature point; according to the method, self-adaptive compensation of flexible deformation of a vehicle body and dynamic reflection of an instrument is realized by adopting unsupervised clustering and spatial interpolation according to a re-projection error, and the precision of cooperative assembly of multiple mechanical arms and the self-adaptive capability of a system in a complex industrial environment are improved.

The self-adaptive welding device comprises a robot, a robot controller, an industrial personal computer, a visual assembly and a welding gun, a visual processing module, a welding seam contour recognition module, a welding seam precision adjustment module and a track generation module are arranged in the industrial personal computer, and the visual assembly is used for conducting multi-angle shooting on a workpiece; the visual processing module is used for identifying geometrical characteristics of a main pipe and a branch pipe of the workpiece; the weld contour recognition module is used for recognizing a weld contour; the welding seam precision adjusting module is used for refining the precise position of the welding seam point at the junction of the main pipe and the branch pipe through a calibration method; the track generation module is used for generating a welding track; and the robot controller receives the welding track and controls the welding gun to move according to the welding track to execute welding operation. According to the method, the reasonable robot welding posture is automatically matched, the track continuity and the welding process stability are improved, through automatic track planning and execution, it is ensured that the quality of each welding seam is stable, and manual operation errors are reduced.

The invention provides a robot grinding and polishing method and system for titanium alloy casing runner welding slag. The system comprises a robot, a robot controller, a six-dimensional force sensor, a displacement sensor, a three-dimensional scanner, a belt sander and a workbench. The method comprises the following steps: firstly, fixing a casing on a workbench, positioning the casing by using a displacement sensor, scanning a casing flow channel by using a three-dimensional scanner to obtain a flow channel welding slag distribution state, grasping a belt sander by using a robot equipped with a six-dimensional force sensor, carrying out gravity calibration on the belt sander before grinding and polishing, and carrying out welding slag distribution on the belt sander; and the gravity of the belt sander is compensated according to the calibration result. Three-dimensional software is used for dividing a flow channel area, a machining path is calculated through an off-line trajectory planning method, a robot executable machining program is generated through post-processing for grinding and polishing, in the grinding and polishing process, in order to adapt to the complex curved surface of the cartridge receiver flow channel, real-time adjustment is conducted according to the contact force value of a tool and a workpiece, and the contact force value is transmitted to a robot controller; the removal amount can be determined, the roughness is guaranteed, and the surface quality is improved.

A robotic controller for controlling a robot according to a sequence of robotic actions. comprises an input interface to receive multimodal inputs specifying instructions for performing a task in audio, video, and a text modality. The controller transforms the multimodal instructions into encodings using a large language model (LLM) encoder and decodes the encodings into a first sequence of robotic instructions and a robot action description of the actions using an LLM decoder. Human feedback input is received corresponding to at least one action in the first sequence of actions and the controller encodes the feedback input with the robot action description. The controller feeds the encoded data along with multimodal features generated from the encodings into the LLM decoder to generate a corrected sequence of actions. The controller is configured to control a robot according to the corrected sequence of actions.

The invention discloses a programming method and system for industrial robot operation teaching based on a knowledge graph, and relates to the technical field of industrial automation and intelligent control. The method comprises the following steps: analyzing an industrial robot PDF technical document, extracting an instruction and an instruction parameter, and constructing a tree structure based on an identified title hierarchy; constructing a hierarchical knowledge graph based on the tree structure; generating an abstract syntax tree based on the instruction, the instruction parameter and the knowledge graph; filling node attributes of the abstract syntax tree into a preset control template, generating a reference RAPID code, importing the reference RAPID code into a robot controller, loading teaching environment parameters, and executing; and comparing execution results of the student self-compiled code and the reference code for students to observe difference comparison learning. The invention aims to break through a PDF technical document understanding threshold and accurately position errors in self-compiled codes of students through knowledge graph construction and reference code generation, so that the learning efficiency of the students is improved, and the teaching burden of teachers is relieved.

A robot controller (110) comprising processing circuitry (111) and a simultaneous connectivity module (113). The processing circuitry is configured to execute an operating system (140) and to execute software applications (140) in the operating system. The software applications include a robot control application for controlling an industrial robot (120). The SCM is configured to maintain two or more simultaneous data links (131, 132) between the processing circuitry and external entities (121, 122). For this purpose, the SCM comprises two or more radio technology layers, each having a transceiver chain and a software stack for supporting the transceiver chain, and a shared processing resource, which is operable for use in the execution of the software stacks. The processing circuitry is authorized to control the execution of each of the software stacks in the SCM.

A surface abrading system is presented that includes a robot arm with an end effector on an end of the robot arm. The end effector is configured to couple to an abrasive article. The system also includes a movement mechanism that moves the robot arm with respect to a surface. The system also includes a robot controller that causes the robot arm to execute an abrasive trajectory on the surface. The abrasive trajectory includes the abrasive article in contact with the surface. The robot controller includes a trajectory retriever that retrieves an abrasive trajectory. The abrasive trajectory includes a surface appearance portion prior to an endpoint. The surface appearance portion comprises a reduction in relative movement speed between the robot arm and the abrasive article or a reduction in effective applied force on the abrasive article. The controller also includes a command generator that communicates the abrasive trajectory to the movement mechanism to execute the trajectory.

A numerical control system 1 is provided with: a numerical control device 5 including a machine tool control module 50; a robot controller 6 including a robot control module 60 for controlling the movement of a robot 3; and a variable storage unit 58 for storing the values of a plurality of variables that can be read and written by both modules 50, 60. The machine tool control module 50 reads the value of a second variable stored in a second storage area 582 of the variable storage unit 58, controls the movement of a machine tool 2 on the basis of the value that has been read, and rewrites the value of a first variable stored in a first storage area 581, and the robot control module 60 reads the value of the first variable, controls the movement of the robot 3 on the basis of the value of the first variable that has been read, and rewrites the value of the second variable.

The present invention belongs to the field of robotics technology, specifically a constant force grinding method for complex surfaces of a robot based on force feedback. The method comprises the following steps: Step 1, collecting information of a six-dimensional force sensor through a robot controller; Step 2, introducing a fastest differential tracker in the self-disturbance rejection control; Step 3, forming an admittance control model by the robot and the environment to realize the outer loop control of the robot manipulator; Step 4, constructing a non-singular terminal sliding film control law to realize the inner loop control of the robot manipulator, thereby realizing the grinding of the curved workpiece surface. The present invention can improve the force tracking effect of the manipulator in a complex and unknown environment, thereby greatly improving the robot grinding accuracy.

The invention relates to a multi-arm mobile robot control system, which comprises a robot, and a joint controller for driving a joint to move is arranged at each joint position of a mechanical arm of the robot; the robot controller is used for enabling the joint controller to execute operation of the joint motor according to the control quantity; the joint position hard analysis unit is used for calculating the coordinate position of each joint or the mechanical arm in a space coordinate system so as to output a result; and the joint space point locus constraint model is used for forming the correction amount of the joint and superposing the correction amount to the original control amount of the joint to form the final control amount for controlling the joint, and the final control amount is used for being output to the joint controller to realize joint movement. According to the multi-arm mobile robot control system provided by the invention, cooperative control among multi-arm robots is effectively realized, mutual collision among mechanical arms is avoided, the avoidance and dynamic response speed of the mechanical arms is increased, and the flexibility of robot actions is improved.

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.

A method and system for proactively monitoring the health of a robot end-of-arm tool based on timing of response to gripping commands. A part presence or other sensor provides a signal when a robot tool successfully grips or ungrips a workpiece. The time between each grip or ungrip command and its completion is recorded by the robot controller. Timing data for all robots in a facility are collected by a data collection device and forwarded to an analytic data center, where the timing data is analyzed for each end-of-arm tool. Alerts are sent advising of issues which have been identified on grippers when grip times exceeding a threshold or a deterioration trend in grip time performance is detected, and all analytic data is provided to a web portal for customer viewing and action. Response timing for other types of end-of-arm tools besides grippers may be similarly analyzed for proactive tool repair / replacement.

The invention provides an automobile cabin modular assembly method and system, and the method comprises the steps: synchronizing actual pose data, assembly contact force data and station parameters to a virtual assembly scene of a preset digital twin system, so as to construct a dynamic mapping relation between a physical assembly state of a cabin module and the virtual assembly scene; on the basis of the dynamic mapping relationship, comparing the actual pose data of each cabin module with design reference parameters through a preset error analysis model so as to acquire a corresponding comparison result; performing correlation analysis on the comparison result in combination with the assembly contact force data and the station parameters to identify an error source and a dynamic change trend, and generating a corresponding error compensation instruction; and issuing the error compensation instruction to a robot controller on the assembly line to control a robot to execute assembly adjustment. According to the invention, the assembly of the cabin module can be accurately completed, and the assembly efficiency is improved.

To provide a conveyance system capable of expanding a range of automation, a control method of the conveyance system, and a program.SOLUTION: A conveyance system includes a robot (21) having a hand (210), a pallet stocker (31) for storing a pallet (410), the pallet stocker (31) including a shelf board (510) on which the pallet (510) for holding a workpiece can be placed, and a plurality of support parts (560) each capable of supporting the shelf board (410) and arranged at intervals in a vertical direction, and a robot controller (620) configured to control the robot (21) to move the shelf board (510) from a first support part (560A) to a second support part (560B) while gripping the shelf board (510) with the hand (210) when receiving a command to reposition the shelf board (101) from the first support part (560A) to the second support part (560B) among the plurality of support parts (560).SELECTED DRAWING: Figure 24

The invention discloses a robot anti-interference integrated circuit system based on multi-sensor fusion, relates to the technical field of automatic control, and aims to solve the problems that in ultra-precision hole machining, due to the fact that complex multi-mode vibration of a boring rod cannot be decoupled and accurately compensated in real time, and the machining precision is high. The system comprises a sensor array which is configured on a key structure of an end effector of an industrial robot and is used for collecting multi-dimensional physical signals related to mechanical vibration in real time; the application-specific integrated circuit is in signal connection with the sensor array and the robot controller, and the application-specific integrated circuit comprises a vibration reconstruction and compensation amount determination module which is used for receiving, fusing and processing multi-dimensional physical signals collected by the sensor array; according to the method, a real-time vibration deformation modal reconstruction and mapping system based on a spatial distributed sensing array and a special integrated circuit is constructed, so that the complex dynamic deformation of the boring rod in the machining process is identified.

The invention relates to the technical field of integrated circuit design and robots, in particular to a special chip architecture for a sensing-computing-control integrated robot controller, which adopts a multi-core heterogeneous system architecture and comprises a control core, a computing core and a sensing core, and is characterized in that the control core is a high-performance real-time processor core cluster based on an RISC-V instruction set; the calculation core is used for accelerating AI task reasoning calculation of a visual language model, reinforcement learning and target detection; the sensing core is used for gathering and preprocessing data from various sensors; the control core, the calculation core and the sensing core are integrated in a single SoC chip, and integrated fusion of multi-mode sensing, high-throughput calculation and high-real-time control functions is achieved. According to the scheme, multi-mode sensing, complex calculation and real-time control are deeply fused into a single SoC chip through software and hardware collaborative design, so that the comprehensive performance of a robot control system is remarkably improved, and unification of high real-time response, high calculation energy efficiency and high design flexibility is achieved.

The utility model provides a circuit for setting current and voltage of a welding machine for a robot controller, and the circuit comprises a main control module which is used for outputting a PWM signal; the input end of the optocoupler isolation module is connected with the output end of the main control module, and the optocoupler isolation module is used for isolating the PWM signals output by the optocoupler isolation module; the input end of the signal conversion module is connected with the output end of the optocoupler isolation module, and the signal conversion module is used for converting the PWM signal output by the optocoupler isolation module into an analog signal; the input end of the operational amplification module is connected with the output end of the signal conversion module, analog signals output by the signal conversion module enter the operational amplification module in a differential input mode, and the operational amplification module conducts buffering isolation and signal conditioning on the analog signals.