661 results about "Robot controller" patented technology

A securable robotic controller comprising internal and external sensors is physically secured to or hosts a controllable device. Based on inferences the securable robotic device controls the controllable device physical control via at least one actuated link. Multiple securable robotic devices may be coupled and composed to host and manipulate multiple controlled devices.

A method of programming an industrial robot (100), composed of a robot manipulator (110) and a robot controller (120), comprises: recording movements of the robot manipulator during a kinesthetic programming session, for thereby obtaining a robot trajectory; capturing speech data while recording the movements of the robot manipulator; decomposing the recorded speech data into a plurality of phases; for each phase of the speech data, parsing the speech data into robot parameter values using a natural-language model (170), identifying a contemporaneous phase of the robot trajectory and annotating it with the robot parameter values; and, on the basis of the annotated robot trajectory, generating a robot program executable by the robot controller.

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.

The invention discloses a space robot finite time anti-interference trajectory tracking control method based on performance constraint and actuator saturation, and the method comprises the steps: firstly solving a state-space equation of a flexible joint free flight space robot, constructing a system error vector in combination with a finite time instruction filter and an anti-saturation auxiliary system, and carrying out the finite time instruction filter and anti-saturation auxiliary system; a novel asymmetric logarithmic obstacle Lyapunov function with an asymmetric fixed time constraint boundary is constructed; and finally, a novel finite time advanced activation anti-saturation auxiliary system and a finite time adaptive controller with a performance constraint effect are constructed, so that finite time anti-interference trajectory tracking control of the space robot is realized. According to the method, the influence of sudden disturbance is considered in the design of the flexible joint free flight space robot controller for the first time, and under the limitation of the saturation performance constraint of the actuator, the trajectory tracking rapidity and accuracy of the space robot are ensured; and the influence of sudden disturbance in a space robot system on the trajectory tracking transient performance can be effectively inhibited.

The invention belongs to the technical field of fusion welding, and particularly relates to a method for planning multi-layer and multi-welding-seam welding parameters according to welding seam feature information, which comprises the following steps: 1) laser emitted by a 3D visual sensor is perpendicular to a welding seam and scans along the direction of the welding seam, and the 3D visual sensor scans welding seam data and transmits the data to a robot controller in real time; (2) the robot controller processes the weld joint data, the whole weld joint is subjected to multi-layer and multi-pass planning calculation, and the number of welding layers and the number of welding passes of each layer are planned; (3) the robot controller calculates the layer number and the channel number of a welding channel needing to be welded currently, a welding gun track coordinate set on a welding path and welding parameters corresponding to welding path points; and (4) the robot controller adjusts the welding track and the welding parameters in real time according to the step (1) to the step (3) in the current welding bead welding process, so that the purpose of multi-layer and multi-pass planning self-adaptive welding of the medium-thickness plate is achieved.

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.

The invention relates to the technical field of medical robots, in particular to an alimentary canal catheterization robot navigation method and system based on multi-modal information fusion. The method comprises the following steps: carrying out real-time data acquisition on a human body cavity by utilizing a multi-mode sensor; the collected multi-modal data is preprocessed; synthesizing multi-modal data, extracting cavity environment characteristics, and establishing a three-dimensional model of a human body cavity in real time; human body cavity environment characteristics are analyzed, and local and global paths are generated; outputting the path to a catheterization robot controller, driving a catheterization robot, monitoring a navigation abnormal state in real time, and collecting and storing the path, the sensor state and operation data in the navigation process; the system comprises a data acquisition module, a data processing module, a three-dimensional model establishment module, a path generation module and a data monitoring module. Through the mode, the environment is comprehensively perceived, the navigation precision and the real-time performance are improved, and the high-precision operation requirement in a clinical complex environment is met.

The invention belongs to the field of computer vision, and particularly relates to a method, a device and a system for monitoring suction-scrabbling falling of a cleaning robot, and the method comprises the following steps: 1) a rear-view camera arranged on the cleaning robot collects suction-scrabbling images, and carries out data labeling; 2) building a deep learning labeling and training environment in a server or a workstation, selecting a YOLOv8 target detection network model, sending labeled suction and scrabbling image data into the model for training, and performing format conversion and quantization on the model after the training is completed; 3) inputting an image acquired in real time into the trained target detection model, and judging whether the suction rake falls off or not; (4) if the suction scrabbling device falls off, the upper computer sends falling abnormal information to a robot controller of the cleaning robot, and the robot controller controls a hub motor to brake emergently; and meanwhile, the upper computer transmits the abnormal information of the suction-scrabbling falling and the position coordinate information of the robot in the global map to the operation and maintenance personnel through the cloud platform and then transmits the abnormal result and the position information of the suction-scrabbling falling to the operation and maintenance personnel.

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 belongs to a robot navigation method, and aims to solve the technical problems of difficulty in establishing a geometric map in a non-structural scene, dependence on tags from laser radar data, easiness in ignoring long-distance features and slow reasoning time in the conventional navigation or exploration method. According to the robot visual navigation method based on comparative learning and the related device, after current observation is obtained, the current observation is input into a trained observation encoder to obtain a corresponding feature vector, and then a pre-selected batch action sequence passes through an action encoder to extract the corresponding feature vector; and calculating the similarity between the current observation and each action sequence through a vector inner product, selecting the action sequence with the highest similarity, and inputting the selected action sequence into a robot controller for controlling the robot to execute corresponding actions. Compared with a method for directly generating the action sequence, the method has the advantages that the difficulty of selecting one action sequence is lower, and the expansibility and generalization are better.

The invention relates to the field of rail traffic intelligent control, and discloses a rail obstacle real-time detection and braking system based on multi-sensor redundancy, which comprises at least two groups of sensing modules arranged at the front end and the rear end of a train, and each group of sensing module comprises a laser radar used for collecting three-dimensional point cloud data of a forward or backward rail area of the train; the binocular camera is used for acquiring color image data and depth image data in corresponding directions; and the robot controller is in communication connection with the sensing module and is used for receiving sensing data acquired by the laser radar and the binocular camera and executing obstacle recognition, redundant information fusion and brake control logic. By constructing a multi-sensor redundancy sensing structure based on the laser radar and the binocular camera, high-robustness recognition of a dynamic or static obstacle target in a complex orbit environment is realized, and the effect of remarkably improving the obstacle detection accuracy and the false alarm suppression capability is achieved.

Systems and methods for mounting a solar panel are provided. The method includes obtaining an image of the solar panel and the mounting structure during installation. The method further includes pre-processing the image by compensating for camera internal parameters or distortions, correcting the image, and / or determining depth information. The method further includes detecting the solar panel by inputting the image into a neural network. The method also includes a first post-processing to calculate a first panel pose based on the output of the neural network. The method further includes generating a control signal based on the first panel pose for operating a robot controller to install the solar panel. In some embodiments, the method further includes a homographic transformation to obtain a second panel pose based on the first panel pose and a visual pattern or reference on the solar panel, and further to generate a control signal based on the second panel pose.

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 present invention provides an automated assembly line for a gripper suction cup assembly. The automated assembly line comprises a seven-axis movement module equipped with a gripper thereon. Arranged around the seven-axis movement module are a vibratory bowl platform assembly, a feeding station, a glue application device, a tightening device, a vibratory bowl for suction cup fixing screws, a robot controller cabinet, and an assembly line control cabinet. The beneficial effects of the present invention are as follows: by replacing manual labor with robots and pneumatic components in the assembly of a gripper suction cup assembly, a fully automated assembly process for the gripper suction cup assembly is implemented, improving the assembly efficiency of the gripper suction cup assembly and enhancing the safety of the assembly process, enabling controllable assembly production by means of the cooperation between robots and sensors, saving production costs and labor costs, and eliminating potential safety hazards during operation.

The invention provides a training method and device for a quadruped robot controller based on reinforcement learning and electronic equipment, and the method comprises the steps: training a first controller according to first sensor data, first elevation map data and a first target control signal, and obtaining a trained first target controller; controlling the quadruped robot to execute a second target control signal in the simulation environment, and determining second sensor data, second elevation map data and RGB image data; constructing training data according to the target position information of each joint, the RGB image data, the second sensor data and the second target control signal; the to-be-trained second controller is trained according to the training data, and the trained second target controller is obtained, so that by using the RGB image data as visual perception information, the method can be more suitable for complex illumination and obstacle environments, and the quadruped robot can be more accurately and efficiently controlled.

A robot controller for controlling a robot arm includes a first space shaping module configured to provide a shaped first space target motion by convolving a first space target motion with an impulse train, where the first space target motion defines a target motion in a first reference space; a second space shaping module configured to provide a shaped second space target motion by convolving a second target motion with the impulse train; where the second target motion defines the target motion in a second reference space; and a motor controller module to generate motor control signals to the joint motors based on the shaped first space target motion and the shaped second space target motion.

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 embodiment of the invention discloses a method and device for determining trajectory data, a robot controller and a storage medium, and belongs to the technical field of computers. The method comprises the steps that in the process that a robot executes a target action on an object, action data of the robot are obtained, and the action data represent the state of the robot in the process that the robot executes the target action on the object; processing the action data through a trajectory prediction model to obtain trajectory data of the object; according to the method and the device, the trajectory of the object can be immediately predicted after the robot executes the target action on the object, and the condition that the object is predicted after being shot for a period of time through a motion capture sensor is not needed, so that the consumed time is saved, and the efficiency is improved; and the accuracy of the predicted trajectory data is ensured.

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.

The invention relates to a robot controller controlling a robot arm, the robot controller is configured to maintain the robot arm in a static posture when only gravity is acting on the robot arm and allow change in posture of the robot arm 5 when an external force different from gravity is applied to the robot arm. The free-drive mode of operation is activatable by a user establishing a free-drive activation signal to the robot controller, which in free-drive mode of operation is configured within at a free-drive safety period to allow a part of said robot arm to be moved within a virtual three-dimensional geometric shape 10 surrounding the part of the robot arm.

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.

A system for system for controlling a robotic welding system having a robotic welding torch manipulator and a welding power source, comprising a motion control interface configured for connection to one of a plurality of brands of robot controller of the robotic welding torch manipulator, a weld control interface configured for connection to one of a plurality of brands of welding power source, an image acquisition interface configured to receive image data from a camera positioned to capture real-time images of a welding operation, a user interface comprising a display for displaying images of the welding operation and at least one input device for receiving user commands specifying adjustments to the welding operation, and control circuitry comprising one or more processors configured to convert the user commands into configuration specifications for the robotic welding system, provide motion control adjustment instructions to the motion control interface utilizing a protocol for a selected one of the plurality of brands of robot controller, and provide weld control adjustment instructions to the weld control interface utilizing a protocol for a selected one of the plurality of brands of welding power source.

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 invention provides an event triggering safety guarantee control method and device of a teleoperation robot system, and relates to the technical field of teleoperation robot system control. The method comprises the following steps: establishing a teleoperation system with dynamic uncertainty and time delay under security constraints; constructing a virtual reference system for each manipulator in the teleoperation system; based on a virtual reference system, designing event triggering safety guarantee controllers for the master robot and the slave robot respectively, and giving event triggering conditions updated by the master robot controller and event triggering conditions updated by the slave robot quadratic programming problem solving and controller updating; the master robot and the slave robot are synchronized, and it is ensured that the state of the mechanical arm of the slave robot is within the safety set of the mechanical arm of the slave robot. The present invention discusses security critical control issues for teleoperation systems with unknown dynamics, time delays and event trigger mechanisms. Under the design of the invention, the safety of the slave robot in an unknown environment is ensured, and master-slave synchronization is realized.