59 results about "Robots actuators" patented technology

The invention is suitable for the technical field of artificial intelligence, and provides a robot visual navigation optimization system based on edge computing, the system comprises a visual sensor module, an edge computing unit, a navigation algorithm module, a communication module and a robot executor, the visual sensor module is used for collecting high-definition images or video streams, and the edge computing unit is used for processing the high-definition images or video streams; the edge calculation unit is responsible for locally executing a visual navigation algorithm, the navigation algorithm module is deployed on the edge calculation unit, and the navigation algorithm module is used for executing a visual odometer, synchronous positioning and map construction, environment perception, obstacle detection, local path planning and motion control; and the communication module is used for carrying out model updating, task scheduling and non-real-time data uploading with a cloud. Complex visual data processing and navigation decision are sunk to the robot body or near-end edge equipment, so that the navigation precision and the response speed of the robot in complex and diversified environments are remarkably improved, and the energy consumption efficiency is optimized.

The invention relates to the technical field of robot control, and discloses a robot hybrid intelligent adaptive control method and system adopting reinforcement learning, and the method comprises the steps: collecting environment perception parameters, and constructing a dynamic environment model; setting and testing a robot execution mechanism dynamic model, and obtaining motion characteristics of the robot execution mechanism; integrating the dynamic model into the dynamic environment model; calculating a task demand parameter and a theoretical control load, and generating a control quantity in combination with motion characteristics; a driving unit action instruction is generated based on the control quantity and control is carried out; and evaluating the execution effect. The system comprises a dynamic environment model construction module, an execution mechanism dynamic model construction module, a model fusion module, a task parameter calculation module, an action instruction generation module, an action control module and an execution effect evaluation module. According to the invention, high-precision self-adaptive control of robot operation in a complex dynamic environment is realized, and environmental adaptability and task execution efficiency are improved.

The invention discloses a multi-robot path coordination system based on reinforcement learning, and the system comprises a state collection module which is used for collecting the operation state and environment perception information of each robot, and generating an original data set; the state modeling module is used for constructing local state representation for each robot in each decision period; the opponent perception module is used for executing opponent learning perception training and outputting opponent parameter estimation vectors; the improved LOLA module is used for generating a final estimation result on the basis of self-strategy updating of the traditional LOLA; the strategy updating module is used for correcting the updating direction of the reinforcement learning strategy of the local machine and generating a feasible action set; the arbitration decision module is used for executing arbitration solution in combination with the candidate path action distribution to generate a scheduling result; and the execution feedback module is used for issuing the control action to a robot executor for execution, generating a path coordination result and storing the path coordination result. According to the invention, path coordination of multiple robots is realized.

The invention provides a dynamic walking exoskeleton control method and system based on man-machine complementary optimization, and the method comprises the steps: defining the step height and normal contact force of a contact point, and constructing a nonlinear complementary problem constraint and model; defining quantitative targets of nine types of motion tasks including contact point centroid position tracking, centroid linear velocity tracking, foot yaw angle alignment, frame attitude tracking, base quaternion derivative regularization, contact force regularization, joint regularization, swing height control and contact control regularization, and establishing a multi-task target function; a static nonlinear complementary problem is coupled with exoskeleton continuous dynamics, and a coupling system is constructed; solving the optimization objective function by adopting a neurodynamics algorithm to obtain the optimal control input of the exoskeleton-human body system; and the control input mapping obtained through optimization is converted into a driving instruction of a robot actuator, and a motion control closed loop is completed. According to the method, the complex movement requirements under strong coupling constraint interaction of the humanoid and the robot can be more accurately met.

An artificial intelligence-based business management system for real-time decision optimization, consisting of: a data acquisition unit configured to ingest structured, semi-structured and unstructured data streams from enterprise resource planning (ERP) systems, customer relationship management (CRM) platforms, Internet of Things (IoT) devices, external market feeds and financial transaction systems, encrypting, timestamping and verifying the data prior to further processing; a graph processing unit that is communicatively connected to the said acquisition layer, wherein the unit is configured to encode heterogeneous data into dynamic graph structures comprising nodes representing business entities and edges representing transaction or relationship dependencies, wherein the unit is further configured to perform deduplication, metadata tagging and real-time data synchronization; a decision optimization unit operationally linked to the graph processing unit, wherein the decision optimization unit includes modules for reinforcement learning, modules for Bayesian optimization and multi-objective solvers configured to simulate multiple alternative decision paths and select an optimal path based on performance indicators such as cost efficiency, resource utilization, customer satisfaction and risk minimization; a real-time inference control unit with specialized hardware cores, including at least one graphics processing unit (GPU), a field-programmable gate array (FPGA) and an application-specific integrated circuit (ASIC), wherein the accelerator performs inference tasks of the decision optimization unit with a latency in the millisecond range; a diagnostic processing unit configured to generate causal diagrams, feature mapping maps, and interpretable result summaries according to the optimization outputs; and a control interface unit configured to transmit optimized decisions to process controls within the enterprise, robot actuators, planning systems or interactive dashboards, with the interface supporting bidirectional communication for higher-level interventions, error feedback and triggers for re-optimization.

The invention belongs to the technical field of robot control, and discloses a foot-arm multi-task control method and system based on time-varying terminal cost, and the method comprises the steps: generating a whole-body reference trajectory of a robot offline, and pre-calculating a time-varying terminal cost matrix sequence based on the reference trajectory; based on the time-varying terminal cost matrix sequence, constructing and solving a nonlinear model predictive control optimization problem to obtain an optimization sequence of a system state and control input; and the optimization sequence serves as a reference instruction and is input into a layered whole-body controller for multi-task priority optimization, and a joint control instruction is generated and output to a robot execution mechanism. According to the method, the problem of short vision of a traditional NMPC in a long-time task is effectively relieved, and the operation precision of the robot is remarkably improved.

The present invention describes a system and control method for rumen in-vitro fermentation, said system comprising: -a bionic rumen with a drive module for controlling its movement; -a bionic reticulum with an external extrusion mechanism for regulating its motion; -a connecting structure linking the bionic rumen and bionic reticulum; -a control method that coordinates the movements of the rumen and reticulum to regulate the fermentation process. The bionic rumen and bionic reticulum are interconnected, enabling simultaneous biomimetic digestion and fermentation. By employing soft robotic actuator, the system effectively simulates the kneading and relaxation of the rumen, closely replicating natural digestive mechanics and fermentation kinetics. A real-time monitoring system has been integrated, allowing for online measurement of key parameters such as gas production and composition, thereby enabling more precise analysis of degradation kinetics. This invention provides an advanced research tool platform for ruminant nutrition, enabling improved digestion modeling accuracy. It also delivers significant environmental and economic benefits, including reduced methane emissions and enhanced feed utilization, thereby promoting sustainable livestock production.

The invention relates to the technical field of robot motion control, and discloses a robot adaptive motion control method and system, and the method comprises the steps: obtaining the environment parameters and motion state parameters of a robot; constructing a terrain fitness evaluation factor based on the terrain feature data, calculating a dynamic compensation coefficient based on the load variation, determining an environmental disturbance error according to the deviation between the external disturbance force information and a preset disturbance threshold, and determining a motion trajectory error according to the offset between the end effector pose and the target trajectory; inputting the joint angle, the centroid acceleration, the terrain fitness evaluation factor, the dynamic compensation coefficient, the environmental disturbance error and the motion trail error into an adaptive strategy model, and generating a gain adjustment instruction of a PID controller; and according to the gain adjustment instruction, the proportional term coefficient, the integral term coefficient and the differential term coefficient of the PID controller are updated, a self-adaptive control instruction is generated, and a robot execution mechanism is driven to move. According to the invention, the motion stability, precision and efficiency of the robot in changeable scenes can be improved.

The invention discloses a liquid crystal elastomer structure multi-objective optimization method based on depth evolution mapping. According to the method, by constructing a mapping model from individual features to operator parameters, an optimization algorithm can adaptively adjust the intensity of crossover and mutation operations according to the position, fitness ranking and neighborhood features of each candidate solution in a search space, so that the local refining effect is enhanced while the global exploration capability is kept. Compared with an existing parameter adjusting method based on a unified parameter strategy or population statistics, the method has the advantage that self-adaptive optimization of an individual level is realized. The method belongs to the cross technical field of computational material science, intelligent optimization algorithms and structural design, can be applied to the performance optimization problem of intelligent material systems such as soft robot drivers, artificial muscles and flexible sensors, and can also be popularized to other engineering design scenes involving high-dimensional parameter space and multi-target tradeoff.

The invention relates to the technical field of robot actuators, and particularly discloses an integrated joint module with torque sensing and energy self-recovery functions and a design method. The design method comprises the steps that a physical framework of the joint module is constructed; a nonlinear elastic torsion model and a dynamic friction model of the harmonic reducer are constructed, and torque is calculated and derived; calculating a physical sampling torque; fusing the derived torque and the physical sampling torque by adopting an adaptive Kalman filtering mode to obtain a final torque signal; an energy feedback model in a motor braking mode is constructed, and when the joint module decelerates or is dragged by external force, the instantaneous flow of recyclable electric energy is calculated in real time based on the energy feedback model; a super capacitor and a DC-DC converter are introduced for energy recovery; and when the joint module is started or enters an acceleration stage, the energy stored by the super capacitor is released to the direct current bus. Nonlinear transmission interference caused by a harmonic reducer can be effectively eliminated, and in-situ recovery and peak power assistance of braking kinetic energy can be achieved.

The invention relates to the technical field of robot hand control, and discloses a multi-camera-based robot hand positioning and musical instrument playing control method and system, and the method comprises the steps: obtaining a global image through a head camera, and providing a hand rough position; the fingertip camera obtains a local image and provides fine positioning of a target; fusing coarse and fine positioning, calculating a relative position, and planning a motion track; a robot execution mechanism is controlled to execute the track to complete playing; monitoring an actual position, calculating an error, and correcting a joint when the error exceeds a threshold value; the system comprises a head camera module, a fingertip camera module, a visual fusion module, a control module, a robot execution mechanism and a feedback and correction module. According to the invention, by acquiring the high-resolution local image and combining the global rough position information provided by the head camera module, effective combination of rough positioning and fine positioning is realized, and the problem that single global vision is easily blocked by hands or the precision is insufficient due to long distance is effectively overcome.

Tool (108) for fixing an energy direction sensor (100) for joining thermoplastic components (104) by ultrasonic welding, wherein the tool (108) has an ultrasonic input, a contact wheel holder (112) and at least one contact wheel (116) rotatably arranged on the contact wheel holder (112) with a structured contact surface (118); tool arrangement (102) for positioning, applying and / or fixing an energy direction sensor (100) for joining thermoplastic components (104) by ultrasonic welding, wherein the tool arrangement (102) has at least one receptacle (106) for a ribbon and / or film-shaped energy direction sensor (100) and such a tool (108); effector for a robot, wherein the effector has such a tool (108) and / or such a tool arrangement (102); and use of such a tool (108) and such a tool arrangement. (102) and / or such an effector,wherein, using the tool (108), the tool arrangement (102) and / or the effector, an energy direction transmitter (100) for joining thermoplastic components (104) by ultrasonic welding is positioned, applied and / or fixed.

A magnet mount for a robotic actuator is disclosed. According to one aspect of the present invention, a magnet mounting base for a robot actuator, which is assembled on the output side of the robot actuator and coupled to a rotating plate, comprises: a mounting member which is coupled to the lower part of the inner surface of the plate and rotates, and which has a hollow cylindrical shape; the magnet part is attached to the outer periphery of the lower part of the mounting part and is made of a magnetic material; wherein an attachment area to which the magnet component is attached is formed on the outer side of the mounting component, and a pattern part with a certain pattern is formed on the attachment area.

The application provides a dynamic walking exoskeleton control method and system based on human-computer complementary optimization, comprising the following steps: defining the step height of the contact point, the normal contact force, constructing the nonlinear complementary problem constraint and model; defining the centroid position tracking of the contact point, the centroid linear velocity tracking, the foot yaw angle alignment, the frame attitude tracking, the base quaternion derivative regularization, the contact force regularization, the joint regularization, the swing height control, the contact control regularization, 9 types of motion task quantization targets, and establishing a multi-task objective function; coupling the static nonlinear complementary problem with the exoskeleton continuous dynamics to construct a coupled system; solving the optimization objective function by using a neural dynamics algorithm to obtain the optimal control input of the exoskeleton-human system; and mapping and converting the control input obtained by optimization into the driving instructions of the robot executor to complete the motion control closed loop. The application can more accurately adapt to the complex motion requirements under the human-robot strongly coupled constraint interaction.

The invention discloses a collimation direct-drive actuator high-fidelity torque estimation method based on increment width learning, and belongs to the technical field of robot actuator torque estimation, and the method comprises the following steps: S1, collecting multi-dimensional state parameters, and constructing a data set; s2, obtaining weights of a feature layer and a top layer according to the data set in the S1, and constructing a basic width learning model; s3, based on the basic width learning model in the S2, when a new data set is obtained, using an incremental learning algorithm to update weights of a feature layer and a top layer, and obtaining an updated model; and S4, deploying the model to a torque control system, and constructing closed-loop control. By adopting the high-fidelity torque estimation method for the collimated direct-drive actuator based on increment width learning, the representation capability can be improved, the estimation precision can be ensured, the training overhead can be reduced, the model can be updated in real time to adapt to dynamic working conditions, high-precision estimation can be realized without an additional torque sensor, and actuator control can be effectively supported.

To provide a robot that can improve calibration accuracy of a rotation sensor for detecting movement of an actuator of the robot.SOLUTION: A robot has a connection frame (63) which supports a rolling actuator. The connection frame (63) has a first fitted part (63g) which is fitted to a rotary output part (12c) of the actuator (12), and a remainder (a first arm part (63b), a support part (63a), a second arm part (63c)) that is connected to the first fitted part (63g). a sensor rotation part (16a) of a rotation sensor (16) is fitted to the first fitted part (63g). In the state that the first fitted part (63g) is fitted to the rotation output part (12c) and the remainder of the connection frame (63) is removed from the first fitted part (63g), the first fitted part (63g) and the rotation output part (12c) can rotate through an angle greater than 360 degrees.SELECTED DRAWING: Figure 8

The embodiment of the invention provides an actuator and a robot. The actuator is suitable for driving the robot to execute actions and comprises a body and two driving mechanisms. The driving mechanisms are arranged on the two opposite sides of the body respectively, each driving mechanism comprises a planet wheel set, a power output assembly and a power source, and the power output assembly comprises a first power output ring and a second power output ring. Power output by the power source is output to a connecting rod mechanism of the robot through the planet wheel set and the power output assembly, so that the waist of the robot acts. Therefore, in the embodiment of the invention, through the driving change of the two driving mechanisms, the four power output rings can act synchronously or asynchronously, so that the waist of the robot generates actions close to the waist of a real human body, such as bending or swinging the waist.

This invention discloses a robot actuator with autonomous feedback and rapid deformation. It includes actuators mounted on the legs at the bottom of the robot. When the robot lands on a landing platform, the actuators adjust the tilt and shorten / extend of the legs to achieve a smooth landing. The actuator comprises a housing, tilt adjustment structures, shortening adjustment structures, extension adjustment structures, and front and rear transmission rods and adjustment plates. The transmission rods contact and output applied pressure and sense the shape of the external contact surface, transmitting pressure changes to the tilt, shortening, and extension adjustment structures. This invention can automatically sense and feedback the shape and pressure of the external contact surface, automatically deform, and adapt to the tilt of the external contact surface, solving the problems of lack of sensing and difficulty in adaptation between the robot and the external contact surface.

The present invention provides a control system for a building waterproof coating spraying robot applied to open flat sites, comprising a control terminal, a local human-machine interface, a remote teleoperation unit, a motor drive unit, a robot actuator, a data acquisition unit, and an alarm unit. The motor drive unit comprises: a steering gear drive module, a first servo motor driver, a second servo motor driver, a first DC motor driver, a second DC motor driver, a third DC motor driver, and a fourth DC motor driver, respectively connected to the control terminal; the robot actuator comprises: a steering gear, a first servo motor, a second servo motor, a first DC motor, a second DC motor, a third DC motor, a fourth DC motor, a first solenoid valve, and a second solenoid valve. The present invention can enable the robot to move straight, turn, and turn in place in a work site, thereby improving the robot's movement flexibility and enhancing work efficiency.

The present disclosure provides a method and system for impact force suppression based on power detection. The method detects the contact force received by the end of the robot actuator, obtains the contact force change x according to the contact force, generates the impact force suppression compensation of the end of the actuator according to the contact force change x, and compensates the expected motion trajectory. Compared with the commonly used compliant control strategy, a different control strategy is adopted, the "dynamic" power is used as the input of the controller, a different power compensation module is designed, the synchronous adjustment is carried out through the forward input channel of the force closed loop controller, the impact vibration can be reduced, the larger contact force at the end of the robot can be suppressed, and the stability of the robot operation can be improved.

A magnet mount for a robot actuator is disclosed. According to an aspect of the present disclosure, the magnet mount includes a cylindrical mount member that is coupled to a lower inner side surface of a plate to rotate and has a hollow; and a magnet member that is attached along a lower outer circumference of the mount member and made of a magnetic material, in which an attachment area to which the magnet member is attached is formed on an outer side of the mount member, and a pattern part having a predetermined pattern is provided in the attachment area.

This invention relates to the field of magnetic code disk materials technology, specifically disclosing a magnetic code disk material for humanoid robot actuators, its preparation method, and its applications. The magnetic code disk material for humanoid robot actuators comprises a substrate, a Bi layer, an AlNiFeCo thin film, an Nb layer, and a Ta layer stacked sequentially. The novel structural design provided by this invention introduces a dual-intercalation cladding structure of Bi and Nb layers, which synergistically act on the AlNiFeCo thin film, meeting the application requirements of high-precision magnetic encoder code disk materials for high coercivity and high remanence. Simultaneously, the element diffusion is a diffuse pinned network distribution, which is beneficial for obtaining uniform and consistent high-quality sine wave signal output performance during code disk writing. The magnetic code disk material prepared by this invention is suitable for the preparation of high-performance, high-uniformity magnetic code disk materials and high-precision, miniaturized magnetic encoder technology, and has excellent application prospects in humanoid robot actuators.

The application discloses a multi-object-oriented action sequence generation system and method and a robot control method, relates to the technical field of artificial intelligence, and solves the technical problems of target selection deviation and operation failure caused by perception attention drift and strategy lazy learning in a multi-object scene.The technical solution points are that a perception grounding expert module performs explicit space coordinate regression on the extracted fusion feature map, and outputs the normalized boundary box coordinates of the target object;then the coordinates are encoded into independent anchor token, and a decoupled input sequence of visual token, state token, anchor token and action token is constructed;the decoupled input sequence is modulated, and finally the anchor token is forced to be queried by the action expert module in each denoising step, so that a short-time action block sequence of the precise anchor target is generated and delivered to the robot executor to drive the current operation step.The target selection accuracy in the multi-object interference task is improved, and the instruction following robustness and operation success rate are enhanced.

The utility model relates to the technical field of robots, in particular to a robot actuator driving board, which comprises at least one power supply and communication interface connected with a power supply and / or a controller; and the at least one actuator interface is connected with at least one actuator. The robot actuator driving board is in direct insertion connection with the actuator through the interface, a cable between the robot actuator driving board and the actuator is omitted, the problem of complex structure caused by wiring is solved, the integration degree of the actuator is improved, the actuator driving structure is simplified, the cost is lower, and the control stability is higher.

The invention discloses an artificial pneumatic muscle based on electromagnetic driving and a robot actuator. The artificial pneumatic muscle comprises an electromagnetic head, a compression device and a woven mesh body. One end of the electromagnetic head is fixedly connected with one end of the compression device; the compression device is of a rigid body structure and comprises a piston cylinder and a piston arranged in the piston cylinder and driven by electromagnetism. The woven mesh body covers the outer side wall of the compression device, and forms a closed air cavity together with the piston cylinder; compressed air with pre-tightening pressure is pre-filled in the closed air cavity; when the electromagnetic head generates electromagnetism, the piston is driven to move in the piston cylinder in a reciprocating mode so as to change air pressure in the closed air cavity and drive the woven mesh body to contract or stretch in the axial direction. The problems that a pneumatic muscle system is heavy and poor in portability are solved, and a new-generation flexible driver is achieved.

This invention belongs to the field of collaborative robot automation control, specifically a collision detection method for collaborative robots based on decision trees. It includes the following steps: constructing a kinematic model for the robot; performing singularity analysis on the kinematic model to remove cases where the robot is located at singular points; obtaining the robot's theoretical torque based on kinematic gravity compensation theory; training the decision tree model using robot actuator data and the robot's theoretical torque; and inputting real-time robot actuator data and theoretical torque into the trained decision tree model to determine whether a collision has occurred at the current moment. This invention's machine learning algorithm based on decision trees uses velocity, acceleration, real-time torque, theoretical torque, and the derivative of real-time torque as judgment criteria, resulting in more comprehensive and accurate data consideration.

A robot, a robot actuator, and an actuator frame are disclosed. The actuator frame includes a base frame, a fixed base, an outer shaft, and an inner shaft. The base frame has motor mounting plates on its left and right sides, each with a fixed workstation for storage. An inverted U-shaped groove is formed between the two motor mounting plates. The inner shaft faces the Y-axis and is mounted in the inverted U-shaped groove. The fixed base has a rotating hole. One end of the outer shaft is rotatably connected to the rotating hole around the X-axis. The other end of the outer shaft is rotatably fitted onto the inner shaft around the Y-axis. The left and right sidewalls of the inverted U-shaped groove have sidewall openings, and the inner shaft has a hollow structure inside. The sidewall openings expose the hollow structure, forming a wiring channel between them. This solution enables the robot actuator to move in multiple directions (front, back, left, right), and also allows the wires to be internally placed within the wiring channel of the inverted U-shaped groove, avoiding the problem of wires becoming tangled around the shaft during multi-angle movement of the actuator.

The application provides a body intelligent control system, and belongs to the technical field of artificial intelligence. The system comprises: an external input module, which is used for receiving external input data in real time; a three-dimensional Gaussian field construction and maintenance module, which is used for constructing and maintaining a dynamic semantic three-dimensional Gaussian field in real time; a spatial language analysis module, which is used for analyzing natural language instructions, extracting operation entities, spatial relationship words and action words; a spatial relationship geometry anchoring module, which is used for determining a target three-dimensional area corresponding to the operation entities in the dynamic semantic three-dimensional Gaussian field; a three-dimensional action planning module, which is used for carrying out end-to-end action planning in the dynamic semantic three-dimensional Gaussian field, and generating a collision-free action trajectory; and an execution control module, which is used for converting the collision-free action trajectory into a control instruction sequence, and driving a robot executor to complete the operation corresponding to the action words.

An engineering system comprises a memory having instructions stored thereon and at least one processor configured to execute the instructions to cause the system to collect a plurality of tasks for a manipulator actuated by a motor. Structural parameters of the motor, a plurality of reference trajectories of the motor for actuating the manipulator to perform the plurality of tasks, and parameters of a feedback control policy for the manipulator are jointly determined to increase overlap between a probability distribution of values of operational data of the motor operating according to different real trajectories from a plurality of real trajectories and an efficiency map of the motor defined in a domain of the operational data of the motor. The structural parameters of the motor, the plurality of reference trajectories, and the feedback control policy are output for performing the plurality of tasks.