13002results about "Manipulator" patented technology

A humanoid robot includes an upper region includes a head and neck assembly having a neck portion and a head portion coupled to the neck portion. Said head portion includes: a rear shell, and a frontal shell coupled to the rear shell to define a head volume between the frontal shell and the rear shell, and an electronics assembly with a display located in the head volume between the frontal shell and the rear shell. The frontal shell of the head housing assembly includes: a first arc length at a first location below the display, a second arc length at a second location aligned with a portion of the display, and wherein said second arc length is greater than the first arc length, and a third arc length at a third location above the display, and wherein said third arc length is greater than both the first arc length and the second arc length.

The invention relates to the technical field of man-machine interaction, in particular to a robot behavior mode dynamic adjustment method based on multi-mode perception, which comprises the following steps: S1, collecting a visual image, a voice signal and an environment parameter of a target scene in real time; s2, extracting each modal feature; s3, dynamically allocating weights, and generating a fusion feature vector; s4, identifying a current scene type and a user attribute; s5, matching a corresponding interaction mode from a preset strategy library based on the scene type and the user attribute identified in the step S4; and S6, executing the matched interaction mode in the S5, and updating the weight distribution rule according to the feedback data. According to the method, vision, voice and environment characteristics are fused through a multi-mode perception technology, the behavior mode of the robot is dynamically adjusted based on a self-adaptive weighted fusion algorithm, and the interaction strategy is optimized in combination with user feedback, so that the interaction accuracy and the intelligent level of the robot under different scenes and user attributes are improved.

To realize improvement of complicated task execution ability under unpredictable circumstance, understanding and execution of high-level abstract instructions, effective integration of multi-modal feedback, enhancement of ability to adapt itself to change of environment and uncertainty, efficient use of knowledge base, and securing expandability.SOLUTION: The present invention is directed to a robot control system which integrates a large-scale language model, retrieval-enhanced generation technique, a visual system, a force sense module, a voice recognition and synthesizing module, a multi-modal integration module, and a robot control system. A language processing component recognizes high-level instructions, and dynamically selects and adapts relevant examples from a knowledge base by using the retrieval-enhanced generation technique. The visual system generates a three-dimensional expression of an environment. The force sense module measures force of an end effector. The multi-modal integration module integrates information from different modalities to realize environment understanding and adaptive action generation. Thus, it is possible to adapt the system to execution of complicated tasks and change of the environment under an unpredictable environment.SELECTED DRAWING: None

The invention provides a comprehensive and intelligent mariculture net cage management and control system. The system integrates a multi-parameter sensor module, an underwater robot module, an underwater camera module, a central control module, a data storage and analysis module, an early warning module, a remote communication module and an automatic execution module. By monitoring multiple environmental parameters such as water temperature, salinity, dissolved oxygen and the like in real time and utilizing the underwater robot and the underwater camera to carry out autonomous inspection and fish behavior observation, the system can accurately master the culture environment condition. The AI algorithm and the intelligent model are combined, the system dynamically adjusts the bait casting amount, the oxygenation frequency and the net cage position, and the breeding benefits are effectively improved. Meanwhile, the early warning module carries out graded early warning on risk events such as typhoon and diseases, and the breeding safety is ensured. The remote communication and visual human-computer interface further enhances the remote monitoring and management capability of the system.

The invention discloses a robot anthropomorphic interaction method based on multi-modal emotion recognition and customized portrait generation. The method comprises the following steps: S1, dynamically fusing multi-modal emotions; the method comprises the following steps: S1, synchronously acquiring voice, visual and text signals through a multi-source heterogeneous sensor, capturing a user voice stream by a high-fidelity microphone array, and extracting acoustic characteristics such as intonation and speed, S2, performing cross-modal reasoning; s3, synchronously generating contents; step S4: style migration; step S5, anthropomorphic voice and expression generation; according to the method, man-machine interaction emotion is analyzed and generated by utilizing a large language model and multi-modal information fusion, the singleness of interaction emotion and the deficiency of emotional sharing ability are avoided, a strong emotion interaction characteristic is achieved, the image of the robot is obtained through a generative technology and can be migrated to any image, the limitation that a specific image is independently made is broken through, and the interaction effect of the robot is improved. The advantage that one robot can be suitable for different scenes is achieved.

Various systems and methods are described for obtaining compensation for tasks performed by a humanoid robot, where the humanoid robot is associated with a first party. The method includes a first party providing a humanoid robot for use in an operating location. The humanoid robot engaged in performing a plurality of tasks at the operating location. A third party compensates the first party with a specified amount of currency for a pre-determined time interval during which said humanoid robot has engaged in performing the plurality of tasks at the operating location.

The invention discloses a substation autonomous inspection and foreign matter cleaning cooperative control system and method, and belongs to the technical field of intelligent inspection and foreign matter cleaning. The system comprises a multi-modal detection module used for acquiring images, point clouds and multi-source sensing data and identifying foreign matter coordinates and visual features; the space positioning module is used for executing space registration to obtain a three-dimensional coordinate of the foreign body; the risk decision module fuses the multi-dimensional information and evaluates the foreign matter risk level; the cleaning execution module generates a cleaning path and execution parameters and issues the cleaning path and the execution parameters; and the inspection execution module plans inspection paths and actions based on the state and constraint conditions, and completes subsequent equipment inspection tasks. According to the scheme, the system realizes clear division of labor and accurate control in multiple stages of foreign matter identification, space positioning, risk assessment, cleaning instruction generation, polling after cleaning and the like, and the expansibility and the overall response efficiency of the system are improved, so that efficient, safe and stable execution of autonomous polling and foreign matter cleaning tasks of the transformer substation is guaranteed.

The invention relates to the technical field of robot decision making, and provides a robot multi-modal fusion autonomous decision making method and system based on a large language model.The method comprises the steps that a robot obtains multi-modal environment information through a visual sensor, a touch sensor, an auditory sensor and a laser radar which are carried by the robot; performing preliminary filtering and noise reduction processing on the original sensor data, and synchronously recording all the sensor data by timestamps; performing space-time semantic alignment on the preprocessed multi-modal data, mapping pixel coordinates of a target in a visual target coordinate quantization original image to a robot coordinate system, performing uncertainty evaluation on a multi-modal signal through a dynamic Bayesian network, and taking entropy or variance as an uncertainty quantitative evaluation index. According to the method, the information quality is improved from a data fusion source, accurate and reliable basic support is provided for subsequent decision making, and decision making errors caused by data deviation are greatly reduced.

The invention provides an intelligent inspection operation robot, which comprises a self-adaptive interaction assembly for collecting unstructured features in an inspection environment of the inspection operation robot in real time, converting continuous signals of the unstructured features into discrete interaction decision nodes, and generating an interaction parameter set capable of being iteratively optimized through a cross validation mechanism; the autonomous intention analysis component constructs a probabilistic decision-making program based on implicit features of an operator behavior track of the inspection operation robot, extracts a potential mode of an operation intention through nonlinear correlation analysis in combination with an interaction parameter set, and recognizes an interaction demand which is not clearly expressed; and the collaborative response component constructs a response decision mechanism with self-organizing characteristics, and jointly inputs an interaction parameter set and an interaction demand into the response decision mechanism by establishing a dynamic association rule between different interaction channels of the inspection operation robot and an operator to generate a composite interaction scheme. According to the method, the composite interaction scheme comprehensively considering multiple factors can be generated.

A solar panel installation system comprising a solar panel presentation system comprising a solar panel dispensing hopper having a hopper enclosure; and a solar panel installation vehicle operable with the solar panel presentation system, and operable to support the solar panel dispensing hopper, and to maneuver about a solar panel support assembly comprising one or more solar panel retention systems which can be oriented transverse to a torque tube of the solar panel support assembly, wherein the installation vehicle is operable to position the solar panel dispensing hopper in an overhead position relative to the one or more solar panel retention systems, and to facilitate installation of a lead solar panel in an installed position in one of the one or more panel retention systems from the overhead position.

Certain aspects of the disclosure generally relate to devices, systems, applications, and / or objects of applications, and may be generally directed to artificial learning and / or use of artificial knowledge. Other aspects of the disclosure generally relate to consciousness, and may be generally directed to learning and / or implementing one or more purposes. One or more purposes may drive the use of artificial knowledge in implementing the one or more purposes. Therefore, in some aspects, a conscious device, system, application, and / or object of application may include one or more purposes and artificial knowledge so that the device, system, application, and / or object of application can act upon a world in implementing the one or more purposes. The disclosure also describes other functionalities.

The invention relates to the technical field of robots, and discloses a robot nondestructive testing method and system based on artificial intelligence, and the method comprises the steps: obtaining multi-modal sensing data and motion state parameters; constructing a three-dimensional material feature model and analyzing to generate an initial defect feature evaluation model; loading material attributes and detection precision constraints to generate a comprehensive model, and combining motion parameter simulation to obtain path regulation and control data; training the dynamic defect prediction model to obtain a detection path correction model and generating initial detection parameters; obtaining dynamic correction simulation information based on the initial parameters and the like; constructing a multi-objective optimization model, and optimizing to obtain an optimal detection path parameter; and generating a safety detection probability by combining real-time model reasoning, and adjusting a detection strategy to realize dynamic path matching. The system comprises a data acquisition module, a feature modeling and analysis module, a comprehensive evaluation and simulation module and the like. The method improves the detection precision, efficiency and adaptability, and is suitable for nondestructive detection of complex targets.

The invention discloses a multi-modal fusion real-time environment monitoring visual robot system, and relates to the technical field of real-time vision. The system comprises a multi-mode sensing module, and is equipped with various sensors such as a binocular stereo camera and a laser radar to collect environment data. The heterogeneous data preprocessing unit cleans and downsamples data such as images and point clouds; the space-time alignment fusion module realizes multi-source data space-time registration and synchronization; the environment semantic understanding engine constructs an environment semantic graph through a multi-branch network in combination with an attention mechanism; the abnormal event detection unit identifies abnormity based on a historical data model; the path planning and decision-making module integrates multiple targets to generate an optimal path; the autonomous movement execution module controls the robot to move and operate; and the cloud cooperative control center supports model updating and remote intervention. According to the invention, through cooperative work of all the modules, full-process intelligentization of environment monitoring data acquisition, processing, analysis and decision making is realized.

The invention discloses a pole climbing robot for a wind power tower pole, which is characterized in that the robot mainly comprises a robot body, 4-8 pole climbing mechanisms, a snake-shaped swing arm and a movable studio, wherein the snake-shaped swing arm and the movable studio are mounted on one side of the robot body; the robot body is an annular body formed by combining two semicircular cambered bodies or three equal cambered bodies; the diameter of an internal ring of the circular body is matched with the diameter of the wind power tower pole; the pole climbing mechanisms mainly comprise upper foot wheels, lower foot wheels, connecting arms, driving gears, thrust screw rods, nut gears and supporting seats; the upper foot wheels are connected with the lower foot wheels by the connecting arms through wheel shafts; the connecting arms are connected with the thrust screw rods by connecting pin shafts on the connecting arms, and form movable hinges; the 4-8 pole climbing mechanisms are distributed in the circular robot body uniformly; the snake-shaped swing arm consists of three swing arm parts, namely a large arm, a middle arm and a small arm; and the movable studio comprises two paralleled linear guide rails, a walk driving device and an operation room.

The invention relates to the technical field of automatic manufacturing, and discloses a metal pipe part welding path intelligent planning and monitoring system which comprises a path planning module used for generating an optimal welding path according to the geometrical shape of a metal pipe part, welding process requirements and sensor feedback information; the sensor module monitors key parameters in the welding process in real time through a visual sensor, a thermal imaging sensor and a force sensor; the data processing and analyzing module is used for processing and analyzing the real-time data acquired by the sensor; the welding control module is used for controlling operation of welding equipment according to path planning and sensor feedback data; and the quality monitoring and feedback module is used for monitoring the quality in the welding process in real time. According to the system, the welding path is generated through the intelligent path planning module, and the path is dynamically optimized in combination with real-time sensor data, so that the accuracy of the welding process is improved, the system can adapt to changes in a complex welding environment, and the welding efficiency and quality are improved.

The embodiment of the invention provides a robot suitable for plant protection spraying operation in hills and mountains. The quadruped robot comprises a main body machine body and four independent leg structures which are connected to the main body machine body through joints and have multiple motion freedom degrees. The pesticide box is mounted on the main body; the pesticide pump is installed on the main machine body and comprises a pesticide suction opening and a pesticide injection opening, and the pesticide suction opening is communicated with a liquid outlet of the pesticide box through a first connecting pipeline; the mechanical arm is installed at the preset position of the main machine body through a base, the mechanical arm is in a multi-joint series connection mode, and the mechanical arm comprises a plurality of driving joints capable of rotating or swinging and a rigid connecting rod for connecting the joints. The stable moving and obstacle crossing ability is achieved through the four-foot structure, continuous pesticide supply is provided through the pesticide box and the pesticide pump, the precise spraying and metamorphic functions are achieved through the multi-degree-of-freedom mechanical arm, and therefore the excellent performance and effect are shown in plant protection spraying operation in hills and mountains.

The invention provides an intelligent spraying composite robot system based on a large language model and a method thereof, and relates to the field of intelligent robots and automatic spraying, the intelligent spraying composite robot system comprises a chassis, a mechanical arm, a spraying gun, a camera, an instruction receiver and a controller; a mechanical arm and an instruction receiver are carried on the chassis; spray guns and cameras are mounted on the mechanical arms; the instruction receiver receives a natural language voice instruction, analyzes semantics through a large language model, and generates an action instruction; the controller comprises a motion control module, a three-dimensional point cloud data acquisition module, a feature point extraction module, a track planning module and a spraying operation module; the method improves the man-machine interaction, reduces the use threshold of the robot, is easy to operate, gives play to the spraying advantages of the composite robot, does not need to program in mainstream offline simulation software, can generate a spraying path with adjustable and controllable parameters only by collecting the point cloud template of the workpiece and selecting the feature points, and can be widely applied to furniture, furniture and the like. And spraying operation in the fields of automobiles, aerospace and the like.

The invention discloses grinding equipment with a surface self-adaption function for civil aircraft maintenance, and relates to the technical field of grinding equipment, the grinding equipment comprises a grinding mechanism, a self-adaption mechanism and a positioning mechanism, the grinding mechanism is fixedly connected with the self-adaption mechanism, and the self-adaption mechanism is fixedly connected with the positioning mechanism. The grinding mechanism is used for driving a grinding disc to work, and flexible grinding of the surfaces of different areas can be achieved. The self-adaptive mechanism is composed of a self-adaptive assembly, an expanding and contracting assembly and a rotating assembly, the grinding disc has the flexible adjusting capacity when making contact with the surface of a workpiece, the expanding and contracting assembly achieves expanding and contracting, the rotating assembly drives an expanding and contracting block to revolve, and therefore the adaptability of the grinding disc on the complex curved surface is guaranteed. And the positioning mechanism is used for positioning parts needing to be maintained, so that the purposes of adapting to complex curved surfaces, improving the polishing precision and efficiency, avoiding the problem of difficult attachment and ensuring the maintenance quality and the operation safety are achieved.

The invention discloses a visual prediction method for space-time manifold and implicit state deduction of a robot, and relates to the technical field of robot space visual perception. The motion state and the visual image of the robot are collected; calculating carrier pose offset and generating a reverse compensation matrix; modeling an image target into a visual cone probability manifold, and extracting an explicit manifold observation vector; monitoring the confidence coefficient in real time through an observation quality evaluation network, and activating an implicit deduction mode during observation degradation; reading historical time sequence characteristics by using an improved Transform model, and performing prediction and deduction on a future nonlinear motion state of the target; performing coordinate correction and probability field decoding on a prediction result in combination with the reverse compensation matrix, and outputting a three-dimensional prediction trajectory and a spatial covariance ellipsoid; according to the method, the problem that traditional visual tracking fails under the conditions of violent shaking of a carrier and target shielding is solved, and continuous and foresight physical scale positioning and safety decision making of a robot on a dynamic target are achieved.

The invention discloses a self-adaptive control method for operation of a coupler unhooking robot under multiple working conditions, and relates to the technical field of coupler unhooking, and the method comprises the steps: obtaining a target unhooking robot, and collecting and obtaining an operation environment data flow and a coupler state data flow; working condition sensing and coupler recognition are conducted, and the current working condition and coupler feature information are obtained; performing traversal retrieval and adaptive adjustment in the unhooking strategy database, and determining target unhooking strategy parameters; and executing unhooking operation according to the target unhooking strategy parameters, and performing adaptive closed-loop control and abnormal emergency control on the target unhooking robot based on the unhooking operation state data flow. The technical problems that in the prior art, a car coupler unhooking robot is difficult to adapt to complex and various working conditions, and consequently the unhooking operation accuracy, safety and efficiency are poor are solved, accurate sensing of the working conditions of the car coupler unhooking robot is achieved, and the technical effect of improving the unhooking operation accuracy, safety and efficiency is achieved.

The invention discloses a robot fault diagnosis method and device, electronic equipment and a storage medium. The method comprises the following steps: acquiring an abnormal description of a robot; fault reasoning is carried out on the abnormal description based on a preset fault tree and a preset reasoning rule, a first fault diagnosis result is obtained, and the first fault diagnosis result comprises the initial weight of each fault reason; based on a preset neural network model, performing mode recognition on the anomaly description to obtain a second fault diagnosis result, the second fault diagnosis result including a prediction weight of each fault cause; and carrying out weighted fusion on the initial weight and the prediction weight to obtain a comprehensive weight of each fault reason, and determining a target fault diagnosis result according to the comprehensive weight of each fault reason. According to the method, the possible fault causes and the comprehensive weight of each fault cause are deduced by combining the fault diagnosis result obtained by the preset fault tree and the fault diagnosis result obtained by the preset neural network, so that the accuracy of fault diagnosis is greatly improved.

The invention discloses a full-size integrated humanoid robot which comprises a trunk mechanism, arm mechanisms arranged on the left side and the right side of the upper end of the trunk mechanism, a hip mechanism arranged at the lower end of the trunk mechanism and leg mechanisms arranged at the left end and the right end of the hip mechanism. The driving modules of the arm mechanisms and the leg mechanisms are mounted in the inner cavities of the corresponding curved-surface metal shells through bolts respectively; the hip mechanism comprises a hip assembly and hip curved surface shells installed on the front side and the rear side of the hip assembly. The hip assembly comprises a hip base connected with an output shaft of a trunk driving module of the trunk mechanism. Hip driving modules are symmetrically arranged at the left end and the right end of an inner cavity of the hip base; a control circuit board of the hip driving module is arranged on the top of the hip base through a fixing plate. On the basis of replacing a traditional shell and a skeleton with the curved metal shell, the size of the hip mechanism is reduced, the assembly steps are simplified, the light weight of the humanoid robot is achieved, and the requirement for structural strength is met.

The invention relates to a robot environment perception method based on single-view three-dimensional scene generation, and the method comprises the steps: collecting a two-dimensional image containing target environment information through employing a monocular camera, generating multi-view information through combining depth estimation, normal prediction and a two-stage semantic guidance diffusion model, and constructing a high-quality three-dimensional scene. And reconstructing three-dimensional point cloud data through the neural radiation field, and performing texture rendering optimization on the point cloud data. A Point Net + + network is used for carrying out semantic analysis on point clouds, a multi-frame time sequence point cloud registration and Kalman filtering tracking method is introduced, modeling is carried out on a dynamic target, and a dynamic semantic map with a motion state is constructed. And finally, structured output environment information is used for robot navigation, path planning and task execution. The problems of high cost, high complexity and insufficient real-time performance and robustness of a three-dimensional scene generation technology in the field of robot environment perception are solved, and the method is high in structuring degree, standard and unified in output format and high in universality and engineering adaptation capacity.

The invention discloses a locating weld robot system based on active and passive visual sensing, and relates to the technical field of robot welding, the locating weld robot system comprises a weld tracking module, the weld tracking module is used for monitoring a weld and a welding state and adjusting the position of a welding gun; the welding seam tracking module comprises a visual sensing unit, a deviation detection unit and an automatic deviation correction unit, the visual sensing unit is connected with the deviation detection unit through Bluetooth, and the deviation detection unit is connected with the automatic deviation correction unit through Bluetooth. By designing the welding seam tracking module, the automatic welding seam positioning function is achieved, the problem of welding seam position deviation is solved, the welding quality and efficiency of the welding seam robot are improved, and active and passive vision fusion is achieved.

The invention discloses a rotating wheel nondestructive testing robot and a testing method thereof, and belongs to the technical field of specialized robots and nondestructive testing. The rotating wheel nondestructive testing robot comprises a permanent magnet adsorption walking mechanism, a multi-degree-of-freedom mechanical arm, a module flaw detection unit, a multi-sensor positioning system and a central controller; the adsorption walking mechanism is used for realizing all-attitude stable crawling on the curved surface of the rotating wheel; the multi-degree-of-freedom mechanical arm is arranged above the middle part of the permanent magnet adsorption walking mechanism and is used for moving the module flaw detection unit to a specified position; the module flaw detection unit is used for performing high-resolution detection on the damage of the composite material on the rotating wheel; the multi-sensor positioning system is used for real-time pose feedback of the robot; the central controller is used for controlling all the components to work cooperatively. According to the nondestructive detection robot for the runner and the detection method thereof, the problems that in the prior art, detection of internal cracks of turbine runner blades depends on a manual frame erecting mode, the high-altitude operation risk is large, the number of detection blind areas is large, and efficiency is low can be effectively solved.

A method and computing apparatus are disclosed for allowing a tidying robot to organize objects into non-standard categories and deposit them at non-standard locations that match a user's needs. The tidying robot navigates an environment using cameras to map the type, size, and location of toys, clothing, obstacles, furniture, structural elements, and other objects. The robot comprises a neural network to determine the type, size, and location of objects based on input from a sensing system. An augmented reality view allows user interaction to refine and customize areas within the environment to be tidied, object categories, object home locations, and operational task rules controlling robot operations.

The invention provides a water surface target grabbing system and a control method thereof, and relates to the technical field of marine operation equipment. The system comprises an unmanned ship and a cooperative mechanical arm, the unmanned ship and the cooperative mechanical arm share a processor; the unmanned ship supplies power to the cooperative mechanical arm; the unmanned ship is positioned through an inertial navigation system on the unmanned ship and a scene camera and a depth camera on the cooperative mechanical arm; a scene camera, a depth camera and an integrated sensor on the cooperative mechanical arm transmit data to a processor on the unmanned ship through a local area network, the processor calculates and analyzes the data transmitted by the scene camera and the depth camera, and an action instruction is sent to the cooperative mechanical arm through a CAN bus. According to the water surface target grabbing system, automatic grabbing is achieved, and the grabbing precision, stability and adaptability of the system in the dynamic marine environment are improved.

The invention discloses a whole-course accompanying robot for disabled old people and an automatic control system of the whole-course accompanying robot, relates to the technical field of intelligent accompanying, and is used for solving the problems of inaccurate positioning, untimely task response and poor service continuity in the accompanying process of the disabled old people. The multi-modal perception and state analysis module divides the accompanying environment into a plurality of sub-regions based on region characteristics, and accurately perceives the position and state change of the disabled elderly. And the task generation and scheduling execution module intelligently judges service requirements of disabled old people, and dynamically screens optimal robot resources for task matching and execution. The task feedback closed-loop module collects and analyzes task execution process and result data, and timely rechecks the state of the old person according to feedback. And the self-control module adjusts the accompanying strategy and periodically reviews the priority of the task queue. Through cooperative operation of the above modules, the system can achieve precise perception, intelligent decision and dynamic optimization of accompanying of disabled old people, and remarkably improves continuity, intelligence and reliability of accompanying service.

The invention relates to an underwater cleaning robot positioning and tracking method. Positioning comprises the steps that data of multiple sensors on an underwater cleaning robot are fused through an extended Kalman filter, and coordinates of the underwater cleaning robot on the surface of a ship body are obtained after sensor measurement noise is filtered through a first-order low-pass filtering algorithm. The tracking method comprises the step of realizing the path tracking of the underwater cleaning robot based on the positioning method in combination with an iterative linear quadratic regulator (ILQR). According to the invention, a multi-sensor fusion scheme of the encoder, the IMU and the depth meter is innovatively provided, and the positioning problem of the underwater cleaning robot in a wall attaching state is solved. And double-plane differential treatment is adopted, so that the working state of the robot on the ship wall or the ship bottom is better fitted, and positioning is more accurate. A target point updating mechanism of geometric distance constraint is provided, the nearest neighbor point of the reference trajectory is adjusted in real time, and the problem of tracking lag caused by updating rate mismatch in a traditional method is solved.

The invention relates to an emotion accompanying robot system based on multi-dimensional perception and an interaction method, and belongs to the technical field of intelligent robots. The system comprises a sensing module which captures micro-expression, voice, body temperature, touch and other multi-source data through a biological radar array, multispectral imaging and a touch sensing fabric; the decision-making module quantifies the emotion intensity by using an emotion state calculation engine, constructs a user personalized emotion file in combination with the dynamic knowledge graph, and generates a dynamic emotion graph; and the execution module realizes anthropomorphic emotion expression through bionic face driving, joint compliance control and thermal feedback. The interaction method comprises the steps of data capture, emotion file construction, dynamic graph generation, interactive execution and feedback adjustment, definition of an emotion intensity quantification formula, a graph edge weight model and the like. According to the method, physiological signals, environment situations and bionic expression are fused, multi-modal precise emotion perception and safe interaction are achieved, man-machine naturalness is improved, the method is suitable for elderly accompanying, psychological counseling and other scenes, and the emotion accompanying effect is enhanced.