585 results about "Humanoid robot" 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 frontal shell having a rear edge, a rear shell having a frontal edge, and an illumination assembly. The illumination assembly is configured to illuminate a region that: (i) extends between a rear edge of the frontal shell and an extent of the frontal edge of the rear shell, (ii) is positioned adjacent to the extent of the rear edge of the frontal shell, and (iii) is positioned adjacent to the extent of the frontal edge of the rear shell.

The disclosure presents a humanoid robot with an upper region (head, torso, arms with forearm assemblies, end effectors), lower region (legs), and connecting central region. Each end effector features index, middle, ring, little finger, and thumb assemblies attached to a housing of said end effector. The housing includes interior wall extents creating spaces for tendon routing, where the first distance between first and second wall extents is less than 45% of the second distance between third and fourth wall extents. Tendons controlling finger movements pass between these wall extents. The robot incorporates a wrist assembly connecting the housing of the end effector to the forearm, actuators housed in the forearm that control the tendons, and a carpal tunnel-like structure that guides tendons from forearm to base of the housing, enabling precise hand movements without requiring actuators in the hand itself.

The invention discloses a multi-mode instruction analysis system for a humanoid robot. Comprising a voice input module, a visual input module, a voiceprint feature extraction module, an object recognition and pose estimation module, a multi-modal alignment network based on a space-time attention mechanism, a scene semantic tree construction module, an instruction node mapping module, a confidence evaluation module and a decision module. According to the system, accurate alignment of voice and visual information is realized through a space-time attention mechanism, environment information is represented in combination with a scene semantic tree structure, and the instruction analysis accuracy is improved. And dynamically evaluating the confidence coefficient by adopting a fuzzy instruction backtracking algorithm, and if the confidence coefficient is lower than a threshold value, starting multi-round dialogue clarification to reduce misoperation. According to the method, multi-modal data are fused, the historical interaction learning ability is optimized, the understanding efficiency and interaction robustness of complex instructions are remarkably improved, the method is suitable for scenes such as family service and logistics storage, and the intelligent level of man-machine cooperation is enhanced.

The invention discloses a deep learning-based arm trajectory planning method and control system for an intelligent humanoid robot with a body. The method comprises the following steps: acquiring a three-dimensional grid map of a multi-modal data construction environment; generating an initial feasible path through a path planning strategy network based on deep reinforcement learning; extracting the collision probability of each path node on the initial feasible path; according to the collision probability of each path node, judging an area in which local re-planning needs to be triggered; and carrying out smoothing processing to obtain a smooth obstacle avoidance path. The initial feasible path is generated through the path planning strategy network based on deep reinforcement learning. According to the collision probability of each node, an area needing local re-planning is screened out, and the path of the area is adjusted through an artificial potential field method, so that the capability of avoiding dynamic obstacles in the path planning process is improved, the collision risk in the path planning is reduced, and the path planning efficiency is improved. And the self-adaptive capability of the arm path planning complex environment of the intelligent humanoid robot with the body is improved.

The invention relates to a long-range task-oriented VLA model method for a humanoid robot, which comprises the following steps of: S01, analyzing a natural language instruction through a space-time semantic analyzer to generate an atomic operation sequence with a space-time dependency relationship; s02, maintaining a task state machine by using a dynamic memory network, and tracking the task execution progress in real time; s03, integrating vision, language and sensor data through a multi-modal perception fusion engine; s04, calling a predefined action primitive based on an adaptive execution system and optimizing a motion track; and S05, performing online updating and optimization on the model through a continuous learning mechanism. According to the method, a natural language instruction is analyzed into a structured task sequence with space-time dependence through a space-time semantic analyzer, an execution sequence and preconditions are defined, the semantic understanding ability and the structuring degree of task planning are improved, and task decomposition and replanning in a dynamic environment are supported; according to the method, the LSTM and the knowledge graph are combined, and the task state is maintained in real time.

The invention discloses an interaction test method for gait simulation of a humanoid robot, which is applied to a test platform. Comprising the following steps: controlling a current gait simulation model corresponding to a virtual robot to perform a gait simulation test in a virtual test environment in a current preset time period; the virtual test data is sent to the physical robot; controlling the physical robot to execute corresponding gait operation according to the virtual test data in the actual test environment, and sending the actual test data to the virtual robot; updating the current gait simulation model based on the virtual test data and the real test data; and continuing to perform the gait simulation test based on the updated gait simulation model, and ending the updating operation until the gait simulation test is ended, so as to generate a complete gait scheme. Therefore, by constructing a closed-loop interaction mechanism between the virtual robot and the physical robot, dynamic adjustment of the gait simulation model is achieved, the gait of the physical robot is restored, and the stability and precision of the gait of the physical robot are improved.

The invention provides a humanoid robot predictive control method based on redundancy degree of freedom constraint and a robot. The method comprises the steps of creating a first dynamic model of a biped lower limb system in the humanoid robot based on product parameters of the humanoid robot; according to the first dynamical model and a reference trajectory planned based on the motion task of the humanoid robot, control parameters of the biped lower limb system walking along the reference trajectory and corresponding control costs are predicted, and the control costs comprise the state cost and the input cost of the biped lower limb system; based on the control parameters, a cost function in a quadratic programming form is created, and the cost function comprises redundant joint constraint terms of the humanoid robot; determining an optimal control parameter of the humanoid robot based on the cost function and a first constraint condition with a priority corresponding to the motion task; and joint motors in the humanoid robot are controlled to operate based on the optimal control parameters. Therefore, the problem that two feet of the humanoid robot are difficult to stably run in a complex environment can be solved.

The invention belongs to the field of robot motion control, and discloses an online generation and control method and system for whole-body coordinated walking motion of a humanoid robot, a computer readable storage medium and a computer program product. According to the method, in walking motion generation, a whole-body walking motion track including upper body joint motion information is generated in real time by adopting a whole-body kinematics-centroid dynamics model; a model predictive control model is adopted to realize organic combination of motion trail generation and real-time tracking control; and solving the model prediction control model, and taking the optimal state x * and the corresponding control input u * as the input of whole body control. According to the method, in the planning stage, namely the whole-body walking motion trail including upper body joint motion information, the whole-body dynamic characteristics of the arms, the waist and the like are comprehensively considered, and a new method of long-time-domain trajectory optimization and online control is combined, so that real whole-body coordinated walking is fundamentally realized.

The invention relates to the technical field of motion capture data processing, and discloses a robot reinforcement learning model construction method based on optical inertial fusion whole body motion capture, and the method comprises the steps: measuring and recording a plurality of key parameters of a target human body; carrying out primary calibration and recording on all inertial sensors worn on a target human body, and calibrating all cameras arranged around at the same time; in the process that the target human body executes the specified action, synchronously acquiring action sampling data of the target human body; the action sampling data comprises motion data corresponding to the inertial sensor and camera image data corresponding to the camera; the motion data and the camera image data are processed, fused and optimized, and optimized joint posture quaternary data and human body motion sequence data are obtained; and inputting the human body action sequence data into the reinforcement learning model of the humanoid robot, and configuring the preset reward function to perform reinforcement learning training, so that the learning efficiency of the robot and the accuracy of action execution can be improved.

The invention relates to a humanoid robot lower limb structure and a robot. The lower limb structure comprises a hip unit, a thigh unit, a shank unit and a foot unit. The hip unit comprises a hip seat body, a first joint structure, a thigh swing drive, a thigh rotation drive and a thigh side-sway drive; the first joint structure comprises a first movable seat and a second movable seat; the thigh swing drive is mounted on the inner side of the hip seat body, and an output rotating shaft of the thigh swing drive is connected with the first movable seat; the thigh rotation drive is fixedly connected with the second movable seat, and an output rotating shaft of the thigh rotation drive is connected with the upper end of the thigh unit; the thigh side-sway drive is fixedly connected with the first movable seat, and an output rotating shaft of the thigh side-sway drive is connected with the second movable seat; the axial direction of a rotating shaft driven by thigh swing is parallel to the first direction; the axial direction of a rotating shaft of the thigh side-sway drive is perpendicular to the first direction; the axial direction of the rotating shaft of the thigh rotation drive is perpendicular to the first direction and the axial direction of the rotating shaft of the thigh side-sway drive.

The invention discloses a high dynamic response control method and system for a linear actuator of a humanoid robot, and the method comprises the steps: collecting the pressure and moment data of a contact point, carrying out the data preprocessing and signal calibration processing, and obtaining the calibration pressure and moment data; based on the calibrated pressure and torque data, performing high-frequency signal extraction to obtain dynamic change characteristics, and performing distribution diagram construction in combination with the pressure and torque data to obtain a pressure distribution diagram and a torque distribution diagram; performing data fusion processing according to the pressure distribution diagram and the torque distribution diagram, generating real-time contact area distribution, and performing dynamic prediction model construction based on the pressure and torque data to obtain a dynamic prediction model; according to the dynamic prediction model, actuator output force and joint angle adjustment amount are calculated, output torque and angle compensation amount are generated, torque distribution optimization and force feedback compensation are carried out, and an optimized final control signal is obtained. According to the method, high-dynamic response control of the controller can be realized.

The invention provides a humanoid robot knowledge enhancement decision-making system. A dynamic knowledge constraint mechanism is constructed through fusion of an industry knowledge graph and real-time sensor data. The system comprises an industry knowledge graph module for storing structured operation knowledge, an SPARQL query engine for extracting knowledge constraints, sensor data for generating environment vectors through state feature coding, a Q-learning algorithm combined with the knowledge constraints for dynamically adjusting a Q value updating strategy, balancing exploration efficiency and a security boundary, and outputting an optimization action instruction. The action parameter adjusting module converts an instruction into a mechanical arm control signal, an execution result generates feedback data through the effect evaluation module, and the graph increment updating module is driven to achieve knowledge base iterative optimization. According to the architecture, the problem of execution errors caused by semantic deviation in a traditional method is effectively solved, and reliability and operation accuracy of autonomous decision making in a complex dynamic environment are enhanced through knowledge-guided reinforcement learning and closed-loop verification of physical operation.

The invention provides a multi-scene fusion perception system and method of a humanoid robot olfaction sensor, and relates to the technical field of intelligent sensors, and the system comprises an olfaction perception optimization module which is used for obtaining an olfaction perception optimization network; the first matrix module is used for monitoring a gas pipeline to obtain a first matrix; the second matrix module is used for performing interference compensation according to a real-time environment; the third matrix module is used for correcting according to the state of the sensor; the leakage detection module is used for detecting pipeline leakage; and the suppression verification module is used for carrying out false alarm suppression verification on the pipeline leakage detection result to obtain a pipeline early warning signal. The gas leakage detection method and device can solve the technical problem that the gas leakage detection precision is limited due to the fact that the gas leakage detection device is prone to environmental interference and high in false alarm rate in the prior art, and can adjust the multi-node olfaction sensing network in real time through historical data, conduct multi-level correction on monitoring data and introduce false alarm suppression verification, thereby improving the detection accuracy of gas leakage. The accuracy of gas leakage detection in a multi-scene environment is improved.

The invention discloses a dexterous hand finger based on connecting rod transmission, a bionic mechanical arm and a humanoid robot, belongs to the field of bionic mechanical arms, solves the problem that a transmission mechanism of an existing dexterous hand is low in response speed, and adopts the technical scheme that the dexterous hand finger mainly comprises a finger base and a finger body, a driver and a transmission mechanism in transmission connection with the driver are arranged on the finger base, the driver drives the finger body to bend and / or swing through the transmission mechanism, the transmission mechanism comprises a guide piece and a sliding block installed on the guide piece in a sliding mode, and the sliding block is in transmission connection with the finger body. A traction rope connected with the sliding block is wound on an output shaft of the driver, the driver controls the output shaft to rotate forwards and backwards so as to drag the sliding block to slide back and forth along the guiding piece through the traction rope, and then the finger body is controlled to bend and / or swing. The finger is mainly used for driving the sliding block to move through the pulling rope so as to control the finger body to bend and swing, and the response efficiency of the finger body can be improved.

A torque protection apparatus comprising: a gearbox coupled to an axle; an output ring with first and second planar disc surfaces coupled to the gearbox output; an outer body surrounding these components; an output adaptor attached to the outer body; an inner body within the outer body; a first clutch friction plate between the output adaptor and first planar disc surface; fluid in a chamber between the inner body and outer body; and a hydraulic pressure mechanism. The pressurized fluid pushes the inner body toward the output ring, pressing the output ring against the clutch friction plate. This creates friction causing the outer body to rotate with the axle until rotational torque exceeds a predetermined threshold, at which point the clutch friction plate slides against the disc surface, protecting the gearbox from excessive torque.

The invention discloses a humanoid robot and a shank structure thereof. The shank structure comprises a knee frame, a foot plate, a driving assembly and a cam; the foot plate is rotatably connected to the knee frame around the X axis; the knee frame is provided with a rotating seat; the inner shaft is rotationally connected to the rotating seat around the Y axis; the fixing sleeve is rotatably mounted on the inner shaft; the driven planetary gears are meshed with the driving planetary gears on the two sides; one end of the side shaft is limited to the fixing sleeve, and the driven planetary gear is rotationally arranged on the side shaft in a sleeving mode. The upper end of the connecting rod is rotatably connected to the connecting seat, and the lower end of the connecting rod is rotatably connected to the foot plate; when the cams at the left and right positions rotate towards the same direction, the connecting seat drives the foot plate and the knee frame to rotate around the Y axis through the connecting rod; when the cams at the left and right positions rotate in opposite directions, the connecting seat rotates around the side shaft and drives the foot plate to rotate around the X axis relative to the knee frame through the connecting rod. According to the scheme, more flexible gait control can be achieved, and the problem that the weight burden of shanks is too heavy due to a direct drive mode in a traditional system is solved.

The invention relates to the technical field of robots, and discloses a humanoid robot lower limb system, comprising: a crotch portion comprising a rope-driven motor; the thighs are installed at the two ends of the crotch respectively and can rotate along a pitch axis and a roll axis; the shanks are installed at the lower ends of the two thighs respectively, a knee joint motor is installed on the upper portion of each thigh, and the shanks are driven to rotate relative to the thighs through the knee joint motors and the synchronous belts; the ankles are mounted at the lower ends of the two shanks respectively; the rope drive motor drives the shank opposite to the ankle to rotate through the steel wire rope. The synchronous belt has the characteristics of high transmission precision and strong anti-interference capability in a non-severe environment, the rope drive has the characteristic of high sensitivity, and all motors are intensively arranged at the uppermost end of the leg structure, so that the center of gravity is concentrated on the upper part, the inertia of leg movement is reduced, and the movement control is facilitated. Meanwhile, the principle that the left leg and the right leg are designed into blocks is adopted, so that the left leg and the right leg can rotate independently, and walking in multiple terrains is facilitated.

The invention discloses a wheelchair humanoid robot controlled by humanoid mechanical arms. The wheelchair humanoid robot comprises a chassis, a robot trunk, the two mechanical arms and a control calculation unit. The chassis comprises four independent driving wheels; a wheelchair seat is arranged on the robot trunk; the mechanical arm is a seven-axis mechanical arm and comprises three tail end joints and an operation tail end. The control calculation unit is provided with an operation control moving mode; in the operation control movement mode, the control calculation unit senses the operation intention of a user on the operation tail end by collecting data of the joint position sensor and the force feedback sensor, generates a movement command of the chassis through mapping of the operation intention, and converts the movement command into a wheel speed control command of the independent driving wheels. The tail end joint of the mechanical arm serves as a sensing and input device, the independent driving wheel chassis serves as an execution device, and the whole system has the advantages of being high in freedom degree, natural in interaction, safe, smooth and high in space adaptability through cooperation of the two devices.

The invention discloses an emotion analysis processing method for a humanoid robot, and the method comprises the steps: obtaining first multi-modal data of a user, and carrying out the preprocessing of the first multi-modal data, and obtaining second multi-modal data; performing time sequence synchronization and feature extraction on the second multi-modal data to obtain voice feature data, posture feature data and visual feature data; according to the voice feature data and the posture feature data, performing self-attention feature fusion on the visual feature data to obtain fusion features; inputting the fusion features into an emotion classification model for emotion recognition to obtain emotion state information; and inputting the emotional state information into an emotional interaction generation model for emotional interaction generation to obtain emotional interaction information. According to the method, by improving the accuracy and robustness of emotion recognition in the man-machine intelligent interaction process, the matching degree of the generated interaction content and the user emotion can be improved, and the user experience is improved. The invention relates to the technical field of emotion analysis.

The high-torque-density light-weight humanoid robot harmonic reducer comprises a rigid gear, a flexible gear and a wave generator, the rigid gear is of an annular structure with an inner gear ring, the tooth shape of the inner gear ring is an involute tooth shape, the flexible gear is of a thin-wall cup-shaped structure, an outer gear ring is arranged on the outer wall of the flexible gear, and the wave generator is arranged on the outer wall of the flexible gear. The tooth shape of the outer gear ring is matched with the tooth shape of the inner gear ring of the rigid gear, an installation shaft hole is formed in the center of the cup bottom of the flexible gear, the wave generator comprises an oval flexible bearing and a cam installed on the outer side of the flexible bearing, the cam is in interference fit with the flexible bearing, and the wave generator is installed in the installation shaft hole of the flexible gear. The flexible gear is used for enabling the flexible gear to generate elastic deformation, and a heat dissipation assembly is detachably installed in an installation shaft hole of the flexible gear. By arranging the heat dissipation assembly, the heat dissipation effect of the harmonic reducer is remarkably improved, the internal temperature is reduced, the working stability of the reducer during high-load operation is improved, and the service life of the reducer during high-load operation is prolonged.

The invention belongs to the technical field of robots, and discloses a man-machine-data three-element integrated robot teleoperation and data acquisition system and method, and the system comprises a man-machine interaction module, a physical robot, a prediction simulation module, a digital robot, a virtual environment and a data management module. Wherein the prediction simulation module is used for aligning information of a natural person to execution action information of the physical robot, predicting an action instruction sequence and correcting the state of the digital robot in real time according to state information fed back by the physical robot; the digital robot is used for executing a corresponding action in the virtual environment according to the combined action instruction sequence, if a safety problem exists in the execution process, execution is stopped, and otherwise, the combined action instruction sequence is sent to the physical robot; the data management module is used for collecting data in the system operation process. The technical problems of operation delay and lack of humanoid robot training data in a traditional teleoperation system are solved.

The invention relates to a humanoid robot foot based on a human arch, and aims to solve the problems that a foot structure of a biped humanoid robot is insufficient in the aspects of stability, rigidity, flexibility, energy efficiency, diversity, ergonomics and the like. The five toes, the first metal vertical plate and the second metal vertical plate are fixed to the sole metal plate, the hallux toe sleeve is sleeved on the toes and connected with the toes through the first elastic metal driving rod, and the final toe sleeve is sleeved on the toes and connected with the toes through the second elastic metal driving rod. A first C-shaped connecting rod connected with a first elastic metal driving rod and a second elastic metal driving rod is inserted into the front portion of an ankle connecting block, the bottom of the ankle connecting block is connected with a heel metal plate through a plurality of spring columns, and a second C-shaped connecting rod is inserted into the rear portion of the ankle connecting block. And the second C-shaped connecting rod is fixed with the heel metal plate through the heel elastic metal driving rod. According to the scheme, the shoe sole has better adaptability and balance.

The invention discloses a joint module of a humanoid robot. The joint module comprises a shell, a first cooling pipeline, a motor and a speed reducing mechanism, wherein the motor and the speed reducing mechanism are coaxially arranged in the shell; the motor comprises a main shaft rotationally arranged in the shell, and a first rotor, a stator and a second rotor which are sequentially arranged along the axial direction of the main shaft; the annular base of the stator is fixed in the inner cavity of the shell; the main shaft is coaxially arranged on the inner ring of the annular base, and the two ends of the main shaft extend out of the stator and are connected with the double rotors respectively. Stator iron cores which are distributed at intervals along the circumferential direction are arranged on the annular base; the shell is provided with an internal oil way, and the internal oil way comprises a spiral oil way surrounding the periphery of the speed reducing mechanism. And the first cooling pipeline is annularly fixed on the inner ring of the stator. On the basis that a single-stator double-rotor motor structure is adopted, the first cooling pipeline is arranged on the stator, and the spiral oil way is arranged on the periphery of the speed reducing mechanism in a surrounding mode, so that the joint module is effectively cooled, and the service life of the joint module is prolonged.

The knee joint assembly comprises a first thigh web, a knee joint motor is arranged at the upper end of the side wall of the first thigh web in the X direction, and the output end of the knee joint motor is connected with a first flange plate; a knee joint connecting rod is hinged to the eccentric part of one end of the first flange away from the knee joint motor; the lower end of the side wall of the first thigh web is rotationally connected with a shank web in the X direction. The end, away from the first flange plate, of the knee joint connecting rod is hinged to the upper end of the shank web. The hinge point of the knee joint connecting rod and the first flange plate, the rotating shaft point of the first flange plate, the hinge point of the knee joint connecting rod and the shank web and the rotating shaft point of the shank web form a contra-parallelogram structure. The motion angle range of the knee joint connecting rod can be narrowed on the basis that the requirement for large-angle-range motion of the knee joint of the humanoid robot is met.

The invention provides a humanoid robot control method and system, a storage medium and a program product, and belongs to the field of computer vision. The method comprises the following steps: preprocessing expert action data, and processing the expert action data into expert data equivalent to a skeleton architecture of a target robot; in a simulation environment, a humanoid structure is adopted to build a robot, joint parameters of the robot are configured, and the degree of freedom of each joint is controlled by an independent physical control module; constructing a strategy representation method of the robot, wherein the strategy representation method comprises a state space, an action space, a reward function and a multi-frame control mode; the robot is initialized; and the difference between the robot action and the expert action on each frame is minimized, the reward function is maximized, and the robot is driven to learn. The method can assist the learning process of the humanoid robot, so that the robot can be personified while completing tasks, and the training speed is improved.

The invention discloses a humanoid robot voice-driven facial expression control method and system. The extracted voice audio features are subjected to face corresponding key point prediction through an audio emotion key point prediction model, and the audio emotion key point prediction model is a regression model based on a long short-term memory network and is used for learning a nonlinear mapping relation between an audio feature sequence and face key point coordinates; outputting a predicted key point position difference value or a relative distance; the predicted face key points are input into a steering engine angle mapping model, and the steering engine angle mapping model maps the geometrical relationship of the face key points into angle instruction parameters for controlling a robot face micro steering engine based on a pre-trained nonlinear regression model; and according to the predicted angle instruction parameters, driving a robot face mechanism to make human expression simulating motion synchronous with the voice content. The problem that multi-channel interaction of a traditional robot is not coordinated is solved, and the naturalness and emotional expressive force of man-machine interaction are remarkably improved.

The invention discloses a bionic joint humanoid robot navigation positioning method, device and equipment, and the method comprises the steps: monitoring a landing shock wave signal and reflection echo data of a robot, carrying out the time domain expansion of the shock wave signal to form a pulse characteristic spectrum, extracting multipath propagation components, and carrying out the time difference correlation to generate an environment response value. Screening a direct wave component by using an environmental response value, positioning a sound wave propagation trajectory, and detecting impedance mutation to construct an acoustic matrix. A strong reflection zone is identified through node analysis, a sound pressure gradient field is extracted to determine an obstacle boundary, and a landmark feature bit is determined in combination with an environmental response value. And adjusting a dynamic stride frequency interval based on a landmark feature bit, forming an adaptive detection sequence, and performing sparse processing to construct path configuration. The mechanical vibration component of the shock wave signal is used for piezoelectric conversion to generate recycled electric quantity, the recycled electric quantity is matched with path configuration power to determine a sensing period, intermittent sensing is executed to obtain detection data to construct a detection convergence field, and finally an accurate positioning window is determined and converted into position coordinates.

The invention discloses a humanoid robot situational social behavior expression method, which comprises the following steps of: sensing user behaviors by adopting multiple sensors, constructing a multi-layer interactive situation sensing structure, and establishing association between a human-computer interaction situation and the user behaviors; self-adaptive layered isolated word recognition and voice emotion recognition based on an optimized neural network are adopted, user voice features are fully utilized, a matching relation between user emotion and robot situational social action emotion is constructed, and an emotion-fused robot situational social behavior expression decision is provided. Therefore, the multi-modal social behavior expression of the humanoid robot, which can express emotions while implementing an interaction task, is realized. According to the method, the relationship between the user behavior and the interaction situation and the relationship between the interaction situation and the social behavior of the humanoid robot are constructed, the problem that in the prior art, the emotion interaction is less when the humanoid robot executes the social task is solved, and the environment situation and the user emotion are fully considered; and a multi-situation social expression realization path of the humanoid robot is provided.

The invention discloses a cloud collaborative robot control system, which comprises a cloud control platform and a robot, and is characterized in that the robot is provided with an edge calculation module and a hardware module; the hardware module provides hardware components, collects environment data and uploads the environment data to the cloud control platform. The edge computing module monitors the state of the robot, collects execution data, uploads the execution data to the cloud control platform, updates local model parameters of the robot, uploads the parameters to the cloud control platform, and controls the robot according to a task strategy and an optimization strategy; the cloud control platform formulates a task strategy according to the received production task and environmental data based on the large model, formulates an optimization strategy according to the received uploaded data, updates the large model according to the uploaded data, local model parameters and a task experience pool, and issues the task strategy, the optimization strategy and large model parameters to the robot; and the task execution efficiency and the system control efficiency are improved. The embodiment of the invention can be widely applied to the technical field of robot control.

A method of generating a drum play motion of a robot includes generating a plurality of rhythms of a melody, assigning each of a plurality of notes forming a rhythm of each part to one of the right hand and the left hand of the robot, scheduling swing time of each of the right hand and the left hand to which each note is assigned, and generating a trajectory of each of a plurality of joints of the robot for playing the rhythm of each part based on the swing time of each of the right hand and the left hand, and by controlling a motion of each of the plurality of joints according to the trajectory of each of the plurality of joints generated in this way, creative drum play of a humanoid robot may be done when only a melody is input.