381 results about "Humanoid robot" patented technology

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 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.

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 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 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 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 relates to a humanoid robot leg structure and sole assembly based on rope driving, which comprises a hip assembly, a thigh assembly, a shank assembly and a sole assembly, the joint of the hip assembly and the thigh assembly is a hip joint, the joint of the thigh assembly and the shank assembly is a knee joint, and the joint of the shank assembly and the sole assembly is an ankle joint. A first driving source is arranged on the upper side of a hip joint and used for driving the hip to roll, a second driving source and a third driving source are arranged on the left side and the right side of the hip joint respectively and used for driving the hip to pitch and yaw, and a fourth driving source and a fifth driving source are arranged on the left side and the right side of the upper portion of a thigh assembly respectively and used for driving the hip to roll. The fourth driving source is used for driving the knee joint to move, the fifth driving source is used for driving the ankle to do pitching motion, and the sixth driving source is arranged at the joint of the shank assembly and the sole assembly and used for driving the ankle to do rolling motion. The dynamic performance of the whole robot can be improved.

The invention relates to the technical field of cables, in particular to a cross-linked polyethylene insulated power cable for a humanoid robot, which comprises a plurality of groups of conductors, a heat insulation and heat conduction structure, a sheath, a heat dissipation structure and a power cable, and the insulating layer is arranged on the sheath and is in contact with the heat-insulating heat-conducting structure inside the sheath. The conductors are separated through the partition plates and the partition edge strips on the partition plates, and the situation that heat cannot be dissipated effectively due to the fact that the cable cores are attached together is avoided. By means of the heat conduction strips embedded in the separation edge strips and the heat conduction aluminum foil layers making contact with the heat conduction strips, heat generated by the conductors can be conducted outwards, and heat concentration in the cable is avoided. Through the heat dissipation structure which is arranged on the cable joint and is in contact with the heat-conducting aluminum foil layer, heat in the heat-conducting aluminum foil layer can be rapidly taken away through the cooling channel in the heat dissipation structure, so that the purpose of heat dissipation is achieved.

The invention relates to the technical field of intelligent robots, and discloses a dynamic sparse attention-multi-modal space-time constraint humanoid robot control method, which comprises the following steps: S1, multi-modal information collection: collecting robot surrounding environment information, S2, reasoning engine processing and instruction generation: processing the information, and S3, processing the information. S3, time-space synchronization and force constraint; S4, driving mechanism motion control; and S5, emotion expression unit response. By adopting a dynamic sparse attention mechanism and an optimized calculation method, the calculation efficiency of the system is greatly improved, and the reasoning delay is reduced. The NSA inference engine dynamically adjusts the number of activated heads, and axial partitioning calculation, KV cache compression and 4-b-it integer calculation are combined, so that the inference delay is greatly reduced. Through the optimization, the robot can make a faster response to the environment change, and can quickly complete the reasoning and decision-making process and adjust the action of the robot in time in the face of complex and changeable task scenes.

The invention belongs to the field of pressure sensors, and particularly discloses a flexible ionizing pressure sensor and a preparation method thereof. According to the invention, a firm chemical bonding interface is constructed between the electrode layer and the ionic elastomer layer of the ionizing pressure sensor, and a microstructure is introduced on the ionic elastomer layer, so that the ionizing pressure sensor has mechanical stability, reliability and sensitivity, and the ionizing pressure sensor also has good flexibility and transparency, and is suitable for being applied to the field of electronic devices. The method can be applied to the fields of preparation of humanoid robots, intelligent prostheses and the like.

The invention provides a cable production stranding device for a humanoid robot, and relates to the technical field of cable production, the cable production stranding device comprises a hollow shaft arranged on a bottom plate, a doubling mold and a wind-up roller, one end of the outer side of the hollow shaft is fixedly provided with a winch provided with a plurality of threading holes, and the cable production stranding device further comprises a tension detection device used for detecting the tension balance degree of a plurality of stranded wire layer wires; and the driving mechanism drives the hollow shaft to rotate. Through the tension detection device, the tension of a plurality of stranded wire layer wires can be detected, and if the tension of any stranded wire layer wire is detected to be reduced, a circuit can be switched on to lighten a warning lamp at a corresponding position, so that a worker can find and adjust the tension of the stranded wire layer wires in time, and the working efficiency is improved. Therefore, the tension of a plurality of stranded wire layer leads can be monitored in real time, the cables can be more uniformly stranded together, the stranding quality of the cables is improved, the overall structure of the cables is more stable, and the mechanical performance of the cables is improved.

The invention relates to the field of humanoid robots, and provides a control method for biped robot step-by-step gait strategy fusion in order to solve the problems that a biped robot is large in training difficulty, unnatural in gait, poor in adaptability and the like. Training various different terrain categories through an imitation learning algorithm and a reinforcement learning algorithm to obtain a gait strategy model; s2, performing pairwise fusion gait strategy switching between the gait strategy models corresponding to various different terrain categories; s3, the terrain category of the current position is recognized in real time according to an information collection unit of the biped robot, a corresponding gait strategy model is obtained through a strategy execution control unit, and the biped robot is controlled to walk in the corresponding motion state; and S4, when the terrain category of the biped robot is changed, smooth transition between the two gait strategy models is achieved through gait strategy switching, and control over gait strategy fusion of the biped robot is completed.

The invention belongs to the technical field of robot control, and discloses a humanoid robot series-parallel connection structure accurate modeling method, which comprises the following steps: respectively acquiring a first target parameter of a parallel connection type linear joint and a second target parameter of a series connection type linear joint, and calculating to obtain the length of the parallel connection type linear joint and the length of the series connection type linear joint; according to the first target parameter and the second target parameter, Jacobian matrixes of the parallel-connection type linear joint and the series-connection type linear joint are determined respectively, and thrust of a parallel-connection joint linear actuator and thrust of a series-connection joint linear actuator are determined respectively according to the torque of the joints and inversion of transposition of the Jacobian matrixes; and force-position hybrid control is conducted on the parallel joint linear actuator and the series joint linear actuator according to the length and the thrust. According to the invention, the motion of the linear joint of the series-parallel hybrid structure and the precise modeling of the mechanical model are realized, so that the stable force-position hybrid control is carried out on the motor.

The invention provides a joint module of a humanoid robot, and relates to the technical field of robot joints, the joint module comprises a joint driving mechanism, the joint driving mechanism comprises a module lower shell, a module upper shell, a radial adjusting end, a frameless torque motor, a harmonic reducer and an encoder; and the frameless torque motor is detachably mounted in the module lower shell. The radial distance adjusting mechanism is matched with the synchronous pushing mechanism, accurate adjustment of the radial distance and the position of the radial adjusting end is achieved, the driving unit controls the power switching assembly, power of the frameless torque motor is transmitted to the screw rod through the speed reduction transmission assembly, the limiting embracing ring is driven to ascend and descend, and therefore the position of the radial adjusting end is accurately adjusted; meanwhile, the infrared distance detection assembly detects distance data in real time and feeds back the distance data to the control system, data support is provided for accurate adjustment, and the problem that in the prior art, a joint module cannot meet the requirement for complex operation accuracy is effectively solved.

The invention provides a humanoid robot motion test platform, which comprises a base, a belt-type motion mechanism, a height adjusting device and a control system, and is characterized in that the height adjusting device comprises a linear driving mechanism of which the bottom is hinged to the base; the first sliding mechanism is connected with the output end of the linear driving mechanism; the second sliding mechanism is in sliding fit with the first sliding mechanism and is connected with the test platform; and the brake mechanism is used for limiting relative movement of the two. During slope changing, the two sliding mechanisms slide relatively to automatically compensate the space horizontal displacement difference, and lateral stress interference is eliminated; the high-frequency large-load stepping impact of the robot can be effectively resisted, the step loss of the system is prevented, and the unification of smooth slope change and high-rigidity and high-precision testing is realized.

The utility model discloses a leg device of a foot type robot and the foot type robot. The leg device of the foot type robot comprises a robot leg and further comprises a driving motor arranged in the robot leg, the driving motor comprises a shell, a power cavity formed in the shell and a power assembly arranged in the power cavity, and a first containing cavity is formed in the end face of the tail of the shell; a motor controller electrically connected with the power assembly is arranged in the first containing cavity, and cooling fins are arranged on the motor controller and connected with the shell in a heat conduction mode. The utility model further discloses the foot type robot which adopts the leg device of the foot type robot. The motor controller has the advantage of solving the problem that the motor controller for installing the motor in the leg of the humanoid robot is easy to overheat. The cooling fins are connected with the shell in a heat conduction mode, heat generated by the motor controller can be rapidly transmitted to the shell and then dissipated to the surrounding environment through the shell, faults caused by overheating of the motor controller are avoided, and stable operation of the motor controller is guaranteed.

The invention belongs to the technical field of humanoid robots, and discloses a full-connecting-rod-driven 21-degree-of-freedom humanoid five-finger dexterous hand which comprises a palm base and a five-finger executing mechanism. Each of the four fingers has four active degrees of freedom, so that near knuckle side sway, near knuckle bending and middle and far knuckle coupling bending are realized respectively; the thumb has five active degrees of freedom and can independently complete palm aligning, forward falling, abduction and knuckle bending movement. All motions are converted into linear motions through a motor driving lead screw and then converted into rotary motions of knuckles through a push rod and a connecting rod mechanism, and full-connecting-rod transmission is achieved. According to the multi-degree-of-freedom parallel mechanism, the double-fish-eye connecting rods, the universal joints and other structures are adopted to ensure that movement among multiple degrees of freedom does not interfere with one another, the far knuckles have passive self-adaptive bending capacity through the design of the compressible push rods, and the multi-degree-of-freedom parallel mechanism has high load, high precision, high bionic performance and grabbing adaptability and is suitable for fine operation of a robot.

The invention discloses a multi-modal man-machine interaction optimization system integrating multiple large language models, and focuses on the man-machine interaction field of intelligent humanoid robots. And by fusing technologies such as prompt engineering, natural language processing and personalized role configuration, the flexibility, adaptability and personalized level of human-computer interaction are remarkably improved. According to the technology, the advantages of various large language models are utilized, complex dialogue logic is processed, personalized voice, emotion and action feedback matched with human settings, emotions and contexts is generated, and therefore real-time human-computer interaction is optimized. According to the specific implementation, the system comprises a voice awakening unit, a voice recognition unit, a function calling unit, an anthropomorphic dialogue unit, a keyword matching unit and a voice synthesis unit, and finally highly natural and immersive man-machine interaction experience is achieved. The method shows excellent performance in the aspects of speech recognition accuracy, response speed, emotion action representation, personalized interaction and the like, and provides more vivid, immersive and personalized user experience.

A humanoid robot system comprises vision sensors for capturing image data, a computing architecture with processing hardware and memory, and a bipedal spatial perception model. The model includes a feature extractor that extracts hierarchical feature maps from input images, a robot data module that detects robot parts, and a robot vector data module that calculates three-dimensional spatial position and orientation data for each detected robot part. The feature extractor uses a feature pyramid network generating multi-scale feature maps through bottom-up and top-down pathways with lateral connections. The robot vector data module predicts 2D-to-3D point correspondences and solves perspective-n-point problems to obtain final position and orientation vectors, enabling real-time robot self-awareness and closed-loop visual servoing for precise object interaction.

The invention relates to the technical field of power supply, and discloses a humanoid robot modular distributed power supply system which comprises a power supply battery pack, a power management distribution board and a plurality of power utilization modules. The power utilization module at least comprises a control computing power unit, a sensing system, an upper limb joint module, a lower limb joint module and other joint modules; the power management distribution board is electrically connected with the power supply battery pack and each power utilization module. The power management distribution board comprises an MCU control unit, a DCDC power supply unit, a soft start unit, a high-power output unit and a voltage and current detection unit. Through a modular distributed power-on strategy and in combination with soft start pre-charging, voltage and current real-time detection and a regenerative braking absorption unit, voltage and current peaks generated at the moment of power-on of the capacitive high-power load are remarkably suppressed, the risk that a power device is damaged due to overvoltage and overcurrent impact is fundamentally avoided, and the reliability of the power device is improved. And the system reliability and the service life are greatly improved.

The invention provides a humanoid robot joint assembly method, which relates to the technical field of robot joint assembly, and comprises the following steps: S1, carrying out pretreatment work, and carrying out cleaning, drying and surface detection on a to-be-assembled joint part; s2, all the joint assemblies are assembled, and preliminary positioning and mounting are conducted through a positioning tool of an assembling mechanism; s3, placing the bolt coated with the thread glue in the threaded hole position of the connecting piece; s4, the bolts coated with the thread glue are tightened through a bolt mounting mechanism, and then the steering engine rotating ends of all the joint parts and the flange support are subjected to bolt mounting; s5, the waist joints are assembled; and S6, wiring processing is conducted on steering engines and controllers of all the joint parts, all the installed joint modules are debugged and detected, and classified qualified products are selected. And by arranging the parts in advance and using the positioning tool, disorder in the assembling process is reduced, and the assembling efficiency is improved.

The invention discloses a robot autonomous assembly method and system based on imitation learning, a storage medium and computer equipment, and the method comprises the steps: constructing a universal expert strategy suitable for polygonal shaft hole assembly through analyzing and summarizing the polygonal shaft hole assembly experience of an expert; according to the strategy, task type images and human assembly demonstration data including assembly force / torque and assembly actions are collected; modeling a human assembly skill into a universal assembly skill model based on shared knowledge and specific knowledge; using a loss function guidance algorithm to train and optimize the general assembly model; and deploying the optimized general assembly model into a control system of the robot so as to drive the robot to execute humanization-like assembly. According to the method, the problems of poor generalization performance, slow convergence of an end-to-end learning mode and high cost of an imitation learning method can be solved, rapid learning of human skills can be realized, and humanoid robot autonomous assembly is realized.

The invention provides an automatic mushroom harvesting humanoid robot. The automatic mushroom harvesting humanoid robot comprises a movable operation table, a picking module, a root cutting module and a collecting module, the movable operation table is used for adjusting the picking position; the picking module is used for identifying and picking roots to the root cutting module; the root cutting module comprises a blade fixed to the movable operation table and a conveying belt arranged on the movable operation table. A plurality of mushroom containing grooves are formed in the conveying belt and used for bearing mushroom bodies picked by the picking module, and through holes are formed in the bottoms of the mushroom containing grooves and used for allowing mushroom roots to penetrate through; the mushroom accommodating groove moves along with the conveying belt to cut mushroom roots by the blade; and the collecting module is used for collecting the mushroom bodies after root cutting. According to the mushroom harvesting machine, the whole process of mushroom harvesting is integrated, and the harvesting efficiency is greatly improved. All the mechanical arms can work independently, efficient picking is achieved, and mushroom roots are uniformly and efficiently cut through cooperation of the mushroom containing grooves and the blades; the mushroom containing groove can effectively protect mushroom bodies, and the root cutting success rate is guaranteed.

The invention discloses a full-closed-loop control method for a humanoid robot joint module based on an FPGA (Field Programmable Gate Array), which relates to the technical field of robot control and comprises the following steps of: performing second-order active low-pass filtering and programmable gain amplification on analog signals of an encoder, a gyroscope and a force sensor to convert the analog signals into digital signals; a multi-dimensional feature sequence is constructed, temperature signals of a joint driver and an encoder are collected through a temperature sensor interface, a temperature drift model is constructed, and zero drift compensation parameters are obtained; further obtaining a joint elastic deformation error, and applying the joint elastic deformation error to an encoder signal for online offset correction; outputting a reconfiguration region selection signal based on the lightweight neural network; and triggering bit stream local refresh corresponding to the PR Region according to a region selection signal output by the lightweight neural network. The problem that a control loop is difficult to eliminate flexible errors due to the fact that a traditional rigid model or a constant parameter model is difficult to reflect deformation characteristics under the heat-lubrication-load combined action in real time is solved.

The invention belongs to the technical field of intelligent humanoid robots, and discloses a remote operation data acquisition and data closed-loop system for an intelligent humanoid robot, which builds an instruction, action and acquisition ternary time sequence synchronization mechanism through a time sequence coordination module, realizes dynamic coordination of the three parts by using a time sensitive network technology, effectively reduces time sequence deviation, and improves the system performance. Meanwhile, a space-time alignment algorithm of the data processing module is combined, so that the consistency of the multi-modal data in time and space dimensions is guaranteed; acquired data can accurately fit human operation logic and a robot action state, the optimization efficiency of a data closed loop is improved, and the requirements of high-precision operation scenes such as complex assembly and flexible material processing are successfully met; a quantitative association system of data quality and control effects is established by means of the evaluation module, invalid data such as sensor faults and action fuzziness can be screened in real time, and occupation of redundant storage and computing resources is reduced.

The invention relates to a humanoid robot three-dimensional complex environment navigation method and system, and belongs to the technical field of robot navigation. Comprises: obtaining a random path node; constructing a collision detection model according to the gait cycle of the robot; detecting whether the random path node passes collision detection by using a collision detection model; if not, deleting the random path node, and obtaining the random path node again; otherwise, adding the random path nodes into the random tree; for each node added to the random tree, collision detection and plane size detection at the node are carried out, and when the detection is passed, candidate nodes are added to a global path point sequence; screening the sequence according to the complexity of the current plane to obtain complex region path nodes and flat region path nodes; and corresponding motion instructions are generated according to the operation requirements of the robot on the path nodes in the different areas. According to the method, the dynamic envelope space calculation cost is reduced, and the global path planning accuracy is improved.

The present invention relates to the field of motor technology, and discloses a reduction servo motor for a humanoid robot, comprising a motor body, a reduction mechanism, and a transmission shaft, wherein the motor body is connected to the transmission shaft via the reduction mechanism, the reduction mechanism comprising a housing, a sun gear, a plurality of planetary gears, a planetary carrier, and a ring gear, wherein a first locking member and a second locking member are slidingly arranged in the housing, wherein when the first locking member is in a first locking state, the first locking member locks the planetary carrier and the transmission block, and when the first locking member is in a second locking state, the first locking member locks the planetary carrier and the housing, and when the second locking member is in the first locking state, the second locking member locks the ring gear and the transmission block, and when the second locking member is in the second locking state, the second locking member locks the ring gear and the housing. The present invention is used to solve the problem in the prior art that the transmission ratio of the reduction servo motor is fixed and cannot be adjusted to different transmission ratios corresponding to different loads.