1082 results about "Mechanics model" patented technology

The invention discloses a dangerous rock falling motion feature prediction method based on multi-source data fusion, and belongs to the technical field of engineering geology. Comprising the steps of collecting dangerous rock multi-source data to construct a basic information base; processing dangerous rock multi-source data based on a CNN algorithm, identifying a dangerous rock contour and calculating geometric features; the dangerous rock multi-source data is processed through multiple algorithms, and the terrain is reconstructed to generate a digital elevation and terrain model; analyzing a vibration signal frequency spectrum, quantifying dangerous rock multi-source data features and determining a fusion weight; fusing the multi-source data of the dangerous rock to construct a three-dimensional real scene model and construct a physical and mechanical model; establishing a historical database, selecting a machine learning algorithm to construct a data driving model, and adopting an optimization algorithm to predict a rockfall movement track and state; and determining a two-dimensional simulation key section, establishing a two-dimensional numerical model, and dynamically simulating and calculating rockfall movement and rock-soil body response. According to the scheme, the defects in the aspects of dangerous rock falling motion feature prediction and protection design in the prior art are overcome, and the prediction accuracy and efficiency are improved.

The invention provides an industrial robot control system and method. The system comprises a trajectory planning module, a dynamic compensation module, a feedback control module, an execution module, a sensor module and a data storage module. The trajectory planning module generates an expected trajectory of an end effector of the robot; the dynamic compensation module calculates a dynamic compensation torque based on the expected trajectory and a robot dynamics model; the feedback control module generates feedback control torque according to the deviation between the real-time pose data acquired by the sensor module and the expected trajectory; the execution module drives robot joints to move according to the synthesized moment of the dynamic compensation moment and the feedback control moment; the sensor module collects robot joint angle, angular velocity and torque data in real time; the data storage module stores robot dynamic model parameters, control algorithm parameters and historical motion data. High-precision and smooth robot motion control can be achieved, the dynamic response and stability of the system are improved, and energy consumption and motion errors are reduced.

A legged robot planning and control method and apparatus, a robot, and a storage medium. The method comprises: according to the motion state of a legged robot and swing parameters of each leg at the next moment, determining a foot-end reference state of each leg; for a leg to swing at the next moment, according to a foot-end dynamics model and a discrete collision model, planning a swing-leg trajectory having collision awareness; and, according to the motion state, a reference state sequence and the foot-end reference states, controlling the whole body of the legged robot, wherein for a leg which should be a planned supporting leg but is not in contact with the ground, whole-body control having collision awareness is performed according to a whole-body dynamics model and the discrete collision model. Thus, the problems are solved that legged robots in the prior art are limited in passive flexible buffering in collision, involves a large amount of control algorithm calculation and relatively low control precision, exhibit a relatively high degree of hardware wear and relatively short service lives, and cannot meet actual needs.

A joint simulation and operation operability evaluation method based on wind power operation and maintenance ship motion dynamic response and active compensation gangway ladder motion control comprises the steps that an operation and maintenance ship frequency domain seakeeping model is built, and a hydrodynamic coefficient library is calculated; wave exciting force is reconstructed based on a Cummins time domain motion equation, and ship motion response prediction is realized by adopting implicit generalized alpha time domain composite integral; the dynamic positioning system extracts low-frequency motion through a Kalman filter and optimizes thruster thrust distribution to stabilize the position of the ship. A gangway ladder dynamic model is established based on a Lagrange equation, real-time control over displacement, speed and acceleration of the top end of the gangway ladder is achieved through a feedforward-feedback composite control strategy, and nonlinear output of a hydraulic actuator is optimized. And realizing joint simulation of the coupling system through time domain synchronization and self-adaptive PID (Proportion Integration Differentiation) control. And checking gangway ladder movement based on a preset threshold value and a space boundary condition, and evaluating the operability of the climbing operation. According to the method, the limitation of traditional single-disciplinary analysis is broken through, and the forecasting precision of wind power operation and maintenance operation operability is effectively improved.

The invention discloses a PINNs high Reynolds number flow field solving method based on regulatory factor optimization, and the scheme comprises the steps: firstly building a physical model, on one hand, building a geometric model according to the actual condition of a reactor core rod bundle channel, and on the other hand, building a fluid mechanics model containing continuity, momentum conservation and energy conservation equations; a data set is obtained, and experimental data is preprocessed and then integrated with simulated data through experimental measurement and numerical simulation; and then training a physical information neural network, designing a neural network model of specific input and output, introducing a regulatory factor to balance the difference between a physical equation and data, constructing a comprehensive loss function containing internal data points, boundary data points and equation loss, and training the network by using a training data set until convergence. And finally, solving a flow field by using the trained neural network, outputting predicted values of a velocity field, a pressure field and a temperature field, and solving the high Reynolds number flow field of the reactor core.

The invention discloses a cluster computing power energy efficiency perception scheduling and green computing system, which relates to the technical field of computers and comprises a multi-source energy efficiency perception and data acquisition module used for acquiring power consumption, utilization rate, temperature, cooling state, PUE index and environmental data of cluster nodes. According to the invention, through the multi-modal energy efficiency fusion sensing network and the multi-scale convolution and time sequence attention fusion network, multi-source heterogeneous energy efficiency data such as current, voltage, temperature, airflow and the like of a node level can be collected and fused in real time and with high precision, noise is effectively removed, abnormity self-correction is realized, the defect of energy efficiency sensing granularity in the prior art is made up, and the energy efficiency sensing precision is improved. And reliable input is provided for subsequent scheduling decisions. A cross-scale dynamic twinborn collaborative modeling mechanism is adopted, a physical information neural network and a computational fluid mechanics model are coupled, optimization is carried out through a generative adversarial network structure, and accurate prediction of a complex energy consumption evolution curve and a cooling flow field is achieved.

The invention discloses a dynamic compensation intelligent formwork real-time regulation and control method and system, and relates to the technical field of building intelligent control. According to the method, pulse signal sensing and cooperative compensation between nodes are realized by constructing a distributed neural unit network, and a three-level compensation mechanism is triggered when displacement or stress is detected to exceed a threshold value. A generative adversarial network is innovatively adopted to construct a virtual scene library to simulate extreme working conditions, a cross-scene migratable strategy library is generated through feature alignment, and intelligent strategy matching of a new construction site environment is realized. A full-structure rigidity field is dynamically generated based on an elastic mechanical model, a supporting arm rigidity switching path is optimized in combination with an ant colony algorithm, and directional dissipation of wind vibration energy is achieved through triangular rigid network construction. The system adopts a biological heuristic self-organizing algorithm to realize redundant network reconstruction when nodes fail, a supporting arm adopts a shape memory alloy and carbon fiber composite structure, and a micro strain sensor is integrated to realize directional release of corrosion stress. According to the method, the adaptive capacity of the formwork system under the complex working condition is effectively improved, and the structural failure rate is reduced through multi-modal compensation strategy fusion.

The invention discloses a whole-span bridge hoisting construction method. The method comprises the steps that prefabricated bridge components are transported to a construction site; in the construction preparation stage, a foundation monitoring mechanical model of a construction site is built, and the optimal position and operation parameters of a crane are determined; before hoisting, a laser emitting device is installed on a bridge component, a laser receiving device is installed at the front end of a crane suspension arm, and a plurality of laser reflection targets are arranged on the periphery of a preset installation position of a pier; in the lifting and translation processes, the laser positioning system monitors the spatial position and attitude information of the bridge component and the suspension arm in real time, and transmits the data to the control center in real time; and the control center compares the actual position deviation with the target position deviation in real time according to the preset hoisting path and the in-position precision requirement, and when the deviation exceeds the threshold value range, a control instruction is sent to a power system and a hydraulic control system of the crane. According to the method, the position and posture of the bridge component can be accurately monitored in real time, the action of the crane is timely and accurately regulated and controlled according to the deviation, and the construction precision and safety are improved.

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 crossing field of mechanical engineering and automatic control, in particular to a global path planning and anti-swing control method for a ship unloader, and aims to solve the problems of rigid path planning and poor synergism of out-of-control swing of a lifting appliance in traditional ship unloading operation. The method comprises the following steps: constructing a dynamic three-dimensional operation space model with fusion of a laser radar and binocular vision, and updating obstacle information in real time; an improved fast extended random tree algorithm is adopted to generate a high-smoothness initial path; establishing a six-degree-of-freedom lifting appliance swinging dynamic model and identifying parameters on line; path tracking and anti-swing torque are synchronously optimized through a model prediction controller, and the control period is smaller than or equal to 20 milliseconds; and closed-loop feedback correction is implemented by combining an encoder and an inertial measurement unit. According to the scheme, environment dynamic sensing, path-anti-swing depth cooperation and multi-disturbance self-adaptive compensation are achieved, the operation rhythm is improved by 30% or above, the system still operates stably under the 8-level wind condition, and high precision, high robustness and engineering implementability are achieved.

The invention relates to the field of constructional engineering, in particular to a selection method for a hoisting system of a steel box girder and related products, and the selection method comprises the steps that a parameterized mechanical model is established according to parameters of the hoisting system, and hoisting point positions are variable parameters; the hoisting system comprises a steel box girder and a sling; based on the parameterized mechanical model, carrying out stress analysis in the hoisting process, and calculating the stress conditions of the sling and the steel box girder; by taking minimization of the maximum stress of the sling, the maximum stress of the steel box girder or the maximum deformation in the hoisting process as an optimization target, determining an optimal hoisting point position and matched sling parameters by utilizing an optimization algorithm; according to the method, by establishing the parameterized mechanical model of the hoisting system and carrying out nonlinear finite element analysis in the hoisting process, the sling stress, the steel box girder stress and the system deformation under different hoisting point positions and sling parameter combinations can be accurately calculated.

The invention relates to a rigid-flexible trans-mass self-adaptive robot force position and rigidity collaborative optimization method and system, and relates to the technical field of robot control, and the method comprises the steps: firstly, carrying out the linearization processing of a robot dynamic model through a semi-implicit integral method, and obtaining a robot dynamic model; and in combination with an extended Kalman filter, stiffness parameters in the contact operation process are estimated in real time, a dynamic stiffness sensing model is constructed, and the system response capability is effectively improved. Then, a rigidity parameter is embedded into a Hertz contact model, the dependence of a traditional model on prior information of a contact surface is broken through, a dynamic interaction model between the robot and an operation object is established, and high-precision real-time sensing of normal force and friction force is achieved. And finally, under a nonlinear model predictive control framework, multi-dimensional physical constraints are constructed based on the contact force, the position and the contact rigidity, an optimal control model is obtained, control input is dynamically and adaptively updated through rolling optimization, and the stability and the control precision of the robot in rigid-flexible heterogeneous contact operation are improved.

The invention discloses a motor-driven tractor-semitrailer driving stability control method which comprises the following steps: firstly, establishing a tractor-semitrailer three-degree-of-freedom dynamic model, and solving yaw velocity expected values and side slip angle expected values of a tractor and a semitrailer according to driver input and actual vehicle states; secondly, according to the deviation between the expected value and the actual value of the vehicle state quantity, an upper-layer controller outputs the expected additional yaw moment, and the adaptive capacity to the parameter change of the semitrailer is achieved; the lower layer controller then outputs a torque on each wheel according to the desired additional yaw moment and the vehicle state, including a driving torque on the driving wheel and a braking torque on all wheels. By the adoption of the method for controlling the running stability of the motor-driven tractor-semitrailer, unstable working conditions such as rollover and folding of the tractor-semitrailer in the running process can be avoided, the running stability is improved, and meanwhile the method has the self-adaptive capacity for load changes of the semitrailer.

The invention belongs to the related technical field of mobile robots, and discloses a rolling-walking composite motion control method and device for a double-wheel-foot robot, and the method comprises the steps: (1) simplifying the rolling motion of wheels of the double-wheel-foot robot into the sliding motion of a sliding block; (2) constructing a system kinetic equation of the double-wheel-foot robot based on the simplified kinetic model; constructing a constraint equation based on the contact state of the two legs and the ground; discretizing the system kinetic equation, the cost function and the constraint equation, and converting model prediction control problems corresponding to the system kinetic equation, the cost function and the constraint equation into nonlinear problems for numerical solution so as to complete leg motion planning; (3) calculating the rotation speed of the wheel based on the leg motion planning result; and (4) based on the rotation speed of the wheels and the leg motion planning result, a whole-body control algorithm is adopted to calculate and obtain moment instructions of leg joints and the wheels. According to the invention, the state space dimension is reduced, and the wheel-ground contact constraint is simplified.

The invention provides a mechanical arm predefined time trajectory tracking control method and system based on time delay estimation, and relates to the technical field of multi-degree-of-freedom mechanical arm trajectory tracking control. Constructing a predefined time error conversion function to define a system error and conversion error system, designing a barrier function and a feedback control rate based on the conversion error system, and designing a Lyapunov function to prove the stability of the system so as to track an expected trajectory; according to the method, time delay information is deeply fused, dependence on a complex model approximate structure is not needed, stable convergence of the mechanical arm system state within predefined time can be achieved when a mathematical model is not accurate, the system control performance and robustness are effectively improved, and the requirement of modern industry for mechanical arm high-performance control is met.

The invention discloses a robot arm control method and device, equipment, a medium and a product, and the method comprises the steps: obtaining a pre-training dynamic model and a real visual depth map of a real robot arm visual angle, and the pre-training dynamic model is used for completing a specified task; determining a joint control value according to the real vision depth map and a pre-training kinetic model; hybrid action control is carried out based on the joint control value, and remote target navigation is carried out on the response action of the real robot arm through a visual navigation model; and the controlled simulation target image and the actual image are obtained, feature matching and closed-loop estimation are carried out based on the simulation target image and the actual image, and pose error compensation is carried out on the action of the real robot arm. The motion is observed and deduced through a real visual depth map, then real and simulated mixed motion control is carried out to reduce a visual and dynamic gap, and finally pose error compensation is carried out. And the pose error of the arm is reduced, and a start pose guarantee is provided for downstream control.

Belongs to the technical field of motion control of foot-type robots, and particularly relates to an anti-interference whole-body control method and system for a quadruped robot based on stability margin perception. The expected joint position, speed and foot end contact force are obtained through nonlinear model predictive control NMPC; a whole body controller WBC based on hierarchical quadratic programming calculates a joint driving torque according to the task priority; according to the joint position, the speed and the torque fed back by the driver and a robot dynamic model, estimating the foot end contact force; calculating resultant force which causes instability of the robot relative to each support polygon side line of the robot; projecting the resultant force, and calculating an included angle between the projection force and the vertical direction; calculating a compensation acceleration through a PI controller; and the compensation acceleration is used as a part of a fuselage linear acceleration task in the WBC, so that the anti-interference capability of the robot is improved. The method is used for solving the problems that in the prior art, the stable state of the quadruped robot cannot be effectively sensed, and an anti-interference control strategy cannot be rapidly generated according to the stable state.

The invention belongs to a robot control method, and provides a human-guided robot-environment interaction self-adaptive control method and a related device for solving the technical problems that an existing human-guided robot-environment interaction control method is insufficient in motion stability, low in human operator safety and low in control precision. And estimating an optimal impedance parameter through a state space model, and learning a human-guided reference trajectory through a neural network in combination with the optimal impedance parameter. Then, in combination with a robot Jacobian matrix and a human-guided reference trajectory, a reference joint speed and an estimated acceleration of a joint space are obtained through closed-loop inverse kinematics, then network parameters of a robot dynamic model are obtained through approximation of an uncertain dynamic model, and finally, the robot dynamic model is obtained through combination with the reference joint speed and the network parameters of the joint space. And the mechanical arm control torque is obtained through the offset width fuzzy neural network. Accurate and compliant control under uncertain motion and dynamics conditions is realized.

The invention relates to the technical field of equipment control optimization, in particular to an intelligent factory equipment energy efficiency optimization system which comprises the following steps: acquiring wall thickness distribution data of a steel pipe, local residual stress and a temperature gradient field in a straightening process; and a preset plastic mechanical model is used for calculating the actual yield strength and the theoretical straightening energy threshold value of each section of the steel pipe, so that a straightening parameter set of the steel pipe straightening machine is generated. And further correcting the straightening parameter set according to the temperature gradient field so as to optimize and eliminate energy consumption. A steel pipe straightening area is divided, a heat sensitive area and a low-temperature hardening area are identified, correction weights are distributed according to the area difference of the areas, then a corrected straightening parameter set is generated, and the straightening process of the steel pipe is optimized.

The invention relates to the technical field of gas turbine performance prediction, and provides a thermodynamics-based gas turbine performance lightweight modeling method, which comprises the following steps of: 1, acquiring actual operation data of a gas turbine, and preprocessing the operation data; 2, establishing a thermodynamic model of the gas turbine; 3, establishing a gas turbine agent model; and step 4, training the gas turbine proxy model to obtain a trained gas turbine proxy model. According to the method, the influence of external environment conditions and power requirements on working condition operation conditions can be eliminated, and key gas turbine performance parameters can be quickly obtained.

A multi-body dynamics simulation method, system, device and medium for a chain system, the method comprising: acquiring a connection relationship among a plurality of target components in the chain system, a structure parameter, a space environment parameter and a task parameter of each target component, and a physical property of a lubricating medium of the chain system under the space environment parameter; correcting the structure parameter of each target component based on the space environment parameter to obtain a target structure parameter; based on the target structure parameters and the connection relation, determining friction characteristic indexes and motion freedom degrees among the multiple target assemblies; constructing a lubrication-volatilization-friction coupling matrix among the plurality of target components; constructing a multi-body dynamic model according to the target structure parameters and the lubrication-volatilization-friction coupling matrix; and acquiring a rotating speed fluctuation curve and load torque data corresponding to the task parameters, and inputting the rotating speed fluctuation curve and the load torque data into the multi-body dynamic model to obtain a dynamic simulation result of the chain system. The reliability of multi-body dynamics simulation of the chain system can be improved.

The invention belongs to the technical field of vehicle steering control, and relates to a van semitrailer steering synchronization angle closed-loop test calibration system, which comprises the following steps of: firstly, executing a static steering test on a no-load combined vehicle, and constructing a mapping reference table of a saddle space position and an ideal hinge angle; then multi-working-condition dynamic steering testing is carried out on the load combination vehicle, vehicle frame deformation data are collected in real time, the deformation data are converted into a hinge angle compensation value through a pre-trained deformation mechanical model, selective correction is carried out on the actually-measured hinge angle based on a deformation compensation starting threshold value, a calibration target is generated to reversely analyze the target saddle position, and the target saddle position is corrected; the problem that in the prior art, inevitable elastic structure deformation and real mechanical steering asynchronous faults of the van semitrailer under the actual dynamic load working condition cannot be fully considered and distinguished is effectively solved, and then multi-working-condition driving verification data are collected, deformation mechanical model parameters are iteratively updated, and a compensation threshold value generation strategy is generated. And closed-loop optimization is realized.

The invention provides a classroom simulation method for virtual reality, and relates to the technical field of data processing, and the method comprises the steps: obtaining a high-dimensional data matrix with a time-space correlation characteristic; constructing an electrical connection relation graph; obtaining a quantum state evolution result of the transient process of the power system; calculating to obtain a multi-physical field distribution parameter corresponding to the equipment; based on the multi-physics field distribution parameters, combining molecular dynamics simulation and a fluid mechanics model to obtain arc dynamic characteristic data; collecting an electromyographic signal of an operator, and generating a force feedback control instruction through a neural network mapping model in combination with mechanical parameters of equipment; and according to the eye movement tracking data, the arc dynamic characteristic data and the force feedback control instruction, generating a virtual reality scene adaptive to the visual response and the operation state of the operator by using a dynamic rendering engine. According to the embodiment of the invention, the authenticity and interactivity of virtual reality classroom simulation can be improved.

The invention discloses an automobile EMB system clamping force accurate control method based on an extended state observer, and belongs to the technical field of electric automobile EMB systems, and the method comprises the following steps: S1, building a novel EMB system five-degree-of-freedom dynamic model containing a LuGre friction model by using an EMB system dynamic relationship; s2, simplifying the five-degree-of-freedom dynamic model of the novel EMB system, estimating the load torque of an EMB driving motor according to the extended state observer, and then estimating the clamping force of the EMB system according to the load torque and the simplified five-degree-of-freedom dynamic model of the novel EMB system; and S3, replacing the measured value to be a feedback value of clamping force closed-loop control of the EMB system according to the estimated EMB clamping force, and accurately controlling the clamping force by adopting fuzzy PID control. By the adoption of the automobile EMB system clamping force accurate control method based on the expansion state observer, the problems that a pressure sensor is high in cost and automobile braking performance is prone to being reduced are solved, and clamping force response is accurately controlled through a fuzzy PID closed loop.

The invention relates to the technical field of modeling, in particular to an aero-engine main bearing kinetic model correction method based on sensitive feature fusion, which comprises the following steps: constructing an aero-engine main bearing kinetic model; simulation data are generated according to the collected actual measurement data, time-frequency domain features of the actual measurement data and the simulation data are extracted, and an initial feature set is constructed; based on a binary improved horse swarm optimization algorithm, sensitive features are screened out from the initial feature set, a sensitive feature set is constructed, a component matrix coefficient of the sensitive feature set is calculated in combination with a principal component analysis method, and a fused sensitive feature expression is obtained; calculating fusion sensitive features of the measured data and the simulation data by using the fusion feature expression, and taking a difference calculation formula of the two as a target function for model correction; and performing optimization based on a horse group optimization algorithm and the target function, updating model parameters of the aeroengine main bearing dynamic model, and realizing correction of the aeroengine main bearing dynamic model.

The invention discloses a road adhesion coefficient estimation method based on adaptive unscented Kalman filtering, and the method comprises the steps: obtaining the static parameters of a vehicle and the driving parameters of the vehicle in the driving process, and carrying out the modeling of the vehicle based on a seven-degree-of-freedom dynamic model, modeling a vehicle tire based on a Dugoff tire model on the basis of the seven-degree-of-freedom dynamic model to obtain a nonlinear system of the vehicle; estimating a road adhesion coefficient in the Dugoff tire model based on an adaptive unscented Kalman filter algorithm and a seven-degree-of-freedom dynamic model to obtain a road adhesion coefficient estimation value; according to the adaptive unscented Kalman filtering algorithm, a proportion correction coefficient is introduced in an unbiased transformation link, and an adaptive noise coefficient is introduced in a standard UKF. According to the method, a proportion correction coefficient and an adaptive coefficient are introduced into an adaptive unscented Kalman filtering algorithm, so that the response capability and estimation precision of a sudden change state are enhanced.

The invention belongs to the technical field of intelligent control, and provides a double-fan parallel operation control system and method based on dynamic flow balance, and the system comprises a flow guide assembly, an electric control valve, a flow sensor and a control assembly; the flow sensors are used for collecting air flow data at the inlets and outlets of the corresponding fan branches and sending the air flow data to the control assembly; the control assembly is used for inputting the air flow data into the three-dimensional dynamic fluid mechanics model to obtain a flow deviation value between the current air flow and the target air flow, inputting the flow deviation value into the control decision model to obtain a control instruction, and issuing the control instruction to the flow guide assembly and / or the electric adjusting valve. And the flow guide direction of the flow guide assembly and / or the opening degree of the electric control valve are / is controlled. According to the scheme, the three-dimensional dynamic fluid mechanics model and the control decision model can be combined, the accurate control instruction is obtained, and the accuracy, reliability and convenience of the double-fan parallel operation control link are improved.

Provided are a planning and control method for a legged robot, an apparatus, a robot, and a storage medium. The method includes: determining, based on the movement state and the swing parameter of each leg at the next moment, a foot-end reference state of each leg, and planning, based on a foot-end dynamic model and a discrete collision model, an impact-aware swing leg trajectory for a leg that starts to swing at the next moment; and performing, based on the movement state, the reference state sequence, and the foot-end reference state, whole-body control on the legged robot, and performing, based on a whole-body dynamic model and the discrete collision model, impact-aware whole-body control for a leg that is a supporting leg in planning but does not touch the ground.

The invention discloses a multi-source cooperative rocker arm-tracked robot composite mechanical structure for earthquake search and rescue, and belongs to the technical field of intelligent rescue equipment. A rocker arm-crawler belt-wheel three-dimensional motion structure system is innovatively designed, a multi-degree-of-freedom rocker arm structure driven by a steering engine is adopted in the middle of the robot, and a double-crawler belt differential driving module driven by a motor is arranged at the bottom of the robot; a swing arm balance wheel set is arranged on the front portion to assist climbing operation. According to the composite structure, a posture stability control algorithm is established through a mass center dynamic model, and intelligent switching of three motion modes of wheel type high-speed maneuvering, crawler belt obstacle crossing and rocker arm climbing can be achieved. Tests show that the structure can enable the robot to stably cross a 100 mm vertical obstacle, good posture stability is kept in unstructured terrains such as gravel and rubble, and meanwhile the environment is sensed through various sensors. Compared with a traditional single motion structure, the multi-dimensional maneuvering ability in the complex post-disaster environment is achieved through mechanical structure innovation, and the terrain adaptability of rescue equipment is effectively improved.

The invention discloses a double-foot wheel-legged robot pose control method and device based on hierarchical cooperative control, a medium and a product, and relates to the field of robot control, and the method comprises the steps that a hierarchical cooperative control framework is constructed; the layered cooperative control framework comprises a balance controller and a whole body attitude controller; the balance controller determines a reference wheel joint driving torque based on a simplified inverted pendulum dynamic model according to the pose information of the upper mass center of the biped wheel-leg robot; the whole-body attitude controller performs optimization control on all joints of the biped wheel-leg robot by adopting an incremental model prediction control algorithm combined with a reference wheel joint driving moment based on a whole-body dynamic model; state information of the biped wheel-legged robot is obtained; according to the state information, a driving torque instruction of each joint is obtained based on a hierarchical cooperative control framework; and driving the double-foot wheel-leg robot to move according to the driving torque instruction of each joint. The precision, robustness and real-time performance of robot motion control can be improved.