125 results about "Kinematic modeling" patented technology

The invention relates to the technical field of underwater navigation, and discloses a real-time attitude estimation method of an underwater inertial navigation system. The method comprises the steps that the underwater vehicle collects multi-axis angular velocity and linear acceleration data through an inertial measurement unit and uploads the data to a central processing module, and the central processing module conducts kinematics modeling on the data to generate attitude change initial feature vectors; receiving water flow velocity data of a Doppler velocimeter and pressure data of a depth sensor, and performing flow field interference compensation optimization on the attitude change initial feature vector based on the data to generate an anti-interference attitude feature vector; fusing the anti-interference attitude feature vector and a historical attitude estimation result to generate space-time fusion attitude state representation, and then resolving a real-time Euler angle through a nonlinear filter; and matching a corresponding attitude stability control instruction from the navigation strategy library according to the real-time Euler angle, and issuing the attitude stability control instruction to a propeller execution unit. The method can effectively cope with underwater complex environment interference and guarantee stable operation of the underwater vehicle.

The invention relates to the technical field of automatic laying of composite materials, in particular to an automatic compensation method, system and equipment for errors between silk laying belts and a storage medium. The method for compensating the error between the automatic silk laying belts comprises the following steps: establishing a mathematical mapping relation between the error compensation amount between the belts and robot control parameters through a standard sample piece laying test, and forming an error compensation theoretical model; the method comprises the following steps: aiming at a robot type fiber placement machine structure, constructing an inter-band error model based on pose kinematics modeling, robot and additional axis multi-axis interpolation modeling and error vector decomposition; the tail end target position, the attitude angle and the error compensation amount in the laying program are read in real time, and real-time control input is obtained; and on the basis of the error model, the corrected tail end position is inversely solved into a real-time adjustment angle of each joint, a robot inverse solution algorithm is corrected, and a joint control instruction is generated. According to the automatic tow belt laying device, the laying position precision of the automatic tow belt laying can be remarkably improved.

The invention relates to the technical field of industrial robots, in particular to a five-degree-of-freedom industrial robot path planning method and system based on D-H parameters and dynamics modeling, and realizes high-precision path planning and dynamic environment adaptation by combining kinematics modeling, dynamics analysis and MATLAB simulation technologies. The method comprises the steps of building a robot kinematics model, building a kinetic equation, mixing a path planning strategy, solving inverse kinematics and performing multi-sensor fusion control. The system covers modeling, calculation, planning, simulation and feedback modules, and the operation efficiency and safety of the industrial robot in a complex scene are effectively improved.

The invention relates to the field of exoskeleton robot technology and robot control, in particular to an intelligent self-adaptive exoskeleton robot multi-view sensing obstacle avoidance method and system. A binocular camera is combined with a laser radar to monitor the external environment, and when it is detected that an obstacle exists around a wearer, the obstacle avoidance is performed; and path searching is carried out by using an improved fast expansion random tree star algorithm, a control instruction is generated based on exoskeleton kinematics modeling, and the exoskeleton robot is driven to realize an obstacle avoidance function. The obstacle avoidance method can flexibly deal with various complex conditions in a dynamically changing environment, is high in real-time performance, can help a wearer to complete obstacle avoidance in some emergency conditions, fully reflects the intelligent self-adaptive capability of the system, and enhances the safety and reliability.

The invention discloses a lower limb exoskeleton control system and method based on phase recognition and model prediction control. The system comprises a kinematics modeling module, a gait database module, a data processing and feature extraction module, a gait phase recognition module, a dynamics modeling module, a model prediction controller and an actuator control unit. By recognizing the gait phase and dynamically adjusting and controlling the target, precise assistance of the natural gait of the wearer is achieved. The system calculates the trajectory of the ankle joint relative to the hip joint in real time based on a kinematic model, and constructs a database in combination with gait data collected under multiple working conditions to provide an expected trajectory and reference parameters for control. In the dynamic modeling process, motor driving torque and man-machine interaction torque are introduced, a system dynamic model is established in a unified mode, and control characteristics under different gait phases are reflected.

The invention provides a unilateral step obstacle crossing attitude control method for a wheel-track combined type mobile system, which relates to the field of mechanical engineering control and comprises the following steps of: establishing an initial coordinate system of a robot, and defining space attitude parameters of the robot in an obstacle crossing attitude adjustment process; representing topographic conditions by using the wheel center position, representing a vehicle body attitude by using the spatial attitude parameters, and performing spatial transformation on the initial coordinate system to obtain a kinematic model about the wheel center position and the spatial attitude parameters; on the basis of kinematics modeling, obstacle crossing stability of the robot is used as a control target, the swing angle of a rear swing arm of the robot and the length of an electric push rod are used as control variables, the control variables are used as an initial population of an improved genetic algorithm, and the improved genetic algorithm is used for carrying out iterative solution on the control variables until an optimal solution is obtained. The obstacle crossing posture of the single-side step obstacle of the robot is adjusted by controlling the optimal solution, then the pitch angle and the roll angle are cooperatively adjusted, and the obstacle crossing stability is improved.

The invention discloses a forward and reverse design and simulation method for virtual excavation of a sunken vertical shaft heading machine. The method comprises the following steps: S1, initializing a terrain; s2, kinematic modeling of the heading machine; s3, track surface generation and virtual excavation; s4, forward design; s5, carrying out reverse design; and S6, outputting data. According to the forward and reverse design and simulation method for virtual excavation of the sinking type vertical shaft heading machine, geometric-level virtual excavation simulation can be realized based on geometric parameters, a kinematic model and stratum data of a VSM; the excavation effect of the preset excavation parameters can be verified through forward design, and a feasible excavation parameter set can be intelligently and reversely solved from the target excavation morphology through reverse design; and meanwhile, a standardized geometric model and structured data which can be directly used for subsequent engineering numerical analysis and construction guidance can be exported, so that the parameter determination precision, the process controllability and the scheme optimization capability before construction are improved.

The invention belongs to the technical field of mechanical arm joint control, and particularly discloses a preset performance self-adaptive joint control method for a rope-driven super-redundant snakelike mechanical arm, and the method comprises the following steps: carrying out kinematics modeling on a rope joint link of the rope-driven super-redundant snakelike mechanical arm, determining a relation between a rope speed and a joint angle, and determining a preset performance of the rope-driven super-redundant snakelike mechanical arm; calculating a joint jacobian matrix; designing a joint angle controller, defining an angle error and constraining the angle error in a preset performance range, and obtaining control input through an error transformation and return-to-zero dynamics principle so as to realize joint angle control; according to the method, a joint Jacobian matrix is estimated on line, and the joint Jacobian matrix is dynamically updated according to a rope speed error and a return-to-zero dynamic theory so as to adapt to the flexibility, time-varying characteristics and external disturbance of a rope, and the control precision is ensured. According to the method, it can be guaranteed that the joint angle of the rope-driven super-redundant mechanical arm can be accurately controlled under different working conditions, and it is guaranteed that the mechanical arm completes high-precision operation under the complex working conditions.

The invention relates to the technical field of automatic guided vehicle control, in particular to a multi-differential wheel set AGV trajectory tracking method and system, and the method comprises the steps: building a special kinematics forward / inverse solution model, and determining the speed and angle mapping relation between a driving wheel and the center of a vehicle body; constructing a double-layer framework of upper-layer pure tracking trajectory tracking and lower-layer wheel set cooperative control, and introducing a steering cooperative optimization strategy; an intelligent self-correction mechanism is set, and a strong correction mode or a smooth correction mode is selected according to the deviation distance; and deep fusion of a pure tracking algorithm and a special chassis is realized, and a complete closed-loop control system is formed. The system comprises a chassis module, a kinematics modeling module, a double-layer control module, a self-correction module and a closed-loop feedback module. According to the method, the problems of poor adaptability, motion coupling, unbalanced heavy AGV tracking precision and stability and the like of a traditional algorithm are solved, high-precision trajectory tracking is realized, tire wear and energy loss are reduced, the robustness of the AGV in a complex environment is enhanced, and the method is suitable for heavy and heavy-load AGVs.

The invention discloses an IMU (Inertial Measurement Unit) drift error calibration method for long-term attitude measurement of an industrial robot. The IMU drift error calibration method comprises the following steps: deducing a pose matrix between a robot base coordinate system and a navigation coordinate system; deriving a pose matrix between a robot tail end coordinate system and a sensor body coordinate system; kinematics modeling is conducted on the industrial robot, and motion parameters are obtained; deriving a homogeneous transformation matrix between two adjacent joints according to the kinematic parameters; acquiring actual joint corner information when the robot runs and actual information measured by a tail end IMU when the robot runs; wherein the actual information of the IMU comprises actual angular velocity information and actual attitude information; the collected actual joint rotation angle information is substituted into the homogeneous transformation matrix, theoretical attitude information of the tail end of the robot is obtained, and the theoretical attitude information is converted into a navigation coordinate system; converting the theoretical attitude information converted into the navigation coordinate system into an Euler angle; designing a Kalman filter; according to a Kalman filter, data fusion of theoretical attitude information and actual attitude information is completed, and calibration is achieved. According to the method, joint angle information, the industrial robot end theoretical attitude obtained through forward kinematics calculation of the kinematics model and actual attitude data obtained through IMU measurement are fused, and accumulated error calibration formed in long-term attitude measurement of the IMU is achieved.

The invention discloses a joint calibration method based on a rotary laser radar and a camera, and the method comprises the following steps: S1, carrying out the kinematic modeling of the camera, the laser radar and a motor rotating shaft based on a DH parameter method; s2, collecting synchronous laser radar point cloud data and camera image data of a motor rotating shaft at different angles; s3, processing the laser radar point cloud data; s4, processing the camera image data; s5, projecting the extracted laser point cloud depth continuous edge features to an image plane based on a current external parameter estimation value, and matching and associating the extracted laser point cloud depth continuous edge features with the image edge features extracted in the step S4; s6, constructing a projection residual equation about the external parameters according to the successfully matched feature pairs; and S7, the residual equation is linearized. According to the joint calibration method based on the rotary laser radar and the camera, high-precision and high-robustness automatic calibration is completed in an environment without an auxiliary target through kinematics modeling of a system and an advanced feature extraction matching technology. The invention further discloses a joint calibration device and system based on the rotary laser radar and the camera, and a storage medium.

The invention discloses a universal dual-mode active-disturbance-rejection control method for an air-ground amphibious robot. The method comprises the steps that kinematics modeling is conducted on a flight end and a ground end according to the structure of the air-ground amphibious robot; carrying out ground-air double-end common disturbance pre-modeling; constructing an extended state observer; detecting a current motion mode; weighting a nonlinear least square model, compensating disturbance information, and estimating total disturbance in real time; and a bimodal active-disturbance-rejection controller is designed, disturbance is compensated in real time, and bimodal active-disturbance-rejection control over the air-ground amphibious robot is achieved. According to the method, information of all motion mode models and common disturbance of the air-ground amphibious robot are preprocessed, the improved active-disturbance-rejection control method is applied under dual modes, the adaptive capacity of the air-ground amphibious robot to external disturbance and complex environments during reconnaissance work is greatly improved, and the method has universality in control over the air-ground amphibious robots of various mechanical structures.

The invention relates to a human body multi-cycle gait track prediction method based on small sample space-time decoupling. The method comprises the following steps: firstly, obtaining a single-cycle gait sample through kinematics modeling and cycle segmentation, and extracting, expanding and normalizing parameters such as stride and stride frequency; secondly, establishing a gait parameter joint distribution model by using a Gaussian mixture model and Gaussian mixture regression, and predicting gait parameters according to the target speed; and then space and time decoupling reconstruction is carried out, a high-fidelity joint trajectory is generated by adopting an adaptive collaborative attention LSTM network in space, a zoom factor is calculated based on a predicted stride frequency and a target speed in time, a time sequence is adaptively adjusted through a dynamic motion primitive, and finally a multi-period and multi-speed high-fidelity gait trajectory is generated through fusion. The method has high precision, interpretability and strong generalization ability under the small sample condition, the generated gaits are natural and coordinated and accord with the biomechanical law, and the application cost of a humanoid movement device is remarkably reduced.

The invention relates to the technical field of intelligent control, and particularly to a gantry platform kinematics modeling method considering parallelism and perpendicularity errors, which is applied to a gantry platform device. The gantry platform device comprises a crossbeam, a first guide rail and a second guide rail, one end of the crossbeam is in sliding fit with the first guide rail, and the other end of the crossbeam is in sliding fit with the second guide rail; the first guide rail is provided with a first longitudinal motor, and the second guide rail is provided with a second longitudinal motor; and the crossbeam is provided with a transverse motor configured to drive the gantry platform to move along the crossbeam. The method comprises: establishing a two-dimensional coordinate system; constructing a forward kinematics solution model; and constructing an inverse kinematics solution model.

The invention discloses an inverse kinematics method for a redundant seven-degree-of-freedom robot. The method specifically comprises the following steps: step 1, establishing forward kinematics modeling of the seven-degree-of-freedom robot; step 2, inputting a target pose, and defining a tail end pose error of the seven-degree-of-freedom robot as a Riemannian distance on a three-dimensional special Euclidean group manifold; 3, adopting a three-stage hybrid optimization strategy; 4, carrying out constraint processing between joints; and 5, verifying convergence and robustness. The adaptive differential evolution algorithm is used as a core optimizer, parameters of the adaptive differential evolution algorithm can be dynamically adjusted along with an iteration process, and global exploration and local development capabilities are balanced; and a dynamic parameter adjustment strategy of nonlinear progressive increase of a scaling factor and linear progressive decrease of a crossover probability is designed, and a DE / current-to-pbest variation strategy is adopted, so that the algorithm pays attention to global exploration in the initial stage of iteration and is biased to fine development in the later stage, and the convergence speed and the global search capability are effectively improved.

The invention provides a safety management system and method for an offshore wind turbine generator, and relates to the technical field of offshore wind power. Comprising a meteorological sensing subsystem, a wave analysis subsystem, a dynamic modeling subsystem and a safety regulation and control subsystem, wherein the meteorological sensing subsystem comprises a wind speed monitoring module, an air pressure monitoring module, a temperature and humidity monitoring module and a data fusion module; the wave analysis subsystem comprises a wave height monitoring module, a wave period monitoring module, a wave direction monitoring module and a wave coupling calculation module; the dynamic modeling subsystem comprises a kinematics modeling module, a dynamics modeling module, a wind wheel load calculation module and a platform stability evaluation module; the safety regulation and control subsystem comprises a wind speed sudden change response module, a wave coupling optimization module, a platform posture adjustment module and an emergency shutdown module. According to the scheme, the operation safety of the offshore wind turbine generator is improved.

The invention discloses a continuum robot position tracking and joint limiting avoidance method, and belongs to the field of robot control. According to the method, a current path is obtained through forward kinematics modeling, joint limiting constraint and ideal path generation are combined, a nonlinear programming problem with the maximum path deviation and the minimum path deviation as the target is constructed, and joint increment is iteratively solved to achieve end tracking and overall path fitting. According to the method, the problem that inverse kinematics is difficult to solve is avoided, joint overrun is explicitly avoided, and the method is suitable for high-precision and high-reliability control in a narrow space and an obstacle environment.

Disclosed are a rigid-flexible coupling continuum robot unit and a continuum robot. In the rigid-flexible coupling continuum robot unit, structural unit blocks are connected to each other in an interlaced manner to form a whole mechanical arm; a flexible nickel-titanium rod is connected to two adjacent structural unit blocks at two ends, respectively; a front-end unit block is arranged at the frontmost end of the mechanical arm; and a rear-end unit block is arranged at the rearmost end of the mechanical arm. In use, the memory alloy nickel-titanium rod forms a flexible joint, a limiting clamping jaw and a limiting boss form a rigid joint, the two joints complement each other, after a driving wire exerts a pressure, the limiting clamping jaw and the limiting boss are in a wrapping relationship, the movement track of the robot unit is limited, the robot unit always rotates along a circular arc around a rotation center, and the robot unit has the advantages of simple and accurate kinematic modeling, strong torsion resistance, strong load bearing capacity and the like, and is suitable for operation in various complex environments.

The invention relates to the technical field of intelligent manufacturing, and discloses an enterprise production data traceability control method based on artificial intelligence, and the method comprises the steps: actively implanting a digital coding disturbance sequence as a physical traceability fingerprint, and combining with kinematics modeling based on a Lagrange view angle, thereby achieving the traceability control of enterprise production data. Compared with a traditional statistical matching method which only depends on waveform geometric similarity, the method has the advantages that a physical sensing time sequence alignment mechanism is constructed, a time mapping path is forcibly required to follow the displacement conservation and entropy increase law, and the accuracy of the real-time tracking is improved. According to the technical scheme, mass balance verification is further utilized to carry out physical checking calculation on a traceability result, and the technical span from signal correlation advanced to physical causality effectively eliminates false alignment and quantization errors caused by shutdown and speed change, ensures absolute accuracy and non-tampering property of responsibility entity locking, and improves the reliability of the system. And the robustness and legal credibility of the industrial data management and control system are greatly improved.

The invention relates to the technical field of robot man-machine interaction, in particular to a kinematics analysis method for a new-configuration six-degree-of-freedom force feedback hand controller, and the method comprises the steps: constructing a joint coordinate system of each rod piece of the hand controller; obtaining D-H parameters of a joint and a rod piece in the hand controller; performing joint processing on the kinematic model of the hand controller; obtaining a conversion matrix between adjacent joints; and the pose of the end effector of the hand controller in the base coordinate system is obtained. According to the method, kinematics modeling is carried out on the six-degree-of-freedom force feedback hand controller which is subjected to shaft shifting processing and added with the virtual joints by utilizing a D-H method, so that the six-degree-of-freedom force feedback hand controller obtained through modeling is more accurate.

The present invention discloses a multi-degree-of-freedom path planning method for unsupported additive manufacturing of a hanging structure. The present invention sequentially performs preprocessing, conical transformation processing, and slicing processing on the model to be printed to convert and obtain the planned path of the conical transformation model; sequentially performs path segmentation processing and inverse conical transformation processing on the planned path of the conical transformation model to obtain the planned path of the model to be printed in the coordinate system of the model to be printed; performs exponential product kinematic modeling on the device to obtain the kinematic conversion relationship between the coordinate system of the model to be printed and the coordinate system of the device; and then performs conversion to obtain the planned path of the model to be printed in the coordinate system of the device and performs 3D printing. The present invention is applicable to most existing slicing software, and can realize unsupported printing of hanging structures by using the path planning of the generated slicing software, thereby simplifying the post-processing process after 3D printing and further improving the quality and surface flatness of the printed parts.

The invention discloses a kinematics semi-analytical modeling method and terminal for a human wrist-simulated parallel mechanism, and the method comprises the steps: constructing a global coordinate system, a first coordinate system and a second coordinate system when the wrist parallel mechanism is subjected to kinematics positive solution, and then obtaining a target D-H expression corresponding to the tail end pose of the human wrist-simulated parallel mechanism, a target D-H expression is obtained, the target D-H expression shows the relation between the tail end pose and a first joint angle and the relation between the tail end pose and a second joint angle, then a target modular length expression is obtained, the target modular length expression shows the relation between a first modular length and the first joint angle and the relation between a second modular length and the second joint angle, and finally, the target D-H expression shows the relation between the tail end pose and the second joint angle. And obtaining numerical values of a first modulus length and a second modulus length, and substituting the numerical values of the first modulus length and the second modulus length into the target D-H expression and the target modulus length expression to obtain a tail end pose. The invention provides a solution capable of completing operation on a low-computing-power platform for a parallel mechanism simulating a human wrist.

The invention discloses a method for analyzing the influence of a rod length error and a kinematic pair gap on the motion of an ornithopter. The method comprises the following steps: carrying out kinematic modeling on an ornithopter structure to obtain a kinematic model; acquiring a motion trail of the end point of the tail end of the outer wing in the kinematic model as a first influence factor; the average flapping position change of the rod piece at the tail end of the outer wing is obtained in the kinematic model to serve as a second influence factor; performing margin modeling on the ornithopter structure in combination with the first influence factor and the second influence factor to obtain a margin model; and performing reliability solution analysis on the input ornithopter to be analyzed according to the margin model. According to the method, the error influence can be accurately captured, and the actual working state of the ornithopter can be more accurately reflected by defining the motion trail of the end point of the tail end of the outer wing and the average flapping position change of the rod piece at the tail end of the outer wing as influence factors of specific reliability. The two indexes are directly associated with the key parameters of the flight performance of the ornithopter, thereby ensuring that the evaluation of the system reliability is closer to the reality.

The invention relates to the technical field of mechanical arm control, and provides a mechanical arm trajectory planning method and device, equipment and a medium. The method comprises the steps that the pose of an obstacle bounding box under a robot coordinate system is fitted; fitting a robot bounding box; taking the center point of the tool at the tail end of the operation arm as a starting point, taking the center point of the tool at the tail end of the conveying arm as an ending point, and combining the to-be-fitted track length and the obstacle avoidance space to generate a motion track curve of the operation arm; track point positions are extracted from the motion track curve, the posture of the operation arm at each track point position is planned, and the posture of the operation arm at the corresponding track point position is adjusted under the condition that whether the track point positions of the operation arm are reachable or not is verified; and under the reachable condition, the track point location of the operation arm is matched with the current endoscope conveying length, and the track point location of the operation arm is described through the pose of the operation arm. According to the invention, through environment perception, kinematics modeling and trajectory generation, accurate obstacle avoidance is realized in a complex and changeable operation environment, and the safety and reliability are improved.

The present application relates to the field of robotic arm control technology, and provides a robotic arm trajectory planning method, device, equipment, and medium, including: fitting the position and posture of the obstacle bounding box in the robot coordinate system; fitting the robot bounding box; using the center point of the tool at the end of the manipulator arm as the starting point and the center point of the tool at the end of the conveying arm as the ending point, and combining the length of the trajectory to be fitted and the obstacle avoidance space to generate a motion trajectory curve of the manipulator arm; extracting trajectory points from the motion trajectory curve, planning the posture of the manipulator arm at each trajectory point, verifying whether the trajectory points of the manipulator arm are reachable, and if not reachable, adjusting the posture of the manipulator arm at the corresponding trajectory point; if reachable, the trajectory points of the manipulator arm are matched by the current endoscope conveying length, and the trajectory points of the manipulator arm are described by the position and posture of the manipulator arm. The present application achieves precise obstacle avoidance in a complex and changing surgical environment through environmental perception, kinematic modeling, and trajectory generation, thereby improving safety and reliability.

The invention discloses an intelligent steer-by-wire automatic parking method for a semitrailer, which comprises the following steps of: S1, modeling a parking environment, defining a vehicle state and performing kinematics modeling; s2, generating a parking path based on a mixed A * algorithm; and S3, designing a target function and carrying out optimization solution by utilizing a model prediction control algorithm to realize rolling optimization of the automatic parking process. According to the intelligent steer-by-wire automatic parking method for the semitrailer, autonomous parking control of the semitrailer in a complex environment is achieved, and automatic collision avoidance, posture adjustment, path minimization and cost control are achieved in the parking process.

The present invention discloses a robotic arm inverse kinematics device that integrates the Taguchi method with an improved artificial bee colony algorithm. After completing the kinematic modeling of the robotic arm, the method needs to apply the kinematic model and constraints to construct a fitness function for the problem, then use the improved artificial bee colony algorithm to search for the inverse kinematics solution of the robotic arm, and finally use the Taguchi method to screen the important parameters of the improved artificial bee colony algorithm. The method introduces a new intelligent swarm algorithm, an improved algorithm of the artificial bee colony algorithm, to solve the inverse kinematics problem of the robotic arm. By considering the swarm movement speed and introducing relevant parameters, the algorithm's solution accuracy for the problem is effectively improved, and the shortcoming of falling into local optimality in solving the robotic arm inverse kinematics problem is improved. At the same time, applying the Taguchi method to select the most appropriate algorithm parameters can obtain better solution results.

The invention discloses an endoscope active following motion control method, which comprises the following steps of: 1, carrying out kinematics modeling on a continuum endoscope, obtaining a pose transformation matrix of the continuum endoscope so as to obtain a working space of the continuum endoscope, and verifying a reachable range of the working space in an eyeball; step 2, constructing a visual servo following controller based on the endoscope image, collecting the endoscope image and identifying the tip of the surgical instrument in the endoscope image based on an image processing algorithm of a YOLO neural network architecture; and extracting the deviation between the pixel space coordinates of the feature points and the expected features in real time, and controlling the camera at the tail end of the continuum endoscope to move based on the deviation of the feature points until the image features reach a target state. The multi-view intraoperative image can be provided in the continuous bending movement process of the continuum endoscope, the tail end of a surgical instrument is followed in real time in the operation, the posture of the surgical instrument in the operation is observed in real time, and the automation degree of the continuum endoscope is improved.

The invention relates to a kinematics modeling method for a heterogeneous multi-branch rope-driven mechanical arm, belongs to the technical field of kinematics modeling of robots and mechanical arms, solves the problem of performing kinematics modeling on the heterogeneous multi-branch rope-driven mechanical arm, and comprises the following steps: respectively establishing kinematics recursion relations of a large-span mechanical arm, a rope-driven agile mechanical arm and a rope-driven flexible mechanical arm; the kinematics recursion relations of the large-span mechanical arm, the rope-driven agile mechanical arm and the rope-driven flexible mechanical arm are integrated, so that a kinematics model of the large-span mechanical arm-the rope-driven agile mechanical arm and a kinematics model of the large-span mechanical arm-the rope-driven flexible mechanical arm are obtained; the model established through the method is simple in structure, the corresponding relation between the joint rotation angle and the tail end pose of the mechanical arm can be accurately reflected, the accuracy of the model is guaranteed, practicability is high, and the mechanical arm can be further controlled conveniently.

The application discloses a kind of unmanned aerial vehicle cluster formation fault-tolerant method based on original pigeon chaotic adaptive sliding mode control, including the following steps: step one: the kinematics of unmanned aerial vehicle is modeled, the initial state of unmanned aerial vehicle is determined and the formation flight control system of wingman and long machine;Step two: introduce the virtual reference unmanned aerial vehicle dynamics model, design tracking error, obtain dynamic tracking error equation, ensure the accuracy of reference model;Step three: design sliding mode surface function, obtain reduced order sliding mode kinematics equation by using adaptive sliding mode control technology;Six steps such as.The method of the application is simple, the proposed chaotic pigeon group mechanism can greatly optimize the parameters in adaptive control and sliding mode control parameters, increase the control convergence speed, and give a robust solution to the difficult problems such as unmanned aerial vehicle unable to adapt to complex environment due to communication failure.