104 results about "Forward kinematics" patented technology

The invention discloses a security constraint type inverse kinematics solving method and device and a storage medium. The method comprises the following steps: firstly, forming a joint angle-tail end pose pairing data set by students through forward movement of a robot; training an improved RBF (Radial Basis Function) network by using the data set to establish initial mapping from a tail end pose to a joint angle to obtain an initial approximation model; taking the prediction output of the model as an initial population of a PSO algorithm, and updating the speed and position of particles in the initial population through iteration; designing a comprehensive cost function, introducing a joint angle constraint and an obstacle collision constraint, and evaluating the advantages and disadvantages of each particle; and when the PSO algorithm reaches the maximum number of iterations or the comprehensive cost function value is lower than a set threshold value, outputting a global optimal particle position as a final inverse kinematics solution. On the premise of ensuring the solving precision, the joint limit constraint and the obstacle avoidance constraint are explicitly processed, so that an accurate, safe and feasible inverse solution is output, and the reliability and the safety of robot operation are remarkably improved.

The invention provides a digital twinning five-axis machine tool contour error prediction method and system and electronic equipment, and belongs to the technical field of numerical control machine tool precision control and digital twinning. According to the method, servo axis data are collected in real time at a numerical control system end, electromechanical parameters are identified on line, comprehensive disturbance is estimated, and an autoregressive exogenous (ARX) model is updated accordingly; an interpolation instruction is generated in a digital twin body end mirror image numerical control system process, an updated model is utilized to predict a shaft position with deviation, a tool path is obtained through kinematics positive solution, and finally contour errors are calculated through geometric alignment. According to the digital twinning five-axis machine tool contour error prediction method and system and the electronic equipment, dynamic and high-precision prediction of the five-axis machine tool machining track contour error is achieved through the online identification and digital twinning technology, the limitation of a traditional static compensation method is overcome, and the precision of the digital twinning five-axis machine tool contour error prediction is improved. And a key basis is provided for prospective process optimization and precision control, and the machining precision and efficiency are effectively improved.

The invention discloses a multi-degree-of-freedom pose adjustment method for a large-length-diameter-ratio target, and belongs to the technical field of multi-degree-of-freedom pose adjustment of automatic spraying equipment.The multi-degree-of-freedom pose adjustment method comprises the steps that firstly, the tail end pose deviation value of the target is obtained; and establishing a five-connecting-rod model and a forward kinematics model of the pose adjusting device. A five-connecting-rod model is constructed along the tail end of the large-length-diameter-ratio target, the pitching unit, the rotation unit, the transverse moving unit and the supporting foot unit in sequence; constructing a forward kinematics transformation matrix based on a product of coordinate transformation of the five connecting rods; and based on the forward kinematics transformation matrix, inversely solving the adjustment amount of each motion axis of the pose adjustment device at the target tail end pose deviation amount. And finally, according to an inverse solution result, adjusting each motion axis of the pose adjusting device so as to realize multi-degree-of-freedom pose adjustment of the tail end of the target with the large length-diameter ratio. According to the method, high-precision adjustment of the tail end posture is achieved, the purpose of precise adjustment of the automatic spraying length-diameter ratio target posture is achieved, and good practicability is achieved.

The invention relates to an excavator trajectory planning method based on an improved multi-objective particle swarm algorithm, and belongs to the technical field of engineering machinery trajectory planning. The method comprises the following steps: establishing a forward kinematics model through a D-H homogeneous coordinate transformation method; based on the forward kinematics model, establishing an inverse kinematics model through a geometric method; setting six path points in the track according to the mining track; based on an inverse kinematics model, converting the space coordinates of the six path points into space angles of joints; interpolation is carried out on the joint path points through a five-time B spline curve, and a track is generated; determining an optimization objective function according to actual application requirements, and setting constraint conditions according to a specific excavator type; and finally, the optimization problem is solved through an IADEMOPSO algorithm, an optimal Pareto solution is selected by using an average optimal evaluation formula, and an optimal track is generated. The track planning of the excavator can be realized.

The invention discloses an intelligent robot grabbing control method and system based on AI vision, original vision and kinematics flow are fused through space-time alignment, and a physical-level dynamic shielding mask is accurately extracted through forward kinematics and reverse perspective projection. Then, the limitation of traditional pure semantic matching is broken through, a narrow-band gradient reference field of a shielding boundary is explicitly extracted to serve as a spatial topology bias injection attention mechanism, feature illusion completion guided by physical continuity prior is executed in a hidden space, and high-fidelity perspective features are generated; on the basis, the network synchronously regresdes six-degree-of-freedom grabbing pose and execution uncertainty, the uncertainty serves as an independent variable to dynamically attenuate and adjust the impedance rigidity of the mechanical arm, finally, self-adaptive compliant interaction in a blind area is achieved in a bottom layer physical servo link, and space positioning precision and operation safety are both considered.

The application discloses a mobile redundant manipulator real-time grabbing and trajectory tracking method and system based on optimization theory. In the method, the mobile redundant manipulator platform carries out real-time distance measurement on a target object based on a camera, and when the distance is less than a set threshold, a grabbing operation is performed. The application constructs a mobile redundant manipulator platform dynamics model based on robot forward kinematics, establishes a mobile redundant manipulator platform optimization model based on kinetic energy loss, designs a corresponding objective function, and sets constraint conditions of the corresponding optimization model in combination with physical limit conditions of the mobile redundant manipulator platform. By sampling time, inputting a current state of the mobile redundant manipulator platform, solving joint angular velocity and mobile platform speed at a next time, real-time trajectory tracking of the mobile redundant manipulator platform is realized. The application greatly increases the working range of the manipulator, the model is simple and easy to solve, accurate trajectory tracking can be realized, and the application prospect is wide.

The invention provides a digital twinning five-axis machine tool kinematics transformation method, system and device and a medium, and belongs to the field of numerical control technology and digital twinning crossing technology. The method comprises the steps that axis parameters are collected from a five-axis machine tool controller; constructing a unified five-axis parameter set comprising axis types, axis reference points and direction vectors; a hierarchical homogeneous transformation chain is constructed in a machine tool base coordinate system based on the parameter set, and forward kinematics transformation from a mechanical coordinate system to a workpiece coordinate system is achieved; and based on the unified parameter set and the transformation chain, reversely solving an axis position vector from a tool position instruction of the workpiece coordinate system and mapping the axis position vector back to a controller coordinate. By adopting the digital twin five-axis machine tool kinematics transformation method, system and equipment and the medium, the problems of poor model reusability and inconsistent virtual-real mapping caused by machine tool structure difference and numerical control system diversity are solved, cross-platform and cross-model general reversible kinematics transformation is realized, and the method has the advantages of high practicability and high practicability. And the engineering applicability and deployment efficiency of the digital twin model are improved.

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 robot whole body control method and system based on real-time inertia motion capture and reinforcement learning, and belongs to the field of robot control. The system comprises a motion capture module, a data processing and forward kinematics module, a motion redirection and optimization module, a general motion strategy control module and a real-time control and driving module which are connected in sequence, and an end-to-end closed-loop control assembly line is formed through a shared memory and a high-speed communication protocol. According to the method, human body joint data are collected through inertia motion capture equipment, high-quality mapping from a human body posture to a robot model is achieved through posture calculation, non-uniform scaling and two-stage differential inverse kinematics optimization, and a stable joint instruction is generated in combination with a reinforcement learning strategy trained by a PPO algorithm. The method solves the problems of lack of feedback closed loop, joint deadlock, contradiction between fidelity and stability and the like in the prior art, has the characteristics of high robustness and high expansibility, and can be widely applied to scenes of remote operation, action reproduction and the like.

The invention belongs to the technical field of semiconductor manufacturing safety control, and particularly relates to a collision detection method and system for a wafer transfer robot, and the method comprises the steps: receiving a joint angle sequence and height coordinates outputted by a robot trajectory planning module; cartesian coordinates of all nodes of the mechanical arm are calculated through a forward kinematics solver; preferentially checking whether the node is located in a predefined safety area or not by utilizing a point area judgment and line segment area detection algorithm; performing regionalized wafer collision detection on the wafer outside the safe region; if the wafer collision does not occur, constructing an oriented bounding box (OBB) for the risk connecting rod; detecting whether the vertex of the OBB crosses a boundary or not, and performing line segment intersection detection on each edge of the OBB and a chamber boundary line segment of a corresponding area; and finally outputting a collision judgment result, and deciding whether to execute motion or not by a robot control system. According to the invention, efficient and accurate collision detection is realized through a multi-stage detection mechanism and highly adaptive section selection, and the method has the advantages of high real-time performance, low cost, easy integration and the like.

Embodiments of the application disclose a screw-based gesture recognition method and device, electronic equipment and a storage medium. A first key point position corresponding to a hand key point in a continuous frame image is detected. A three-dimensional coordinate of each hand key point in a corresponding first coordinate system is calculated. The first coordinate system is a three-dimensional coordinate system determined by adjacent key points away from the fingertips of the hand key point. The three-dimensional coordinates are input into a preset screw-based forward kinematics model to obtain a pose transformation set of the hand key point corresponding to each frame of image. According to the pose transformation set, a Jacobian matrix corresponding to each frame of image and a predicted three-dimensional coordinate corresponding to each hand key point are calculated, and a corresponding second key point position is calculated according to the predicted three-dimensional coordinate. The pose transformation set is optimized based on the positions of the key points and the Jacobian matrix. Parameters are output based on the optimized pose transformation set. The application ensures the consistency of the processing of the shapes of the front and back hands, thereby improving the accuracy of the processing results.

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.

The embodiment of the invention provides a regular hole cutting method and device, a cutting robot and a storage medium, and relates to the technical field of robots. Geometric parameters and cutting parameters corresponding to the to-be-cut regular holes set by a user are obtained, and a plurality of cutting point positions corresponding to the to-be-cut regular holes are determined according to the geometric parameters; under the condition that the current cutting mode is determined to be wrist cutting according to the cutting parameters, the robot Cartesian position of the six-axis body when the sixth joint position serves as the zero-degree position is calculated through a kinematics positive solution; according to the Cartesian position of the robot, the point position Cartesian position of each cutting point position and the tool parameters of the cutting tool, the wrist joint position of the wrist mechanism under each cutting point position is calculated; and the wrist mechanism is driven to move according to the positions of all the wrist joints, so that the cutting tool is moved to all the cutting point positions for regular hole cutting, and therefore the machining efficiency can be improved while the regular hole cutting precision and the automation degree are improved.

This invention discloses a multi-loop hierarchical control method and system for hydraulic robotic arms based on hybrid modeling, belonging to the field of hydraulic robot control technology. The method includes: utilizing historical operating state data of the hydraulic robotic arm, aiming to minimize data loss, physical loss, and regularization constraints, and constructing a physical-data hybrid dynamics model through physical information neural network for system dynamics identification; using the physical-data hybrid dynamics model to track the trajectory of the hydraulic robotic arm's end effector, and combining forward kinematics to determine the desired joint angle, desired joint angular velocity, and desired joint angular acceleration, which are then input into an active disturbance rejection servo controller; and using a nonlinear feedback control law to perform servo control on the hydraulic robotic arm. This method can improve the operating efficiency and accuracy of the hydraulic robotic arm, solving the problem that the trajectory tracking accuracy of existing hydraulic robotic arms under complex working conditions needs improvement.

The invention relates to an autonomous capturing method and system for an earth orbit non-cooperative target. The method comprises the following steps: acquiring left and right images of the earth orbit non-cooperative target; inputting the left image and the right image into a DETR model for target detection, and outputting a semantic identifier of a target component; performing nonlinear mapping and binocular parallax calculation on the semantic identifier to obtain two-dimensional world plane coordinates and depth information, and fusing the semantic identifier, the two-dimensional world plane coordinates and the depth information to generate three-dimensional space positioning of the target component; the method comprises the following steps: converting a task instruction in a natural language form into a standardized control instruction based on a framework combining semantic analysis and a rule base; and mechanical arm forward kinematics is established on the basis of a D-H parameterized model, a standardized control instruction is converted into a target tail end pose through inverse kinematics solution, and high-precision capture of a non-cooperative target is achieved. Compared with the prior art, the method provided by the invention has the advantages of precision and real-time performance of spatial non-cooperative target autonomous capture and the like.

The invention relates to the technical field of robot control, in particular to a hybrid control method for high-precision parking of a four-wheel independent steering robot, which comprises the following steps of: constructing a robot system model, establishing an inverse kinematics model, a forward kinematics model and an actuator model, sensing global pose parameters of the robot by using the forward kinematics model, and in an advancing stage, controlling the robot to stop in a high-precision manner. A non-linear predictive control method is adopted, a PID control method is adopted in the stopping stage, the two control methods are comprehensively adopted in the transition stage, a robot body motion instruction is output, target control parameters of all wheels are worked out through an inverse kinematics model, execution parameters of all the wheels are worked out and executed through an actuator model, and the wheels are driven to move. The robot can be guided to efficiently and smoothly advance along the preset path in the advancing stage, high-precision stopping is rapidly completed in the stopping stage, and the control method is seamlessly and smoothly switched in the transition stage.

The application provides a three-dimensional displacement monitoring method and system based on GNSS and fusion of inclination sensors, and relates to the technical field of displacement monitoring.The application determines key monitoring points of a to-be-measured structure and arranges an inclination sensor chain through modal analysis, sets a GNSS-inclination integrated monitoring unit at an end point to establish a unified reference, obtains reference absolute displacement and high-frequency attitude angle data, and then takes the reference displacement as a starting point to perform forward kinematics recursion along the sensor chain to reconstruct the theoretical three-dimensional displacement of each point, and finally outputs the fused three-dimensional displacement as a deformation monitoring result as an indirect correction of the recursion result is performed based on the principle of minimum strain energy with the reference displacement as a fixed boundary constraint.The application realizes the complementary advantages of low-frequency precision and high-frequency response through a double-layer fusion architecture of front-end enhancement and rear-end reconstruction, that is, the long-term drift of the inclination sensor is constrained by the GNSS absolute reference, and the dynamic details of the GNSS are compensated by the high-frequency response of the inclination sensor.

The invention discloses a three-dimensional visualization method of a five-degree-of-freedom hybrid robot, and relates to the field of robot technology visualization, and the method comprises the following steps: obtaining real-time joint data collected by position sensors deployed at all active joints of the robot; performing forward kinematics calculation on the real-time joint data to obtain tail end pose data of the robot; inverse kinematics calculation is carried out on the tail end pose data, and theoretical pose data describing the spatial positions and postures of all parts of the robot are obtained; a three-dimensional surface model file of the robot is obtained and analyzed, and initial geometric data of all parts are extracted; according to the method, closed-loop kinematic chain constraint resolving of the hybrid mechanism is achieved through kinematics of the five-degree-of-freedom hybrid robot, and it is ensured that the poses of all the parts are accurately described.

This invention relates to a markerless real-time registration and tracking method and system for mandibular surgery. The method includes the following steps: the patient performs multiple opening and closing movements of the upper and lower jaws while the robotic arm is fixed, and the system synchronously records the changes in the angles of each joint of the robotic arm; based on the forward kinematics of the robotic arm, the continuous motion trajectory of the distal end of the jaw in space is calculated to form an actual jawbone trajectory point cloud; a preoperative image model is formed using the actual jawbone trajectory point cloud, a simulated jawbone trajectory is constructed in the preoperative image model, and the actual trajectory is aligned using the ICP registration algorithm to achieve automatic registration; the system establishes a mapping between angle changes and the spatial posture of the jawbone to achieve dynamic tracking and visual navigation during surgery. This invention solves the problems of large errors, high complexity, many limitations, and low efficiency in preoperative image data registration technology during maxillofacial surgery, avoids the need for preoperative implantation of markers, and achieves high-precision registration, high automation, and strong real-time performance under natural conditions.

The application provides a robot joint space angle acquisition method and a path planning method and device, wherein a plurality of sets of robot external shaft joint space angles are obtained according to prior joint movement ranges of the robot external shaft, then the plurality of sets of robot external shaft joint space angles are substituted into forward kinematics of the robot external shaft, a pose of a base of a robot mechanical arm in a world coordinate system corresponding to each set of joint space angles is obtained, then a plurality of sets of poses of a robot mechanical arm end in a robot base coordinate system are obtained according to prior poses of the robot mechanical arm end in the world coordinate system, the plurality of sets of poses of the robot mechanical arm end in the robot base coordinate system are substituted into inverse kinematics of the robot mechanical arm, and the plurality of sets of corresponding robot joint space angles are obtained in combination with corresponding robot mechanical arm joint space angles and robot external shaft joint space angles. The application solves the problems that the prior art cannot fully utilize the redundancy characteristics of a redundant robot, and the success rate of path planning is low.

The application discloses a rope-driven mechanical arm convolution dynamic jerk planning method and system, and a computer storage medium, which plans rope acceleration and speed of a rope-driven mechanical arm by using a twice continuous convolution method; an expected end displacement of a task space of the rope-driven mechanical arm is converted into joint angle change of a joint space by a robot inverse kinematics method; joint angle change of the joint space of the rope-driven mechanical arm is converted into rope displacement change and speed change of a rope space by a robot forward kinematics method; four displacement conditions, i.e., super-long displacement, long displacement, medium displacement and short displacement, are divided according to the size of the expected rope displacement; the displacement condition is selected according to the size of the expected rope displacement of the rope-driven mechanical arm; the size of the jerk is dynamically set; the expected rope acceleration and speed are planned by using the twice continuous convolution method; and the convolution planning motion process comprises accelerating motion, uniform decelerating motion, uniform speed motion, uniform variable acceleration accelerating motion and decelerating motion.

The invention relates to a loader working device control method and system based on a spinor theory, and belongs to the technical field of engineering machinery automation control. According to the method, a positive kinematics model based on the spinor theory is established, and the relation between the pose of the end effector and the joint angle is accurately described; and solving inverse kinematics according to the target pose to obtain a target joint angle, and driving a single-joint controller to realize accurate motion control. The system comprises a working device, an angle sensor, a single-joint controller and a processor. The method effectively solves the problems that a traditional method is complex in modeling, has singularity and is insufficient in precision, and has the advantages that modeling is efficient, control is accurate, stability is good, and an advanced control algorithm is easy to integrate.

A digital twin system construction method for a five-fingered dexterous hand of a humanoid robot comprises the steps that an onboard computing unit at a humanoid robot end synchronously collects posture data and pressure data of a mechanical arm and the five-fingered dexterous hand and RGB-D image data of a 3D camera, and a unified timestamp is added to all the data; the attitude data, the pressure data and the optimized RGB-D image data are packaged into data frames, and the data frames are sent to a control end through a network; the control end receives and analyzes the data frame, and drives the three-dimensional models of the humanoid robot and the five-fingered dexterous hand to move in real time through forward kinematics calculation by using posture data; pressure data are mapped into color changes of fingertips of the five-finger dexterous hand model, pressure visualization is achieved, RGB-D image data are converted into three-dimensional point cloud, and the three-dimensional point cloud is fused with the humanoid robot model. According to the method, attitude, pressure and high-fidelity three-dimensional visual information can be efficiently integrated, and low-delay, high-immersion and lightweight deployment is realized.

The application discloses a DH parameter automatic calibration method, device and equipment of a redundant mechanical arm and medium. The method comprises the following steps: acquiring a redundant mechanical arm and a calibration device of a robot to be calibrated, and controlling the end effector of the redundant mechanical arm to physically contact and rigidly lock with multiple different planes on the calibration device; under the condition that the position of the end effector of the redundant mechanical arm is unchanged, the motion of multiple different joint configurations is controlled at each locking position of the calibration device, and the joint angle data corresponding to various joint configurations is collected; the joint angle data collected at each locking position of the calibration device is used as an optimization target to minimize the dispersion degree between multiple end poses calculated by forward kinematics with the same set of DH parameters, and the DH parameters of the redundant mechanical arm are optimized; and the DH parameters of the redundant mechanical arm obtained after optimization are updated to the robot control system. The application improves the calibration accuracy of the DH parameters of the mechanical arm.

The invention provides a low-complexity human body motion reconstruction method based on a sparse inertial measurement unit, and belongs to the technical field of virtual reality and three-dimensional human body motion reconstruction, and the method comprises the following steps: obtaining a data set required for reconstruction training based on human body postures, carrying out time modeling through a time sequence encoder, updating joint features on a human body skeleton graph, and obtaining a reconstruction result; a skeleton is divided into a trunk and four limbs according to a human anatomical structure, global rotation of a root joint and local rotation of each joint are respectively predicted by a partition kinematics regression head, low-rank decomposition is introduced into a large-scale linear layer to compress model parameters, and forward kinematics is utilized to recover three-dimensional joint positions of the whole body. In the training process, a two-stage teacher-student distillation model framework is adopted, a teacher network is trained through real labels, and then joint rotation and joint positions output by a teacher are used as soft targets to jointly restrain a student network through rotary distillation and position distillation. While the parameter quantity is reduced, the reconstruction precision and the motion smoothness of the whole body are improved.

The invention discloses a robot tail end pose joint angle determination method, related equipment and a program product, a first model is introduced, and the first model represents a manifold where a reasonable feasible region of a robot joint angle is located; the reasonable feasible region is a sub-region formed by the joint angle of the robot in a non-singular state in the complete feasible region of the joint angle of the robot. Based on the target tail end pose and the first model, a target joint angle is solved through an optimization algorithm, an optimization target comprises a first sub-target and a second sub-target, the first sub-target is used for minimizing the deviation between the tail end pose obtained through forward kinematics calculation of the candidate joint angle and the target tail end pose, meanwhile, the joint angle physical constraint condition is met, and the joint angle is obtained; the second sub-target is used for enabling the candidate joint angle to approach the manifold represented by the first model. The determined target joint angle is in the reasonable feasible region of the joint angle, so that the probability that the robot is in a singular state is reduced, and the stability and safety of robot operation are improved.

This invention discloses a motion control method for a rigid-flexible coupled space robot, belonging to the field of aerospace robot control technology. The method includes: setting critical path points and generating a smooth end-effector trajectory using cubic spline interpolation; establishing a forward kinematics model including a rigid multi-link and a flexible piecewise constant curvature; solving the inverse kinematics point-by-point along the trajectory time sequence using the Levenberg-Marquardt algorithm to obtain a joint command sequence; and sending the commands to the rigid arm joint space PD control subsystem and the flexible arm IMU-based world coordinate system pose closed-loop control subsystem, respectively. This invention enables high-precision trajectory tracking of rigid-flexible coupled space robots in confined environments, providing a reliable motion control solution for on-orbit assembly and servicing missions.

This invention discloses a hand-eye calibration method and system for a first-link follower camera in confined spaces. The camera is rigidly mounted on the first link of a robotic arm, rotating with the first joint, while a calibration plate is fixed to the end effector. During the calibration phase, the first joint is locked, and images and joint angles under multiple poses are acquired. A closed-loop constraint equation is constructed using visual pose estimation and forward kinematics to solve for the constant extrinsic parameters X of the camera relative to the first link and Y of the calibration plate relative to the end effector. During the operation phase, the first joint is unlocked, and the camera base pose is calculated online using the real-time first link pose and the constant X, eliminating system errors caused by the follower. Simultaneously, closed-loop consistency verification is introduced to achieve abnormal sample removal and robust iterative solution. This invention effectively solves problems such as end-effector camera occlusion and entanglement, limited field of view of external cameras, and mismatched follower mounting models, and is suitable for robot vision-guided operations in confined environments such as cavities and boxes.

The invention provides an inverse solution method and device for a multi-degree-of-freedom mechanical arm. The method comprises the steps that a forward kinematics expression of the mechanical arm is converted into a first expression; randomly sampling the fourth joint angle to determine a current fourth joint angle, and solving the first expression by using the current fourth joint angle to determine a third joint angle; the forward kinematics expression of the mechanical arm is converted into a second expression used for representing the problem of rotation around the ordered double shafts, the second expression is solved, and a first joint angle and a second joint angle are determined; determining a fifth candidate position according to the first joint angle, the second joint angle, the third joint angle and the current fourth joint angle; and when the fifth candidate position does not meet the error allowance condition, sampling the fourth joint angle serving as the variable again, and returning to execute the step of determining the third joint angle. By adopting the inverse solution method and device of the multi-degree-of-freedom mechanical arm, the solution efficiency and the numerical stability of the inverse solution process of the mechanical arm are improved.

The invention discloses an industrial robot multi-machine cooperative intelligent manufacturing management and control system and method, and the method comprises the steps: collecting the bottom physical state data of a plurality of robots in real time through a sensing monitoring accessory set based on a global nanosecond clock network; constructing a rigid-flexible coupling interference matrix to perform forward kinematics solution, and separating a total displacement error into a dynamic elastic deformation error and an external disturbance contact force to realize joint-level decoupling; calculating a global coupling compensation amount containing a feed-forward current pulse compensation sequence based on the dynamic elastic deformation error; kinetic energy differential is calculated in combination with the speed and the load to generate a dynamic anti-collision safety threshold, and predictive feed-forward compliance compensation is triggered and a current pulse is issued when the dynamic threshold is approached. According to the invention, inertia sudden stop caused by mistake under heavy-load and high-speed working conditions can be shielded, and self-adaptive flexible concession is realized before collision, so that the safety anti-collision capability and the operation precision of multi-machine cooperation are obviously improved.