46 results about "Time trajectory" patented technology

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 provides a multi-sensor fusion robot grabbing path planning method and device, and relates to the field of automation. The method comprises the following steps: constructing a first time correction relation based on observation parameters of a multi-source sensor; correcting the relation based on the first time; inputting the hardware timestamp synchronized to the master clock source into the extended state estimation model; iteratively updating the observation parameters of the multi-source sensor based on the extended state estimation model, and constructing a second time correction relation according to the updated observation parameters of the multi-source sensor; constructing a pose continuous time trajectory function corresponding to the target robot based on the second time correction relation; the continuous time trajectory function and the multi-source sensor observation parameters serve as input, and a grabbing path corresponding to the target robot is output through a time sequence consistency constrained joint optimization model; and controlling the target robot to execute grabbing operation based on the grabbing path. The problem that in the prior art, the precision of a robot grabbing path is low is solved.

The invention discloses a robot motion path real-time deviation rectifying method based on digital twinning, which comprises the following steps that an off-line programming system generates an initial welding track according to a welding requirement, converts the initial welding track into a code file, transmits the code file to a digital twinning system, and generates a preset track Q; the virtual model layer synchronously maps a motion path of a welding robot entity to obtain a real-time mapping track P; track points of the two tracks are matched, and wrong matching is eliminated; a robot track model is constructed, a predicted track T of entity motion of the welding robot is obtained, and track point matching is conducted on the predicted track T and a preset track Q; and the deviation value of the matched track points of the two tracks is calculated, the robot electric control system corrects the welding track of the welding robot entity according to the deviation value, and the welding track is corrected in real time. According to the correction method, track points are matched only by means of a digital twin system for real-time correction; the adopted track point matching algorithm is small in error and high in matching precision.

The invention discloses an industrial safety detection method combining time alignment and motion consistency, and belongs to the technical field of industrial safety monitoring. According to the method, through seven steps of multi-camera data acquisition and preprocessing, target feature extraction, coordinate projection, instantaneous speed estimation, multi-dimensional similarity fusion, soft matching optimization and model training and target trajectory generation, the problem of space-time inconsistency during multi-camera cooperative detection in an industrial scene is solved. A camera clock offset parameter is innovatively introduced to correct a cross-camera time difference, appearance, geometry and time prior multi-dimensional similarity are fused, a multi-loss function optimization model is constructed, and cross-camera target accurate matching and long-time trajectory tracking are realized. High-precision technical support is provided for personnel safety monitoring and equipment abnormal behavior detection in an industrial scene, and the industrial production safety protection capability is improved.

The invention provides a Markov jump-based mechanical arm preset time trajectory tracking control method, which comprises the following steps of: calculating a trajectory tracking error by establishing a two-degree-of-freedom mechanical arm dynamic model with a Markov jump characteristic; a trajectory tracking error is subjected to nonlinear transformation, a nonsingular terminal sliding mode surface is constructed in combination with a preset convergence time upper limit function, and then a control torque is synthesized through an equivalent control item and a robust switching item containing a sliding mode surface sign function and a switching gain to drive a mechanical arm. And the trajectory tracking error is difficult to converge in the preset time.

The invention discloses an intelligent robot trajectory planning method and system based on visual inspection. The method comprises the following steps: acquiring obstacle motion state data through a sensor array, performing time alignment and multi-modal fusion, and constructing an initial state vector; iteratively updating the state by adopting a particle filter algorithm, and generating a smooth trajectory sequence through continuity correction and time sequence integration; determining a potential collision area based on polynomial fitting, and performing extension to obtain a predicted collision boundary; extracting passable grids to construct a dynamic risk map, screening low-risk routes, and sequencing to determine an optimized path; performing correction according to deviation feedback by simulating a forward verification path to generate a final execution instruction; state deviation is continuously monitored in the execution process, and the control scheme is dynamically adjusted. According to the invention, real-time trajectory planning and intelligent path optimization of the robot in a dynamic obstacle environment are realized, and the movement safety of the robot is remarkably improved.

This application relates to a predetermined-time tracking control method for a free-floating space manipulator system, and pertains to the field of trajectory tracking control technology for manipulator systems. The aim is to address the poor stability and low robustness of free-floating space manipulator systems when facing model uncertainties and external disturbances. This application establishes a dynamic model of the space manipulator in free-floating mode; designs a nonlinear disturbance observer based on predetermined-time convergence; constructs piecewise continuous sliding mode variables based on the dynamic model; constructs a non-singular predetermined-time sliding mode controller based on the dynamic model, the nonlinear disturbance observer, and the piecewise continuous sliding mode variables; and utilizes the non-singular predetermined-time sliding mode controller to perform predetermined-time trajectory tracking control on the free-floating space manipulator system.

A kind of double-runner dehumidification energy-saving optimization control method for multivariate collaborative regulation, comprising: obtaining the state observation data and equipment limit value of each measuring point, generating material regeneration demand estimation curve and desorption boundary threshold set.According to material regeneration demand estimation curve and desorption boundary threshold set, calculate the regeneration heat trajectory and residence time trajectory required for desorption, generate a set of safe operation constraints.Based on regeneration heat trajectory, residence time trajectory and a set of safe operation constraints, combined with the decision quantity corresponding to the set optimization target, determine the control setting sequence and reference path at the current time.The control setting sequence is issued to the execution unit, and the execution unit is scheduled according to the reference path, and the actual execution record and execution deviation data are monitored and output in real time.Based on actual execution record and execution deviation data, update the estimated value of material adsorption capacity and desorption temperature, and correct the regeneration heat trajectory and residence time trajectory in adjacent rolling time window.

The invention discloses an intelligent ocean vessel scheduling method and system based on AIS space-time trajectory data, and the method comprises the steps: obtaining the AIS space-time trajectory data of a plurality of vessels in a target sea area, constructing a space-time correlation structure of the plurality of vessels in the dimensions of course, speed and arrival time, and constructing a vessel group cooperative behavior mode based on the space-time correlation structure; identifying a space-time area where the ship tends to decelerate, stay or converge intensively in a preset time window, and dynamically generating a virtual anchor ground area according to the stability and continuity of group behaviors in the space-time area; taking the virtual anchor ground area as an implicit navigation constraint condition, forming a joint constraint in combination with a ship group collaborative behavior mode, and performing potential navigation path prediction on a ship with an AIS signal missing or abnormal state; and adjusting the scheduling of the ocean vessels based on the predicted trajectory to obtain a scheduling decision scheme. According to the invention, the congestion risk and waiting time are reduced, and the marine traffic efficiency and the scheduling intelligence level are improved.

The application relates to the field of space-time trajectory calculation, in particular to a space-time trajectory completion method and device based on big data, equipment and medium, wherein the method comprises the following steps: acquiring trajectory data of a specified target, wherein the trajectory data comprises position information and time information; generating a to-be-completed trajectory coordinate graph based on the position information; if there is a blank trajectory in the to-be-completed trajectory coordinate graph, calculating the similarity between the to-be-completed trajectory and an approximate trajectory in a historical trajectory based on a disconnected point of the blank trajectory; completing the blank trajectory according to the approximate trajectory with a similarity within a specified threshold; and performing matching degree calculation based on the completed trajectory, and retaining the completed trajectory with the highest matching degree. The method disclosed by the application can draw a reasonable complete trajectory under the condition that the position information is lost, and has low calculation complexity and high calculation performance.

The embodiment of the invention relates to the technical field of body intelligence, and provides a space-time trajectory splicing method and device of a robot, electronic equipment and a medium, and the method comprises the steps: obtaining current observation data and current absolute time when a target robot executes a current action sequence; determining a residual expected action sequence based on a time node corresponding to the current absolute time in the current action sequence; estimating a planning state starting point on the expected action sequence based on the current observation data, the current absolute time and the estimation model reasoning time; inputting the current observation data and the planning state starting point into a vision-language-action model, and outputting a target action sequence through the vision-language-action model; and the target action sequence is spliced to the expected action sequence according to the time sequence, and a space-time trajectory splicing result of the target robot is generated. Therefore, asynchronous, continuous and smooth real-time action output under large model reasoning delay is realized, and pause, jitter and impact are eliminated.

The invention provides an adaptive predetermined time trajectory tracking control method for a rigid-flexible coupling tendon-driven mechanical arm. The adaptive predetermined time trajectory tracking control method comprises the following steps: establishing a dynamic model of the rigid-flexible coupling tendon-driven mechanical arm which comprehensively considers the flexible deformation of an arm lever structure and the elastic deformation of a rope; designing a nonsingular terminal sliding mode surface according to the trajectory tracking error, and estimating system lumped interference by adopting an RBF neural network; and designing a self-adaptive predetermined time nonsingular terminal sliding mode controller, adjusting parameters through a self-adaptive law to suppress and control input buffeting, and controlling a joint trajectory tracking error to converge within a predetermined time range. The vibration of the tail end of the mechanical arm is restrained, and meanwhile it is ensured that the joint trajectory tracking error converges within the preset time range; the influence of initial conditions is avoided; according to the method, system uncertainty and external disturbance are estimated through the RBF neural network, and control robustness is improved; a self-adaptive parameter adjusting mechanism is introduced, the control input buffeting problem is effectively solved, and the tail end operation precision of the mechanical arm is improved.

The embodiment of the invention relates to the technical field of transmission, in particular to a mover control method of a transmission line, which comprises the following steps: controlling a target mover in the transmission line to move according to a preset position and time trajectory diagram to obtain an actual position and time trajectory diagram; according to the actual position and time trajectory diagram and the preset position and time trajectory diagram, performing position ring adjustment processing on the target mover to obtain a target position and time trajectory diagram; controlling the target rotor to move according to the target position and the time trajectory diagram to obtain an actual speed and time trajectory diagram; according to the actual speed and time trajectory diagram and a preset speed and time trajectory diagram corresponding to the target rotor, performing speed ring adjustment processing on the target rotor to obtain a target speed and time trajectory diagram; and obtaining a first control parameter according to the target speed and the time trajectory diagram. According to the invention, through layered adjustment of the position ring and the speed ring, double optimization of the motion accuracy and smoothness of the rotor is realized, and finally, the control stability of the rotor under load change is improved.

The application provides a screening method and device for associated target archives, comprising: obtaining a space-time trajectory corresponding to a reference archive and a space-time trajectory corresponding to a to-be-associated archive, the reference archive being an archive of a known target; calculating a first similarity value of the space-time trajectory corresponding to the to-be-associated archive and the space-time trajectory corresponding to the reference archive; determining a same-trip probability according to the number of same position collection points in the space-time trajectory corresponding to the reference archive and the space-time trajectory corresponding to the to-be-associated archive, the number of position collection points included in the space-time trajectory corresponding to the reference archive, and the number of position collection points included in the space-time trajectory corresponding to the to-be-associated archive; determining an association parameter according to the first similarity value and the same-trip probability; and when the association parameter is greater than or equal to a first preset threshold, classifying the to-be-associated archive into an associated target archive library corresponding to the known target. Through the method, the problems that the current method is only applicable to judging same-trip targets, has a small range of action, and has low archive screening efficiency are solved.

A double-rotating-wheel dehumidification energy-saving optimization control method oriented to multivariable cooperative regulation comprises the steps that state observation data and equipment limiting values of all measuring points are obtained, and a material regeneration demand estimation curve and a desorption boundary threshold set are generated; and according to the material regeneration demand estimation curve and the desorption boundary threshold set, calculating a regeneration heat trajectory and a residence time trajectory required by desorption, and generating a safe operation constraint set. And based on the regenerative heat trajectory, the residence time trajectory and the safe operation constraint set, determining a control setting sequence and a reference path at the current moment in combination with a decision amount corresponding to a set optimization target. And issuing the control setting sequence to an execution unit, controlling the execution unit to perform feedforward scheduling according to the reference path, and monitoring and outputting actual execution records and execution deviation data in real time. And based on the actual execution record and the execution deviation data, updating the estimated values of the adsorption capacity and the desorption temperature of the material, and correcting the regeneration heat track and the retention time track in the adjacent rolling time window.

The application provides a multi-sensor fusion robot grasping path planning method and device, and relates to the field of automation. The method comprises the following steps: constructing a first time correction relationship based on multi-source sensor observation parameters; inputting hardware timestamps synchronized to a master clock source into an extended state estimation model based on the first time correction relationship; iteratively updating the multi-source sensor observation parameters based on the extended state estimation model, and constructing a second time correction relationship according to the updated multi-source sensor observation parameters; constructing a pose continuous time trajectory function corresponding to a target robot based on the second time correction relationship; taking the continuous time trajectory function and the multi-source sensor observation parameters as inputs, and outputting a grasping path corresponding to the target robot through a joint optimization model with a time sequence consistency constraint; and controlling the target robot to perform a grasping operation based on the grasping path. The application solves the problem of low precision of the robot grasping path in the prior art.

The application discloses an AUV preset time trajectory tracking control method considering performance constraints and interference influence, and relates to the technical field of trajectory tracking control.The application is to solve the problem that the existing AUV trajectory tracking control method is difficult to accurately complete trajectory tracking within the expected time.The application comprises the following steps: establishing an AUV kinematics model by using the six-degree-of-freedom position and posture of the AUV in an inertial coordinate system; combining the AUV kinematics model to establish an AUV dynamics model; establishing a performance function; converting the trajectory tracking error by using the performance function and the AUV dynamics model to obtain a trajectory tracking error vector; designing an adaptive lumped interference estimator by using the trajectory tracking error vector; and designing an adaptive posture tracking controller by using the trajectory tracking error vector and the adaptive lumped interference estimator.The application is used for AUV trajectory tracking control.

The application discloses an unmanned ship scheduled time trajectory tracking method based on asymmetric preset performance, which comprises the following steps: S1, a kinematics model and a dynamics model of a three-degree-of-freedom unmanned ship are established based on an Euler-Lagrange method, and the kinematics model and the dynamics model are expressed as a state equation of the unmanned ship system; S2, a system structure with scheduled time convergence characteristics is constructed, and stable convergence of the state of the unmanned ship system within scheduled time is realized; and S3, an asymmetric preset performance function is designed, trajectory tracking errors of the unmanned ship system are constrained, a dynamic evolution process of the errors is limited, and the errors are guaranteed to meet preset performance indexes. The application has the beneficial effects that a novel asymmetric preset performance function is constructed, the dynamic evolution process of system errors can be effectively constrained, the state errors of the system are always kept within preset performance boundaries, and therefore, the stability and control precision of the trajectory tracking process of the unmanned ship are improved.

The application discloses a kind of ocean-going ship intelligent scheduling method and system based on AIS space-time trajectory data, method includes: obtaining the AIS space-time trajectory data of multiple ships in target sea area, constructs the space-time association structure of multiple ships in the dimension of heading, speed and arrival time, constructs ship group cooperative behavior mode based on space-time association structure;Identify the space-time region that ship presents convergence deceleration, stay or dense convergence in predetermined time window, and dynamically generate virtual anchor area according to the stability and persistence of group behavior in space-time region;Virtual anchor area is used as implicit navigation constraint condition, and combined with ship group cooperative behavior mode to form joint constraint, potential navigation path prediction is carried out to ship with AIS signal missing or abnormal;Based on predicted trajectory, the scheduling of ocean-going ship is adjusted, and scheduling decision scheme is obtained.The application reduces the congestion risk and waiting time, improves the efficiency of maritime traffic and the intelligent level of scheduling.

The invention discloses an agricultural robot intelligent scheduling method based on big data and space-time coupling, and the method comprises the following steps: collecting agricultural data and agricultural robot data, and generating an agricultural state data set; generating an agricultural operation irreversible constraint set; mapping the agricultural operation irreversible constraint set into an irreversible barrier map, and generating a barrier map constraint representation; generating a candidate scheduling scheme set; mapping each candidate scheduling scheme into a scheme spatio-temporal trajectory, and generating a barrier avoidance verification result; when at least one barrier node is triggered, a shortest counter-example trajectory is generated, a minimum contradiction substructure is extracted, a non-executable certificate is generated and bound, and when any barrier node is not triggered, an executable certificate is generated and bound, and an intelligent scheduling result of the agricultural robot is formed. According to the method, by constructing the irreversible barrier map and verifying the spatial-temporal trajectory of the scheduling scheme, pre-judgment screening of the agricultural robot scheduling scheme is achieved, and the method has the advantages of being high in execution reliability and low in rework risk.

A method, apparatus, non-transitory computer readable medium, and system for performing an accelerated denoising process includes obtaining a noise map from a noise distribution. Embodiments then compute, using an image generation model, a denoising vector based on an accelerated denoising trajectory, where the accelerated denoising trajectory accelerates a denoising rate based on a diffusion timestep. Then, embodiments generate, using the image generation model, a synthetic image by denoising the noise map based on the denoising vector.

The invention discloses an unmanned aerial vehicle formation real-time trajectory planning method based on a time coordination strategy. The method comprises the following steps that information interaction is established between different unmanned aerial vehicles; for any unmanned aerial vehicle, according to the obtained interaction information, planning state information of the tail end of the first prediction time domain; for any other unmanned aerial vehicle, the prediction time domain is progressively increased, the unmanned aerial vehicle plans the state information of the unmanned aerial vehicle at the end moment of the prediction time domain according to the state information obtained through interaction until the state information meets a preset threshold value, and a second prediction time domain is obtained; obtaining a second prediction time domain of all unmanned aerial vehicles, and obtaining an average residual number of iterations; and any unmanned aerial vehicle acquires state information of other unmanned aerial vehicles at each moment, and plans state information and control information at different moments in an average prediction time domain, so that the aircraft is controlled by the acquired control information to complete time cooperative flight. The method disclosed by the invention can ensure that the multi-unmanned aerial vehicle system can simultaneously arrive at the specified target position to complete the synchronous implementation of task execution.

The invention relates to the technical field of process engine control, and discloses a training planning process control method and system based on an Activity process engine. The method comprises the following steps: extracting an instance state snapshot from a process engine, analyzing to construct a time trajectory map of process evolution, marking a key path and a branch point, and generating a process evolution mode template library; and the current evolution stage is accurately determined by matching the real-time process with the template. And then dynamically loading a corresponding control strategy, analyzing the rule to generate a node-level operation instruction, and converting the node-level operation instruction into a model adjustment command which can be identified by an engine. Synchronously monitoring the synchronization state of the resource consumption and the flow track, and automatically calculating a resource quota adjustment scheme when deviation occurs. And finally, cooperatively scheduling a model adjustment command and a resource scheme, forming a control instruction set, and distributing the control instruction set to an engine and a resource manager to realize efficient and adaptive evolution of a flow according to an expected path. According to the invention, the intelligent level of process management and the resource utilization efficiency are improved.

The invention relates to a flight trajectory prediction method and device, and the method comprises the steps: constructing a prototype trajectory library based on a collected trajectory curve set; receiving an input real-time flight path; calculating a plurality of similarities between the plurality of prototype trajectories and the real-time flight trajectory; in the plurality of similarities, determining the prototype trajectory corresponding to the preset number of highest similarities as a predicted trajectory; respectively calling Gaussian models corresponding to the preset number of prediction trajectories to predict the real-time flight trajectory to obtain a preset number of prediction results; determining prediction weights corresponding to the preset number of prediction trajectories; and performing weighted calculation on the preset number of prediction results according to the preset number of prediction weights, and determining a final prediction result of the real-time flight trajectory. According to the scheme, the real-time trajectory is predicted according to the prototype trajectory in the prototype trajectory library, the future trend of the current real-time trajectory can be accurately predicted, the prediction result can be quickly determined, and the real-time requirement is met.

The invention relates to the technical field of exercise training, in particular to a real-time trajectory deviation correction method of a virtual-real fusion training system, which comprises the following steps: predicting a behavior trajectory of an operator in a future first time period through a first prediction model, and predicting an intention trajectory of the operator in the future first time period based on a physiological signal, and finally fusing the behavior track and the intention track. Calculating a proficiency score according to historical performance data of the operator, and dynamically adjusting parameters of a correction algorithm based on the proficiency score; compared with the prior art which mainly depends on single motion sensor data to carry out hysteresis trajectory tracking and has the defects of large response delay and late intervention opportunity, the neural intention decoding based on the electromyographic signals and the behavior trajectory prediction based on the motion sensor are fused; advanced perception and prediction of the motion intention of the operator are realized, so that the system can carry out early intervention before deviation occurs, and the real-time performance and foresight of correction are remarkably improved.

The present application belongs to the technical field of trajectory tracking, and particularly relates to a robot online strict on-time trajectory tracking method based on arc length driving, steps of which comprise: collecting environment input information; calculating arc length increment of adjacent discrete points and arc length node sequence; in each sampling control period, adopting fixed time sliding mode control to correct expected linear velocity, controlling robot to move with the corrected expected linear velocity; obtaining linear velocity amplitude and expected heading angle; designing angular velocity control law to realize heading adjustment; estimating instantaneous curvature, applying discrete first-order change rate constraint to the limited expected linear velocity and uniformized angular velocity to obtain smooth instruction to control robot to move; when the remaining arc length is less than the arc length threshold, adopting linear interpolation to gradually lower the linear velocity to the lower limit of linear velocity, and repeatedly executing the control flow in each sampling control period until the robot reaches the target position. The present application can consider on-time arrival and path geometry invariance, and has small calculation cost.

The application discloses a time domain segmentation method and early warning system for recognizing goose pecking feather behavior, and particularly relates to the technical field of behavior recognition, and is used for solving the problem that the existing time domain segmentation technology causes behavior breakage and cannot restore complete events due to occlusion; the goose group motion trajectory is generated through target tracking; the broken point generated by occlusion is recognized and cut to obtain a non-continuous sub-fragment; the feather vibration damping characteristic and neck muscle group synchronism in the sub-fragment are extracted to form a motion feature vector; the vibration damping characteristic change quantity between adjacent sub-fragments is calculated; the motion feature similarity, the space-time trajectory continuity and the vibration damping change quantity are fused to determine the associated sub-fragments; the associated sub-fragments are combined to form a complete behavior time period, and the early warning is triggered according to the accumulated length exceeding a threshold value, so that the continuous restoration and accurate early warning of the pecking feather behavior in the occlusion scene are realized.

The invention discloses a multi-modal spatial-temporal trajectory fusion method, device and equipment, a medium and a program product. The method comprises the following steps: acquiring multi-modal spatio-temporal trajectory data to be processed; based on a preset time threshold value and a preset space threshold value, determining a co-occurrence relation pair which is adjacent in time and space between the to-be-processed space-time trajectory data of each mode; edges are established according to the co-occurrence relation pairs so as to construct a heterogeneous connection graph between the modal nodes, and attributes carried by each edge comprise space-time co-occurrence features and association strength features of the corresponding co-occurrence relation pairs; inputting the heterogeneous connection graph into the trained graph convolutional neural network to generate a target embedded vector; and performing clustering fusion on the target embedded vector according to a preset similarity threshold value to obtain a trajectory fusion result. The spatial-temporal trajectory is mapped into the spatial-temporal topological graph, so that the graph convolutional neural network can be successfully applied to the field of trajectory fusion, efficient and accurate trajectory fusion is realized, and meanwhile, the method can be well adapted to multi-modal data and sparse data.