141 results about "Optimal trajectory" patented technology

The invention discloses a directional drilling track accurate control technology based on machine learning, and relates to the technical field of drilling engineering. The directional drilling track accurate control technology comprises the following steps that underground parameters of a drilling tool during underground operation are obtained; establishing a dynamic model based on the drilling tool structure and the motion state; based on the dynamic model, introducing a long-short-term memory neural network, and constructing a hybrid prediction model; drilling parameters are input into the hybrid prediction model, and trend information of multiple tracks is output; based on current geological conditions, drilling tool configuration and operation safety constraints, performing simulation evaluation on the trend information of the plurality of candidate tracks, and screening out an optimal track meeting track precision and underground safety requirements from the candidate tracks; based on the optimal track, control strategy input is constructed, and a state space containing a tool face angle, target azimuth deviation and a drilling tool state is set; and through a deep reinforcement learning method, an advanced adjustment instruction for the guiding tool is generated, and drilling operation is executed according to the optimal track and the advanced adjustment instruction.

Techniques are discussed herein for determining optimal driving trajectories for autonomous vehicles in complex multi-agent driving environments. A baseline trajectory may be perturbed and parameterized into a vector of vehicle states associated with different segments (or portions) of the trajectory. Such a vector may be modified to ensure the resultant perturbed trajectory is kino-dynamically feasible. The vectorized perturbed trajectory may be input, including a representation of the current driving environment and additional agents, into a prediction model trained to output a predicted future driving scene. The predicted future driving scene, including predicted future states for the vehicle and predicted trajectories for the additional agents in the environment, may be evaluated to determine costs associated with each perturbed trajectory. Based on the determined costs, the optimization algorithm may determine subsequent perturbations and / or the optimal trajectory for controlling the vehicle in the driving environment.

The invention belongs to the field of track planning and intelligent control of a reusable vehicle, and relates to an intelligent track planning method for a cruise section of the reusable vehicle. The method comprises the following steps: constructing a three-degree-of-freedom centroid motion dynamics model of a cruise section vehicle, generating an offline optimal trajectory sample library covering wide working conditions based on a Gaussian pseudo-spectral method, designing a mapping relation between deep neural network learning task parameters and trajectory features, and outputting a high-quality trajectory planning initial value online. The distribution of collocation points is dynamically adjusted in combination with a self-adaptive collocation point method, a nonlinear programming problem is iteratively solved with a high-quality initial value as a starting point, and efficient and accurate optimization of the trajectory is achieved. Simulation results show that the method significantly reduces the sensitivity of online optimization to initial guess, still has fast response ability and high robustness under complex constraint and uncertainty working conditions, effectively improves the autonomous trajectory planning ability of the cruise section of the reusable vehicle, and ensures flight reliability and control precision.

The invention relates to a mechanical arm control method and device, computer equipment and a readable storage medium. The method comprises the steps of generating a plurality of candidate trajectories for a target task through a target diffusion strategy model; the target diffusion strategy model is obtained by training an original diffusion strategy model based on collected example data; evaluating and screening the plurality of candidate trajectories according to a single-step value discriminator to obtain an optimal trajectory in the plurality of candidate trajectories; the single-step value discriminator is a multi-modal feature regression model constructed based on a target diffusion strategy model; and the target mechanical arm is controlled to execute the target task according to the optimal track. By the adoption of the control method and device, the control accuracy and safety of the mechanical arm can be improved.

The invention belongs to the technical field of intelligent transportation, and particularly relates to a large transport track planning method considering internal and external comprehensive safety. Comprising the following steps: acquiring road information, and constructing a three-dimensional safety corridor; obtaining a dynamic model of the large transportation system with cargo connection characteristics; setting road trafficability safety boundary conditions, namely external constraint conditions; planning a driving track of the large transportation system, and optimizing a driving track set by adopting a multi-objective optimization algorithm; and an evaluation index is selected to design a trafficability efficiency comprehensive evaluation system of the large transport system, the comprehensive trafficability efficiency of each node on different transport routes is evaluated, and an optimal track is selected. According to the invention, the problems of passing safety and passing efficiency of trajectory planning of a large-piece transportation system in a complex environment are solved.

The invention discloses a moon leap trajectory planning method, system and device and a medium. The method comprises the steps of obtaining target landing point data; based on the acquired data, establishing a moon surface leap device kinetic model by defining a specific coordinate system and a state variable; based on the kinetic model, discretizing the kinetic equation through a numerical integration algorithm, constructing and solving a leap trajectory convex optimization problem with optimal burnup, and obtaining an obstacle avoidance-free optimal trajectory; based on the obstacle avoidance-free optimal trajectory, performing obstacle avoidance iteration through an iteration obstacle increase strategy to obtain a static obstacle avoidance trajectory; and on the basis of the static obstacle avoidance trajectory, the flight trajectory is adjusted again by calculating the trajectory error band width and the maximum extension distance, and a dynamic safety enhanced trajectory is obtained. According to the method, safe, robust and efficient moon surface leap trajectory planning in a complex and uncertain environment is realized.

The invention relates to the technical field of trajectory planning, and provides a rapid evaluation and search method and system for an optimal trajectory and terminal equipment, and the method comprises the steps: sampling a plurality of state points in a pre-planning space, and carrying out the pre-collision detection of the state points to remove points conflicting with an obstacle, and obtaining effective sampling points; performing cost evaluation on the effective sampling points, wherein the cost evaluation comprises heuristic cost based on historical planning trajectory information and static cost based on motion features; and iteratively searching from the initial state point based on the result of the cost evaluation: calculating the trajectory cost of the neighborhood state point and updating the search path along the gradient direction until the optimal feasible trajectory is output. According to the method, invalid sampling points are screened out through pre-collision detection, a gradient iteration search mechanism is adopted, and the track search efficiency is improved.

The invention discloses an intersection dynamic path planning method and system based on vehicle-road cooperation, and the method comprises the steps: obtaining vehicle trajectory data, carrying out the preprocessing of the vehicle trajectory data, carrying out the trajectory prediction based on the preprocessed trajectory data, carrying out the global path planning based on the predicted trajectory, and carrying out the conflict analysis and S-T diagram construction based on the determined global path planning. And then carrying out local trajectory planning, trajectory evaluation and optimal trajectory selection. According to the scheme, trajectory smoothing and lane matching are integrated to improve the accuracy of trajectory prediction, trajectory level analysis is carried out on potential conflicts between vehicles to enhance the refinement and pertinence of conflict detection, and in the global path planning stage, the path planning efficiency is improved. By improving a heuristic function of a Hybrid A * algorithm, a generated path is smoother and has fewer nodes while meeting vehicle kinematics constraints; in the local trajectory planning stage, a Lattice trajectory sampling method is fused, it is ensured that a fine-grained feasible trajectory can still be generated in a complex dynamic environment, and high calculation efficiency is maintained.

The invention discloses a double-AGV (Automatic Guided Vehicle) linkage omnidirectional dynamic path planning method based on a dynamic window method, and the method designs a real-time dynamic path planning scheme based on an omnidirectional differential composite motion model by utilizing the omnidirectional movement characteristic of Mecanum wheels. The method comprises the following steps: firstly, introducing a Y-direction linear velocity in a velocity sampling stage, and constructing an omnidirectional motion model to improve the omnidirectional motion capability; and meanwhile, by combining angular velocity sampling, dynamic adjustment of the attitude of the AGV is realized, an omnidirectional differential composite motion model is constructed, and the omnidirectional motion flexibility is enhanced. And secondly, fusing an artificial potential field method, designing an omnidirectional motion evaluation sub-function, carrying out multi-dimensional comprehensive evaluation on candidate trajectories, screening out an optimal trajectory facing a target point, and effectively improving the efficiency and safety of path planning. And finally, in combination with the contour parameters of the double-AGV linkage system, ensuring that the pilot AGV and the following AGV can be prevented from colliding with obstacles in the environment in the navigation process. According to the method, the transportation efficiency and the system stability are remarkably improved.

The invention discloses a self-adaptive laser head trajectory planning method for a complex workpiece, which relates to the technical field of intelligent manufacturing, and comprises the following steps: establishing a multi-constraint symbol distance field according to a workpiece point cloud model in combination with nozzle appearance geometric parameters, A / C axis motion range constraint and clamp forbidden area information, and calculating a reachable probability value of each voxel; forming a dynamic voxel reachable field reflecting the space feasibility of the workpiece; based on a dynamic voxel reachable field, generating a plurality of candidate trajectories in the reachable area, performing swept volume obstacle avoidance simulation, calculating a clearance distance evaluation value of each candidate trajectory, and selecting an optimal trajectory with the lowest cost in combination with the clearance distance and trajectory curvature features to generate an initial path. According to the method, the spatial quantitative evaluation of the machining feasibility of the complex workpiece is realized, and an accurate reachability map is provided for track planning.

The invention particularly relates to a special vehicle trajectory planning method considering perceptual uncertainty, and the method comprises the steps: obtaining the position information and uncertainty of an obstacle in an environment based on environment three-dimensional point cloud data, calculating the position uncertainty based on a preset motion model, obtaining a position uncertainty reference trajectory of the obstacle, and obtaining the position uncertainty reference trajectory of the obstacle; determining a collision probability based on the collision probability, and constructing a risk assessment model based on the collision probability according to a preset progressive decrease type dynamic confidence distribution strategy and a preset collision risk assessment condition; and sampling the at least one determined target state point by using a preset coordinate system to obtain a candidate trajectory set, constructing a chance constraint based on the collision probability, screening the candidate trajectory set based on a deterministic boundary constraint obtained by the chance constraint to obtain a plurality of trajectories, and selecting an optimal trajectory from the plurality of trajectories based on the risk assessment model. Therefore, the problems of sensing uncertainty and the like of the special vehicle caused by the environment are solved.

The invention discloses a multi-unmanned-ship multi-trajectory planning method and system based on a synchronization time consensus mechanism, and solves the problems of low precision and poor trajectory adaptability of multi-unmanned-ship cooperation synchronization in a complex water area environment by constructing a cooperation framework of the synchronization time consensus mechanism and dynamic trajectory optimization. The method is characterized in that the time information interaction frequency between the unmanned ships is dynamically adjusted by adopting an event trigger type communication mechanism, and the global optimal synchronization time is determined through a distributed consensus algorithm; and on the basis of the quintic polynomial parameterized trajectory, curvature minimization, path minimization and obstacle avoidance safety are taken as multiple trajectory planning targets, and an optimal trajectory adaptive to synchronization time is generated in combination with numerical differentiation and iterative optimization algorithms. According to the invention, the method can achieve the precise time synchronization and high-precision trajectory tracking of a plurality of unmanned ships in a scene with the limited network bandwidth and the dynamic change of environment interference, and remarkably improves the efficiency and reliability of an unmanned ship cluster in tasks such as cooperative hunting and regional patrol.

The invention discloses a robot smooth path planning method and system based on an improved TEB algorithm and a storage medium, and the method comprises the following steps: S1, creating a robot motion environment, generating a cost map, and planning a global initial path; s2, performing adaptive dynamic sampling on path points on the global path according to the bending degree of the global path; s3, screening global path points; s4, initializing a track to be optimized; s5, updating the track to be optimized and the cost map; s6, constructing a total objective function, and creating a hypergraph; s7, solving the hypergraph to obtain an optimal track; s8, confirming whether the optimal track is feasible or not, and if not, returning to the step S4; s9, controlling the robot to move; and after the robot moves, re-screening the global path points and returning to the step S4 until the robot reaches the target point. According to the invention, frequent pose regulation and control and frequent speed fluctuation of the robot can be reduced.

The invention provides an optimization-free trajectory planning method for an autonomous vehicle in a highly dynamic environment. The optimization-free trajectory planning method comprises the following steps: performing path planning by using a Bezier curve; generating a plurality of smooth candidate paths without static obstacle collision through the Bezier curve; speed planning based on backstepping control: aiming at each selected candidate path, adopting a backstepping method based on a barrier Lyapunov function to carry out controller design so as to construct an accelerated speed and a distance constraint condition of the target vehicle; and optimal trajectory selection: proposing a comprehensive cost function, considering multiple evaluation indexes for evaluating the quality of the candidate paths, and selecting the optimal trajectory of the target vehicle. Compared with the prior art, the automatic driving track obtained in the scheme does not need to be subjected to complex nonlinear optimization, the calculation load is reduced, and meanwhile, the safety and the constraint satisfaction capability of the track are guaranteed through the obstacle Lyapunov function and the backstepping control.

The application relates to a layered decoupling unmanned personification trajectory planning method, which comprises the following steps: S1, upper path planning: for different road scenes, a sampled-based path planning method, a search-based path planning method and an optimization-based path planning method are combined to plan an optimal path; S2, lower speed planning: a search method based on an ST obstacle space-time collision prediction graph and vehicle acceleration constraint is adopted to obtain a speed curve of a vehicle along the optimal path, and finally an optimal trajectory is obtained. Compared with the prior art, the application provides a safer, more reliable, stable and smoother personification driving trajectory for an unmanned vehicle.

The application discloses a trajectory planning method and device, equipment and storage medium, and belongs to the technical field of vehicle navigation auxiliary driving or automatic driving. The application obtains a sampling trajectory cluster, determines actual motion trajectories of vehicles corresponding to each sampling trajectory in the sampling trajectory cluster, and screens a target trajectory from the sampling trajectory cluster according to the actual motion trajectories, so that the optimal trajectory is screened from the sampling trajectory cluster again based on the actual motion trajectories of the vehicles after the actual motion trajectories of the vehicles corresponding to each sampling trajectory are determined. In the above manner, it can be ensured that the optimal cost trajectory selected is the optimal selection when the vehicle is actually executed, and the safety and comfort of the navigation auxiliary driving system are improved.

The invention relates to an SPMSM time optimal trajectory planning method considering a short-time dynamic feasible region, and belongs to the technical field of servo motor control and trajectory planning. The method comprises the following steps: constructing a trapezoidal feasible region consisting of a peak torque boundary, a constant power curve boundary and a maximum rotating speed boundary based on an actual torque-rotating speed characteristic of the SPMSM as a basic dynamic constraint of trajectory planning; on the basis of the trapezoidal feasible region, introducing short-time overload thermal power constraint based on an energy consumption model, and forming a short-time dynamic feasible region of the trapezoidal feasible region and the thermal power constraint; the method comprises the following steps: by taking'positioning time minimization 'as a target, combining short-time dynamic feasible region constraint, and adopting a high-order polynomial trajectory and an SLSQP algorithm, completing solution and optimization of a time optimal trajectory. According to the invention, the reliability and wide working condition adaptability of the trajectory planning scheme are improved.

The invention relates to an automatic aiming throwing device and a control method thereof, through a damping buffer structure arranged between a power source interface and a shoulder rest in series, recoil energy at the moment of launching is dissipated through fluid damping, the mechanical transmission characteristic of equipment is improved, and the safety and stability of operation are improved. Meanwhile, a distance measuring module, a posture sensing module and a wind field sensing module are integrated on the gun body, environment data are obtained in real time, a processor calculates optimal ballistic parameters containing aerodynamic characteristics of the cable, a man-machine interaction module on the surface of the shell is matched to output a visual guide feedback signal, and an operator can rapidly adjust the posture of the gun body according to feedback under an unsteady platform. And the throwing hit rate under the complex sea condition is improved.

The invention relates to the technical field of robot control, in particular to a magnetorheological damper-based flexible landing control method for a hydraulic leg unit, which comprises the following steps of: S1, establishing a rigid-flexible coupling dynamic model, optimizing parameters, and simplifying a landing process into a mass-spring-damping system; the hydraulic cylinder is equivalent to a spring module, the magneto-rheological damper is equivalent to a variable damping module, and the optimal landing track and the optimal rigidity and damping parameters are obtained by minimizing the foot end impact force; s2, decomposing the optimal trajectory into joint target displacement through an inverse kinematics model; and S3, position and force double closed-loop control is conducted on the hydraulic damping actuator, displacement is tracked by the position outer loop control hydraulic cylinder, damping force is output by the force inner loop control magnetorheological damper, the intervention and quit time of the hydraulic damping actuator is decided, the damping force is dynamically distributed, and actual force signals are fed back to correct target displacement. The method realizes flexible landing, reduces impact, gives consideration to control precision and energy consumption, adapts to multiple terrains and prolongs the service life of equipment.

This application discloses a path planning method and system for a quadruped robot based on an improved Direct Weakening (DWA) algorithm. The method includes: acquiring a global path point sequence and the turning state of the previous control cycle; fusing multi-source sensor data to construct a local environment map and the robot's own state set; evaluating the scene complexity coefficient and determining the current tracking point; sampling candidate velocity combinations and predicting the trajectory; filtering candidates that meet stability conditions based on the turning state of the previous cycle, and eliminating collision trajectories; dynamically adjusting the evaluation function weights according to the tracking point distance, heading deviation, and scene complexity to select the optimal trajectory; smoothing the trajectory before execution, and monitoring and correcting deviations in real time. This application avoids attitude fluctuations caused by frequent switching through turning state constraints, achieves accurate approximation through distance grading and heading deviation linkage, and improves scene adaptability through multi-source fusion and dynamic weights. It solves the problems of poor attitude stability, low tracking accuracy, and insufficient robustness in complex scenes found in existing DWA algorithms.

Title: Anti-collision system for a mobile device. The invention relates to an anti-collision system (1) for an autonomous mobile device (D) configured to move in three dimensions. The system comprises an onboard memory (10) configured to save an optimal trajectory (Topt) to reach a destination position, a detection system (20) configured to detect the presence and position of intruding mobile devices (D'1, D'2, … D'i, …, D'N) within a detection zone (100) around the mobile device (D), and a control system (30) configured to impose a modified trajectory (T') on the mobile device (D) to reach the destination position. The modified trajectory is a function of the optimal trajectory and the position of each intruding mobile device at each time t during the movement. Figure for the abstract: Fig. 7

The application relates to the field of low-altitude safety technology and provides an aircraft optimal trajectory screening method and system based on an adjustable phase quantum search. A candidate trajectory is generated according to flight task constraints, and a generation cost is calculated, a high-quality solution is identified based on a cost threshold value, an adjustment search phase is based on, a balanced quantum superposition state of an encoded trajectory index is iteratively searched and measured by using a Grover quantum search algorithm to obtain an output index, the index is mapped to a trajectory, and an optimized trajectory is obtained through classical local optimization, a phase parameter and a cost threshold value are adaptively adjusted based on performance evaluation and repeated execution until an optimal trajectory is determined by meeting an end condition. The adjustable phase mechanism is introduced to realize online reconfiguration of the strategy, a feedback closed loop is established to realize adaptive optimization of the parameters, and the real-time requirements of urban air traffic control, unmanned aerial vehicle clusters and other scenes are met.

The invention discloses a three-mode aircraft based on a ground effect and a control method of the three-mode aircraft. The aircraft integrates three modes of vertical take-off and landing, ground effect cruising and fixed wing high-speed cruising, and efficient mode switching is achieved through aerodynamic layout optimization and self-adaptive control. And an airfoil profile geometric parameter self-adaptive adjustment technology is adopted, so that the flight performance of a ground-effect area is enhanced. According to the control method, adaptive PID, sliding mode control and LQR algorithms are integrated, and a hierarchical control architecture is constructed. And the LQR controller realizes optimal trajectory tracking based on the aerodynamic model in the high-speed cruise stage. A differential control strategy is adopted for each modal characteristic, and accurate control over the height and the speed is achieved. And through cooperative adjustment of the propeller angle and power, it is guaranteed that mode switching is stable and rapid. The problems that a traditional aircraft is low in mode conversion efficiency, insufficient in ground effect utilization and the like are solved, and the method has the advantages of being high in interference resistance, high in stability and wide in application range and is suitable for various low-altitude application scenes.

The present application relates to a kind of close approach trajectory robust control method in multi-target tracking, it is related to optimal control problem analytical objective function, constraint establishment and robust approach trajectory control scheme, belong to spacecraft situation awareness and control field.The present application first establishes optimal trajectory control problem, considers information gain and security constraint comprehensively, to establish the model basis of robust control instruction.Second, by establishing the analytical expression of Hellinger distance in optimal control problem under the theory of Outer Probability Measures (OPMs), the difference between the prior estimate and the posterior estimate of the target state is effectively evaluated, and then the information gain value under different control instructions is calculated to select the optimal control instruction.At the same time, by establishing the analytical upper and lower bound expression of the void probability in the constraint condition of optimal control problem under the theory of OPMs, the void probability of the approach trajectory at any time under different control instructions can be efficiently calculated, so as to evaluate the safety of the approach trajectory and select the control instruction that meets the constraint condition.Finally, a robust trajectory control and a possibility label multiple Bernoulli filter module are designed to form a close approach trajectory robust control scheme, which realizes the goal of generating optimal control instructions in real time during the approach and tracking process, and achieves the effect of maximizing information gain and ensuring the safety of the approach trajectory.

This invention addresses the need for autonomous navigation of low-cost, high-spin munitions by providing a factor graph-based navigation method for dynamically optimizing trajectories and inertia under elliptical geometric constraints. This method uses an ideal trajectory as a benchmark, constructs elliptical geometric constraints, and generates multiple candidate trajectories that satisfy these constraints, forming a candidate trajectory set. By evaluating the similarity between measured inertial data (gyroscope and accelerometer) and the inertial data derived from each candidate trajectory, a trajectory sequence that meets threshold requirements is dynamically selected. Using the optimized trajectory and the inertial pre-integration results as constraint factors, a factor graph-based navigation scheme integrating the optimized trajectory and inertial data is designed to achieve high-precision autonomous positioning of high-spin munitions under satellite denial scenarios. This invention solves the technical challenges of rapid error accumulation and significant decrease in navigation accuracy inherent in pure inertial navigation schemes under satellite denial conditions.

The application relates to the technical field of trajectory planning, and proposes a fast evaluation search method, a system and a terminal device of an optimal trajectory. The fast evaluation search method comprises the following steps: sampling a plurality of state points in a pre-planning space, performing pre-collision detection on the state points to remove points in conflict with obstacles, and obtaining effective sampling points; performing cost evaluation on the effective sampling points, wherein the cost evaluation comprises heuristic cost based on historical planning trajectory information and static cost based on motion characteristics; based on the result of the cost evaluation, iteratively searching from an initial state point: calculating the trajectory cost of a neighborhood state point and updating a search path in a gradient direction until an optimal feasible trajectory is output. The application improves the search efficiency of the trajectory by pre-collision detection to screen out invalid sampling points and a gradient iterative search mechanism.

The invention discloses a valve core soft landing optimal trajectory planning and control method, and relates to the field of high-speed switch valve control, and the method comprises the following steps: (1) building a non-linear dynamic model of a high-speed switch valve under multi-field coupling; (2) giving a soft landing state constraint equation and a soft landing objective function of the high-speed switch valve to construct a soft landing nonlinear programming problem of the valve element of the high-speed switch valve; (3) solving an optimal soft landing curve of the valve element of the high-speed switch valve by using a primal-dual interior point method; (4) constructing a sliding mode observer to estimate the displacement of the valve element, feeding the displacement back to a sliding mode controller, and inversely solving a driving voltage curve; soft landing of the valve element is achieved. According to the method, the optimal soft landing track of the valve element of the high-speed switch valve can be solved, soft landing control is conducted on the valve element, noise and vibration are reduced, abrasion is reduced, and the service life is prolonged. The method is suitable for the fields of high-speed switch valve control strategies, soft landing trajectory planning and control and the like, and a new thought is brought to the high-speed switch valve driving control strategies.

Embodiments of the present application provide a trajectory determination method, device, equipment and vehicle. The method comprises: obtaining at least two initial trajectories of a vehicle; determining rule information corresponding to each trajectory decision dimension in N trajectory decision dimensions; determining reference rule information from the rule information according to the priority of the rule information, and comparing each initial trajectory according to the reference rule information to obtain at least one candidate trajectory; and determining an optimal trajectory of the vehicle from the initial trajectories according to the at least one candidate trajectory. The method can realize the transparency of trajectory determination logic and reduce the complexity of parameter tuning.

The invention relates to a trajectory prediction method and system based on a dynamic hybrid model. The trajectory prediction method based on the dynamic hybrid model comprises the following steps: constructing an environment complexity evaluation system based on multi-dimensional environment characteristic historical data; building a model performance knowledge base based on historical data of a plurality of different types of trajectory prediction models; developing a reinforcement learning decision-making agent based on the environment complexity evaluation system and the model performance knowledge base; inputting real-time environment characteristics of a current scene, obtaining a dynamic grade of the current scene and a precision score and a delay score matched with the dynamic grade, and inputting the dynamic grade and the precision score and the delay score into a reinforcement learning decision-making agent to obtain an optimal trajectory prediction model combination; performing trajectory prediction based on the optimal trajectory prediction model combination; and correcting the predicted trajectory based on the real-time prediction error in the optimal trajectory prediction model combination operation process, and outputting a final predicted trajectory. According to the invention, the accuracy, switching continuity and environmental adaptability of trajectory prediction can be improved.

The present application belongs to the field of robot technology and driver, and specifically relates to a trajectory checking planning method for a safety boundary of a driver layer, which comprises the following steps: 1) position and acceleration constraint setting; 2) the driver checks the current mechanical arm position and speed through a safety boundary triggering function, and evaluates whether the mechanical arm is about to or has exceeded the preset safety boundary; 3) when the safety boundary is triggered, a re-planning stage is entered, and the driver automatically calculates and generates a time-optimal trajectory re-planning strategy by using the position, speed and acceleration information of the current mechanical arm; and 4) the driver adjusts the driver instruction generated according to the re-planning strategy to ensure the safe movement of the mechanical arm. The present application combines the position constraint and the maximum stop acceleration constraint of the driver layer, and effectively deals with the misoperation or unreasonable planning of the upper-layer trajectory planning instruction.