433 results about "Trajectory planning" patented technology

This invention relates to a multi-constraint trajectory planning method for bouncing movement on the surface of complex small celestial bodies, belonging to the field of deep space exploration. The implementation method is as follows: Establishing a closed-form relationship between bouncing movement distance, velocity, takeoff angle, and energy consumption, and a two-layer expansion radius obstacle representation model; establishing escape velocity constraints, no-fall constraints, fly-through feasibility constraints, and convex obstacle fly-through constraints; using the two-layer expansion radius obstacle representation model and multiple constraints, establishing a fly-through feasibility determination mechanism for obstacles; using Poisson-disk sampling to establish the bouncing reachability domain and an analytical solution for the energy-optimal trajectory satisfying multiple constraints; establishing a reachability domain filtering method based on the bouncing reachability domain and the analytical solution for the energy-optimal trajectory; using energy consumption as the weight, employing the A* algorithm to search for a global energy-optimal bouncing path point sequence and the corresponding velocity and takeoff angle of each path point, generating a global energy-optimal trajectory, thus realizing multi-constraint trajectory planning for bouncing movement on the surface of complex small celestial bodies.

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.

This invention discloses a method for reusing obstacle avoidance trajectory parameters based on local environmental geometric and motion constraint features. The method includes the following steps: acquiring a local point cloud to construct a local map; calculating the geometric residuals from points to planes based on the local map to obtain residual statistical features; calculating the plane normal distribution based on the local map to obtain structural orientation features; and constructing an information matrix based on the Jacobian matrix optimized by the direct method pose to obtain motion constraint features; combining the residual statistical features, structural orientation features, and motion constraint features into a local environmental feature descriptor; binding the local environmental feature descriptor with trajectory generation parameters of historical obstacle avoidance trajectories and storing it in a database; calculating the similarity between the current local environmental feature descriptor and the historical feature descriptors in the database, and selecting the corresponding historical trajectory generation parameters based on similarity matching; and using the historical trajectory generation parameters as the initial parameters for the current obstacle avoidance trajectory planning.

This invention discloses a method, system, device, and storage medium for UAV trajectory planning in remote sensing monitoring. The method includes: determining the monitoring area range based on task requirements and initial target position, dividing it into a transition zone and a remote sensing monitoring image area; setting imaging attitude constraint parameters to obtain the turning radius and altitude constraint parameters of the Dubins trajectory; generating a two-dimensional Dubins trajectory and converting it into a planar waypoint sequence; performing linear altitude interpolation on the remote sensing monitoring image area to obtain a three-dimensional waypoint sequence; subscribing to the UAV attitude in real time within the image area, verifying and adjusting the roll and pitch angles to obtain the adjusted three-dimensional waypoint sequence; updating the target area range based on the adjusted trajectory and iteratively optimizing until the stopping condition is met. This invention integrates two-dimensional path optimization, three-dimensional altitude interpolation, and real-time attitude closed-loop adjustment, which can effectively suppress attitude deviations during low-speed flight and improve the orthorectification quality and continuity of remote sensing monitoring images.

The application discloses a kind of based on visual perception nimble hand motion planning method, equipment and medium, it is related to robot control technical field, including, based on the multi-modal visual data of real-time acquisition execution object instance segmentation and object six degree of freedom pose estimation, generate the environment state representation including object category, segmentation mask and pose information;When arbitration decision instruction comprehensive risk difference index does not satisfy preset stable execution condition, start global re-planning and generate new planning instruction, and continuously update environment state representation in executable main trajectory execution process.The application is estimated to object six degree of freedom pose by covariance analysis to result and applies counterfactual disturbance, forms the multi-state environment representation around the perception uncertainty in trajectory planning phase, realizes multi-trajectory planning expression under the same task instruction constraint.

The present application relates to the technical field of vehicle automatic driving, in particular to a kind of intelligent Agent trajectory planning control method and system based on HDMap;The method mainly includes four steps of the initialization of vehicle Agent, formal path query, entry mode confirmation and automatic driving according to path;High-precision semantic map and the idea of intelligent Agent are used in the present scheme, and a kind of vehicle Agent implementation scheme for flexible operation along lane is presented;In the entry mode of vehicle Agent, the present scheme designs a kind of ingenious vehicle Agent entry mode from the angle of time and space;The present scheme utilizes lane center line segment information in map, regulates the motion trajectory of vehicle, and provides flexible acceleration setting interface, so that the speed of vehicle Agent can change in real time according to the demand of user or traffic condition while automatically driving along lane, which reserves interface for the access of subsequent vehicle anti-collision strategy.

This application relates to the field of automotive driving technology, and discloses a trajectory planning and decision-making method, device, vehicle, medium, and program product to ensure more reasonable avoidance decisions while reducing computational power consumption. Specifically, the method includes: detecting an avoidance target during vehicle operation; determining a target reference line for the vehicle to bypass the target, wherein the target reference line indicates the bypass direction and endpoint of the vehicle to bypass the target, and the target reference line is one of at least two reference lines, and at least two of the at least two reference lines have different bypass directions; determining a target avoidance trajectory that meets set constraints based on the target reference line and obstacle and road information in the surrounding environment of the vehicle; and controlling the vehicle to steer around the target based on the target avoidance trajectory.

This invention provides a method and system for cooperative obstacle avoidance and trajectory planning in UAV swarm formation, relating to UAV swarm control technology. By introducing three-dimensional affine transformation parameterization of formation motion, the dimensionality and search space complexity of UAV swarm system modeling are reduced, alleviating computational burden. An affine A-RRT planning algorithm is employed to construct path topology in affine space, improving sampling search efficiency and reducing redundant nodes and ineffective expansion. ESDF gradient information is used for path correction and to construct sequential convex regions, simplifying the construction process of safe regions and ensuring sufficient safety margins. By constructing a quadratic programming model integrating multiple performance indicators and solving it online, a balance is achieved between trajectory smoothness, energy efficiency, and swarm formation maintenance performance, meeting the real-time planning requirements for cooperative obstacle avoidance in complex environments.

This invention relates to the field of shield tunnel segment inspection technology, and discloses a visual inspection-based shield tunnel segment assembly machine assembly quality inspection device and method, including: achieving autonomous perception and rapid recovery of calibration parameters when they fail due to vibration or temperature drift through time-efficiency monitoring and sliding window optimization technology; overcoming calibration bottlenecks through texture perception and active exploration trajectory planning technology; solving the calibration instability problem caused by the lack of natural textures by artificially creating multi-view geometric constraints using micro-motion trajectories; achieving intelligent decision-making and adaptive adjustment in the active exploration process through information gain-driven convergence judgment and global optimization technology; significantly enhancing parameter estimation confidence through global optimization integrating multi-source data; and constructing an unattended autonomous calibration management system through result encapsulation and closed-loop feedback technology, enabling persistent storage of calibration parameters, accumulation of prior knowledge, and real-time timeliness monitoring.

A trajectory planning system that calculates a laterally offset trajectory based on a maximum allowable in-lane lateral offset with respect to the center of a host lane of a vehicle includes one or more controllers including one or more processors that execute instructions to monitor perception data collected by a plurality of perception sensors until determining an occurrence of an offset event requiring the vehicle to deviate from an original trajectory. In response to determining the occurrence of the offset event, the one or more controllers calculate a non-linear error component of the maximum allowable in-lane lateral offset. The one or more controllers update the laterally offset trajectory of the vehicle with the maximum allowable in-lane lateral offset and apply a rate limiter to the maximum allowable in-lane lateral offset in real-time while instructing the vehicle to travel along the laterally offset trajectory.

A vehicular driving assist system, includes a sensor disposed at a vehicle equipped with the vehicular driving assist system and sensing exterior of the vehicle that captures sensor data. The vehicular driving assist system detects, responsive to processing at an ECU of sensor data captured by the sensor, an object in the field of sensing. The vehicular driving assist system determines, based at least in part on detecting the object, a plurality of waypoints that represents a reference trajectory of the vehicle. The vehicular driving assist system determines, for each waypoint of the plurality of waypoints, a constraint with respect to the detected object. The vehicular driving assist system adjusts, based at least in part on the constraints with respect to the detected object, the reference trajectory of the vehicle to determine an updated trajectory of the vehicle.

This application provides a trajectory planning method, apparatus, and electronic device for autonomous vehicles, relating to the field of autonomous driving technology. The trajectory planning method for autonomous vehicles includes: generating multiple candidate trajectories from a first pose to a second pose based on scene information and dynamic constraint information of the autonomous vehicle; for each candidate trajectory, predicting the future environmental state information of the autonomous vehicle under the candidate trajectory based on scene information, and constructing a trajectory scene tree for the autonomous vehicle based on the future environmental state information; the future environmental state information includes the autonomous vehicle's own state information in future time periods and the environmental response information of traffic participants; evaluating the candidate trajectories based on the future environmental state information; and determining the target trajectory of the autonomous vehicle based on the trajectory evaluation results and the trajectory scene tree. This application achieves real-time performance and accuracy in trajectory planning for autonomous vehicles, ensuring the smoothness and safety of vehicle operation.

This invention relates to the field of robot motion control technology and provides a method for generating high-order smooth trajectories for industrial robots. The method includes: constructing a fifth-order polynomial trajectory planning model and establishing start and end state boundary conditions; adaptively tuning the running time based on physical limit constraints and discretizing it; constructing a linear matrix equation and analytically solving the polynomial coefficients to generate discretized trajectory instructions; and issuing the instructions to the underlying control system for closed-loop execution. This invention utilizes the high-order continuity of the fifth-order polynomial to achieve globally smooth and bounded jerk, completely avoiding abrupt jerk step jumps; it adopts a deterministic algebraic analytical computation architecture, avoiding complex piecewise logic and iterative solutions, significantly reducing computational overhead and timing fluctuations. This invention ensures high-order trajectory smoothness while meeting real-time requirements, effectively reducing mechanical soft impacts, and is suitable for the underlying servo control of multi-axis industrial robots.

The application discloses a fault scanning control method and device, a fault scanning equipment and a storage medium. The method comprises the following steps: identifying a key anatomical structure of an initial projection image based on a pre-trained trajectory planning model, generating a probability distribution map, determining a sparse scanning angle sequence and corresponding first scanning parameters, densely sampling and appropriately increasing a radiation dose in a high-weight area, and sparsely sampling and reducing a dose in a low-weight area; controlling the fault scanning equipment to perform scanning, obtaining first projection data and reconstructing the first projection data into a sparse reconstruction image; performing multi-modal fusion and scoring on the sparse reconstruction image and the current scanning parameters through an image quality evaluation model, adaptively optimizing scanning instructions according to the probability distribution map, a fusion feature vector, an image quality score, an equipment state and historical action data, generating second scanning parameters, making the scanning trajectory more continuous and smooth through an artificial intelligence technology, and realizing regional adaptive regulation and control of angles, doses and paths, so that the imaging resolution can be improved.

The present application relates to a kind of serpentine coiling bionic control system and method and system, belong to industrial automation control technical field, system includes controller, network communication transmission unit, executing mechanism, feedback element and man-machine interaction module;The controller is built-in serpentine coiling algorithm curve calculation module, for receiving feedback data, executing trajectory planning calculation and outputting control instruction;The network transmission unit uses redundant network system, realizes the transmission communication of data;The executing mechanism includes servo motor and variable frequency motor, servo motor and variable frequency motor are closed loop cooperation by controller to realize the rotation speed-axial displacement;The feedback element is in real time by multiple sensors Feedback working condition parameter;The man-machine interaction module: for parameter setting, working condition monitoring and fault alarm.The present application realizes efficient, uniform, non-interference, low stress coiling operation by serpentine coiling bionics.

The application relates to the technical field of path planning, and particularly discloses an intelligent path planning method and system for a fire extinguishing aircraft. The method comprises the following steps: collecting aircraft state data, extracting a load-thrust mutation feature at a load release moment, and constructing a transient dynamic reachable domain; obtaining task point coordinates, performing vector homotopy analysis on the reachable domain in combination with a target heading, calculating a cooperative gain coefficient to determine whether to assist in approaching the target; if the condition is met, a dynamic attitude preset trajectory is generated; the preset trajectory is mapped to the dynamic reachable domain for compatibility analysis under time-varying constraints, an execution saturation risk curve is calculated, and adaptive boundary contraction optimization is performed on the trajectory. The system comprises a reachable analysis module, a vector analysis module, a trajectory planning module and an intelligent optimization module, and is used for realizing the above method. The application is beneficial to improving the maneuvering efficiency of fire extinguishing operation under the premise of flight safety.

The present application belongs to the technical field of metal sheet plastic forming and digital control cross, and discloses a kind of aluminum veneer multi-axis linkage numerical control bending method based on springback compensation.The method collects historical bending process data, with sheet thickness, bending radius, die slot width and feed speed as input features to divide process feature subspace, and establishes a bending angle springback amount mapping matrix in each subspace to obtain initial down pressure depth compensation value for performing feedforward control.In the multi-axis linkage bending stage, real-time servo motor torque feedback signal and grating displacement signal are collected, and the real-time plastic deformation resistance of the current bending zone is calculated, and the online compensation correction amount is solved using the dynamic differential equation of deformation resistance and springback angle, and the correction amount is added to the remaining trajectory planning of multi-axis interpolation algorithm.The present application makes the down pressure trajectory self-adaptive correction according to real-time resistance, eliminates the fixed compensation deviation, and improves the compliance of bending angle to target value.

This application discloses a vehicle trajectory planning method, apparatus, device, medium, and product, belonging to the field of autonomous driving technology. The method includes: acquiring a set of future trajectories for a target vehicle; determining the target predicted driving trajectory corresponding to each drivable trajectory in the future trajectory set for surrounding vehicles based on the future trajectory set, the historical trajectories of surrounding vehicles, and current traffic environment information; wherein the target predicted driving trajectory is obtained by adjusting the initial predicted driving trajectories of surrounding vehicles based on the drivable trajectories; the initial predicted driving trajectory is obtained based on historical trajectories and current traffic environment information; determining the target score of the drivable trajectory based on the drivable trajectories and the target predicted driving trajectories corresponding to the drivable trajectories of surrounding vehicles, and outputting the drivable trajectory with the highest target score in the future trajectory set. This application can improve the autonomy and flexibility of trajectory planning for the target vehicle, and also improve the traffic efficiency of the target vehicle.

The utility model discloses an aluminum alloy door and window surface spraying homogenization equipment, it includes: support frame upper surface fixed connection has support station, and support station upper surface is rotatably connected with carousel, and carousel upper surface fixed connection has square column, and square column upper surface fixed connection has top plate, and the frame body is set between top plate and carousel, and the clamping assembly is set up on the frame body, and the multi -shaft robot is set up on support station upper surface and is provided with grabbing module, cleaning drying module, spraying module, solidification module respectively, through above -mentioned structure, the orderly link of grabbing, cleaning drying, spraying, solidification etc. process, form closed -loop assembly line operation, compared with traditional manual operation, and the processing period is shortened greatly, and the high -precision positioning and trajectory planning ability of multi -shaft robot are combined simultaneously, ensure that the coating evenly covers each place of surface, through intelligent control system realizes each module cooperation operation, and real -time monitoring spraying parameter and dynamic adjustment, guarantee product quality stability and consistency.

This invention discloses a gravity field orientation adaptability analysis method based on image texture features. This method can select adaptability regions rich in gravity information, providing directional guidance for gravity field trajectory planning and effectively improving the accuracy of multi-directional gravity field matching. This invention comprehensively considers both gravity field statistical feature parameters and image texture feature parameters, fusing these two features to determine the adaptability region, making the selected adaptability region more continuous and the texture features more obvious. During dataset training, a parallel convolutional neural network is used, simultaneously training statistical feature parameters reflecting gravity field statistical features and gray-level gradient co-occurrence matrix parameters reflecting image texture features. These features are mapped to the output layer for classification, and the gravity field adaptability region is determined based on the classification results, thus achieving the evaluation of the orientation adaptability of the gravity field adaptability region.

This application proposes a method and apparatus for planning the trajectory of carbon fiber winding in a robot, relating to the field of carbon fiber winding technology. The method includes: collecting key winding data at the current moment through the robot's online sensing system; generating theoretical control data for the next moment using a geodesic algorithm; constructing a trajectory planning objective function and constraints; substituting the key winding data at the current moment into the constraints to determine whether trajectory correction is triggered; when trajectory correction is not triggered, the robot winds the carbon fiber according to the theoretical control data for the next moment; when trajectory correction is triggered, substituting the key winding data at the current moment into the trajectory planning objective function, solving it using a quadratic programming QP solver to obtain incremental control data for the next moment; correcting the theoretical control data for the next moment based on the incremental control data to obtain corrected control data for the next moment; and then winding the carbon fiber according to the corrected control data for the next moment.

This invention discloses an adaptive lid opening control method and system for laptops. The core of this method lies in constructing an integrated control system of "state perception - intelligent decision-making - collaborative execution" to solve the technical contradiction of difficulty in coordinating efficiency, accuracy, and non-destructive requirements in the automated lid opening of laptops. Thickness, material, and pose information are acquired through a multi-dimensional state perception module of the laptop body. The central controller dynamically calculates and outputs differentiated clamping, adsorption, and motion commands based on a pre-built mechanical model of the laptop model. A two-stage safe lid opening strategy is adopted. In the initial stage, non-destructive pre-opening is achieved based on material recognition and adsorption parameters. In the main stage, the trajectory planning module dynamically coordinates the combined motion of the vertical lifting and horizontal translation mechanisms, enabling the lid to open smoothly along a non-collision optimized trajectory. After opening, the vehicle pose adjustment amount is calculated in reverse based on visual fusion positioning information to achieve precise self-alignment with multiple detection stations.

Embodiments of the present application provide a trajectory planning method and device, model training method and device, automatic driving system and medium, and relate to the technical field of automatic driving. The method comprises: obtaining driving perception data of a vehicle in a current scene; using world knowledge built in a large language model, taking lane lines in a future scene associated with the driving perception data as static physical constraints, and taking traffic participants in a drivable area of the vehicle defined by the lane lines and associated with the driving perception data as dynamic physical constraints, reasoning the driving perception data to obtain a future scene image; and using the large language model, taking a space-time thinking chain as an intermediate reasoning carrier, reasoning the driving perception data and the future scene image to obtain a trajectory sequence of the vehicle. The scheme establishes a causal relationship of the physical world, improves the reasoning accuracy of the trajectory sequence, covers long-tail scenes, and improves the safety of automatic driving.

This invention discloses a machine vision-based adaptive spraying planning method and system for workpiece trajectories. The method includes: using a spraying sensor device to capture a stereoscopic image of the workpiece to be sprayed; preprocessing the stereoscopic image to obtain an image to be inspected; uniformly meshing the image to be inspected to form a pixel grid, and identifying the gradient magnitude of the vertices of the pixel grid; acquiring path points according to a preset spray gun travel direction, assigning the gradient magnitude of the vertices to the path points, identifying initial feature inflection points, and forming feature inflection lines; dynamically adjusting the spray gun's moving speed based on the feature inflection lines; and forming a spraying trajectory based on the feature inflection lines and the moving speed. This fully demonstrates the advantages of combining machine vision and intelligent path planning in industrial spraying, significantly improving spraying quality, efficiency, and material utilization, while reducing the complexity of manual adjustments.

The application provides a robot joint space trajectory planning obstacle avoidance point optimization method and system based on operation space dynamics, and belongs to the technical field of industrial robot motion planning and optimization. The method comprises the following steps: constructing a dynamics model of a mechanical arm and initializing a task environment to obtain a joint space dynamics equation, a starting point, a target point and obstacle information; deducing and constructing a Cartesian operation space dynamics evaluation model based on the dynamics model of the mechanical arm; iteratively searching for an intermediate obstacle avoidance point in an obstacle avoidance space based on a particle swarm optimization algorithm and taking the starting point, the target point and the obstacle information as constraints; using the Cartesian operation space dynamics evaluation model, combining joint space displacement, and calculating the comprehensive generation value of a collision-free path from the starting point to the target point via each candidate point; and outputting the candidate point with the minimum comprehensive generation value to generate a final PTP motion trajectory of the mechanical arm. The application integrates dynamics evaluation, optimizes the obstacle avoidance point, and improves the efficiency of the PTP trajectory.

The application provides a close operation robot, an obstacle avoidance method and a control unit thereof, and belongs to the technical field of robots.The method comprises the following steps: acquiring a color image of an operation scene and depth information corresponding to each pixel point in the color image; identifying a workpiece target in the color image based on a pre-trained instance segmentation model to obtain a workpiece mask; performing inflation processing on the workpiece mask to obtain a safe workpiece area; based on the safe workpiece area, screening the pixel points in the depth information, projecting the retained pixel points into three-dimensional space points to construct an obstacle point cloud; updating an obstacle avoidance map according to the obstacle point cloud; based on the updated obstacle avoidance map, performing collision detection and trajectory planning on a close operation process of the robot, and controlling the robot to perform an obstacle avoidance operation.The obstacle avoidance method, the control unit and the close operation robot provided by the application can effectively distinguish workpieces from obstacles in a close operation scene, and improve the reliability of online obstacle avoidance.

Embodiments of the present application provide a trajectory planning method and device, and relate to the technical field of robots. The method comprises: in the case that a pause instruction is received during robot movement, determining a first target position of a first target trajectory point, a current position and velocity of a robot end, and a current position, and in an original position trajectory corresponding to current movement, an execution time of a current trajectory point is earlier than an execution time of the first target trajectory point; taking the position and velocity of the first target trajectory point as 0 as a requirement, and according to the current movement, the current position and velocity, the current position, and the first target position, pause position trajectory planning information corresponding to a pause process is planned, a starting point of the pause position trajectory is the current position, an end point of the pause position trajectory is the first target position, and the pause position trajectory planning information comprises a corresponding relationship between a time and a position. In this way, the occurrence of accidents such as end tool collision and robot collision can be effectively avoided, and the stability and safety of robot operation are greatly improved.

The application discloses a kind of man-machine cooperation's industrial robot hybrid PSO-PS trajectory optimization method and system, and the application relates to intelligent robot control and path planning technical field, comprising the following steps: S1: obtaining initial feasible trajectory generated by human expert demonstration, constructs the digital twinborn environment matched with physical robot, and defines the task parameter set including space constraint, safety envelope and obstacle avoidance area.The man-machine cooperation's industrial robot hybrid PSO-PS trajectory optimization method and system solve the problem that traditional artificial demonstration trajectory is difficult to achieve optimal in execution efficiency, motion smoothness, avoid the defect that pure autonomous optimization algorithm brings from the large calculation overhead of random solution space start search, slow convergence speed.Realize the bidirectional promotion of global optimization coverage capability and local solution accuracy, optimize the execution efficiency of robot operation trajectory, and can adapt to the trajectory planning demand under complex industrial scene.