16 results about "Potential field" patented technology

The invention discloses an obstacle avoidance control method and system for unmanned aerial vehicle inspection, and relates to the technical field of unmanned aerial vehicle inspection path planning, the surrounding environment is sensed through a sensing system carried by an unmanned aerial vehicle, and navigation points falling into a sensing range are dynamically obtained; if multiple navigation points exist in the sensing range, the multiple navigation points serve as local targets at the same time to apply a gravitational potential field, the gravitational force of the navigation points is automatically distributed according to the distance, then the gravitational force of all the navigation points is summed, the total gravitational force is obtained, and multi-target resultant force guiding is achieved; when obstacle repulsive force calculation is carried out, a speed vector of an obstacle is extracted, future position changes of the moving obstacle are predicted, a time factor and an obstacle volume parameter are introduced into a potential field model, and self-adaptive adjustment is carried out on a repulsive force function; the problems that the unmanned aerial vehicle is prone to deviating from the global direction during obstacle avoidance, the path is discontinuous or the unmanned aerial vehicle detours too far, and an active avoidance mechanism still lacks when a high-speed dynamic obstacle occurs are effectively solved.

The invention belongs to the related technical field of lithium ion batteries, and discloses a method and a system for predicting dendritic crystal and crack evolution in a solid-state lithium metal battery. The method comprises the following steps: establishing a computational domain of a solid-state lithium metal battery and a pre-cracked solid-state electrolyte, applying stacking pressure and lateral pressure on the computational domain, and performing grid division on a two-dimensional model of the lithium metal battery and the solid-state electrolyte in the computational domain; establishing a multi-physics field model in the two-dimensional model after grid division, wherein the multi-physics field model comprises a dendritic phase field equation, a concentration diffusion equation, a potential field equation, a solid mechanical equation and a crack phase field equation; and combining the multi-physical field model to solve an optimization model with the minimum cracking failure degree of the solid electrolyte as a target, and obtaining the cracking failure degree of the solid electrolyte under different material parameters and working pressures. Through the method, the problems that in the crack evolution process, prediction precision is low and pressure constraint is not optimized due to the fact that micro-scale prediction is not carried out are solved.

The invention belongs to the technical field of magnetic field measurement and instruments, and relates to a magnetic gradient tensor field interpolation method under physical potential field constraint, which comprises the steps of establishing a Gaussian process model of a magnetic gradient tensor field, acquiring a magnetic potential core and performing hyper-parameter optimization. According to the method, multi-component interpolation and curving are fused into a unified Gaussian process regression framework, and the multi-component interpolation and the curving are subjected to potential field physical constraints in a unified manner; a complete potential field physical constraint is used, meanwhile, no-rotation and no-divergence constraints are met, and magnetic gradient tensor measurement data interpolation with measurement errors is more accurate and better in anti-interference capability; by introducing a complete physical constraint fusion Gaussian process regression framework, the magnetic gradient tensor interpolation precision and stability are improved. Based on the magnetic potential core, all magnetic gradient tensor components can be modeled at the same time in the joint probability model, physical constraints among the components are guaranteed, non-planar data which are distributed at will can be processed naturally based on a Gaussian process regression framework, and an additional potential field continuation step is not needed.

The invention discloses a multi-layer potential field and dynamic target generation-based unmanned ship formation control method and system. The method comprises the steps of judging whether an unmanned ship formation reaches a target point or not; if the terminal point is not reached, switching to the next target point; judging whether the distance between the target point and the end point exceeds the radius of the global potential field, and if so, activating a dynamic target generation mechanism to generate a temporary target point; updating the current target point; monitoring an environment obstacle state; the acting force of the formation gravitational field, the acting force of the inter-boat repulsion field and the acting force of the obstacle repulsion field are synthesized; and obtaining control input according to the synthetic acting force, updating the formation position and environment sensing data in real time until the terminal point is reached, and ending the navigation task. According to the method, the formation collaborative operation efficiency is improved, and a brand new path is developed for reliable application of the unmanned ship formation in a complex environment by radically solving two major problems of potential field imbalance and collaborative interference.

The invention relates to the technical field of cable detection, in particular to a method and system for detecting the thickness of an insulating layer of a cross-linked insulated cable. The method comprises the following steps: acquiring a cable cross section image, performing region segmentation to identify three topological connected domains, and extracting inner and outer boundaries; establishing a physical field model and applying a first type of boundary conditions; solving a Laplacian equation in the insulating layer region to generate a convergent scalar potential field; performing differential operation on the scalar potential field to obtain a gradient vector field, and searching gradient modulus length extreme points on the virtual equipotential line to mark thinnest and thickest feature points; and taking the thinnest feature point and the thickest feature point as starting points, respectively executing streamline tracking along positive and negative gradient directions, and calculating the sum of path lengths so as to respectively obtain the minimum thickness of the insulating layer and the maximum thickness of the insulating layer. Noise is eliminated by solving the Laplacian equation, rapid positioning is performed by using the gradient modulus length extreme value, and the detection precision is remarkably improved.

The invention belongs to the field of gravity exploration, and particularly relates to a method for acquiring gravity anomaly blank area data based on potential field characteristics, which comprises the following steps: acquiring gravity and topographic data of an exploration area and a neighborhood, and generating standard grid data and identifying a blank area through preprocessing and gridding; multiple interpolation algorithms are combined for parallel calculation, cross validation quantitative evaluation is carried out, and an optimal model is selected to obtain a reliable Bouguer gravity abnormal value of the blank area; mathematical analysis and filtering smoothing processing are carried out on the interpolation result, noise is eliminated, and a Bouguer gravity abnormal value conforming to the physical continuity and smoothness of the gravity field is obtained; and superposing the processed Bouguer gravity anomaly with a terrain gravity effect to obtain a complete space gravity anomaly field. Through systematic processing of existing Bouguer gravity anomaly and topographic data, filling and balancing of gravity anomaly values in areas with complex terrains and sparse data are successfully realized by using technical means of interpolation, analysis, smoothing, reduction and the like.

According to the method, a surface gravity wave and inner interface wave velocity potential field is analyzed into a product form of a vertical characteristic item and a horizontal diffraction field, and dimensionality reduction solution of a three-dimensional wave problem is realized; a vertical characteristic function orthogonal system meeting free liquid level, seabed boundary and interface coupling conditions is constructed, horizontal diffraction potential is decomposed into an incident field, a local column and an adjacent column scattering effect, and a Bessel function addition theorem is applied to construct a closed linear equation set of a multi-column interference field; establishing an extended dispersion equation containing density spring layer parameters, and revealing a modulation rule of layered strength on complex wave propagation characteristics; and finally, through tensor product coupling of a vertical mode and a horizontal diffraction field, constructing a full-three-dimensional diffraction velocity potential analytical solution, synthesizing a cross-layer pressure field integral by adopting a domain decomposition technology, and establishing a multi-column array generalized wave excitation force forecasting model. According to the method, efficient analytical calculation of the wave load of the multi-column system in the layered fluid is innovatively achieved.

The invention provides a path planning method and device for an intelligent machine, electronic equipment and a storage medium, and the method comprises the steps: initializing the current position of the intelligent machine, a final target point and the position information of an obstacle in an environment, and building a rectangular plane coordinate system for path calculation; generating an initial path from the current position to the final target point by adopting a global path planning algorithm, and dividing the initial path into a plurality of sub-path sections; constructing a virtual potential field model containing a gravitational potential field and a repulsive potential field; in the autonomous navigation process of the intelligent machine, the obstacle state in the environment where the intelligent machine is located is dynamically sensed, the comprehensive guiding amount acting on the intelligent machine is calculated in real time based on the virtual potential field model, a motion control instruction is generated according to the comprehensive guiding amount, and the intelligent machine is driven to deviate from the original path to avoid the obstacle. And a target track is generated until the intelligent machine reaches the final target point. The problem that the target is not reachable is solved, it is ensured that the target point can stably reach, and the quality and reliability of path planning are remarkably improved.

The application discloses a kind of based on random projection's physical property parameter inversion method of potential field data, comprising the following steps: S1: measured potential field data is obtained, according to survey area and depth range is profiled in underground space, sensitivity matrix in inversion is calculated based on potential field data forward theory, and then the forward calculation relationship of full space is established;S2: random projection matrix is designed, and sensitivity matrix is projected to multiple low-dimensional subspace, and the subspace forward calculation relationship is established;S3: based on the regularization equation of subspace forward calculation relationship, and the physical property parameter in subspace is solved using conjugate gradient algorithm;S4: the final physical property parameter inversion result is obtained by the weighted average calculation of multiple physical property parameters in subspace.The physical property parameter inversion method of potential field data based on random projection has higher depth resolution and inversion reliability, and improves the practicability of physical property inversion method in actual data processing.

This invention relates to a prediction-based robotic arm path planning method, apparatus, electronic device, and medium. The method involves real-time acquisition of hand position data and storage in a raw dataset, which also includes the current position data of the robotic arm, target position data, and actual obstacle position data. Based on the raw dataset, an Informer model is trained to obtain model weights and output predicted hand position data. The predicted hand position is used as a virtual obstacle, and a predicted repulsive potential field is obtained based on the predicted hand position data. Based on the predicted repulsive potential field, the repulsive potential field of the actual obstacle, and the gravitational potential field of the target position, the current resultant force is calculated to optimize the robotic arm's trajectory, control the robotic arm's movement, and perform sorting. The target position is the endpoint of the robotic arm's movement. Compared with existing technologies, this invention has advantages such as higher prediction accuracy, faster calculation speed, and higher human-machine collaboration efficiency.

The present disclosure provides a three-dimensional speed obstacle avoidance method and device for a UAV. The method comprises constructing an inertial coordinate system, a body coordinate system, a spherical protection region and a tangent point circular region according to position information of the UAV and position and speed information of an obstacle; generating a potential field model according to a center of a preset repulsive potential field and the spherical protection region, and generating a radial speed based on the potential field model in a case where a modulus of a position vector of the position information of the obstacle meets a preset condition; obtaining a point set according to a vertex coordinate of a preset collision cone and a first rotation matrix; determining a second rotation matrix according to position information of a target point and a rotation angle, and processing the vertex coordinate, the tangent point circular region and the point set to obtain a boundary point set; determining a speed amount of the UAV towards the target point according to the boundary point set and a discretized first parameter variable; and generating a target speed component of the UAV flying towards the target point while avoiding the obstacle according to a third rotation matrix, the speed amount and the radial speed.

The invention discloses a highway ramp entrance path planning method based on an improved artificial potential field method. The highway ramp entrance path planning method comprises the following steps: determining road information of a highway ramp entrance, an initial state of a driving vehicle and an initial state of an obstacle; establishing an expressway ramp opening potential field, and converting an actual road space into a virtual potential field environment; constructing an obstacle repulsion potential field; building a highway ramp scene artificial potential field model based on a ramp potential field and the obstacle repulsive force potential field; path planning is carried out, when a driving vehicle falls into local optimum, auxiliary force is introduced to calculate and adjust the path, meanwhile, a distance influence factor is introduced to weaken the influence of an obstacle repulsion potential field, and obstacle speed information is incorporated into the artificial potential field model to be used for processing a plurality of dynamic obstacles; and integrating the influence of the gravitational potential field, the road boundary repulsive force field and the obstacle repulsive force potential field in the artificial potential field model to obtain the resultant force of the driving vehicle in the moving process of the highway ramp, thereby realizing path planning.

The invention belongs to the technical field of geophysical exploration, and provides a boundary identification and fracture feature determination method, device, equipment and medium, and the method comprises the steps: obtaining the analysis signal vertical guide number of a gravity and magnetic anomalous body; a tilt angle technology and a Laplacian equation are used for analyzing a vertical guide number of the analytic signal, and a boundary position is determined by calculating a difference perpendicular to a signal gradient direction; identifying the position and shape features of the gravity and magnetic anomalous body boundary to obtain fracture features; calculating analytic signals and curvatures of a gravity and magnetic anomaly field and an upward extension field of the gravity and magnetic anomaly body, and quantitatively extracting the top surface depth and the structure index of the boundary of the gravity and magnetic anomaly body to obtain the property of the fracture feature; according to the method, the Laplacian equation is introduced to deeply analyze the vertical guide number of the analysis signal, and only the first-order vertical guide number of the potential field needs to be calculated, so that the influence of high-frequency noise is reduced to a certain extent, and a basis is provided for subsequently determining the boundary position of the gravity and magnetic anomalous body.

The application relates to the technical field of cable detection, in particular to a method and system for detecting the thickness of the insulation layer of a cross-linked insulation cable. The method comprises the following steps: obtaining a cable cross-section image and performing region segmentation to identify three topologically connected domains and extract inner and outer boundaries; establishing a physical field model and applying a first type of boundary condition; solving a Laplace equation in the insulation layer region to generate a convergent scalar potential field; performing differential operation on the scalar potential field to obtain a gradient vector field, searching for gradient modulus extreme points on virtual equipotential lines to mark the thinnest and thickest feature points; taking the thinnest feature point and the thickest feature point as starting points, respectively performing streamline tracing along positive and negative gradient directions, and calculating the sum of path lengths to obtain the minimum thickness of the insulation layer and the maximum thickness of the insulation layer respectively. The application eliminates noise by solving the Laplace equation, quickly locates by using the gradient modulus extreme value, and significantly improves the detection accuracy.

The invention belongs to the technical field of artificial intelligence and computer vision, and particularly discloses a track refining method based on a learnable potential energy field and physical dynamics, and the method comprises the steps: obtaining observation features and a rough track; on the basis of a physical LNN refining module, a PhysicsLNNCell simulating physical dynamics is used for refining the rough trajectory; and finally refining the track. According to the method, physical PhysicsLNNCell inspired by physical dynamics (Euler-Lagrange equation) is adopted to replace a standard RNN or a black box LNN, and a trajectory refining process is simulated in an interpretable manner; a refinement process is modeled as a physical system jointly driven by an internal correction force (from a learnable potential energy field) and an external traction force (from a rough trajectory), and model interpretability is provided while high precision is achieved.