39 results about "Area coverage" patented technology

The application relates to the technical field of intelligent control of engineering machinery, and provides a tower crane hoisting whole-process dynamic mapping and perception coverage method and system. The method comprises the following steps: installing two rotating radars on rotatable supports of a tower crane; acquiring a current hoisting operation stage of the tower crane in real time; switching the shooting angles of the two radar modules according to the hoisting operation stage, and controlling the two radar modules to acquire continuous point cloud data of the corresponding operation stage; collecting tower crane operation parameters, combining the continuous point cloud data acquired by the two radar modules to generate a continuous hook trajectory; identifying dynamic obstacles and static backgrounds contained in a target monitoring space from the continuous point cloud data, and constructing a construction environment point cloud model; performing space-time registration on the construction environment point cloud model and a physical coordinate system, and establishing a global dynamic map; fusing the continuous hook trajectory and the global dynamic map to construct a dynamic perception area coverage map, and realizing real-time perception of the space environment of the tower crane hoisting operation.

The application provides a full-area coverage path planning method and device for a mowing robot, a terminal and a medium. The method comprises the following steps: abstracting an environment map by setting a virtual boundary line of one or more target mowing areas; determining a long-axis direction of a bow shape for each target mowing area and rotating each target mowing area; dividing the one or more target mowing areas into one or more sub-areas based on the boundary points of the rotated target mowing areas; performing path planning for each target mowing area based on the long-axis direction of the bow shape of the target mowing area; and connecting the bow-shaped paths of the target mowing areas based on a navfn algorithm to obtain a full-area coverage path corresponding to the environment map. The application can realize full-area coverage path planning, has a high coverage rate even for a complex mowing area, has a low repetition rate, and greatly increases the path planning efficiency of the mowing robot.

This invention relates to a multi-satellite joint regional coverage planning method based on an improved multi-objective evolutionary algorithm, comprising the following steps: decomposing the area to be covered into discrete strip sets of all remote sensing satellites based on the imaging conditions of each satellite; binary encoding the strips in the discrete strip sets, using all encoded individuals as input to the improved multi-objective evolutionary algorithm, which employs a combination of the NSGA-III and S-CDAS algorithms to achieve an extreme solution preservation mechanism; constructing a multi-objective optimization model composed of multiple objective functions, and solving the multi-objective optimization model using the improved multi-objective evolutionary algorithm to obtain the regional coverage result. The improved multi-objective evolutionary algorithm in this invention can preserve extreme solutions, thus achieving satisfactory regional coverage results, and can also optimize the rationality of the regional coverage scheme from other objective dimensions.

The invention provides a message relay forwarding method based on vehicle-road cooperation, and aims to solve the problem that RSU (road side unit) or OBU (on-board unit) cannot effectively receive target information due to shielding, signal interference and other factors. The method comprises the following steps: firstly, comprehensively evaluating the communication quality of peripheral communication equipment to obtain key indexes including signal strength (RSSI), signal-to-noise ratio (SNR), bit error rate (BER) and the like; and screening out a reliable vehicle list of which the communication quality meets the requirement based on an evaluation result. And then, a K-means clustering algorithm is adopted to perform clustering processing on surrounding reliable vehicles, and a clustering number range (such as 1-K) is limited, so that the effectiveness and coverage rationality of a clustering result are ensured, and over-scattered vehicle distribution is avoided. In each cluster, a vehicle located or closest to the cluster center is selected as a relay node, and the relay node broadcasts target information, so that message diffusion in each cluster coverage area is efficiently realized. According to the mechanism, the area coverage capability and the service reliability of the target information are remarkably improved.

This invention provides a method for optimizing unmanned surface vessel (USV) area coverage paths based on constrained reinforcement learning, belonging to the technical field of autonomous navigation and path planning for marine unmanned systems. Each USV acts as an intelligent agent, and the USV area coverage path optimization problem is modeled as a constrained Markov decision process. The constraint condition is that the difference between the optimized path and the planned path is within a preset area. The reinforcement learning framework consists of: a policy network outputting an action probability distribution based on the current environmental state; a reward evaluation network evaluating the expected rewards of states and actions; and a cost evaluation network evaluating the expected cumulative cost of state-action pairs. With the goal of maximizing policy entropy and expected rewards, the penalty strength of the cost constraint is dynamically adjusted using Lagrange multipliers, jointly optimizing the policy network, reward evaluation network, and cost evaluation network. The minimum coverage requirement is modeled as a hard constraint condition for policy optimization, ensuring navigation safety and the integrity of the mission area coverage.

This invention relates to a method, device, and medium for multi-agent coverage search and task allocation path optimization. The specific method includes: scenario construction and problem description, which describes the characteristics of the task area, the attributes of agents and targets, and clarifies the area coverage search problem and the target task allocation problem; area coverage model design, which establishes a minimum task time model objective function and constraints, and then solves the area coverage model; and task allocation strategy and path planning algorithm, which, considering agent speed and target attributes, combines a greedy strategy and a genetic algorithm to allocate target exploration tasks to agents, optimize target exploration paths, and reduce total task time. Compared with existing technologies, this invention improves the efficiency of marine area search and target exploration through multi-agent cooperation, achieving full area coverage search and accurate target exploration.

The invention provides a high-precision troposphere delay modeling method, device and equipment under a sparse GNSS (Global Navigation Satellite System) site, and belongs to the technical field of spatial scientificity, and the method comprises the steps: calculating an initial ZTD (Zero Time Division) value of a real GNSS site through a first preset empirical model, constructing a ZTD residual time sequence by combining a GNSS actually measured ZTD value, analyzing a periodic signal, constructing a residual model to obtain a ZTD residual, and calculating the ZTD residual according to the ZTD residual. Further obtaining a ZTD improved value of the GNSS real station; based on a second preset empirical model in which an error correction term is introduced, virtual sites are arranged in the sparse region, and ZTD values of the virtual sites are generated; performing weighted fusion on the real and virtual ZTD values through a variance component estimation method to obtain a unified ZTD observation data set; and adopting spherical crown harmonic analysis to solve the adaptation coefficient, constructing a continuous ZTD model, outputting full-region data, and generating a high-resolution and high-precision ZTD map. According to the method, the defect that sparse GNSS station data coverage is insufficient is effectively overcome, and troposphere delay modeling precision, space continuity and area coverage integrity are remarkably improved.

The invention discloses a visual marking method and equipment based on fusion positioning, and a medium, belongs to the technical field of airport scene monitoring and management, and aims to solve the problems that the recognition accuracy is reduced, the high computing power requirement is needed, the real-time monitoring adaptability is poor, and the recognition efficiency is high due to the fact that existing airport scene monitoring is easily shielded by vision. And accurate geographical location information is difficult to obtain. The method comprises the following steps: performing coverage calculation of a maximum monitoring area on a visible area on an airport map to obtain a polygonal visible area; acquiring positioning terminal signals of key equipment and workers in an airport range; carrying out conversion processing of related camera point locations on a real-time geographic coordinate system in the real-time position information to obtain a camera coordinate system; performing conversion processing on the camera coordinate system to obtain a two-dimensional image coordinate system; mapping the two-dimensional image coordinate system into a polygonal visible area; and performing shielding labeling display on part of shielding targets in the initial labeling display information to obtain fused labeling display information.

The invention belongs to the technical field of collaborative interception guidance, and particularly relates to a bias differential game collaborative interception method based on region coverage. The method comprises the steps of establishing a probability distribution model of a target in an interception plane, performing Monte Carlo sampling, and converting a coverage strategy design into an optimal coverage problem of a finite center point in the interception plane; segmenting, iteratively solving the standard maneuver of each interceptor through a Voronoi diagram method to obtain the standard maneuver aTsi of each interceptor; and based on the standard maneuvering aTsi of each interceptor, deploying to a corresponding optimal array position and carrying out offset item design of a differential game guidance law to jointly realize the offset of the coverage range of each interceptor, and finally completing the optimal coverage and interception of the target. According to the method provided by the invention, the defects that an existing disc coverage model has limitation on maneuvering distribution simplification and only a fixed solution can be applied mechanically are overcome; the miss distance and the overload demand of the interceptor are obviously reduced, and the interception efficiency is improved.

This invention discloses a method for optimizing the layout of airport noise monitoring points based on a genetic algorithm. The method involves dividing the monitoring area into grids based on a noise prediction contour map; calculating the distance from any point within the monitoring area to the monitoring point; defining the probability of whether a point is covered by a monitoring point; calculating the sensing probability based on distance and monitoring point reliability parameters; establishing a joint sensing probability model and calculating the area coverage rate; setting a coverage rate optimization objective function; introducing multi-objective constraints; and using a genetic algorithm to optimize the comprehensive benefit function. A dynamic point quantity control mechanism is introduced to gradually reduce the number of monitoring points, outputting a simplified monitoring point layout scheme while maintaining the coverage rate above a set threshold. The optimization process of this invention fully incorporates the actual airport point layout constraints, reducing the number of monitoring points and prioritizing the elimination of redundant points, while maintaining a relatively stable overall coverage rate, significantly reducing equipment installation, maintenance, and data processing costs.

The invention relates to a UUV coverage path energy efficiency optimization method and an offshore surveying and mapping system, and the method comprises the following steps: obtaining a satellite remote sensing image, multi-beam sounding data and underwater topographic data of an offshore region, recognizing a sea-land boundary contour, and constructing an offshore seabed three-dimensional surveying and mapping region model; a UUV energy consumption model is constructed, a surveying and mapping area coverage rate maximization and total energy consumption minimization are taken as targets, a surveying and mapping area model is combined, an intelligent optimization algorithm is adopted to carry out global path planning, and a UUV surveying and mapping operation path is determined; the underwater environment is monitored in real time through a sensor carried by the UUV, whether an original planned path is feasible or not is judged, and when the original planned path is not feasible, local path re-planning is carried out by taking minimization of extra energy consumption as a target and adopting an improved path search algorithm. Compared with the prior art, the method has the effects of improving the accuracy and integrity of a surveying and mapping area, reducing the energy consumption of the UUV, improving the surveying and mapping efficiency and the like.

Embodiments of the present application provide a map processing method, device and self-moving equipment. The map processing method comprises: acquiring at least one of working state information of a current working process of the self-moving equipment in a working area and a real-time obstacle map, the working state information comprising at least one of positioning quality and working area coverage rate, the real-time obstacle map being obtained based on real-time images collected in a moving process; determining whether to update at least one of an original visual feature map and an original obstacle map used by the self-moving equipment according to at least one of the working state information and the real-time obstacle map, the original visual feature map being used for positioning of the self-moving equipment in the working area, and the original obstacle map being used for path planning of the self-moving equipment; if the update is needed, acquiring an image frame of the working area, and updating at least one of the original visual feature map and the original obstacle map using the image frame. The method can update the map in time.

The application discloses a kind of based on machine vision's magnetic force polishing state detection method, equipment and medium, it is related to surface processing quality control technical field, including the dynamic image of the contact area of magnetic brush and workpiece is collected, obtains the image sequence of the contact area of magnetic brush and workpiece, extracts and smooths the upper boundary of magnetic brush, constructs the time series of upper boundary disturbance rate of magnetic brush;Magnetic brush trajectory coverage heat map is constructed, under-coverage, over-coverage and normal coverage area are divided, and area coverage index is calculated;Fusion upper boundary disturbance rate time series of magnetic brush and area coverage index, construct magnetic force polishing state feature vector, train random forest model, generate real-time magnetic force polishing risk grade label, adjust magnetic field intensity, obtain magnetic brush polishing supplement point set, generate magnetic brush polishing supplement trajectory.Magnetic force polishing process is quantified tracking in real time to the disturbance state, accurately identify magnetic force polishing state and implement regional compensation, improve polishing quality and process stability.

The invention discloses a method for generating a satellite communication beam. The method comprises the following steps: acquiring boundary coordinates of a target geographic corridor and converting the boundary coordinates into satellite angular domain representation; extracting a skeleton curve of a corridor based on the angular domain boundary, and establishing a parameterized beam pattern model distributed along the skeleton curve; constructing a beam forming weight optimization problem which comprises a coverage gain constraint distributed along the skeleton curve and a continuity constraint between adjacent sampling positions on the skeleton curve; and solving the optimization problem to obtain a complex weight vector, and loading the complex weight vector to the beam forming network to drive the phased-array antenna. According to the invention, dimension reduction is carried out on a two-dimensional area coverage problem through skeleton curve modeling, and stable energy transition of a wave beam along a curved corridor is ensured by utilizing a continuous constraint explicit mode, so that the problems of difficult optimization convergence and discontinuous coverage in long and narrow non-convex area coverage are effectively solved.

The invention discloses a uranium mineralization zone identification method and system based on multi-source remote sensing data fusion, and relates to the technical field of geological exploration, and the method comprises a multi-source data obtaining module which obtains multi-platform and multi-band remote sensing data, and the remote sensing data comprises optical remote sensing data, microwave remote sensing data and auxiliary data; constructing a uranium ore zone feature database based on the remote sensing data; the data preprocessing module is used for carrying out noise elimination, atmospheric interference removal and geometric distortion correction on the remote sensing data; the feature extraction and fusion module is used for extracting uranium mineralization zone sensitive features from the preprocessed multi-source data and carrying out cross-modal fusion, and the cross-modal fusion comprises feature layer fusion and decision-making layer fusion; an anomaly detection and geological analysis module; a result output and verification module; according to the method, all-weather, total-factor and non-blind-area coverage of a complex terrain area can be achieved, the exploration range is not limited to roads and gentle zones any more, and the coverage rate of a potential metallogenic zone is increased.

The invention relates to the technical field of water surface pollution monitoring, in particular to a water surface floating object intelligent identification and path planning method, which comprises the following steps: firstly, calculating a solar elevation angle based on real-time time and a geographic position, and determining an environment illumination gear in combination with a seasonal model; and adaptively loading image processing parameters and a detection model to perform initial target identification. Afterwards, target features are extracted through a feature analyzer, difficult categories of the target features are judged, a special module is dynamically called for fine recognition, and a result set with geographic coordinates and labels is output. And calculating an operation priority based on a target category, a label and spatial distribution, and generating an operation instruction to drive the operation in combination with path planning modes such as cluster form intelligent selection point clearing, area coverage or tracking monitoring and the like. New images are collected in real time during execution and fed back to a process starting point, a complete self-adaptive closed loop of sensing, decision making, execution and feedback is formed, and the intelligence level and the operation efficiency of floating object cleaning in a complex environment are remarkably improved.

The application discloses an unmanned cleaning vehicle area coverage optimization scheduling method and system, and particularly relates to the field of environmental sanitation scheduling, and is used for solving the problems that the area to be reswept is difficult to be accurately identified, the path of the reswept task is difficult to be inserted along the way, and the service delay is difficult to be quantitatively evaluated in the scene where temporary obstacles frequently occur, and is achieved by the following steps: generating a basic label with cleaning marks and obstacle marks based on a road section, constructing a reswept area record and merging to form a reswept task path, introducing an along-the-way overlap distance ratio and a service delay offset time, calculating a task allocation priority coefficient through a pre-defined scheduling matching model, cooperatively allocating between the reswept task path and a regular cleaning task, and combining an actual cleaning trajectory to feed back and adjust the reswept area identification rule and the reswept task path generation strategy, so as to realize the closed-loop optimization scheduling of the area coverage of the unmanned cleaning vehicle.

The application provides a tilt photography-based aircraft platform site selection method, and belongs to the field of unmanned aircraft management and optimization. The technical scheme is as follows: a multi-objective optimization model is established after a semantic three-dimensional scene model and a platform site selection characteristic field are sequentially constructed by collecting original task data; and site selection output data for flight task planning are obtained after the multi-objective optimization model is solved. The application has the beneficial effects that: the application uses a semantic three-dimensional scene, introduces a geometric uncertainty field, a semantic value field and a constraint field, and realizes joint site selection through view analysis and multi-objective optimization, so that the key area coverage rate and imaging quality can be improved, and the blind area and invalid flight can be reduced under the premise of meeting airspace safety and regulations.

This invention belongs to the field of power system analysis technology, and discloses a method, system, equipment, and medium for phased state estimation of power systems. The method includes: calculating the node admittance matrix based on the power system topology and branch parameters; configuring SCADA and PMU at the corresponding nodes of the power system to construct a measurement-state Jacobian matrix H; acquiring SCADA and PMU measurement data and performing time synchronization processing on the two types of measurement data; using a GM estimator to perform nonlinear robust state estimation on the SCADA measurement data to obtain a first estimation result; combining the first estimation result with the PMU measurement data, and performing linear robust state estimation on the combined data to obtain the power system state estimation result. By performing phased and differentiated processing on the two types of measurement data, the complementary advantages of SCADA's wide-area coverage and PMU's high-precision measurement are fully utilized, significantly improving the accuracy and reliability of state estimation in mixed measurement environments.

The invention discloses a planar region coverage path generation method, computer equipment and a storage medium. The planar region coverage path generation method comprises the following steps: acquiring related parameters of a planar region to obtain a polygonal region to be planned; decomposing the polygonal region to be planned to obtain a plurality of sub-regions without obstacles; generating four kinds of scanning lines in the sub-regions; constructing a weighted graph model of which sub-regions comprise four scanning lines; according to the weighted graph models of all the sub-regions, obtaining all global scanning lines of the polygonal region; global search optimization is carried out on all the scanning lines, and a total scanning line with the shortest global total path length is obtained; and performing path restoration on the total scanning line to obtain a complete planar region coverage path generation graph. According to the planar region coverage path generation method, the computer equipment and the storage medium, better performance can be obtained when the planar region coverage path is generated.

The invention relates to a real-time area coverage method and device for medium-orbit area observation constellations, and the method comprises the steps: carrying out the subarea division of a target area, and uniformly generating sampling points and area mask vectors corresponding to the sampling points in the target area; according to the pointing information of the satellites to the target area at the current moment, obtaining a single-satellite instantaneous coverage mask vector of each satellite to the sampling point; counting the coverage multiple number of each sampling point to obtain an instantaneous multiple coverage vector; obtaining an instantaneous region coverage vector according to the instantaneous multiple coverage vector and the region mask vector; according to the instantaneous region coverage vector, calculating an instantaneous i-fold coverage proportion of the sub-region at the current moment; taking a pointing vector formed by all satellites as a decision variable, and constructing a target function according to an instantaneous i-fold coverage proportion; and solving the objective function by adopting a particle swarm algorithm to obtain an optimal pointing vector so as to realize area coverage. According to the invention, a real-time area coverage area observation task can be realized.

This application discloses a method and system for surface strengthening process identification and coverage detection, relating to the field of intelligent surface detection technology. The method involves fluorescently treating the workpiece surface to obtain a fluorescence image of the treated surface. A trained deep learning dual-branch network is then used to output the probability of the strengthening process category and the coverage of the strengthened region. The deep learning dual-branch network includes a feature extraction module, a process discrimination branch network, and a coverage segmentation branch network. The feature extraction module generates a fused feature map from the fluorescence image of the workpiece surface. The process discrimination branch network uses a convolutional block attention mechanism to obtain the strengthening process category probability from the fused feature map. The coverage segmentation branch network uses an encoder-decoder semantic segmentation network to determine the coverage of the strengthened region based on the strengthening process category probability and the fused feature map. This application enables accurate discrimination of surfaces with different strengthening processes and precise quantitative detection of coverage.

The invention provides a satellite Internet of Things system, a construction method, an application method and a storage medium, and a satellite constellation in the system comprises a perception application satellite used for collecting multi-source monitoring data and transmitting the multi-source monitoring data to a network transmission satellite; the network transmission satellite is used for transmitting the multi-source monitoring data to the calculation storage satellite; the calculation storage satellite is used for carrying out real-time preprocessing on the multi-source monitoring data and sending a data processing result to the ground station; the sensing application satellite is deployed at the top of a low earth orbit or a near space, the network transmission satellite is deployed at a middle earth orbit or a GEO adjacent orbit, the calculation storage satellite is deployed at a geosynchronous orbit, and laser links are respectively established between the network transmission satellite and the sensing application satellite and between the network transmission satellite and the calculation storage satellite. Through satellite function decoupling and reconstruction deployment, the reliability of the system is improved, wide-area coverage space complementing is realized, an emerging Internet of Things industry support is formed, and emergency communication guarantee requirements are met.

The method comprises the following steps: initializing the positions of N robots which can communicate with each other, and setting a virtual position outside the coverage area; in each iteration period, all robots move to the next target neighbor point synchronously; determining whether all robots have moved, if yes, resetting the movement state of all robots, and ending the iteration period; otherwise, determining whether there is a robot trapped in a "deadlock", if yes, releasing the "deadlock", and ending the iteration period when all robots trapped in the "deadlock" have moved to the target neighbor point. The above robot movement iteration period is repeated until the iteration number reaches a preset value or all environment areas are covered. The method can effectively respond to the change of the environment area to be covered in real time in a communication-limited obstacle-free environment, and realize complete coverage of the area at a minimum cost.

The invention discloses a region coverage discrete optimization and attitude maneuver planning method for a satellite with a rotary table, and belongs to the technical field of satellite application and observation planning. According to the method, through regional grid division and candidate strip set generation in any direction, an optimized strip capable of achieving the maximum regional coverage rate with the minimum number is obtained through integer programming modeling solution. According to the method, a two-dimensional turntable rotation angle sequence meeting pointing constraint and speed parallel constraint is planned, and a body attitude quaternion trajectory of satellite execution stripe push-broom imaging is obtained through derivation based on minimum Euler rotation. And for attitude pointing switching between strips, quaternion spherical linear interpolation is carried out on an initial quaternion and a target quaternion by designing an Euler rotation angular velocity trajectory, and a continuous rapid attitude maneuver trajectory is obtained. According to the region coverage discrete optimization and attitude maneuver planning method, generation of optimization coverage strips in any direction is allowed, region coverage attitude maneuver gaps are reduced, and observation task execution efficiency is improved.

The invention discloses a coverage rate determination method and device, equipment, a medium and a product, and relates to the technical field of communication. The coverage rate determination method comprises the following steps: acquiring 4G minimization drive test data, 5G internet public test data and 5G measurement report data corresponding to a coverage rate area to be determined; dividing the coverage rate area to be determined into a plurality of grids; determining a first grid corresponding to first longitude and latitude information in the 5G internet public test data in the plurality of grids; determining a second grid corresponding to the user terminal information in the 5G measurement report data in the plurality of grids according to the 4G minimization drive test data; and according to the first grid and the second grid, determining the 5G area coverage rate of the area with the coverage rate to be determined. According to the scheme disclosed by the invention, the accuracy of the 5G area coverage rate can be improved.

The invention relates to the technical field of radar detection, and discloses an obstacle detection method and system based on a scanning type light curtain radar. Acquiring position coordinates and distribution density information of an obstacle through a scanning type light curtain radar, and obtaining a high-density clustering position through a clustering grouping algorithm; based on the position, generating a particle set containing a clustering dynamic condition and a particle initial weight, constructing a state transition model, and combining historical scanning track data to calibrate particle distribution and correct the weight to form a weighted particle set; generating a direction deviation signal through resampling; constructing an initial angle transition path; mapping a projection intensity parameter and checking a matching degree; adjusting a transition point interval to optimize the path; according to the method, the problems of inaccurate cluster sensing, unstable angle switching and insufficient blind area coverage in traditional detection are solved, the obstacle detection precision and stability are improved, and the obstacle detection requirement in a dynamic scene is met.

The invention discloses a minute-level urban micro-meteorological wind field sparse reconstruction method based on laser radar data, and relates to the technical field of urban meteorological monitoring and data processing, and the method comprises the following steps: multi-source data collection, data processing, optimization model construction, optimization solution and result output. Through an adaptive sparse scanning strategy, intelligent data acquisition is carried out at the source, key area information is preferentially captured, the scanning time can be effectively shortened, city scale three-dimensional wind field real-time inversion of minute-level time updating and meter-level spatial resolution can be realized, a unified multi-source collaborative optimization framework is created, and the method is suitable for large-scale three-dimensional wind field real-time inversion of the city scale three-dimensional wind field. The wide-area coverage capability of a laser radar, the precision of a ground meteorological station and the macrophysical consistency of a fluid dynamic numerical simulation model are deeply fused, and advantage complementation is realized by constructing a data fidelity term and a background field constraint term. A complete three-dimensional wind field which is continuous in space, consistent in physical performance and remarkably improved in precision is obtained in the whole target area, and the anti-interference capability is high.

The present disclosure provides a map optimization method, device, electronic equipment and storage medium. The map optimization method comprises: obtaining an original map, wherein the original map comprises an exploration area, a coverage area and an obstacle area; and determining and deleting an error area in the exploration area in combination with the coverage area and the obstacle area. The scheme of the present disclosure determines and deletes the error area in combination with the points in the areas with different properties in the original map and the positioning principle thereof, optimizes the original map, makes it closer to the actual map, and enables the autonomous mobile device to perform tasks more efficiently according to the optimized map.

A method for automatically path planning for optimizing a path of a machinery moving in an area, comprises the steps of: taking coordinates of an area contour, a working width of the machinery operating in the area, a mathematical description of the dynamics of the machinery operating in the area in form of a system of nonlinear differential equations, determines segments along the headland path which are not feasible with respect to dynamics of the machinery or whose traversal would result in area coverage gaps. A mathematical algorithm is used with a hierarchical two-step framework in combination with a special coordinate transformation from a time into a spatial domain to formulate geographic high-precision constraints. The hierarchical two-step framework addresses two objectives: a generation of headland paths and a generation of smooth transitions between headland path and mainfield lanes, whereby the first hierarchical step varies for the two objectives.