85 results about "Bidirectional search" patented technology

The invention relates to the technical field of path planning, and discloses a real-time path data planning processing method and system based on SLAM. The method comprises the following steps: performing semantic-geometric joint feature extraction through a laser radar and an RGB camera to obtain joint observation data; performing covariance propagation on the SLAM state vector based on semantic constraint Kalman filtering to obtain a positioning covariance and a covariance ellipse; performing constraint propagation on the semantic object set to generate virtual feature points to construct an enhanced feature map; environment grid safety scoring is carried out according to the semantic risk weight and the obstacle distance; semantic cost and SLAM uncertainty processing is carried out through bidirectional A * search, and a real-time navigation path is generated. According to the method, the technical problem of insufficient comprehensive consideration of semantic security constraint and positioning uncertainty in real-time path planning based on SLAM in a feature sparse environment is solved.

The invention discloses an outdoor robot path planning method based on improved bidirectional A * and DWA algorithms. The method comprises the following steps: step 1, A * algorithm improvement; step 2, DWA algorithm improvement; step 3, algorithm fusion; step 4, path planning; the dynamic weight DOMW strategy is introduced into the A * algorithm to optimize a heuristic function, multiple factors are comprehensively considered, path planning is more reasonable, the algorithm calculation amount and search time are reduced by removing redundant nodes, the algorithm efficiency is improved, a bidirectional search mechanism is adopted, and the algorithm efficiency is improved. The search efficiency is improved, the search space is reduced, a local optimal solution is avoided, the robustness of the algorithm is enhanced, the path is smoothed by adopting a Bezier curve optimization strategy, so that the path meets the actual motion requirement of the robot, the damage to hardware is reduced, and the attractiveness and readability of the path are improved; by optimizing a DWA algorithm trajectory evaluation function and speed space constraints, the collision risk is reduced, and local obstacle avoidance and operation stability are improved.

The invention provides a comprehensive scene map path planning method based on an improved A * algorithm, and the method comprises the steps: 1, carrying out environment modeling for a comprehensive scene map: segmenting a two-dimensional plane scene into more than two square grids, and carrying out the assignment of a single grid in a binarization manner to represent the occupation condition of the grids; constructing a protection area formed by a single-layer grid around the obstacle, and filling the protection area into gray; step 2, planning a path by adopting an improved A * algorithm: step 2-1, establishing an improved bidirectional search strategy; step 2-2, establishing a heuristic function with a barrier linear density weight; step 2-3, adopting a variable neighborhood node expansion mode to complete node expansion; and step 2-4, carrying out path secondary optimization. According to the method, the planning efficiency and the path performability in a complex environment are remarkably improved, and an effective solution is provided for navigation systems in the fields of service robots, intelligent warehousing and the like.

The invention relates to the technical field of unmanned aerial vehicle trajectory planning, in particular to a bidirectional tree random search method based on a complex environment node cost function, which comprises the steps of surveying obstacle data in a flight area and modeling, then introducing a target deviation strategy and a bidirectional search tree mechanism, and combining with an improved minimum cost method to obtain a random search result. Alternately expanding the two trees to generate an initial path, and integrating the path length, the obstacle distance and the flight height energy consumption by a cost function; and finally, pruning the initial path, removing redundant nodes, smoothing the trajectory by adopting a cubic spline interpolation method, ensuring curvature continuity, and generating an optimal path meeting the flight performance of the unmanned aerial vehicle. According to the invention, through an improved bidirectional minimum cost fast expansion random tree algorithm, dynamic association of obstacle constraint, target deviation and path cost in unmanned aerial vehicle path planning in a complex environment is represented, and a more efficient search convergence speed and better path quality are obtained. And rapid convergence and global optimization of the track of the unmanned aerial vehicle in a high-dynamic environment are realized.

The invention discloses a maritime unmanned aerial vehicle path planning method, which belongs to the technical field of path planning and comprises the steps of defining a three-dimensional grid map, preliminarily planning a path, optimizing the path and navigating the path. According to the scheme, bidirectional search is carried out through double search trees, the dynamic offset probability is calculated according to the obstacle density, the sampling point is generated, the nearest neighbor node is found, the gravitation of the target point, the repulsive force of the obstacle and the environmental force of the sea wind are combined to obtain the expansion resultant force, and then the adaptive expansion step length is obtained by combining the obstacle density. New nodes are generated and collision detection is carried out, and double search trees are connected to obtain an initial path, so that the efficiency, adaptability and safety of path planning are remarkably improved; according to the method, the Euclidean distance, the energy consumption value and the environment threat value are weighted and combined to obtain a comprehensive evaluation value of a path segment, an optimal jump node is selected for pruning, cubic spline interpolation smoothing processing is carried out to obtain a final path, and the flight requirement of the marine unmanned aerial vehicle can be better met.

The invention discloses a path planning method and system for a mobile robot, and relates to the technical field of path planning methods, and the method comprises the steps: determining a path planning model based on optimized point cloud data, environment complexity and the resolution of a visibility graph; in the determination of the path planning model, the optimized path is determined based on the two-way search of the starting point and the end point, the accuracy of the path planning model is ensured, rapid and accurate path planning is realized based on the two-way search of the starting point and the end point, and the accuracy of the optimized path is ensured. Collecting a plurality of path nodes, and dynamically optimizing each path node; according to the method, the obstacle features are collected according to detection of the optimized path, adaptive filtering is performed on the obstacle features, dynamic optimization of the path nodes and adaptive filtering of the obstacle features are compatible, so that the obstacles which have small influence on path planning can be adaptively filtered, and the calculation burden of path planning can be remarkably reduced.

The invention discloses a robot path planning method based on bidirectional beetle antennae search, and relates to the technical field of path search. The method comprises the following steps: S1, obtaining an obstacle, a feasible region, a starting point and an ending point, and forming an environment model; s2, placing a first long-horned beetle at the starting point, placing a second long-horned beetle at the terminal point, and enabling each long-horned beetle to always move towards the other long-horned beetle based on a beetle search algorithm to obtain a planned path; two-way search is carried out by placing a longhorn beetle at each of the starting point and the ending point, so that the speed of finding a feasible solution is increased, and the path planning efficiency is improved.

The embodiment of the invention discloses a moving body track planning method and device, electronic equipment and a storage medium, and relates to the technical field of track planning, and the method comprises the steps: carrying out the geometric boundary expansion and minimum distance detection of a moving body, and obtaining the environment complexity of a starting point and an end point of the moving body, the method comprises the steps of obtaining an initial trajectory and constructing kinematic constraints based on a mixed A * algorithm of a bidirectional search strategy, constructing a safety corridor based on the initial trajectory to obtain obstacle avoidance constraints, calculating environment complexity of each trajectory point according to the safety corridor, classifying the trajectory points to obtain sampling time constraints, and obtaining final constraints according to the constraints. Using the initial trajectory as an initial solution to obtain a planned trajectory, performing transverse and longitudinal decoupling on the planned trajectory to respectively obtain transverse and longitudinal state equations, and performing tracking control on the moving body by adopting a model predictive control (MPC) algorithm. According to the method, the problems of low calculation efficiency, infeasible trajectory planning result and poor optimization process convergence in the prior art are solved.

The invention discloses a global path planning method for a power converter valve inspection operation robot, and the method comprises the steps: obtaining the spatial point cloud data of a converter valve region through a three-dimensional structured light camera, and constructing a two-dimensional environment map containing obstacle expansion information through projection and rasterization; generating a snakelike or spiral full-coverage global theoretical path according to the scanning step length of the camera; in the inspection execution process, the feasibility of the path section is judged through discrete sampling and continuous collision detection; local obstacle avoidance adopts an improved A * algorithm, forward and backward bidirectional search is simultaneously executed in a limited local search area, and a dynamic heuristic function of a coverage potential item and a safety score item is introduced. And finally, splicing the local path and the theoretical path to form a global feasible inspection path. The method effectively solves the problem that the coverage rate and the obstacle avoidance efficiency are difficult to consider in a complex converter valve hall environment in a traditional method, and is particularly suitable for automatic inspection of equipment-intensive scenes such as an electric power converter valve hall.

The invention provides a robot safety interaction path planning method based on a dynamic danger criterion and bidirectional search, and the method comprises the steps: introducing the dynamic danger criterion in a planning stage, carrying out the quantification of a potential collision risk between a robot and a person, and comprehensively considering the inertia and rigidity of the robot, and the influence of the relative distance between the robot and the person; in combination with forward global search and reverse local search, a safe path is quickly generated in a complex environment. The forward search preferentially reduces danger indexes, the reverse search reversely avoids obstacles from a target position, the path continuity is ensured through an attitude potential energy function, and the local convergence problem of a traditional planning algorithm in an obstacle dense area is solved; the system also combines a real-time monitoring and safety control module, fuses a danger criterion, an obstacle potential field and a target potential field, and supports online path optimization in a dynamic environment so as to ensure that the robot can be always in a safe state in a final interaction process.

The invention relates to the technical field of artificial intelligence, in particular to an operator fusion method, device and equipment and a computer readable storage medium, and the method comprises the steps: determining whether a to-be-split current node and an upstream node which are different in data arrangement type and are directly connected exist in a computational graph or not; if yes, performing downstream one-way search by taking the current node as a starting point to construct a first sub-graph containing a first associated node, and performing two-way search by taking the upstream node as a starting point to construct a second sub-graph containing a second associated node; taking the first sub-graph and the second sub-graph as a new calculation graph, and performing iterative detection until no direct connection node with different data arrangement exists; and if a plurality of first sub-graphs exist, combining the first sub-graphs with the same graph attributes to obtain a third sub-graph so as to realize operator fusion. The invention aims to improve the efficiency of operator fusion.

The invention provides a chemical safety emergency dispatching command method and device, and belongs to the technical field of chemical safety emergencies, and the method comprises the steps: obtaining the operation state information of chemical production equipment and the real-time information of an emergency resource point; determining hidden danger factors of different position nodes in the chemical production network according to the operation state information, and further determining corresponding emergency resource types; modeling the chemical production network into a weighted graph; the hidden danger nodes are used as starting points, corresponding emergency resource types are used as constraints, layer-by-layer outward expansion is carried out according to network levels, bidirectional search is carried out from the hidden danger nodes and resource nodes, and edge weights are dynamically updated; determining response time according to the edge weight, optimizing the resource matching degree, the response time and the resource quantity as a multi-objective function, and generating an optimal path set; and performing scheduling command based on the optimal path set. Therefore, emergency resources can be ensured to arrive at an accident site at the fastest speed, and reasonable distribution and efficient utilization of the emergency resources are ensured.

The application belongs to the technical field of mechanical arm motion planning, and provides a kind of adaptive sampling and multi-channel expansion mechanical arm path planning method, first, the environment obstacle set is constructed, the point to obstacle distance, the clearance configuration and the segment level minimum clearance are established, and the unified safety criterion is constructed;Subsequently, according to the approximation state of bidirectional search tree, the sampling window is adaptively updated, and the random reference sample is generated in combination with the stagnation detection mechanism;On this basis, the hierarchical multi-channel expansion mechanism of direct pointing expansion, bypass expansion, potential field wall expansion and global bottom expansion is used to generate candidate new nodes;When a feasible new node is generated, it is connected to the current search tree and real meeting detection is carried out, if the double trees are successfully connected, path backtracking, splicing, simplification and full path safety review are further executed, and the final executable path is output.The application can improve the safety, search efficiency and environmental adaptability of the path planning of the mechanical arm in the complex limited environment.

The application discloses a kind of global path planning methods for power converter valve inspection operation robot, obtains the spatial point cloud data of converter valve area using three-dimensional structured light camera, constructs two-dimensional environment map containing obstacle inflation information by projection and rasterization;According to the snake shape or spiral shape global theoretical path of full coverage generated by camera scanning step;During inspection execution, the feasibility of path segment is judged by discrete sampling and continuous collision detection;Local obstacle avoidance uses improved A* algorithm, simultaneously executes forward and backward bidirectional search in the limited local search area, and introduces the dynamic heuristic function of coverage potential item and safety score item.Finally, the local path and theoretical path are spliced, and the global feasible inspection path is formed.The application effectively solves the problem that the coverage rate and obstacle avoidance efficiency of traditional method are difficult to consider under complex converter valve hall environment, and is especially suitable for automatic inspection in equipment-intensive scenes such as power converter valve hall.

This application provides a warehouse picking method, device, electronic device, and computer-readable storage medium, relating to the field of warehouse picking. The method includes obtaining an order for goods to be picked; the order for goods to be picked includes at least one type of goods to be picked; performing a bidirectional search based on the warehouse location information of the goods to be picked to generate a picking plan path; the picking plan path is a shortest path that passes through all the goods to be picked in the order for goods to be picked; and picking the goods to be picked in the order for goods to be picked according to the picking plan path. This application can significantly shorten the picking path and improve picking efficiency.

The invention discloses an RT-RRT * global path planning method based on L2 greedy sampling, and belongs to the technical field of automatic driving vehicle path planning. According to the method, the problems of long time consumption and low convergence speed of path search in path search by the existing method are solved. According to the bidirectional search framework disclosed by the invention, two independent search trees are simultaneously constructed from a starting point and a target point to explore a state space, an L2 greedy sampling set is designed, and a small elliptical sampling region is defined around a state with the maximum heuristic estimation cost in a current solution path; according to the method, an L2 greedy sampling set is introduced to guide the search direction of two trees, so that the overall convergence speed of the algorithm can be increased, and the problems of long time consumption and low convergence speed of path search of an existing method are solved. And in combination with road environment constraints, obstacle constraints and a new node expansion strategy, the safety and smoothness of the planned path are enhanced. The method can be applied to path planning.

The invention belongs to the technical field of robot path planning, and particularly relates to a sampling optimal path planning method fusing adaptive heuristic and symmetric bidirectional search, which comprises the following steps: based on an improved EIT * algorithm, realizing symmetric bidirectional search by constructing a quadruple structure of a forward tree, a forward inertia tree, a reverse tree and a reverse inertia tree; in the random geometric graph approximate construction stage, an elliptical information set is adopted to limit a sampling area, and bidirectional edges are defined by connecting radius r or k neighbors; a middle encounter strategy is adopted, so that forward inert search and reverse inert search meet in the middle and share heuristic information, and the search efficiency is improved; the forward search and the reverse search respectively utilize heuristic information provided by inert search of the opposite side to carry out path exploration, the total cost is calculated after meeting and is continuously optimized, and finally an optimal path is obtained through pruning; according to the method, the initial solution obtaining speed is effectively increased, the path quality is improved, and a higher planning success rate is shown in a complex environment.

The invention relates to a quick single-source path-finding algorithm based on bidirectional search, and belongs to the technical field of robot path planning. Aiming at the problems of path congestion and deadlock and poor dynamic adaptability in AGV path planning in warehouse logistics, the invention provides a bidirectional collaborative search mechanism: reversely executing a Dijkstra algorithm from a target point to pre-calculate the cost of the shortest distance from each node to the target, and selecting a node dynamic expansion path with the minimum comprehensive distance and steering cost in real time in combination with forward search; the path to the target point can be quickly generated by quickly combining the information obtained by the reverse search with the state of the AGV during the forward search. According to the algorithm, the next node is generated in real time during AGV movement, the turning frequency is reduced, and the real-time performance and efficiency of path planning in a complex environment are improved.

The application provides a Chinese-oriented named entity recognition method and system, and belongs to the technical field of natural language processing; comprising: an encoding stage step, context encoding of input Chinese text; a feature extraction stage, a double-branch structure of global semantic branch and local boundary branch in parallel is adopted, wherein the local boundary branch carries out boundary feature enhancement through multi-granularity convolution combined with a learnable Gaussian Laplacian operator; a feature fusion and prediction stage step, global and local features are fused through a gating mechanism, and multi-label classification prediction is carried out based on a preset six-tuple grid label system; a decoding stage step, named entities are obtained through bidirectional search strategy decoding according to predicted relationship probability; through boundary perception feature extraction and enhanced label system, the recognition accuracy and recall rate of nested entities and discontinuous entities in Chinese text are significantly improved.

The invention discloses a sequencing data assembly method based on a reference genome, and belongs to the technical field of biological information. According to the method, the problems that the error rate of an existing assembling method is high and the integrity of an obtained assembling result is insufficient under the condition of ultra-low coverage are solved. According to the method, two comparison methods of a read segment and a linear reference genome and a read segment and a generic genome graph are adopted, a comparison tag graph is constructed on the basis of comparison results, then chromosome classification results of nodes in the comparison tag graph are further updated on the basis of bidirectional search and translocation variation detection, and then chromosome classification results of all the read segments are obtained. And finally, according to the chromosome classification result of each read, clustering each read into different chromosome sub-boxes, assembling the read in each chromosome sub-box, and combining the assembling results in each chromosome sub-box to generate a final genome assembling result. The method can be applied to sequencing data assembly.

The invention provides an aero-engine strong non-stationary cross frequency signal time-frequency analysis method and system, and relates to the technical field of aero-engine signal processing and fault diagnosis, and the method comprises the steps: obtaining a vibration signal, and obtaining initial time-frequency distribution; performing adaptive ridge line extraction on the initial time-frequency distribution, and determining a time-frequency block range of an intersection region; carrying out local sub-blocking on the time frequency distribution in the intersection area to obtain optimized time frequency distribution; performing component reconstruction on the vibration signal by adopting Vold-Kalman order filtering to obtain final time frequency distribution; according to the method, the ridge line fracture time-frequency block is determined through bidirectional retrieval repair, the intersection area and the hierarchical cascade reconstruction component are optimized through comprehensive evaluation indexes, the ridge line continuity and instantaneous frequency extraction precision of the intersection area are remarkably improved, and high-resolution representation and accurate separation of strong non-stationary intersection frequency signals are achieved.

The invention discloses a digital low dropout linear regulator based on improved successive approximation logic, which comprises a comparator, an MOS (Metal Oxide Semiconductor) transistor array, an improved successive approximation logic control module, a sampling-holding dynamic comparator, an analog-to-digital converter and a transient detector, a PMOS (P-channel Metal Oxide Semiconductor) transistor array is arranged in the analog-to-digital converter and has a comparison state and a PMOS transistor array state; the improved successive approximation logic control module is used for controlling the state switching of the analog-to-digital converter, whether the sampling-maintaining dynamic comparator works or not and the internal on-off state of the MOS tube array; the improved successive approximation logic control module has an estimation binary search mode, a reverse binary search mode, a bidirectional search mode and a freezing mode; the circuit has the advantages that the precision of output voltage is high, the circuit can be used for a high-precision on-chip power supply, the transient response speed is not limited by the scale of the MOS tube array, the transient response speed is high under any scale of the MOS tube array, obvious overshoot and undershoot phenomena cannot be caused, and the stability of the output voltage is high.

This invention provides a path planning method for industrial robotic arms based on potential field perception and experience-based adaptation, relating to the fields of robot motion planning and intelligent manufacturing technology. Based on the path planning framework of the RRT-Connect algorithm, this method constructs a bidirectional search tree within the search space. It uses the calculated safety margin of the direction-aware space as the initial environmental safety margin for nodes, employs an artificial potential field lateral deflection direction guidance strategy to determine the expansion direction, and uses a parameter adaptive adjustment method with a clearly bounded mapping relationship to adaptively determine the node expansion parameters based on the environmental safety margin of the parent node. This achieves efficient and stable collision-free path planning in complex assembly environments. This method is applicable to path planning problems for multi-degree-of-freedom industrial robotic arms and can significantly improve path planning efficiency and path quality in complex assembly environments.

The invention discloses a synchronous positioning method and system based on multi-channel sound source and panoramic image fusion, and particularly relates to the technical field of target positioning, and the method comprises the following steps: collecting an audio and a panoramic image, embedding a unified time stamp, calculating the credible parameter value of each frame of sound source and image, and calculating the credible parameter value of each frame of sound source and image; if the frame is lower than the threshold value, searching an adjacent frame and estimating or marking the frame as a failure frame; effective frames are input into a fusion proportion control model, registration and weighted synthesis are executed to obtain positioning coordinates, and a movement track is generated according to a time sequence; and finally, calculating a failure ratio, setting a grade identifier, and correspondingly executing acquisition restart, threshold adjustment or model replacement strategies. According to the method, modal alignment is realized through audio and image signal time stamps, and the fusion positioning accuracy is improved; a low-credibility frame is stably processed by adopting an interpolation strategy based on bidirectional search, and the positioning continuity is enhanced; and realizing stable operation and dynamic adjustment capability of the system by fusing proportion self-adaptive adjustment and combining a failure frame proportion setting grade strategy.

The invention relates to the technical field of data storage and processing, and discloses an equity penetration method based on bidirectional search, a terminal and a storage medium. The method comprises the following steps: constructing an equity graph structure: constructing a directed graph based on original stock holding data; the vertex set represents an institution entity, and the edge set represents a stock holding relationship between institutions; the weight of the edge in the stock right graph represents the stock holding proportion between the institutions, and timestamp information is added to the edge to record the timeliness of the stock holding relation; image structure cleaning: deleting unweighted edges in the stock right image, and detecting and eliminating cyclic stock holding; for any given starting point and end point in the stock right graph, initiating forward search from the starting point to obtain a forward path, initiating reverse search from the end point to obtain a reverse path, and when the forward search and the reverse search intersect at one vertex, merging the reverse paths of the forward path and the reverse path to obtain a forward path and a reverse path; and thus, a complete strand-holding link is obtained. According to the invention, stock right penetration between institutions can be effectively realized.

The invention discloses a multi-unmanned-ship task allocation method based on starfish behaviors, and the method is suitable for solving the task allocation problem of multiple unmanned ships in cooperative operation, and especially has important application in the aspect of cooperative obstacle breaking of non-cooperative targets. The method comprises the following steps: firstly, randomly generating a position matrix of each starfish in an initialization stage and calculating fitness, then updating the positions of the starfishes by adopting different search modes according to the dimension of a problem, ensuring that the updated positions of the starfishes are within the boundary of a design variable, and updating the positions of the starfishes in predation and regeneration stages by utilizing a parallel bidirectional search strategy, and finally, outputting a globally optimal solution, and applying an optimization result to the cooperative obstacle breaking task of the unmanned surface vehicle, thereby improving the task execution efficiency and cooperative combat ability of the unmanned surface vehicle in a complex environment.

This invention discloses a collaborative operation system and method for a drone and a robotic dog in a mining scenario. The system includes a drone, a robotic dog, and a wireless communication module. The drone and the robotic dog transmit data through the wireless communication module. The drone includes a laser terrain scanner, and the robotic dog is equipped with a high-definition camera and an infrared sensor. The laser terrain scanner is used to perform a global terrain scan of the mining blasting area to obtain laser point cloud data. The high-definition camera is used to identify obstacle elevation values, and the external sensors are used to collect road slope data. This invention utilizes a bidirectional BFS search algorithm combined with adjacent grid selection weights and priorities to generate multiple planned paths. The drone sends the planned paths to the robotic dog in advance, and the robotic dog only needs to select the optimal path based on the actual road conditions. The lightweight MobileNet model improves the robotic dog's computation speed and time, and the selection of the optimal path based on actual road conditions requires low hardware computing power.

The application discloses a substation secondary circuit path identification method, device, equipment and medium, and belongs to the field of power systems, the method is: obtaining the first connection relationship of each screen cabinet and each element to construct the first connection relationship matrix, determining the simplified judgment result according to the element quantity and the connection density corresponding to the screen cabinet and simplifying the first connection relationship matrix to obtain the second connection relationship matrix, and then performing bidirectional search in the second connection relationship matrix according to the positive power supply node and the negative power supply node by using a bidirectional depth-first search algorithm to obtain the secondary circuit path, so that the problem of low path identification efficiency of the substation secondary circuit in the prior art can be solved by implementing the application.

The invention provides a path planning method and system for personnel evacuation and obstacle avoidance, and belongs to the technical field of personnel evacuation dynamic obstacle avoidance path planning. The invention provides a Bi-RRT *-based personnel evacuation path planning algorithm with self-adaptive bias and a new improved self-adaptive extended step length. On the basis of the standard Bi-RRT * algorithm, an adaptive bias strategy which is jointly influenced by search experience and obstacles is added, so that the convergence speed of the algorithm is effectively improved, the path search efficiency is improved, and the ability of passing through narrow terrains is improved; based on a self-adaptive step length search strategy combining the repulsion size and the direction included angle, the obstacle avoidance capability is improved; in combination with improved adaptive bias, adaptive step length and bidirectional search capability, the adaptive capability to a complex evacuation space search path and the search efficiency of a multi-obstacle region algorithm are effectively improved. The method has remarkable advantages in the aspects of path planning efficiency, path quality, convergence speed, complex environment adaptability and the like.

The invention relates to the technical field of three-dimensional laser point cloud data processing, in particular to a building contour extraction method based on point cloud hierarchical projection and geometric constraint, which comprises the following steps: slicing a single building point cloud in the vertical direction to obtain a sliced point cloud; projecting the slice point cloud to a plane; performing straight line fitting and segmentation on the slice point cloud projected to the plane to obtain a plurality of line segments; wherein straight line fitting and segmentation are carried out, rough fitting is carried out firstly, then segmentation is carried out, and fine fitting is carried out on the segmented point cloud; screening line segments perpendicular to or parallel to the main line through geometric constraint; according to the screened line segments, removing parallel line segments of the same edge to obtain a non-redundancy line segment set; and connecting the line segments in the line segment set through a bidirectional search connection mechanism and a differentiated closing strategy, and performing closing, smoothing and regularization processing to obtain the building contour. According to the scheme, the building contour line can be efficiently and accurately extracted, and the method is suitable for practical engineering application.