810 results about "Path search" patented technology

The invention relates to the technical field of low-altitude aircraft navigation, and discloses a low-altitude aircraft track real-time planning method and system. The system comprises a flight situation awareness module, a track constraint calculation module, a real-time track planning module, a conflict prediction module and a track dynamic correction module. The flight situation sensing module generates a flight situation matrix through multi-source data fusion; a track constraint calculation module extracts static obstacle contours and dynamic obstacle tracks according to the static obstacle contours and the dynamic obstacle tracks, and generates a multi-dimensional track constraint set in combination with aircraft performance parameters; the real-time flight path planning module builds a three-dimensional flight path search domain by using an adaptive space division technology, and iteratively solves an optimal flight path sequence by using an intelligent search algorithm; the conflict prediction module combines the real-time dynamic obstacle trajectory to calculate the space-time proximity, and generates a conflict early warning map; and the track dynamic correction module re-draws an obstacle avoidance constraint area according to the map, and triggers local track correction. The system improves the comprehensiveness, real-time performance and safety of flight path planning, and guarantees the stable operation of the low-altitude aircraft.

The invention discloses a railway station facility full life cycle information query method based on digital twinning. The method comprises the steps that a unified facility object with a unique logic identifier is generated based on multi-source heterogeneous data aggregation; constructing a facility tense version model containing time sequence nodes by using an event-driven rule; in combination with an engineering constraint knowledge base and statistical characteristics, evaluating physical feasibility and statistical association strength between events, introducing life cycle stage risk factors, and constructing a facility full life cycle causal chain model; and based on the model, responding to the explanatory query, executing a constrained path search in the facility full life cycle causal chain model, and generating a life cycle query result set containing a causal path. According to the method, the pseudo-correlation problem generated by pure data mining can be effectively solved, the cumulative influence of early-stage risks in the design and construction stage on later-stage operation is quantified, and accurate tracing and explanation of cross-stage fault causes are realized.

The invention provides an electric power inspection path planning method and device and electronic equipment, and relates to the technical field of unmanned aerial vehicle electric power inspection. The method comprises the following steps: acquiring obstacle information of an electric power facility environment, wherein the obstacle information comprises the type and position of an obstacle; based on the type of the obstacle and a preset safety distance coefficient, determining a differentiated safety distance, the type of the obstacle including a power transmission line, a transformer substation, a tower and other obstacles; based on the obstacle information and the differentiated safety distance, obtaining an initial global path through a path search algorithm; based on a preset multi-objective optimization function, the initial global path is optimized, a Pareto optimal path set is generated, and the multi-objective optimization function comprises a path length objective, a safety margin objective and an electromagnetic safety objective; and determining a target global path from the Pareto optimal path set based on a preset inspection task mode. According to the invention, the inspection efficiency and adaptability can be improved while the safety is guaranteed.

The invention discloses a branch topological structure automatic switching control method and system based on load balancing, and relates to the technical field of automatic switching control, and the method comprises the following steps: obtaining working condition data, and constructing a joint map; extracting a power conduction path from the trunk node to each load node based on the joint map to form a high-load segment set; aiming at the high-load transmission segment, constructing a multi-target switching feasibility set, and generating a coupling relation mapping graph; based on the coupling relation mapping map, constructing a path search model, and solving an optimal topology switching path by adopting an enhanced iterative algorithm; and generating a topology switching sequence according to the optimal topology switching path, and implementing power transfer regulation and control on a high-load transmission section. According to the method, the joint atlas is constructed, the optimal topology switching path is generated, local overload is effectively relieved, power fluctuation is weakened, and the overall load balancing level and the active regulation and control capability of the system are improved.

The invention discloses a cable trench inspection robot path planning method and device and a medium, a cable trench three-dimensional semantic map is constructed through multi-sensor fusion, and a laser radar and a depth camera are combined to accurately identify the spatial distribution of a cable support, a suspension cable and an obstacle. An improved directional path search algorithm is adopted, firewall passing sequential logic and lifting platform kinematics constraints are integrated, and a multi-mode inspection path is generated. The environment change is sensed in real time in the inspection process, the path is adjusted online through a dynamic path optimization engine, a planning strategy is iteratively optimized based on historical data, a digital twin system is introduced to realize path pre-verification, and the firewall interaction efficiency and the exception handling capacity are optimized by adopting reinforcement learning. According to the invention, the technical problems of poor real-time performance of path planning and low reliability of facility interaction in a complex cable trench environment are solved, and the inspection efficiency and safety are significantly improved.

The invention is suitable for the technical field of robots, and provides a path planning method and a robot, and the method comprises the steps: obtaining the environment information of a target area, building a grid map according to the environment information, and enabling the grid map to comprise a starting point area, an end point area and an obstacle area; determining a global path through a path search algorithm according to the grid map; in the process of controlling the robot to move along the global path, performing local path optimization through a dynamic window algorithm; wherein the dynamic window algorithm calculates the score of each candidate local path through a trajectory cost function and determines the optimal local path, and a strategy network output score obtained by predicting the candidate paths through a pre-trained deep learning strategy model is introduced into the trajectory cost function. The adaptive capacity of the robot in a dynamic environment can be improved.

The invention discloses a dynamic path optimization method based on response time domain attenuation, and relates to the technical field of artificial intelligence and intelligent path planning, and the method comprises the steps: generating a node network composed of navigation points, terrain units or interaction regions, and forming a node network topology structure; generating a dynamic state feature set used for describing game scene changes, and forming input data used for follow-up node priority dynamic adjustment; converting the dynamic state feature set into node-level standardized event data, and distributing the node-level standardized event data to a node state management module through an event bus; setting a current node priority for each node in a node state management module based on the node-level standardized event data; forming a time domain attenuation model of the node priority; the priority recovery coefficient is improved; in the path planning stage, executing a dynamic path search algorithm to generate a passing path with the minimum total cost and the optimal path smoothness; when it is detected that player operation or scene change causes node response mutation, a local re-planning mechanism is triggered, smooth path transition is achieved, and overall jumping is avoided. According to the method, the problems of path congestion, frequent switching and unsmoothness caused by lack of dynamic node state and event response calculation in the prior art are solved. Through node priority time domain attenuation and dynamic path optimization, the technical effects of smooth path, efficient passing and node load balancing are achieved.

The invention discloses a transformer substation positioning and navigation method and system integrating positioning and visual auxiliary positioning. The method comprises the following steps: establishing a background electromagnetic field distribution baseline graph associated with a three-dimensional reference map; electromagnetic field data of the transformer substation in an emergency response mode is collected through the unmanned aerial vehicle, and the abnormal field intensity of a space electromagnetic field and a fault source pointing vector pointing to a fault source are calculated; constructing a risk adaptive elliptical forbidden zone; calculating a passage cost index Cto of the unmanned aerial vehicle passing through each three-dimensional grid in the three-dimensional reference map by using the fault source pointing vector and the risk adaptive elliptical forbidden zone; and searching a path which is from the current position of the unmanned aerial vehicle to a preset target point, bypasses the risk adaptive elliptical forbidden zone, faces the fault source and has the lowest total passing cost index Cto by adopting a preset path search algorithm. According to the method, the risk self-adaptive elliptical forbidden zone is constructed and is used as the three-dimensional grid forbidden assignment processing, so that the dynamic global path avoidance of the sudden dangerous zone is realized.

The invention provides a tunnel drilling and blasting slag removal vehicle autonomous path planning method and device based on a Naligation 2 behavior tree scheduling framework, and the method comprises the following steps: S1, carrying out the data collection and map construction of a tunnel scene after drilling and blasting; s2, identifying a blasting residue area and generating a target point; s3, constructing a behavior tree scheduling structure and planning a path; and S4, performing path search, execution and feedback evaluation based on a path planning algorithm. According to the method, multi-source sensor mapping and deep learning semantic segmentation technologies are combined, high-precision recognition and traffic area extraction of residual obstacles in an unstructured tunnel environment after drilling and blasting are performed are performed, complex scenes faced by slag removal path planning are fully considered, a behavior tree scheduling mechanism is adopted to fuse path planning, target scheduling and an anomaly recovery strategy, and the path planning efficiency is improved. And a path execution system of real-time response and fault-tolerant capability is further constructed, and the operation continuity and robustness of the robot in a complex operation environment are improved.

The invention discloses a subway service robot real-time path planning method based on a graph neural network, and the method comprises the following steps: scanning the environment in a subway station, completing the map construction, and obtaining basic environment data; performing target detection and personnel statistics to form an environment and passenger flow fusion map; taking the fused map as input, setting a starting point and a target position, and outputting a global path search initial state; calling an improved A * algorithm to carry out node expansion, calculating a cost estimation function, and generating candidate paths; performing redundant node deletion and arc smoothing processing on the candidate path, performing step length dynamic adjustment, and outputting an optimized global path; performing local path planning by adopting an improved dynamic window method, and outputting an update path in real time; a passenger evacuation scheme is generated and is output through a display screen and voice broadcast, evacuation is guided, and passing is guaranteed. According to the invention, real-time path planning of the subway service robot is realized.

The invention provides a low-altitude space path planning method and system, and relates to the technical field of low-altitude space management and path planning, and the method comprises the steps: S1, dividing a target airspace into a plurality of levels of three-dimensional voxels, and generating a unified-level three-dimensional code for each voxel; s2, voxelizing a task starting point, a task ending point and constraint elements based on unified hierarchical three-dimensional coding to generate a confinement three-dimensional corridor so as to limit a subsequent search space; s3, in the confinement three-dimensional corridor, hierarchical path search from the coarse hierarchy to the target hierarchy is executed, and a discrete path is output; s4, when the dynamic change of the environment is detected, performing increment re-planning on the basis of the discrete path, and updating the affected local path; and S5, smooth processing and safety verification are carried out on the discrete path or the updated path, and a final continuous flight path is generated. According to the invention, the real-time performance, the safety and the verifiability of the low-altitude flight task path can be realized.

The invention provides a product defect tracing method based on knowledge graph reasoning. The method comprises the following steps: constructing a knowledge graph based on a product hierarchical structure of a bill of materials and a manufacturing process hierarchical structure of a process route; when it is detected that data of a certain node in the knowledge graph is changed, calculating an update priority weight of a change node based on the occurrence frequency of the change node in a historical defect path and the hierarchy depth in the double-hierarchy structure; determining an updating range according to the updating priority weight, and updating the knowledge graph; and positioning defect nodes in the updated knowledge graph according to system response, executing path search from the defect nodes, identifying potential root cause nodes, and realizing product defect tracing. According to the method, accurate and real-time defect traceability of the product is realized based on multi-level feature correlation analysis of causal reasoning and dynamic knowledge graph construction and enhanced reasoning.

The invention discloses an intelligent parking dynamic scheduling optimization method based on multi-source data fusion, and the method comprises the following steps: S1, collecting multi-source data, and carrying out the preprocessing of the multi-source data; s2, constructing a heterogeneous graph structure, and generating a node feature matrix and a heterogeneous adjacency tensor; s3, extracting a state fusion vector, constructing a joint scoring matrix, and generating a candidate path set; s4, setting target parameters, executing path search and pheromone iteration, and outputting a regional path set; s5, adjusting a node preference weight, executing regional path reordering, and outputting an optimal vehicle parking path; and S6, recording the whole scheduling process, updating the network parameter weight through the sliding window memory pool, and generating an incremental learning sample set. According to the invention, high-precision, low-delay and personalized intelligent parking dynamic scheduling under the driving of multi-source data can be realized, and the parking efficiency and the user experience are effectively improved.

The invention belongs to the technical field of three-dimensional mapping, and particularly relates to an occlusion area three-dimensional voxel reasoning method and system. The method comprises the following steps: S10, acquiring an RGB image containing a semantic segmentation result of an occlusion region and a corresponding depth map, and converting the depth map into an initial sparse three-dimensional voxel; and S20, constructing a three-dimensional voxel inference network, and inferring a three-dimensional voxel occupancy probability graph from the initial sparse three-dimensional voxels through the three-dimensional voxel inference network. The occlusion area can be reconstructed based on the monocular image; multi-format output and navigation interface butt joint are supported, and the method can be integrated to SLAM, 3D mapping or path search systems to serve as spatial feasibility constraints; the method can be used for querying whether any spatial position is passable; the method can be used for extracting a trafficability sub-graph from a designated area for path planning.

The invention discloses an equipment disassembly sequence automatic generation and verification method based on a physical engine, which belongs to the technical field of equipment disassembly, and realizes component physical attribute and dynamic connection constraint loading by acquiring an equipment three-dimensional model and initializing a physical engine simulation environment. And in the physical engine simulation environment, iteratively evaluating the feasibility of the disassembly operation, accurately capturing physical behaviors such as gravity and collision, and identifying disassembly obstruction and preset operation to generate candidate operation. A path search algorithm is utilized to intelligently explore and generate a creative disassembly sequence, and the limitation of traditional artificial experience and a static method is overcome. Through a multi-dimensional nonlinear total cost function, factors such as the number of disassembly steps, collision risks, tool replacement and accessibility and the like are comprehensively quantified, and an optimal solution considering efficiency, safety and operation convenience is verified and selected.

The invention provides an indoor navigation and path planning method, device and equipment. Comprising the steps that path planning request parameters are acquired, and the request parameters at least comprise a starting point, an ending point, a time context, a user portrait and a scene template of path planning; generating a runtime snapshot reflecting the traffic state at the current moment in combination with a pre-constructed static grid system, a knowledge graph and a dynamic grid system generated in real time; according to an indoor structure mask and guide identification information in the static grid system, generating a search domain limit of path planning on the runtime snapshot; judging whether the starting point and the ending point are on the same floor; performing path search by adopting a same-layer search strategy or a cross-layer search strategy; and dynamically injecting constraints to the result of the path search and calculating the path cost to generate a path plan. According to the embodiment of the invention, the indoor space can be uniformly expressed, the multi-source dynamic information can be fused in real time, and the path planning scheme can be quickly generated, so that the navigation requirement in a modern complex indoor scene can be met.

The invention belongs to the field of electric power inspection, and provides an electric power scene full-chain ubiquitous dynamic sensing body intelligent inspection operation method and system, and the method comprises the steps: carrying out the semantic analysis of an initial electric power task, combining a target electric power scene model, constructing an executable constraint set, and matching each body intelligent agent in an inspection domain; fusing the task information and a pre-constructed electric power knowledge graph, performing graph path search on the fused electric power knowledge graph by using a pre-trained large language model to obtain a disassembled atomic action sequence, and issuing the disassembled atomic action sequence to a matched and determined corresponding body agent; and evaluating the risk of candidate actions in the atomic action sequence by using the multi-modal task-environment constraint graph to realize preliminary optimization, and dynamically adjusting according to real-time environment information in the target power scene, the state of the agent with the body and the current task completion condition until the atomic action sequence is executed. According to the invention, the intelligence, the accuracy and the safety of the inspection operation can be obviously improved.

The invention provides a multi-modal neural causal inference micro-service fault positioning method and system, and the method comprises the steps: accessing observability data in a service operation process, and representing the tracking information of each request as a directed acyclic graph of a multi-modal feature; performing multi-modal feature coding and graph self-coding anomaly detection on the calling graph, and identifying an abnormal node through a reconstruction error; based on service topology prior, learning a sparse causal relationship graph between services by adopting a multi-scale neural causal inference method; calculating a node root cause score according to the causal relationship graph and the abnormal score, and executing causal path search to generate a fault propagation path; and marking the potential root cause according to the path weight of the propagation graph and the node popularity, and outputting a visual diagnosis result. According to the method, the system operation state is comprehensively described by fusing three kinds of micro-service system multi-modal data of logs, indexes and Trace in the micro-service system, and the structure-perceived causal diagram is constructed, so that accurate and explainable root cause positioning is realized.

The invention relates to the technical field of route planning, and provides a shortest route detection method and system for a low-altitude aircraft. The method comprises the following steps: establishing a three-dimensional environment model of a target area, and identifying an obstacle; marking a driving space according to the obstacle range and the safety range of the identified obstacle, and constructing a flight space map; taking the current position of the aircraft as a starting point, taking the target flight position as an end point, and performing minimum path search in the flight space map based on constraint conditions of a minimum turning radius and a maximum climbing rate to obtain a minimum planned path; and performing intermediate node redundancy verification on the minimum planned path, and taking the minimum planned path meeting the verification result as the shortest determined route. According to the method and the device, the technical problems of insufficient precision of the planning path and potential safety hazards caused by the fact that the three-dimensional obstacle environment and the aircraft motion constraint cannot be considered in the existing low-altitude aircraft route planning process are solved, and the technical effects of improving the low-altitude flight safety and the route planning efficiency are achieved.

The invention provides an unmanned forklift path planning method, system and device and a readable storage medium. The method comprises the steps that a storage reference base map and a road network topological structure are constructed; establishing mapping association between the nodes and the storage locations and storing the mapping association; real-time inventory data is maintained through a distributed cluster, and the storage location is updated synchronously; marking obstacle nodes based on the inventory information and the mapping relation; planning a path by adopting a path search algorithm and avoiding obstacles; and when the preset path section is completed during driving, the inventory updating obstacle is obtained again, the path is regenerated and compared, and an updating instruction is issued when a difference exists. According to the method and the device, the technical problem that the driving path is easy to fail due to the change of the obstacle node because the traditional unmanned forklift path planning cannot respond to the dynamic change of the warehouse inventory in real time is solved.

The invention discloses a chronic disease management AI recommendation anti-illusion method and system based on a knowledge graph, and relates to the technical field of medical health artificial intelligence, and the method comprises the steps: obtaining chronic disease medical data of a patient, extracting a feature vector, and constructing a multi-modal health trajectory vector; constructing a chronic disease tag vector and a directional causal knowledge graph; executing map path search to obtain candidate treatment paths; constructing structured cue words, and inputting the structured cue words into the medical large language model to generate candidate schemes; and calculating a comprehensive illusion score to carry out anti-illusion judgment and correction, and outputting a credible personalized treatment recommendation. By constructing a directional causal knowledge graph, the causal reasonability and semantic consistency of treatment path retrieval are enhanced, and the matching precision of candidate paths and patient states is improved; by calculating the comprehensive illusion score and introducing the four-dimensional score item for anti-illusion judgment, the credibility of the output content of the large language model is improved, and the availability of AI recommendation in clinical aid decision making is guaranteed.

The invention belongs to the technical field of robot path planning, and provides a path planning method for an electric power inspection mobile robot, which comprises the following steps of: firstly, constructing an environment grid map, establishing a corner directional expansion safety boundary, and performing safety expansion on an outer right angle of an obstacle; secondly, establishing an intelligent neighborhood selection mechanism based on fuzzy control, and performing adaptive adjustment neighborhood search; then, a multi-target heuristic function fusing the local obstacle density, the safety distance and the traffic difficulty is established, path search is carried out, and an initial path is obtained; then, constructing a path optimization strategy, and carrying out redundant point deletion and B spline curve smoothing processing on the initial path until a target executable path is obtained; and finally, optimizing an executable track in the target executable path in a time-space domain through an improved time-domain elastic band algorithm to obtain an optimal path. According to the invention, accurate obstacle avoidance of complex geometric obstacles can be realized.

The invention discloses a knowledge graph-based intelligent question and answer method for text travel. The method comprises the following steps of: obtaining and preprocessing related data in a text travel service system; constructing a structured knowledge graph in the text travel field; constructing a candidate entity pair and executing relation extraction and weight updating guided by a behavior sequence; dividing and generating a behavior preference sub-graph according to a behavior mode, and extracting a text travel knowledge slice set according to a theme; natural language questions of tourists are received, and path search and semantic aggregation with behavior weights and path structures as constraints are executed; and generating a text travel intelligent question-answer result through a question-answer generation engine, and recording a text travel question-answer interaction log for iterative updating. According to the method, knowledge graph modeling and behavior guiding relation extraction technologies are fused, dynamic reasoning and personalized question and answer generation of the travel knowledge are achieved, and the method has the advantages of being accurate in semantic understanding, high in answer association degree and continuous in self-adaptive evolution.

The invention is suitable for the technical field of road construction, and provides a wind power plant road intelligent line selection method based on multi-dimensional constraint dynamic modeling, and the method comprises the steps: obtaining a multi-dimensional constraint condition of wind power plant road line selection, and constructing a constraint model; generating a slope grid map based on a digital elevation model, and fusing the slope grid map with a constraint map layer reflecting geological stability and a land cover type to generate a dynamic cost surface; adopting an improved heuristic search algorithm to perform parallel path search from the road starting point to each target fan position, generating a plurality of initial feasible paths, and calculating a comprehensive cost value; screening a candidate line set according to a comparison result of the comprehensive cost values; receiving real-time updating data in a construction process and environment monitoring, inputting the real-time updating data into the constraint model to trigger model updating, performing iterative optimization on the candidate line set based on the updated constraint model, and outputting a final line selection scheme; and the line selection efficiency, economy and reliability are effectively improved.

The invention relates to the technical field of machine path planning, and discloses an island ant colony path planning method for an unmanned trolley, which comprises the following steps: after generating a grid map, decomposing global path search into path exploration between adjacent islands; non-uniform pheromone initialization is adopted between adjacent islands, local paths between the adjacent islands are searched respectively, and the position of a next grid is selected in the searching process by combining an improved node transition probability with a heuristic function and pheromone concentration; and when global pheromone distribution is updated, an optimal path is rewarded, and a worst path is punished. And combining the local paths of the island pairs to obtain global paths, and selecting the global path with the shortest length as the optimal driving path. According to the method, a segmented island strategy is adopted, the complexity of single search is reduced, the early random probing process is shortened through non-uniform initialization pheromones, the convergence speed is increased, the number of deadlock ants is effectively reduced, and the precision, convergence and stability of path planning are improved.

The invention discloses a wheeled robot path planning method for different scenes and a related device, and the method comprises the steps: obtaining environment data around a robot, building a global grid map, carrying out the preprocessing of the global grid map, carrying out the geometric feature recognition and angular point extraction of an obstacle, and fusing a multi-sampling strategy to generate a path search network. Path searching is carried out according to the target point and the pose planning, and a global optimal path conforming to robot driving is obtained; segments in the global optimal path are intercepted through the rolling window principle to serve as local paths to be input into a local path planning algorithm, a local optimal track is generated, and a speed instruction is output; and updating the map in the rolling window in real time, executing an obstacle avoidance task on the obstacle through the local optimal track, driving along the global optimal path again after obstacle avoidance, and moving to a target point according to a speed instruction. According to the method, the problems of large speed fluctuation, low quality of the generated path and calculation burden caused by increase of alternative path points in the current robot driving process are solved.

The invention discloses an unmanned aerial vehicle dynamic path planning method and device based on environment perception, electronic equipment and a storage medium, and belongs to the field of unmanned aerial vehicle path planning, and the method comprises the steps: obtaining an environment risk parameter when an unmanned aerial vehicle executes a task along a current flight path in real time; when each environment risk parameter is acquired, calculating and generating a current trajectory prediction value based on the currently acquired environment risk parameter; and when the current track predicted value exceeds a preset safety threshold value, generating an adjusted flight path capable of bypassing the obstacle by adopting a preset way-finding algorithm and taking the minimum obstacle avoidance path cost as an optimization target, and updating the adjusted flight path as a current flight path. By implementing the method and the device, the problem that the global optimum of path planning cannot be realized due to single sensing dimension and one-sided decision model in the prior art can be solved.

The invention relates to the technical field of navigation assistance, in particular to a dynamic obstacle prediction and obstacle avoidance path planning method based on multi-sensor fusion, which realizes omnibearing perception of a dynamic obstacle through multiple sensors, provides a rich and reliable data basis for subsequent processing, and improves the accuracy of the dynamic obstacle prediction and obstacle avoidance path planning. Meanwhile, motion prediction is carried out on a dynamic obstacle through data processing fusion and model prediction, the motion inertia of the obstacle is fully considered, track prediction of the obstacle is closer to a real physical rule, a global path search problem is converted into a local but large enough space search problem through a mode of delimiting a final obstacle avoidance target area, and the search efficiency is improved. According to the method, the number of grids needing to be processed and the search calculation amount are remarkably reduced, the harsh requirement of the mobile device for the real-time performance is met, the area possibly occupied by the obstacle in the future is avoided in real time in the mode of constructing the cost function, then the obstacle avoidance planning path is generated, and the path safety is improved.

The invention relates to a sweeper path planning method, system and device suitable for a complex environment and a medium. The method comprises the steps that a global map of a sweeping area is acquired, feature vertexes are determined to decompose the global map, and a structural sub-area and a special sub-area are generated; determining a starting point of the structure sub-region according to the feature vertex, and generating a first path covering the structure sub-region by adopting an internal spiral method based on the starting point; determining a non-linear constraint region of the special sub-region, converting the non-linear constraint region based on coordinate system transformation, and generating a second path of the special sub-region; and determining a starting point and a target point of any path, connecting the starting point and the target point based on an improved path search algorithm, and generating a target path of the cleaning area. Therefore, according to the invention, through accurate path planning and dynamic adaptability optimization, the path planning level and the completion quality of the sweeping operation are improved, so that the sweeping vehicle can adapt to the actual scene of a complex environment, and the application range is greatly expanded.

The invention provides a vehicle path planning method and device. The method comprises the following steps: acquiring vehicle parameters, environment sensing data, a path starting point and a path ending point; generating an upper-layer obstacle grid map and a lower-layer obstacle grid map based on the vehicle parameters and the environment perception data; performing collision detection based on the vehicle parameters in the upper-layer obstacle grid map and the lower-layer obstacle grid map to obtain an upper-layer collision detection result and a lower-layer collision detection result; combining the upper-layer collision detection result with the lower-layer collision detection result to generate a planned path from the path starting point to the path ending point; the planned path comprises obstacle-avoiding nodes for bypassing the upper-layer obstacle and obstacle-crossing nodes for crossing the lower-layer obstacle. Therefore, efficient path searching in the multi-obstacle complex scene is realized, and the vehicle has better trafficability in the multi-obstacle complex scene.