19results about How to "Improve path planning efficiency" patented technology

The invention provides a path planning method and system for an automatic driving trolley, and relates to the technical field of path planning, and the method comprises the steps: obtaining the data of an acoustic sensor of an underwater environment, and obtaining the contour of the underwater terrain and the position information of an obstacle; carrying out dynamic environment modeling processing; the Euclidean distance is used as a heuristic function to calculate the dynamic model of the underwater environment, and a second optimized path conforming to kinematics and dynamics constraints of the automatic driving trolley is obtained; carrying out smoothing processing on the second optimization path through a dynamic motion primitive technology; constructing a three-dimensional map for path planning and obstacle avoidance; predicting an action track of the robot in a period of time in the future; and through real-time adjustment processing of the self-adaptive control system, path planning of the automatic driving trolley is completed. According to the method, the dynamic characteristics of the underwater environment and the motion constraint of the automatic driving trolley can be comprehensively considered, the three-dimensional map containing the obstacle and topographic information can be constructed in real time, and the future motion trail of the obstacle can be predicted.

The invention relates to a path optimization method and device based on a hybrid quantum algorithm, computer equipment and a storage medium, and the method comprises the steps: obtaining a weight adjacency matrix of an undirected completely weighted graph of a to-be-optimized path; inputting the weight adjacent matrix into a preset quantum circuit for optimization to obtain a first candidate solution and a corresponding first weight; wherein in the encoding and pruning optimization process of the quantum circuit, all candidate solutions are divided into a plurality of steps; the selection of the traveling salesman in each step is coded into a quantum circuit, and corresponding pruning is executed to form a uniform superposition state containing all candidate solutions; and according to the first weight and a preset first threshold value, updating the first candidate solution to obtain a target path. Through the path planning method and device, the problem of low efficiency of path planning in related technologies is solved, quantum resources required for encoding candidate solutions are effectively reduced, and the path planning efficiency can be improved while precise path planning is realized.

The invention discloses a multi-AGV path planning method based on an improved cuckoo optimization algorithm, and belongs to the technical field of AGV scheduling, and the method comprises the following steps: improving the cuckoo algorithm based on Tent chaotic mapping, adaptive Levy flight and Cauchy variation; an AGV simulation operation network is constructed; in the AGV simulation operation network, performing iterative optimization on a multi-AGV planning path based on an improved cuckoo optimization algorithm; and obtaining an optimal planning path of each AGV based on an optimization result. The invention aims to improve the path planning efficiency of the AGV cluster, reduce the calculation time of the algorithm and improve the working efficiency of the AGV.

The present invention provides a path planning method and device for a robot arm, and a storage medium, wherein the method comprises: receiving a voice grabbing instruction, wherein the voice grabbing instruction is used to instruct to grab a target object; acquiring a scene image of the location of the target object captured by a camera, and detecting the initial posture of the target object based on the scene image; determining the pre-grabbing posture of the robot arm based on the initial posture, wherein the pre-grabbing posture is the preparation posture of the robot arm before grabbing the target object; and planning the movement path of the robot arm in real time according to the pre-grabbing posture. The technical problem of low efficiency of path planning of the robot arm in the related art is solved, and the path planning efficiency of the robot arm is improved.

The embodiment of the invention discloses a path planning method and device, equipment and a storage medium, and relates to the technical field of path planning. The method comprises the following steps: acquiring an ordered binary decision diagram corresponding to the robot based on a path planning instruction; the ordered binary decision diagram is used for representing all planned routes in a target scene where the robot is located; obtaining a constraint condition and a task target corresponding to the target scene; determining a target planning path which simultaneously meets the constraint condition and the task target in the ordered binary decision diagram; by determining the target planning path which simultaneously meets the constraint condition and the task target in the ordered binary decision diagram, the state space of the planning process is reduced, and the robot path planning efficiency is improved.

This invention belongs to the field of dust collection robot technology, specifically relating to a factory intelligent dust collection spray robot system based on multi-sensor collaboration. The system includes a vehicle body, a sweeper mounted on the vehicle body, an electronic control system within the vehicle body, a vision recognition module mounted on the vehicle body, a dust collection module mounted on the vehicle body, and a dry fog module mounted on the vehicle body. The electronic control system controls the operation of the vision recognition module, dust collection module, and dry fog module. The vision recognition module is used to construct a map and optimize the dynamic path in real time. The dust collection module absorbs dust through graded filtration. The dry fog module dynamically adjusts the atomized particle size and spray flow rate of the dry fog nozzles according to the dust concentration to prevent dust diffusion. This invention features improved dust collection efficiency, reduced development and maintenance costs, and dust suppression effects.

The present invention discloses a path navigation method and system for continuous motion of a robot. The method uses dynamic environment map knowledge to determine the initial position and target position of the robot, and counts the motion path between the initial position and the target position in the dynamic environment map knowledge; marks all obstacles on the motion path, and selects the most preferred path according to the path distance; uses the intersection between the most preferred path and other navigation paths as a marking point, and divides the most preferred path into a plurality of bifurcated segments according to the marking points; monitors the dynamic obstacles on the most preferred path in real time and determines the dynamic obstacles that affect the motion of the robot, and uses the front fork or the rear fork of the bifurcated segment as the initial position again according to the bifurcated segment currently located by each robot; reselects the most preferred path until each robot moves to the target position according to the shortest path; the present invention ensures that the path navigation moving path of each mobile robot is the shortest.

The present invention belongs to the technical field of mobile robot path planning, and provides a robot path planning method and system based on a dynamic update mechanism ant colony algorithm. The method includes obtaining the robot's task environment, rasterizing it, obtaining a raster map, determining the robot's starting node, target node, nodes that are prone to deadlock, and obstacle nodes; planning the robot's path based on the dynamic update mechanism ant colony algorithm; the initial taboo list of the dynamic update mechanism ant colony algorithm stores the robot's starting node, target node, nodes that are prone to deadlock, and obstacle nodes; when all ants complete an iteration, the optimal path is saved, and the pheromone volatility coefficient, pheromone concentration, and taboo list are dynamically updated until all iterations are completed to obtain the optimal path.

The invention relates to a mine robot cooperative path planning method based on multi-agent reinforcement learning, and belongs to the technical field of mine robot cooperative control and intelligent decision, and the method comprises the following steps: constructing refined environment characterization based on multi-source sensor information through a terrain cost modeling module, and calculating a terrain cost value; path planning is carried out by adopting a centralized training-decentralized execution mechanism through a multi-agent reinforcement learning framework; motion conflicts between the robots are monitored and solved in real time through a dynamic conflict resolution module; and cross-robot knowledge transmission and strategy migration are realized through the knowledge sharing unit. According to the method, the path planning efficiency, the collaborative operation safety and the learning adaptability of multiple robots in complex dynamic environments such as mine catastrophe are effectively improved, and the method is suitable for collaborative detection, rescue and transportation tasks of multiple types of mine robots.

The present invention discloses a path planning method, device and computer storage medium for a mobile robot. The path planning method for a mobile robot of the present invention adopts a two-way sampling strategy to generate four search trees, and uses the four search trees to search simultaneously, thereby shortening the path planning time and improving the path planning efficiency; when the search tree expands the node, the repulsive field generated by the obstacle is used to constrain the generation of the sampling point, so that the generation of the sampling point has directionality, so that the sampling point is far away from the obstacle, and the obstacle is expanded at the same time, so as to avoid the generated path from being close to the obstacle; in addition, the gradient descent optimization strategy is used to smoothly optimize the generated path, so that the path is more in line with the dynamic model of the mobile robot, thereby making the robot move more smoothly.

The invention provides a path planning method and system in a digital twin environment and electronic equipment, and belongs to the field of path planning. The method comprises the steps that a user instruction is acquired, and an execution task in the instruction is extracted; the method comprises the following steps: abstracting key geographic position information and a passage path in a real environment into nodes and edges in a graph structure based on a digital twinborn sum graph structure construction method, and generating a sparse directed graph; and in combination with the execution task and the sparse directed graph, performing global path exploration by using a Go-Explore algorithm to generate a plurality of candidate paths, and performing local optimization on the plurality of candidate paths by using an ERL algorithm to obtain a target path. Through combination of digital twin environment graph structure modeling and algorithm learning, efficient cooperation of global path exploration and local optimization is realized, the path planning efficiency, task execution flexibility and user interaction experience of a rover in a digital twin environment are remarkably improved, and a comprehensive and accurate solution is provided for navigation and decision making of the rover.

The application discloses a power transmission line path planning method and system based on natural language and a knowledge graph, and comprises the following steps: a large language model is used to analyze a natural language path planning target, an intention classification result and a named entity are obtained, and are mapped to a business rule knowledge graph for reasoning, and a task step sequence is generated; confirmation or modification of each task step by a user is received, and each target task step is obtained; a large language model is used to retrieve a combination corresponding to each target task step from a GIS operation knowledge graph, and the combination is disassembled into a GIS operator call chain; corresponding GIS tools are called through an MCP protocol, spatial analysis operations in the GIS operator call chain corresponding to each target task step are executed in the order of all target task steps, and a path planning result of a power transmission line is generated. The application realizes full automation, process explainability and human-computer interaction collaboration of power transmission line path planning, and improves the efficiency of power transmission line path planning.

The present invention provides a multi-topography integrated path planning method incorporating road factors. Based on the image information of the target area, at least one terrain feature included in the target area is determined, and a grid map corresponding to the target area is constructed. In response to a path search instruction input for indicating searching for a driving path between a starting point and an ending point in the target area, at least one path is determined in the grid map. The sum of the values of the cost function corresponding to each grid passed by each path is obtained. The cost function is associated with the slope value, type of the terrain feature included in the corresponding grid, the speed of a preset vehicle passing through the terrain feature included in the corresponding grid, and the Euclidean distance between the starting point and the ending point. The path corresponding to the minimum value of the sum is determined as the target path. Determining the path corresponding to the target path as the driving path in the target area can improve the passing efficiency of the user.

The embodiment of the present invention discloses a panoramic parking digital camera access system, method, electronic device and storage medium, wherein the system includes a baseboard, a core board and N-way cameras, the core board is provided with a central processing unit, a video processor, and N-way ipex connection ports; the N-way cameras are connected to the N-way ipex connection ports through N-way interfaces; the N-way cameras obtain image data, and transmit the image data to the video processor through the N-way interface and the N-way ipex connection ports, the video processor processes the image data, and transmits the processed image data to the central processing unit, the central processing unit executes the panoramic parking algorithm based on the processed image data, and outputs the display screen corresponding to the panoramic parking algorithm. The implementation of the embodiment of the present application can reduce the interference and abnormal number of video signals, improve the picture quality; and can improve the efficiency of the panoramic parking algorithm and improve the quality of the displayed content.

The invention discloses a path planning method and device based on an adaptive heuristic mode, and relates to the technical field of path planning. The method comprises the following steps: receiving a first request sent by a target user; determining a first position and first information according to the first request; inputting the first position and the first information into a preset path database for query to obtain a plurality of path plans; calculating each path plan to obtain a plurality of adaptive heuristic scores; obtaining a first heuristic score from the plurality of adaptive heuristic scores, and determining a first path plan according to the first heuristic score; acquiring second information sent by a target user; and when the second information is consistent with the preset first information, confirming that the first path plan is displayed to the target user, so that the target user moves according to the first path plan. By implementing the technical scheme provided by the invention, the problem that the preference difference of different runners to routes cannot be considered in traditional route planning is effectively solved, so that the route planning experience of the user is improved.

This invention discloses a method, system, storage medium, and product for unmanned vehicle (UAV) path planning in field environments under UAV collaboration, belonging to the field of UAV path planning, and solving the problem of low data accuracy in the global path planning of UAVs in existing technologies. This invention acquires a top-down visible light image of the passable area and performs image pose calculation and sparse point cloud data generation; then generates a two-dimensional orthophoto and digital surface model of the passable area; a semantic segmentation model performs semantic segmentation on the two-dimensional orthophoto and extracts ground feature classification data; after gridding the digital surface model and ground feature classification data, slope values ​​and ground feature classification values ​​are calculated; based on the slope value and ground feature classification value of each grid cell, the passage cost of each grid cell is calculated; the starting and ending coordinates of the UAV are input, and UAV path planning is performed based on the path planning algorithm and the obtained passage cost map. This invention is used for UAV-collaborated path planning in field environments.

The invention discloses a multi-forest area route scheduling planning method based on a double-layer fusion intelligent algorithm, S1, setting the population of the first-layer genetic algorithm; S2-S6, using decimal coding to initialize the population, calculating fitness, performing selection, crossover, mutation, and reversal operations, reinserting into the population and checking the number of iterations; S7, initializing the pheromone of the ant colony algorithm; S8-S20, setting the number of ants m, randomly placing them on the nodes of the multi-area forest area to be planned, ant k traverses all areas without repetition, and updates local pheromones in time; checking whether the ant index number k is greater than the number of ants m; global pheromone update. Check the number of iterations; output the job sequence path solution set; set the second-layer genetic algorithm population; use the binary coding population Chrom2; calculate the fitness value; perform selection, crossover, and mutation operations; reinsert to obtain the updated population; detect the number of iterations; output the best route scheduling plan.

The present invention belongs to the field of AGV scheduling, and relates to an AGV path scheduling method based on a spatial A-star algorithm and traffic control. The method comprises: collecting current environmental data, identifying and marking key spatial elements on a map; using an improved spatial A-star algorithm to search for paths in the environment, and using the key spatial elements as key information in the search process to participate in path planning; setting multiple traffic control rules in path planning; when the AGV executes the travel path, monitoring the environment in real time, and replanning the path when encountering environmental changes; performing anomaly detection and collision prediction when the AGV executes the travel path, and adjusting the path of the AGV in real time according to the results of anomaly detection and collision prediction; the AGV continues to perform tasks according to the updated path until it reaches the destination. The AGV path scheduling method provided by the present invention adopts an improved spatial A-star algorithm, and significantly optimizes the path search process by introducing spatial information as an additional heuristic factor.