93 results about "Shortest path planning" patented technology

The invention discloses a shortest path planning method for dynamic origins, and belongs to the technical field of dynamic path guidance in an intelligent traffic system. The shortest path planning method is used for optimizing vehicle traveling routes. The shortest path planning method always takes a current vehicle position as a starting point and predicts road condition information such as traffic flow of relevant road sections and road intersections, and the like for many times according to vehicle running time to calculate a shortest path according to a path planning algorithm in a no-request mode at regular time, thereby acquiring a shortest time path in accordance with the real-time conditions of a road network better and directly displaying the shortest time path on the screen of a vehicle navigation system; and meanwhile, by the method, the update operation amount is less so as to shorten calculation time.

The invention provides a path planning method and system, wherein the method comprises the following steps: mapping roads into nodes in a traffic network topological graph and mapping endpoints of the roads into arc sections in the traffic network topological graph; searching bi-directionally from an original node and a destination node, thus obtaining a plurality of current nodes; calculating the cost from a plurality of current nodes to the original node and the destination node sequentially and obtaining a current node of the minimum cost from the original node to the destination node; and according to the current node of the minimum cost, the original node and the destination node, obtaining a path plan from the original node to the destination node. The method and the system overcome the defect in the prior art that a Dijkstra method of adjacent matrices is adopted to store traffic network topological data, although whether (i; j) is a network edge can be queried within the time O (1), the complexities for querying relevant nodes which are the most significant for the shortest path plan are all O (n), which causes higher query complexity.

A method includes defining a two-dimensional geographic region by two-dimensional geographic coordinates to define the bounds of the region, converting each of the two-dimensional coordinates to three dimensional coordinates by way of a lookup stored in a computer readable medium, generating a three-dimensional grid of points, each spaced in an arrangement to encompass coverage of a predetermined ground area, and applying heuristics for a shortest path planning, relative to the three-dimensional grid of points.

The invention relates to an interference-prevention-based multi-automatic-guided-vehicle (AVG) path planning method for a logistics storage system. On the basis of analyses of arrival and departure times of multiple AGVs at and from all road sections and nodes in a logistics storage system, driving overlapping frequencies of the AGVs on the road sections and nodes are calculated. With combination of an interference threshold value, a multi-AGV shortest path planning model with an interference prevention constraint is established by using multi-AGV operation time as a target. With a frame of an ant colony algorithm, an interference-prevention-based multi-automatic-guided-vehicle path planning method with inducing ant colony and particle swarm fusion for a logistics storage system is designed by keeping a pheromone factor is kept, removing a visibility factor, and adding a A <*> factor and an inducing factor. Road features of typical logistics storage systems like a dock, a warehouse, a distribution center, a container station and various storage yards are combined and a multi-automatic-guided-vehicle path planning method is provided. Therefore, the interference can be avoided effectively; the AGVs can arrive at destinations according to respective shortest paths; and thus the working efficiency and security of the logistics storage system can be improved.

The invention discloses a cleaning robot and a shortest path planning method based on the cleaning robot. The shortest path planning method comprises the steps of controlling the cleaning robot to clean a region according to a shape of a Chinese character 'gong' to form multiple cleaning lines; recording midpoint association information of at least part of the cleaning lines so as to form a node skeleton tree with midpoints being represented by nodes, wherein the midpoint association information comprises location information of the node corresponding to each midpoint, location information ofa father node and number information of child nodes of the father node; and compressing the node skeleton tree in the process of traversing upward from the current node in the node skeleton tree or inthe process of traversing upward from the current node and a target node in the node skeleton tree so as to determine the shortest planned path from the current node to the target node. The shortestpath planning method has the advantages that the algorithm is low in time complexity, the occupied storage space is small, and the consumed operation time is less.

The invention discloses a multi-AGV scheduling method based on petri network decomposition. The method comprises the following steps: step 1, converting a warehouse topological graph into a collision-free petri network model; decomposing the whole petri network model into sub-networks according to the drivable route of the single AGV; step 2, adopting a Dijkstra algorithm to realize global shortest path planning of the single AGV, and further adjusting the obtained algorithm according to the actual motion condition of the vehicle; step 3, establishing a target function; step 4, taking a staticshortest path obtained by a single AGV in each sub-network as a basis; using an external point penalty function method to carry out path iteration, obtaining collision and deadlock problems existingin the operation process of multiple AGVs, analyzing and locally optimizing the types of collision and deadlock, locally optimizing the path by taking time optimization as a principle, and generatingan optimal collision-free scheduling scheme. The method is high in operation efficiency, high in reaction speed and high in adaptability.

The invention discloses a path planning method for an orchard tracked robot. An agricultural robot path planning software platform based on A* and B spline algorithms is achieved by using C# in conjunction with ArcGIS Engine secondary development programming; a map for agricultural robot path planning needs to be drawn first; then Windows desktop application software is developed based on ArcGIS Engine component and C# language; on such basis, A* algorithm is compiled so as to arrive at robot shortest path planning and B spline curve algorithm smooth pathing, and to arrive at optimal path planning for an agricultural robot. Agricultural robot path planning based on A* and B spline algorithms is achieved herein, operation of the agricultural robot according to the optimal path is achieved, and efficiency and intelligence of agricultural operations are improved.

The invention provides a navigation control system applying a plurality of mobile robot platforms. The navigation control system is capable of walking on a magnetic stripe track in a wireless control manner and obtaining a specific position by virtue of a self RFID sensor. The invention also provides a control method of the navigation control system applying the plurality of mobile robot platforms. The control method is used for planning shortest paths of the plurality of mobile platforms.

The invention discloses an AGV (Automated Guide Vehicle) path planning method based on the minimum turning cost. The method comprises the following steps: an upper computer system reads path and nodeinformation according to a map model; station demand information is received, an idle AGV nearest to the station is selected, and the coordinate information of the AGV is read; with the AGV coordinates as a starting point and the station coordinates as an end point, a shortest path planning algorithm is called to search for the shortest path between the starting point and the end point; and the shortest path is converted to a motion instruction, and a control processing system controls the AGV to execute a task. According to the AGV path planning method based on the minimum turning cost, a large number of AGV turnings can be avoided, the problem that the existing AGV path planning method does not consider the turning time consumption and thus, the total consumed transportation time of theAGV driving path is not the shortest can be effectively solved, and the transportation efficiency is improved.

The invention discloses an AGV shortest path planning method. The method comprises a step of setting a starting point and an ending point of an automated guided vehicle (AGV) based on a preset map coordinate system, wherein the map coordinate system includes a path node, a step of determining the direction of travel of the AGV according to a preset algorithm and determining marked nodes from the path node according to the direction of travel, and a step of generating a shortest path of the AGV according to the starting point, the marked nodes and the ending point. The invention also disclosesan AGV shortest path planning device and a computer-readable storage medium. The invention is suitable for the shortest path search of the AGV in a factory workshop, the calculation is simple, and thecomplexity is low.

The invention provides a motion planning and cooperative positioning method and device for an unmanned vehicle network formation. The method includes the steps that in one planning cycle, according tothe acquired initial pose, target pose and kinematic parameters of each vehicle in the unmanned vehicle network formation, a path plan is generated, wherein the unmanned vehicle network formation includes a piloting vehicle and several following vehicles; the path plan is sent to each following vehicle so that each following vehicle can complete the corresponding target pose according to the pathplan. According to the motion planning and cooperative positioning method and device for the unmanned vehicle network formation, the piloting vehicle and the following vehicles are set by adopting alayered system structure; in the path planning part, various constraint conditions are considered, and a Dubins shortest path planning way is adopted; in the cooperative positioning part, through extended Kalman filtering, information fusion is performed by using UWB ranging, inertial navigation, a gyroscope and other means facilitating collection, the uncertainty of pose estimation is eliminated,and the positioning efficiency is improved.

The invention discloses a three-dimensional scene path navigation platform for a drone and a three-dimensional improved path planning method thereof. The method comprises loading DEM map data througha platform based on Unity3d, displaying a three-dimensional scene, carrying out VS2010C++ programming to obtain a DEM-based three-dimensional improved path planning method, acquiring a flight safety path of the drone, acquiring path detection and planning effects through a Matlab2012a drawing plan, introducing a drone model, acquiring the current navigation information of the drone through combination with an miniAHRS attitude sensor, fusing the path planning algorithm to the three-dimensional scene, and carrying out three-dimensional display on the drone flight state and the obstacle avoidance process in real time. The three-dimensional improved path planning method combines the DEM-based improved A* algorithm calculation of a first path, linearization of the first path based on the Bresenham line drawing algorithm and Bezier curve smooth optimization of the linear path. The method has short path planning time, displays a flight state in real time and dynamically displays the path planning and obstacle avoidance process.

The invention discloses a method for planning a shortest path of agricultural machinery based on a Dijkstra algorithm, and relates to a method for planning a shortest path. The method comprises the following specific operation steps of: constructing a grid map of an operation area of the agricultural machinery, the grid width being divided according to a vehicle body width; enabling the vehicle body width to be (2i+1) times the grid width according to an accuracy requirement and an actual need; dividing the grid map into a passable state and an impassable state according to unmanned aerial vehicle aerial survey and obstacle distribution fed back by a sensor; and in order to control the diffusion of optimized nodes in a reasonable range, introducing a maximum estimation value K. According to the method provided by the invention, a group of better nodes are selected and the maximum estimation K is introduced to limit the diffusion degree of the group of nodes, and the group of better nodes is taken as a vertex set of the Dijkstra algorithm, so that the search time is reduced, and meanwhile, a found path is guaranteed to be an optimal path rather than a better path.

The invention relates to an intelligent distribution path planning method based on time reservation. According to the intelligent distribution path planning method based on time reservation, expresses are divided into A class orders and B class orders according to the client distribution time requirements and a brand-new distribution scheduling method is designed based on the division result, and a shortest path planning design method is introduced through combination of the load of each distribution vehicle so that each distribution vehicle is enabled to perform distribution according to the optimal path planning, accurate distribution for the A class orders and the B class orders can be realized, the customized distribution service can be provided for the user, the success rate of distribution can be enhanced and the distribution cost can be saved.

The invention discloses an automatic unmanned plane express delivery shortest path program method. The address information of each to-be-delivered express is scanned through scanning equipment, all target sites of a present delivery task are determined, and the shortest path starting from an express distribution center, passing by all the target sites and finally returning back to the express distribution center is programmed. An initialization algorithm is firstly provided, a population including a series of molecules is generated, and each molecule represents a feasible path satisfying the delivery task; four corresponding chemical reaction sub algorithms are further provided, including a decomposition algorithm, a synthesis algorithm, a local search algorithm and a greedy search algorithm, iteration is carried out according to relevant rules, the molecule population is made to realize continuous evolution till iteration termination conditions are satisfied, a molecule of the population having the smallest potential energy is found out, and the optimal path is programmed. The method is advantaged in that on the condition that the delivery task of all the target express sites is accomplished, the total flight path of the unmanned plane is the shortest, the total consumption time is the shortest, consumption energy is effectively reduced, and express delivery efficiency is improved.

The invention relates to a road grade-based shortest route-planning algorithm. The road grade-based shortest route-planning algorithm comprises the following steps: firstly, data preparation and data preprocessing; secondly, road network hierarchical expression, wherein road network grade division and road grade-based hierarchical expression are included; thirdly, road network passing time calculation; fourthly, shortest route approximate calculation. According to the road grade-based shortest route-planning algorithm provided by the invention, a large number of experiments prove that the passing capacity of different grades of roads are taken into full consideration; the passing time is taken as a judgment standard; a calculation method is general; the results are more precise; in emergency rescue, if a fault road section in a rod network can be excluded by road detection information, the real-time passing speed is calculated by acquiring traffic flow, and the planning result is more accurate.

The invention discloses a strip-shaped robot path planning method based on a self-learning ant colony algorithm. The strip-shaped robot path planning method based on the self-learning ant colony algorithm is characterized by comprising the following steps: step 1, environment modeling; step 2, initializing stage; step 3, initial searching; step 4, overall updating of grid map pheromone; step 5, self-learning searching; and step 6, outputting of a planning path. The strip-shaped robot path planning method based on the self-learning ant colony algorithm is greatly improved for an ant colony algorithm calculating process, a self-learning strategy is introduced, grid-process environment modeling is treated specially, by the used grid method, the ant colony algorithm deals with a strip-shaped robot path planning process under the condition that barrier cells do not need to be expanded, a new shortest path calculating method is provided, thought of machine learning is fused in the ant colonyalgorithm, the efficiency of path planning of the ant colony algorithm is improved by effective combination of methods such as pheromone, heuristic information, positive feedback and greedy search, and a strip-shaped robot can pass through a narrow channel according to the outline of the strip-shaped robot so as to implement the shortest path planning.

The invention relate to a shortest route planning and navigating method. The method comprises the following steps: step one, according to the user preference, adding a user preference weight to a route distance weight, and using a formula: M(n)=P(n)+Q(n)*A to preprocessing the data to obtain a comprehensive evaluation weight M(n); step two, selecting a special node that a user has to pass by, taking the special node as the cutting point, cutting the road network into a first network and a second network by the cutting point, wherein the first network is a node network from the start point to the special node, and the second network is a node network from the special node to the final point; step three, replacing the route distance weight P(n) in Dijkstra algorithm by the comprehensive evaluation weight M(n) obtained in the step one, and then using the improved Dijkstra algorithm to carry out shortest route on the first network and the second network so as to obtain the shortest route from the start point to the special node to the final point.

The invention provides a shortest path planning method based on a unidirectional searching model. According to the geometric principle that the line segment between two points is the shortest, in thesearch process, the path is made to be close to a straight line. In comparison with the classic Dijkstra algorithm method of expanding outwards layer by layer with the starting point as the center, the method of the invention has the following advantages: the number of search nodes is small, memory usage is small, and the calculation efficiency is high. In a road network with more than 500 nodes,the calculation efficiency is improved by 90% and above; and through parameter setting, forbidden road sections are avoided or nodes that must be passes by are passed in the path planning process. Then, the method is more suitable for the path planning under actual traffic conditions.

The present invention relates to a scenic spot guide system based on a smart phone APP and belongs to the technical field of scenic spot guide. The scenic spot guide system comprises a smart phone equipped with a scenic spot guide APP application and a scenic spot monitoring center management system. The scenic spot guide APP is associated with the scenic spot monitoring center management system,and the scenic spot guide APP and the scenic spot monitoring center management system realize information synchronization through a wireless communication network. The scenic spot guide APP includes aregistration function module, a positioning function module, a movement recording function module, a guide function module, a scenic spot evaluation function module and a one-button call function module. The scenic spot monitoring center management system performs management and makes plans for tourism information resources in a scenic spot on the basis of relevant information collected by the scenic spot guide APP, has a guide function of planning the shortest route selected based on a personalized scenic spot of tourists, and also has a function of planning a route of a scenic spot or a project which tourists need to queue to experience on the basis of the shortest time algorithm.

The invention discloses a shortest path planning parallelization method based on cooperative computing of a CPU and an MIC. The shortest path planning parallelization method comprises the following steps: S1, whole-network node shortest path planning parallelization design is carried out; S2, one pthread thread is established aiming at each piece of computing equipment by CPU and MIC control threads; S3, a task package between the CPU and the MIC is dispatched; the task package between the CPU and the MIC is distributed by adopting a dynamic task distribution mode; and S4, all nodes are computed and the thread is controlled to quit. According to the shortest path planning parallelization method, the advantages of the cooperation of the CPU and the MIC is sufficiently utilized; and meanwhile, multi-thread parallel computing of the CPU and the MIC is used for accelerating a whole-network node path planning process of a large-size path network. Meanwhile, the invention provides a dynamic distribution manner of the computing tasks between the CPU and the MIC; and a corresponding program can be optimally suitable for CPU / MIC equipment with different computing power ratios through the dynamic task distribution manner, so that the computing tasks can be distributed by the optimal ratio and the optimal cooperation efficiency is realized.

The invention provides a rapid K shortest path planning method applied to a GPS. The method applies a dynamic load data searching method and an elicitation type searching thought to recursively calculate K shortest paths: an A* algorithm is utilized to obtain the shortest paths, bead edges of each node on a former shortest path are traversed successively so that a candidate path collection is obtained; recursive searching from the ith shortest path so that the i+1th shortest path is obtained. Advantages of the rapid K shortest path planning method applied to the GPS are that the K shortest paths are rapidly obtained and applied to the GPS so that a problem that the GPS is single in navigation path is solved to a certain degree. Besides, K path schemes are provided for users to select, other needs in driving process of the users are fully considered and practicality of the device is obviously enhanced.

A cleaning robot and a shortest path planning method based on a cleaning robot are disclosed, a plurality of cleaning lines are formed by controlling the cleaning robot to perform cleaning in an area according to a zigzag-shaped path; association information of midpoints of at least a part of the cleaning lines is recorded to form a node skeleton tree in which midpoints are represented by nodes, the association information of each midpoint includes: position information of a node corresponding to the midpoint, position information of a parent node, and information of the number of child nodes of the parent node; in the process of traversing upwardly from a current node or traversing upwardly from both a current node and a target node in the node skeleton tree, the node skeleton tree is compressed, so as to determine the shortest planned path from the current node to the target node.

The invention discloses a planning method and system for a shortest path. The method comprises the following steps of establishing an initial grid map according to the environmental information, and respectively marking the grid points of the grid map as a starting point, candidate points and obstacle points; traversing the candidate points to calculate the minimum step length from the candidate points to the starting point so as to form a minimum step length matrix graph; and selecting one of the candidate points as an ending point, and performing the recursive traversal through a reverse depth-first algorithm to obtain a shortest path plan from the ending point to the starting point. The method and the system of the scheme are based on a grid map global expansion algorithm, not only solve the problem that the final path is the shortest path, but also greatly reduce the time complexity and the space complexity of the operation.

The invention discloses a fast shortest-path planning method based on road chains and aims to improve problems that the list open in an existing A* algorithm contains many nodes, the A* algorithm is time-consuming and a planned path has many turns. The fast shortest-path planning method includes the steps of firstly, generating a node topology table K according to a city road network; secondly, generating a road chain topology table U according to the node topology table K; thirdly, creating a list open and a list closed; initiating the list open, maintaining the list open and the list closed according to the road chain topology table U, and marking out the shortest traveling path. The fast shortest-path planning method has the advantages that data units which need to be processed in path planning are reduced, path planning time is reduced, road integrity and visual consistency are kept, turns in the output path are reduced, and the method is applicable to vehicle or walking navigation.

The invention discloses a path planning method based on a non-display topology vector map. The method comprises the steps of: (1) constructing a basic hexagonal grid; (2) performing terrain quantification by using DEM data and the vector map, abstracting an original highway map layer as a road attribute on the hexagonal grid, and forming a topological relationship required during A * algorithm calculation; (3) recording original road information associated with an edge; (4) selecting a starting point and an end point of a path, and calculating the shortest path from the starting point to the end point on the hexagonal grid by using an A * algorithm; (5) combining the recorded original highway information with the calculated shortest path result to reversely analyze a shortest path planningresult of the vector map; and (6) judging whether the shortest path needs to be adjusted. When the shortest path is unreasonable due to the terrain quantification and irregular data and other reasons, related data can be manually adjusted, and recalculation is performed to obtain the shortest path. By adopting the path planning method disclosed by the invention, the shortest path planning problemwhen a user has only the non-display topology vector map is solved.

The invention provides a system for improving crop picking precision and controlling a mechanical arm to move to automatically find a way based on computer vision. According to the system, the work ofYolact on ResNet-101 is combined,; a traditional two-stage instance segmentation model is modified into a one-stage model, 64 robust masks are generated from the deepest layer, prediction coefficients are output according to four layers of feature pyramid networks in sequence, and mask coefficients of different layers are endowed with different weights to improve the mask precision. Not only is aplant positioned, but also a mask is generated to tightly cover the crop pixel by pixel, and the central point and contour coordinates of the crop are output. Then an A * algorithm and a heuristic function of the A * algorithm are used for sequentially utilizing the coordinates to carry out piecewise shortest path planning and generate corresponding G code statements to control a mechanical arm to move between plants and on the plants, and finally a mechanical claw is combined with crop center points and contour coordinates to pick crops.

The invention discloses a common distribution route optimization algorithm in a takeout centralized area, belonging to the field of logistics distribution, which is used for solving the problems of long distribution time and waste of transportation capacity in the distribution process in the takeout centralized area. The embodiment of the invention comprises the following steps: step 1: a centralized meal delivery route model hypothesis is assumed, and the basic conditions satisfied in the delivery process are assumed; 2, model that shortest route model, establish equations and constraining conditions to determine a shortest route plan model; 3, that tabu search algorithm is sol, and the shortest route in the delivery process is solved under the conditions that the model and the hypothesisare established, and the computer simulation is carry out by using the MATLAB software. The invention can realize the unified distribution of takeout goods with the same receiving location, reasonably plan the takeout and delivery commodity routes, save the transportation capacity and reduce the total distribution time.

The invention discloses an intelligent vehicle route planning method based on an improved Floyd algorithm. The method comprises the following steps: firstly, numbering parking spots of parking spacesof a parking garage according to a spatial order, and importing a weight matrix between the parking spaces of the parking garage; then, performing calculation according to the weight matrix and the improved Floyd algorithm to obtain a distance matrix and a route matrix, and storing the route matrix in a local system; after a starting parking space serial number and a target parking space serial number are input, searching the route matrix to obtain all possible shortest routes; and finally, displaying all possible equivalent shortest routes in a client interface one by one. According to the method disclosed by the invention, the shortest route planning from the parking spot of the starting parking space to the parking spot of the target parking space in an underground parking garage is achieved, all possible equivalent shortest routes can be obtained, and a client pops up a prompting sign at a route turning point, thereby having practical reference significance for the route planning of intelligent driving of vehicles.

The invention relates to a scenic area tour-guide system based on APP of a smart phone, belonging to the technical field of scenic area tour guide. The scenic area tour-guide system comprises the smart phone equipped with the scenic area tour-guide APP and a scenic area monitoring center management system, wherein the scenic area tour-guide APP and the scenic area monitoring center management system are interrelated, and realize information synchronization through a wireless communication network; the scenic area tour-guide APP comprises a registering module, a positioning module, a movement recording module, a tour-guide module, an evaluating module and a one-key calling module; the scenic area monitoring center management system is used for realizing the shortest path planning tour-guidefunction based on individual scenic spot selection of tourists and the path planning tour-guide function realizing experiencing of the scenic spots or items needing queue-up in the scenic areas basedon the shortest time algorithm according to the relevant information collected by the scenic area tour-guide APP. For the APP of the smart phone provided by the invention, the popularization and useare convenient, the construction cost is low, the time waiting problem caused by queue-up for experiencing the scenic spots or the items in the scenic areas is fully considered, and thus congestion can be effectively avoided.