65results about How to "Improve path planning efficiency" patented technology

The embodiment of the invention discloses a route planning method and device. The method comprises the steps of acquiring a route planning request containing a start point and an end point; acquiring an experience weight set of a section between the start point and the end point according to the route planning request, wherein the experience weight set is determined according to historical routes of a user; according to the experience weight set of the section, performing route planning for the route planning request by adopting a heuristic search algorithm. According to the technical scheme provided by the embodiment of the invention, an existing route planning technology can be optimized, and planning speed and planning result accuracy can be improved.

The invention discloses a dynamic path planning method of a robot by combining an A* algorithm and a VFH obstacle avoiding algorithm. The method comprises steps of representing the environment where the robot is located into a grid map and searching a global initial path in a grid map by use of the A* algorithm; when the robot moves towards a target point along the initial path, judging whether the robot comes across an obstacle, if yes, using the VFH algorithm to carry out obstacle avoidance, or else allowing the robot to move towards the target point; during obstacle avoidance, firstly, setting a stage target point in the initial path, generating an obstacle avoiding path between the current position and the stage target point, moving for one step forwards, updating the current position,judging whether the space between the current position of the robot and the stage target point is shielded, if yes, re-calculating the obstacle avoiding path, or else, allowing the robot to move forone step forwards towards the stage target point along the obstacle avoiding path; and carrying out circulation until the robot reaches the stage target point, returns back to the initial path and continues to move towards a destination. By combining the two algorithms, efficiency of path planning of the robot is improved; and the autonomous navigation ability of the robot in the indoor dynamic environment is ensured.

The invention provides a pilotless vehicle path planning and controlling system, the pilotless vehicle path planning and controlling system comprises a route information acquiring module for acquiringinformation of a starting point and a terminal point of a route, a master control module for generating a path of a pilotless vehicle through a path planning module and transmitting the path to a locating control module through a communication module, the locating control module for controlling the driving of the pilotless vehicle, locating the running pilotless vehicle and feeding back a locating result and the vehicle driving state to the master control module through the communication module, so that the pilotless vehicle drives automatically according to the path generated by the path planning module. Meanwhile, a path planning and controlling method is provided. The pilotless vehicle path planning and controlling system can respond to the operation demand of the pilotless vehicle onany site. The driving path of the pilotless vehicle is designed and the pilotless vehicle is efficiently operated through inputted locating coordinates of the starting point and the terminal point. The operation efficiency of the pilotless vehicle is greatly improved, the comfort level of the user is improved, and the labor cost is reduced.

Embodiments of the invention disclose a method for processing road network data in a navigation map, which is used for reducing computational complexity during data loading. The method of the embodiments of the invention comprises the following steps: obtaining basic road network data from a navigation map, wherein the basic road network data are road network data in a layered topological grade; deleting the road network data at the lowest layer in the basic road network data; combining road network data with a same road and without an intersect node in the basic road network data with deleted road network data at the lowest layer so as to obtain layered road network data; storing the layered road network data. The embodiments of the invention additionally disclose a device for processing road network data in navigation map, and the embodiments of the invention can increase the path planning efficiency of navigation equipment.

The invention puts forward a route planning method and a mobile robot. The route planning method comprises the following steps that: establishing a grid map of an environment to be tested; labeling the position of an obstacle in the grid map; according to the current position of the mobile robot and a target point position, utilizing an A* algorithm to search to obtain route nodes; obtaining an inflection point in the route nodes; carrying out a point spreading operation on the inflection point; through the point spreading operation, obtaining a plurality of sample points, and screening samplepoints which conform to the requirements; judging whether the mobile robot can directly achieve the target point position from the sample points or not; and obtaining an optimal route. By use of themethod, the point spreading operation is combined with the A* algorithm to search the route, search for irrelevant areas on the grid map is reduced, obstacles in the environment can be avoided, the collision of the mobile robot is reduced, route planning time is effectively shortened, route planning efficiency is improved, in addition, the walking safety of the mobile robot is improved, and the experience of a user is improved.

The invention discloses a path planning method combining a dynamic step length RRT* algorithm and a potential field method, and the method comprises the steps: guiding an extension tree to extend towards a target point through constructing a target point suction potential field and an obstacle repulsion potential field, reducing redundant paths, and improving the path planning efficiency; and meanwhile, calculating the extension step length of the extension tree according to the nearest Euclidean distance between a nearest point and the obstacle such that the algorithm convergence speed and path smoothness are both considered, and the obstacle avoidance flexibility of the robot is improved.

The invention discloses a mobile robot full-coverage traversal chaotic path planning method. The method comprises the following steps: carrying out basic design of a mobile robot full-coverage traversal chaotic path; designing a distance evaluation index of adjacent sub-target points in a robot path planning locus; performing operation sub-space division on a work space of a robot; performing affine transformation on a chaotic kinetic equation in operation subspaces; designing a mixed iteration strategy; and carrying out iterative computation based on a given initial point. First of all, a basic chaotic plan planning method is designed, in order to enable the designed chaotic path planning method to be more feasible, then the mixed iteration strategy combining iteration of a whole work area with iteration of the sub-spaces divided by the work area is employed, traversal of the work space is realized, and the chaotic feature of the robot planning locus is maintained basically unchanged, such that the iteration step pitch of the mobile robot is effectively reduced and effective tracking of a robot controller is realized.

The invention discloses a robot path planning method based on an improved fireworks explosion algorithm. The method comprises the steps of initializing a fireworks population, and generating multiplepaths of a robot from an origin to a destination; performing mutation operation on the fireworks population; moving each fireworks path to the position of a first optimal fireworks path according to acrossover probability; mapping the fireworks paths covering infeasible regions; selecting a second optical fireworks path; judging whether a current iteration number reaches the maximum, and if yes,outputting the second optical fireworks path; and otherwise, further selecting the N-1 fireworks paths from the mapped fireworks population for explosion, generating the new path of the robot from theorigin to the destination, and thus acquiring the next generation fireworks population. Through defining the crossover probability, each fireworks path has a certain probability of being crossed withthe optimal fireworks path, and moves to the position of the optimal fireworks path, the convergence speed is improved, the robot path planning speed is improved, and the path planning efficiency isimproved.

The invention discloses a path programming method and apparatus. The method comprises the following steps: rising a current map layer if a distance between a current search position and a path end point position is greater than or equal to a first distance threshold, and searching a path from the current search position to the path end point position according to navigation data corresponding to the risen map layer; searching a path from the current search position to the path end point position according to navigation data corresponding to the current map layer if a distance between the current search position and the path end point position is less than the first distance threshold and is greater than or equal to a second distance threshold; and lowering the current map layer if a distance between the current search position and the path end point position is less than the second distance threshold, searching a path from the current search position to the path end point position according to navigation data corresponding to the lowered map layer if the lowered map layer is a lowest map layer, and searching a path from the current search position to the path end point position according to the navigation data corresponding to the lowered map layer if the lowered map layer is not the lowest map layer.

A shortest annular path navigation method for an automated guided vehicle and the automated guided vehicle are disclosed. The method includes generating an adjacent matrix graph including actual formation of a road segment in a workplace according to node coordinate information in the workplace; finding out a shortest one-way annular path required by a task in the adjacent matrix graph; arranginga millimeter-wave radar in the workplace; measuring, by a gyroscope, the velocity, direction and acceleration of the automated guided vehicle and feeding the velocity, direction and acceleration backto a terminal controller in real time; performing calculation, by the terminal controller, according to feedback information from the millimeter-wave radar; and controlling, by an industrial personalcomputer, a drive module to complete position correction. A one-way annular path planning manner is adopted and a Dijkstra algorithm is adopted to achieve shortest path searching between two points ina non-negative weight graph in a shortest path algorithm, and the path planning efficiency of the automated guided vehicle is increased, thus simplifying path planning. In addition, by utilizing real-time correction through the millimeter-wave radar and the gyroscope, that the automated guided vehicle is ready to reach a target position through the shortest path is ensured.

The invention provides a multi-unmanned aerial vehicle path planning method. The method comprises the following steps: constructing a multi-unmanned aerial vehicle path planning scene model; constructing an undirected complete graph of the monitoring area; carrying out the task allocation on the unmanned aerial vehicle group; and obtaining a path planning result of the unmanned aerial vehicle group. An undirected complete graph of a monitoring area is constructed, a monitoring point traversed by each unmanned aerial vehicle and a starting point are modeled into the undirected complete graph, point transfer and exchange operations are carried out between the undirected complete graphs to continuously optimize a task allocation result, and a minimum Hamiltonian ring of each unmanned aerial vehicle is obtained on the basis of the optimized task allocation result; point transfer is carried out between the minimum Hamiltonian rings, the task allocation result is further optimized, and the path planning result of the unmanned aerial vehicle group is obtained, so the flight distance of the unmanned aerial vehicle with the maximum flight distance in the multiple unmanned aerial vehicles is minimum, and the flight time is the shortest.

The invention relates to a robot path planning method and system. The method comprises the following steps: acquiring environmental information in a robot operation scene; converting the environment information into a global grid map; sensing and acquiring a dynamic target object in a running scene by using sensing equipment, and updating the position of the dynamic target object in the global grid map at a specific frequency; dividing the global grid map into a plurality of sub-graphs, calculating the sub-graphs to be passed through, and obtaining sub-graph global paths of the sub-graphs at acertain frequency; and calculating a local path from the current position of the robot to the sub-graph global path end point of the sub-graph where the current robot is located at a certain frequency. The system for realizing the method comprises a sensing module, a wireless communication module, a cloud robot scheduling module and a robot body module. The method and the system have the advantages that the path planning efficiency in a complex high-dynamic scene is high; the trap problem in a complex scene is solved, and the efficiency and universality of a path planning algorithm are improved; the application range is wide.

The invention relates to a forklift global path planning method. The forklift global path planning method comprises the steps of establishing a cartographic model of a forklift working environment according to an actual working environment of a forklift and a grid method; encoding a forklift path and randomly initializing N particles; on the basis of the length of the forklift path, establishing afitness function according to safety degree and smoothness of forklift working; generating a random number rand (0, 1); judging whether the random number rand (0, 1) reaches a probability condition using an elitist reverse learning strategy or not; updating global optimal particles according to a judging result; judging whether a convergence condition is reached or not; and if the judging resultis that the convergence condition is reached, outputting an optimal path; and otherwise, returning to the step (4). The forklift global path planning method provided by the invention has the advantages that the convergence speed of particle swarm optimization is increased, the forklift global path planning efficiency is enhanced, and the planed path length is effectively reduced.

The invention provides a method of constructing a road network of a digital map. Firstly, a first administrative division is selected, and a plurality of second administrative divisions with a presetrange with the first administrative division are acquired; then, the path starting point and the path ending point of the first administrative division are acquired, and according to the path startingpoint and the path ending point of the first administrative division, an exploration point set for the first administrative division is determined; and finally, starting from each exploration point sequentially, passable paths of exploration points reaching the second administrative divisions are acquired to form a road network. In the method, the exploration points are acquired firstly, the paths are then explored based on the exploration points, and a customizable road network is formed. Through adjusting the administrative division number or a connectivity algorithm, the scheme can changethe road network in any region. The obtained road network is combined with a path planning algorithm of a navigator, and the path planning efficiency of the navigator can be improved. Besides, the method can automatically calculate the road network, the manual operation is reduced, and repeated work can be avoided.

The invention discloses a vehicle path planning method based on chaos gravitational search. The invention adopts the chaotic gravitational search to plan the path of a vehicle. In the chaos gravitational search, each individual stores an order weight of each transport point. In the process of evolution, chaos gravitational search first performs a basic operation operator of the gravitation search, then randomly selects one individual and performs a chaotic local search operation on the selected individual to enhance the algorithm search performance. According to the invention, the efficiency of vehicle path planning can be improved.

The invention discloses a path planning method, a path planning device, equipment and a storage medium. The method comprises the following steps that: a to-be-served task edge is determined accordingto a service request; a task matrix is determined on the basis of the to-be-served task edge; and a planned path is determined according to the task matrix and a preset path planning model. Accordingto the technical schemes provided by the embodiments of the invention, the task edge is used as a minimum unit for providing services, and therefore, path planning efficiency can be improved, the conveying efficiency of an unmanned express delivery vehicle can be improved, and calculation cost can be reduced.