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

The invention discloses a traffic data information service system and a method for realizing a traffic data information service. The method comprises the following steps: acquiring traffic data information through a TSB (Technical Service Bulletin), and outputting the information to a traffic data acquisition unit of a monitoring dispatcher; receiving the traffic data information, obtaining operation state information of each traffic data processor in the system through a cloud computing architecture, distributing cloud computing resources, splitting the received traffic data information according to the cloud computing resources which are distributed to the traffic data processors, and outputting the information to the corresponding monitoring dispatchers of the traffic data processors; receiving the traffic data information, performing abnormal data cleaning processing and missing data compensation processing, performing blocked road condition calculation and travel time calculation according to the processed traffic data information, and outputting calculation results to the traffic data processors of a traffic data information server; and receiving the calculation results and publishing the information by the traffic data information server. By adopting the system and the method, the path planning efficiency can be improved.

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.

The invention provides an abstract method and device of road network topology, belonging to the technical field of map data processing. The method comprises the following steps: reading attribute information of an internal node and attribute information of an internal segmental arc in original road network data; respectively generating attribute information of an abstract node and attribute information of an abstract segmental arc according to the attribute information of the internal node and the attribute information of the internal segmental arc; determining a node to be deleted in the original road network data according to the attribute information of the abstract node and the attribute information of the abstract segmental arc, and deleting the node to be deleted in the original road network data; and according to the attribute information of the abstract node and the attribute information of the abstract segmental arc, carrying out reconstitution processing on a road network the node of which to be deleted is deleted, thereby reducing the number of directed segmental arcs in the road network on the premise that the road network topology relation does not need to be changed,and therefore, the road calculating efficiency is effectively improved.

The invention discloses an unmanned aerial vehicle path planning method based on a transfer learning strategy deep Q-network (DQN). The method comprises the steps of: firstly carrying out the modelingand description of a dynamic environment where a UAV is located through adoption of a grid method, and building a state space model and an action space model of the UAV; secondly, initializing network parameters of a DQN and the current state of the unmanned aerial vehicle; training the DQN by adopting a return mechanism based on a social force model under the static environment model to obtain anetwork weight and an optimal action value; migrating the network weight and the optimal action value obtained by training in the static environment to the dynamic environment by using transfer learning, and continuing neural network training to obtain an action to be executed by the UAV; and finally, calculating the position of the unmanned aerial vehicle at the current moment to achieve path planning of the unmanned aerial vehicle in the dynamic environment. According to the method, the problems of the low DQN training convergence rate, the non-ideal path planning and the low success rate when the unmanned aerial vehicle performs path planning in a dynamic environment are effectively solved.

The invention discloses a path planning method based on a mobile robot. The method comprises the steps that based on a polygonal barrier planar model, Q-IGA is utilized to collaboratively search for the most appropriate control point P which serves as a control point of a Bezier curve, and the control point is utilized to generate an optimal path; the difference between difference paths in a population in each iteration is calculated, a judgment criterion is added to a selection operator for optimization, and the diversity of feasible solutions in the population is guaranteed; and a fitness function considering a barrier distance, a turning angle and a robot volume is constructed with the optimization objective of a maximum fitness function value. Through the method, the situation that steps are tedious when the optimal path is obtained through direct fitting search by use of the Bezier curve in robot path planning is avoided, it is guaranteed that the path planning process is completed efficiently, consumed time is short, and path planning efficiency is higher.

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 relates to a dynamic planning method and device based on automatic driving. The method comprises the following steps: firstly, generating a global road-level path planning result; then,in the global road-level path planning result, selecting a road node in a specified range in front of the vehicle as a local destination node; performing short-distance lane-level path planning from the current position of the vehicle to the local destination node; and when the vehicle approaches the local destination node, repeating local destination node selection and lane-level path planning until the vehicle reaches the destination. Firstly, global road-level path planning is generated, so that the initial path planning efficiency can be effectively improved; then, on the basis of road-level planning, short-distance lane-level planning is carried out, so that the accuracy of local path planning is improved on the premise of ensuring the accuracy of global planning, the data processingload in unit time is reduced, and the data processing efficiency is improved.

The invention provides a blisk blade section online measurement path planning method. The blisk blade section online measurement path planning method comprises the steps of: automatically planning aninterference-free section measurement path according to a blade stacking axis, a set section height, a measuring head and measurement parameters. According to the blisk blade section online measurement path planning method, planning of the blade on-line measurement section measurement path is achieved, the non-interference measuring rod direction of each measurement point is automatically planned,the method is used for blade section gear detection in milling, and the path planning efficiency is high. The whole blisk blade section online measurement is adopted to avoid the problem of efficiency loss caused by disassembly off-line measurement in blade finish machining, improve the utilization rate of a machine tool, rapidly obtain the contour error and characteristic parameters of a detection section gear, provide direct basis for a technician to correct a blade machining tool path or adjust machining parameters in the next step, and improve the production efficiency.

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 relates to a robot path planning method based on a multi-intelligent optimization parallel algorithm, and belongs to the technical field of robots. The method comprises the following steps: S1, realizing path planning of the mobile robot by utilizing the global search capability of a particle swarm optimization algorithm; S2, using a particle swarm optimization algorithm as a trunk, embedding selection, crossover and mutation operators in a genetic algorithm (GA) and chemotactic operation in a bacterial foraging algorithm (BFO) to enhance local search capability; S3, optimizing the path by using a parallel strategy, and improving the path planning efficiency of the robot; and S4, designing a grid environment map for evaluating the superiority of the algorithm. In a complex multi-obstacle environment, compared with other algorithms, the multi-intelligent optimization parallel algorithm makes up for the defects of a PSO algorithm, the local and overall search capability is greatly improved, the path planning speed is high, the path distance is short, and meanwhile higher robustness is achieved.

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 discloses a shortest annular path navigation method for an automatic guide transport cart and the transport cart. A shortest one-way annular path required by a mission is found out in anadjacent matrix through a Dijkstra algorithm; the shortest one-way annular path determined in step 2 is input into a centrally-controlling machine, and an industrial personal computer controls a driving module to drive the automatic guide transport cart; a binocular vision sensor and a high-speed image collecting system collect information, and determine the position of the cart in a ground coordinate system; the centrally-controlling machine sends position correcting information to the industrial personal computer according to the actual position and the movement state. By means of the one-way annular path planning method, the Dijkstra algorithm is adopted for achieving the shortest path search between two points in a non-negative-weight map in a shortest path algorithm, the path planning efficiency for the automatic guide transport cart is improved, and thus the difficulty of path planning is reduced; moreover, through real-time correction of the binocular vision sensor and the high-speed image collecting system, it is guaranteed that the automatic guide transport cart is prepared to arrive at the target position through the shortest path.

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 embodiment of the invention provides a biped robot path planning method and device and a biped robot, and the method comprises the steps: generating a candidate node set of a next foothold through the parameters of the biped robot and the joint movement information of a current node, adding effective candidate nodes in the candidate node set to the priority queue to select optimal nodes to achieve expansion of the next node, wherein the output optimal nodes generate a foothold sequence from the initial node to the target node so that the path node search amount of the biped robot during double-leg crossed landing can be greatly reduced; and thus the path planning efficiency is improved.

The invention discloses a high-usability high-reliability and high-efficiency fire evacuation indicating system and a method. The system adopts a three-layer system structure formed by an evacuation indicating control host machine, passageway evacuation indicating control sub machines and passageway detection / indicating devices, wherein the passageway evacuation indicating control sub machines are positioned at stairs of each floor, each unit of the system exchanges information through an element interconnect bus (EIB), and the passageway detection / evacuation indicating devices are directly embedded into the control sub machines. Wireless backup communication is additionally added between the host machine and the sub machines (the passageway detection / evacuation indicating devices), and the integral reliability and the usability of the system are enhanced. The secondary threshold warning strategy of a composite fire hazard detector is adopted, a corresponding information processing method is used as an auxiliary measure, in addition, evacuation paths are continuously regulated according to the real-time fire conditions, the goals of shortening the warning time and reducing the mistake warning rate are reached, and the usability of the evacuation indicating system is further improved. The space positions of the detection / indicating devices are shown according to the floors on the basis of the three-dimensional geographical characteristics of the tall building evacuation paths, the building typical evacuation structure and the Dijkstra algorithm with an improved data structure are adopted, and the route planning efficiency of the escape route is improved.

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 parking path planning method and system, a vehicle and a storage medium, and the method comprises the following steps: S1, building a simulation model: building a regular parking model, and determining the input quantity and output quantity of the parking model; S2, simulating the parking model by setting different variable parameters; S3, recording simulation data: recording a result of the simulation data, evaluating the result of the simulation data, if the simulation track point collides with the obstacle, considering that the group of simulation data is unavailable data, otherwise, considering that the group of simulation data is available data; and S4, curve fitting: performing curve fitting on the available data to obtain a curve function equation. According to the invention, the calculation of the parking path node is simpler, and the node is accurate.

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.

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.

The invention discloses a dynamic path planning method for a robot combined with an A* algorithm and a VFH obstacle avoidance algorithm. The environment in which the robot is located is expressed as a grid map, and a global initial path is searched out in the grid map by using the A* algorithm; The robot moves to the target point along the initial path, and judges whether it encounters an obstacle, and uses the VFH algorithm to avoid obstacles, otherwise it continues to move to the target point; when avoiding obstacles, first set the stage target point along the initial path, and generate the current The obstacle avoidance path between the position and the stage target point is moved forward one step, and the current position is updated to determine whether there is any occlusion between the robot's current position and the stage target point. If there is, recalculate the obstacle avoidance path. Step forward to the target point of the stage, and cycle until the robot reaches the target point of the stage and returns to the initial path to continue moving towards the end point. The combination of the two algorithms improves the efficiency of robot path planning and ensures the autonomous navigation ability of the robot in indoor dynamic environments.

The present invention discloses a UAV path planning method based on a transfer learning strategy deep Q network. The method first uses the grid method to model and describe the dynamic environment in which the UAV is located, and establishes the state space of the UAV. and the action space model; secondly, initialize the network parameters of DQN and the current state of the UAV; then, under the static environment model, use the reward mechanism based on the social force model to train the DQN to obtain the network weight and optimal action value; Then, use transfer learning to transfer the network weights and optimal action values ​​trained in the static environment to the dynamic environment, continue the neural network training, and get the actions to be executed by the UAV; finally, calculate the position of the UAV at the current moment, Realize the path planning of UAV in dynamic environment. The invention effectively solves the problems of slow DQN training convergence speed, unsatisfactory path planning and low success rate when the UAV performs path planning in a dynamic environment.