60results about How to "Fast planning" patented technology

The invention discloses a uniform angle division orthodontic arch wire bending sequence planning method and relates to the technical field of orthodontic arch wire bending techniques. The uniform angle division orthodontic arch wire bending sequence planning method is provided according to individual orthodontic arch wire curves of patients, on the basis of an orthodontic arch wire curve formationcontrol point information set and a robot movement information set of formation control points and with the combination of characteristic that an orthodontic arch wire is bent by using a robot. The method is technically characterized by comprising the following steps: according to the individual orthodontic arch wire curves of patients, inputting the orthodontic arch wire curve formation controlpoint information set M and the robot movement information set N of the formation control points into an orthodontic arch wire bending system; dividing the individual orthodontic arch wire curves; andsequencing divided uniform division domains.

The present invention provides a time-optimal route planning method based on an improved level set algorithm. The method comprises: 1, constructing a three-dimensional route planning environmental space; 2, initializing a level set function as a symbol distance function, and setting the AUV navigation starting point on a zero level set; 3, constructing a level set evolution equation considering the influence of the ocean current on the AUV navigation, and constructing a narrow band at the starting point and setting a prohibited area; 4, evolving a level set function according to the level set equation established in the step 3, and storing the zero level set interface of each time step length; 5, determining whether a target point is in the current narrow-band range or not; 6, reconfiguring the narrow band, and employing an improved fast marching method to reinitialize the level set function to be a symbol distance function; and 7, employing a back iterative equation, obtaining the time-optimal route of the AUV, and outputting an optimal route. Through adoption of an ocean current reanalysis database, the time-optimal route planning method based on the improved level set algorithm generates an ocean current field and fully considers the influence of the ocean current in the route planning to allow the planning route to have high practicality.

The invention provides a two-dimensional route planning method for a UUV to geometrically bypass circular barriers. The method comprises the following steps: 1, reading a route origin Ob, a route terminal point Oe and parameters of each circular barrier from a mission text; 2, performing expansion processing on each circular barrier, and calculating the parameters of each circular barrier after expansion; 3, establishing a bypassing point set S, making a planning current point Oc to be a starting point Ob, and placing the starting point in the bypassing point set S; 4, if the planning current point Oc is the route terminal point Oe, or the planning current point Oc and the route terminal point O2 are visual, skipping to the sixth step, and otherwise, executing the fifth step; 5, performing geometric bypassing on a circular barrier closest to the planning current point Oc, obtaining a bypassing point, placing the bypassing point in the bypassing point set S, updating the planning current point Oc, and skipping to the fourth step; and 6, placing the route terminal point Oe in the bypassing point set S, and at the moment, planning ends. According to the invention, bypassing of the circular barriers is realized through a simple geometric principle, and the UVV can rapidly and efficiently obtain a safe bump-free two-dimensional route in a complex environment with multiple circular barriers.

The invention discloses a multi-moving time-sensitive target reconnaissance path planning method for an unmanned aerial vehicle group. The method comprises the following steps: 1, constructing a reconnaissance area map environment; 2, constructing an initial search area unit; 3, expanding a search area online; 4, terminating conditions; 5, outputting an unmanned aerial vehicle path; 6, updating targets, if all the targets in the target linked list are planned, completing the task, and ending the task; otherwise, taking out the next target G from the target linked list, and continuing the step7; 7, judging the intersection of the new target and the searched area; and 8, updating information of the searched area. The method has the advantages that the path planning method for reconnaissancetasks of a plurality of moving time-sensitive targets in the task area can meet the real-time requirement of unmanned aerial vehicle path planning in a large range and with high precision, dynamic tracking and fastest arrival of the moving time-sensitive targets are achieved, and therefore the cooperative task efficiency of a swarm intelligence unmanned system is improved.

The invention discloses a path planning method, which is used for realizing obstacle avoidance path planning and can improve the quality of a planned path. The method comprises: acquiring road information, and an initial position and a destination position of a target object (401); determining a Cartesian coordinate system, a Frenet coordinate system and a mapping relationship between the Cartesian coordinate system and the Frenet coordinate system according to the road information; obtaining a path quality index function based on a Frenet coordinate system based on the mapping relationship, wherein the path quality index function is a quadratic function; according to the path quality index function based on the Frenet coordinate system and the initial position and the target position of the target object, determining a target path based on the Frenet coordinate system by utilizing quadratic optimal planning; and according to the mapping relationship, converting the target path into a Cartesian coordinate system (406), the target path being used for path planning control of the target object.

The invention discloses a UUV cluster formation pattern forming method based on circumferential hierarchical planning. The method comprises the steps that initialization is carried out to set a UUV master-slave identity instruction, formation forming parameters and an expected formation instruction; after forming of the formation, each UUV maintains a fixed point and a fixed heading, and determines the master-slave identity; a UUV cluster interacts position and heading information; the master UUV carries out scattered maneuvering planning on the slave UUVs and sends target points of scatteredmaneuvering; the slave UUVs carry out scattered maneuvering, and inform the master UUV after maneuvering is completed; the master UUV carries out radial and circumferential maneuvering planning on theslave UUVs sequentially, and sends target points of radial and circumferential maneuvering sequentially; the slave UUVs carry out radial and circumferential maneuvering sequentially, and inform themaster UUV after maneuvering is completed; and the master UUV sends a formation forming success instruction to the slave UUVs, and the UUV cluster forms the formation. Thus, the UUV cluster can form the expected formation rapidly and safely from an initial random distribution and disordered form.

The invention belongs to the technical field of three-dimensional measurement, and discloses a sensor measurement viewpoint planning method in automatic three-dimensional measurement of surface structured light. The method comprises the steps of: (a), packaging a three-dimensional structural model of an object to be measured by adopting multiple cube volume blocks; (b), constructing six semi-spheres and candidate measurement viewpoints in each volume block; (c), intersecting the single volume block with the three-dimensional structural model to obtain multiple spline surfaces, and solving thecentral point, the average normal vector and the area of each spline surface; (d), calculating the zenith angle and the azimuth angle of the average normal vector of each spline surface in the singlevolume block in a three-dimensional coordinate system, and determining an area, which each spline surface belongs to; (e), calculating measurement quality parameters of the candidate measurement viewpoints; and (f), comparing the quality parameter of each candidate measurement viewpoint with the pre-set threshold value, so that the required measurement viewpoint is obtained. By means of the sensormeasurement viewpoint planning method in automatic three-dimensional measurement of surface structured light in the invention, the calculation process is simple; the automation degree is high; and the sensor measurement viewpoint planning method is suitable for planning measurement viewpoints of complex parts.

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 belongs to the technical field of vehicle path planning, and in particular relates to a method for path planning of an equipped vehicle based on transfer learning. The method comprises the following steps of S1, obtaining basic data of the equipped vehicle; S2, obtaining planning time and a planning goal; S3, obtaining static planning environment data; S4, obtaining equipped vehicledriving data; S5, constructing a path planning model by using a DDPG (Deep Deterministic Policy Gradient) algorithm; S7, obtaining parameter variation data of a dynamic planning environment; S8, constructing a dynamic planning environment domain; S9, slightly adjusting parameters of a deep neural network; S10, with the trained network parameters as input of a path planning algorithm, obtaining theterrain and intelligence data in a battle in real time, and constantly adjusting planning strategies to generate a route planning result for the equipped vehicle; and S11, obtaining the path planningresults of different battlefield environments through the dynamic planning environments in different battles, and taking the path planning results and the corresponding network training parameters thereof as historical samples.

The invention discloses an original ecological food transport scheduling system and method. The transport scheduling method comprises information acquisition, path planning, order generation and transport feedback. The information acquisition comprises obtaining all order information in a server database, and for each order, drawing a user ID, a user credit accumulated score, a product ID included in the order, the weight of each product, a departure place, a transport destination, a distance between transport destinations and a road condition weight between a destination and the transport destination; a path planning module is used for calculating the weight of each transport destination, marking each transport destination on a map, according to the weights, searching for closed transport paths, and establishing a transport path set; and expected delivery time of each transport path is calculated according to a preset value; and the transport path set is sent to each store distribution end, and each store distribution end selects its own road. The original ecological food transport scheduling system and method have the advantages of high intelligentization, accurate path planning, high distribution efficiency and the like.

The invention relates to an image recognition method based on deep learning, and the method comprises the steps: S1, obtaining the corner information and character information of a to-be-recognized house type image, inputting the corner information into a quadratic programming model, and obtaining the connection information of wall lines and doors and windows, wherein the quadratic programming model is pre-established and comprises a plurality of corresponding corner point connection rules and a model of constraint conditions of a position relationship between a wall line and a door and window; S2, inputting the connection information of the wall lines and the doors and windows into a graph theory optimization model, and obtaining region composition information of each room region in the house type graph, wherein the graph theory optimization model is a Graham algorithm model which is established in advance and is improved based on graph theory knowledge; and S3, matching the characterinformation with the region composition information to obtain an recognition result. The problems that in the prior art, the house type image recognition result precision is not high, the recognitionprocess calculation is complex, and the expansibility is poor are solved.

The invention discloses a spatial motion planning method of a multi-degree-of-freedom robot. The method comprises the following steps: S1, acquiring initial state information of the robot, and acquiring spatial information of the robot, surrounding environment obstacles and task targets; S2, determining a feasible region, and calculating optimal posture information and feasible posture information, wherein the feasible region is a spatial region which is formed by combining the position of the task target with the optimal posture or the feasible posture of the robot, the surrounding environment obstacles and other task targets, and in the feasible region, the robot can complete the designated task target; and S3, judging whether a proximity vector of a robot end effector can fall into thefeasible region or not, if the proximity vector of the robot end effector can fall into the feasible region, executing a planning task in the optimal posture or the feasible posture by the robot, andif the proximity vector of the robot end effector cannot fall into the feasible region, reselecting the task target. According to the spatial motion planning method, excessive planning of the robot isavoided or reduced through posture analysis, the operation efficiency of the robot is improved, and the real-time requirement in industrial control is better met.

The embodiment of the invention discloses an obstacle data processing method and device, electronic equipment and a computer readable medium. A specific embodiment of the method comprises the steps of obtaining a point cloud data set obtained by scanning of a target vehicle-mounted laser radar; performing clustering processing on the point cloud data in the point cloud data set to generate a first obstacle information set; generating a second obstacle information set according to the target deep learning model and the point cloud data set; generating an obstacle feature distance matrix; obtaining a third obstacle information set; obtaining a fourth obstacle information set; obtaining a fifth obstacle information set; obtaining a combined obstacle information set; and sending the combined obstacle information set to the target terminal for display. According to the embodiment, the accuracy of obstacle detection is improved.

The invention provides an intelligent mechanical arm obstacle avoidance method and system for human-computer safety interaction and a robot. The robot monitors an identification code on an obstacle inreal time through an identification code visual positioning method to obtain the position of the obstacle; and the motion state of the obstacle is calculated through the position detection result andthe position change of the obstacle, and a corresponding obstacle avoidance strategy is adopted according to the motion state of the obstacle. According to the method, the mechanical arm can make different obstacle avoidance strategies for obstacles in different motion states or human limbs, compared with an existing obstacle avoidance method, the method gets rid of the limitation of environmentmodeling, the planning speed is high enough, and a timely and effective obstacle avoidance strategy can be made for sudden obstacles and dynamic obstacles in a working space.

The invention provides a multi-unmanned aerial vehicle cooperative three-dimensional flight path planning method, which comprises the following steps of: firstly, calculating by using a minimum outsourcing convex polygon algorithm to obtain an abstract minimum convex hull of a target operation area, generating a polygonal area with a specific number of edges by using a convex polygon simplified algorithm, then segmenting the area, performing Z-shaped coverage on each area, and finally performing multi-unmanned aerial vehicle cooperative three-dimensional flight path planning. The method comprises the following steps: determining a flight mission area of each unmanned aerial vehicle, discretizing the flight mission area into abstract graph nodes, establishing a flight path evaluation function, and solving an optimal flight path by utilizing the evaluation function in combination with a genetic algorithm. And finally, obtaining three-dimensional data according to the DSM model and exporting the three-dimensional data as KML data. The method makes full use of the DSM model, the fast convex hull algorithm, the region segmentation and coverage algorithm and the genetic algorithm, has the characteristics of high planning speed, low cost, high precision and good coverage effect, and also has an obvious optimization effect on multi-unmanned aerial vehicle coordinated planning and full-track coverage. And an effective flight path planning method is provided for the field of flight path planning of multiple unmanned aerial vehicles.

The invention relates to the technical field of truck navigation, and discloses a truck navigation on-way traffic restriction data preprocessing method. The method comprises the following steps: S1, establishing a binary tree, and initializing a root node of the binary tree; S2, inputting truck traffic restriction data; S3, matching the truck traffic restriction data to the road section of the bottommost road network; S4, storing the matching result of the bottommost road network into a binary tree; S5, according to a matching result of the bottommost layer road network, matching the truck traffic restriction data to a corresponding upper layer road section; S6, storing a matching result in the step S5 into a binary tree by taking the road network level and the road section number as indexes; S7, performing inorder traversal on the binary tree, and storing truck traffic restriction data corresponding to all road sections in all hierarchical road networks as a data file A; S8, establishing indexes for all road sections in all the hierarchical road networks, wherein the indexes comprise the corresponding truck traffic restriction data quantity and the storage address of the truck traffic restriction data, and the indexes are stored as an index file B.

The invention, which relates to the artificial intelligence technology, discloses an intelligent path planning method. The method comprises: receiving a map image with an obstacle marked and an initialized speed; carrying out grid division on the map image with the obstacle marked, setting an initialized position and a destination position, and generating pulse frequency ft, a pulse emissivity Rt and a loudness At randomly; calculating an optimal direction solution X* in an initial grid and a next time position and generating a uniform distribution random number rand; determining a value relationship between the uniform distribution random number rand and the initialized pulse emissivity Rt and loudness At till location of the predicted position and the destination position in the same grid; and then completing an optimal path by combining predicted positions of all time and outputting the optimal path. In addition, the invention also puts forward an intelligent path planning apparatus and a computer-readable storage medium. Therefore, the precise intelligent path planning function can be realized.