48results about How to "Efficient planning" patented technology

The invention relates to a biological antenna model-based multi-robot underwater target searching method and device. After an underwater detection ship carrying multiple underwater robots reaches a target searching area, all the underwater robots are driven to move by biological antenna models and send detected environmental information data to the underwater detection ship; according to the environmental information data, the underwater detection ship updates a raster map in real time and broadcasts to all the underwater robots; when one certain underwater robot finds a target, information is broadcast to the other underwater robots and the underwater detection ship; the underwater detection ship grabs the target by a mechanical arm after arriving the position of the target, and the other underwater robots board on the underwater detection ship after moving to the position of the target. The invention provides the method and the device which have the advantages that the robots are driven to move by the biological antenna models so as to complete a target searching task by the multiple robots in an unknown environment, and the target searching efficiency of the underwater robots can be greatly improved.

The invention discloses a medical mobile robot path planning method, system, and equipment based on RRT-Connect improvement, and a medium. According to the method, the distance between a starting point and a target point is judged according to a distance cost function; and a second starting point and a second target point with equal distances are sampled simultaneously between the starting pointand the target point through a middle node sampling function, so that the improved algorithm can simultaneously grow six random trees from the starting point, the target point, the second starting point and the second target point, and each random tree simultaneously and quickly expands towards the respective target direction. Meanwhile, a self-adaptive obstacle avoidance resampling principle is added into the algorithm; when a sampling point of the middle node sampling function collides with an obstacle or is located in the obstacle, sampling of the node is abandoned, and then resampling is carried out at the center positions of the node and an adjacent node according to the sampling position of the middle node. Therefore, problems that in a complex environment, a medical mobile robot ishigh in path planning time cost, and a target point is difficult to find in a short time are solved.

The invention relates to a trajectory planning method for variable speed drop of composite press. The trajectory planning method comprises: first, the differential command signals are input in a proportional pilot control valve to control the circulation drop of the press and collect signals of the movable beam displacement, return cylinder pressure and instruction; then, the movable beam displacement is treated by differential method to get the falling velocity signal of movable beam and the mathematical model of valve flow is obtained by training the collected parameters by neural network algorithm; then, combining the force balance equation of the return cylinder and the continuity equation of the flow, a comprehensive mathematical model of the falling system is built; finally, with the error integral of the return cylinder pressure as the optimization index, the improved genetic algorithm is used to optimize the cubic wire interpolation trajectory, and the control trajectory of the moving beam falling is obtained. The trajectory planning method for variable speed drop of composite press adopts the movable beam falling instruction path planning method can effectively avoid the impact of rigid and flexible impact system, restrain the system pressure fluctuations and improve the efficiency and accuracy of trajectory planning activities to enhance the transmission beam falling, improving engineering adaptability.

The invention provides a large-scale electric power system node load flow computing method. A conventional admittance matrix and parameter vector data are stored in a key value pair mode; each Mapper reads a key value pair <key, value> from a K-V database to act as input; each Mapper computes a Jacobi matrix element according to the input; the output results of all the Mapper are ordered for preparation of merging of Reducer; the Reducer merges the Jacobi matrix elements outputted by all the Mapper so that a matrix and a correction equation are formed; the equation is solved and a voltage phase angle is corrected; and the next round of iteration is performed through the correction results. According to the load flow computing method, the Jacobi matrix elements are parallel computed on multiple computers via a cloud computing platform so that superposition of computing power of multiple physical computers is realized, and computing efficiency, fault tolerance of the cloud platform and reliability of the computing results are enhanced.

The invention discloses an apparatus and method for route planning based on a PM2.5 healthy trip. The apparatus comprises three parts of a vehicle-mounted PM2.5 detector, an information transmission module, and a server terminal, wherein the information transmission module includes a GPS module and a GPRS module; the server terminal includes a route planning module; and the PM2.5 detector is mounted on a floating vehicle and is connected to the information transmission module, which is connected to the server terminal. A mobile device of a user can easily access data in the server terminal by means of a browser. According to the method, an improved Dijkstra algorithm is adopted, an integrated PM2.5 concentration is mainly taken as impedance, and a minimum total concentration is taken as a target. A healthy trip is planned according to an optimized function taking a PM2.5 optimal route as the target.

The invention discloses a load flow analysis method of a direct current transmission feed end islanding system. The method includes the following steps that (1) an alternating current system and a direct current system are divided; (2) the load flow of the islanding alternating current system is solved; (3) out-of-limit judgment is conducted on the reactive power exchange capacity of the alternating current system and the direct current system, if reactive power exchange exceeds a normal operation set value, the amplitude of a commutation busbar voltage is adjusted, the step (2) is executed again to continue, and otherwise the step (4) is executed; (4) the number of reactive power compensation groups is determined; (5) the reactive power consumption of a direct current convertor station is determined; (6) converter firing angle amplitude limiting inspection is carried out, if the amplitude is within a normal operation range limiting value, the step (7) is executed, otherwise the number of the reactive power compensation groups is added, and the step (5) is executed again; (7) a commutation tap is determined; (8) load flow convergence is judged; (9) the direct current frequency limiting value function is set. By means of the load flow analysis method of the direct current transmission feed end islanding system, the practical situation of the direct current transmission islanding system can be reflected more accurately, and planning and operating of the direct current transmission islanding system can be guided more efficiently.

The invention discloses a robot route planning method based on a fruit fly optimization algorithm, and belongs to the technical field of artificial intelligence and robot control. A fruit fly algorithm is optimized through a fusion genetic mechanism, interlace operation, mutation operation and other operations are added in the individual search process, the high convergence rate is kept, and meanwhile higher global search capacity is realized. According to the optimized algorithm, the optimal route plan of a robot can be efficiently obtained, the work and production efficiency of the robot route planning system can be improved in various scene application environments, and practicability is high.

The invention relates to a mobile robot full-coverage path planning method, a chip and a robot, and the method comprises the following steps: S1, the robot detects an obstacle in a cleaning region, generates a map containing obstacle information, and divides the map into a plurality of sub-blocks; S2, the robot plans a cleaning path in the sub-block; and S3, the robot determines the initial sub-blocks and performs cleaning, then calculates the path cost between the sub-blocks, selects the next cleaning sub-block according to the path cost, and cycles the step until cleaning of all the sub-blocks is completed. According to the new full-coverage path planning method, the calculation complexity can be reduced, and the coverage efficiency of the robot is improved.

The invention relates to a smart feeder, which has a pick-up position calibration mode. In the pick-up position calibration mode, the feeder calibrates a pick-up position to be lower than a preset deviation value. The feeder also has a material identification counting mode and a normal working mode. In the material identification counting mode, the feeder stores information of material thereon. In the normal working mode, the feeder automatically calculates the quantity of the material thereon. By adopting the smart feeder of the invention, the beneficial effect of quick, convenient and highly accurate pick-up position calibration of the feeder is achieved.

The invention discloses a smart alarm clock based on public traffic and real-time road network information at the same time. The public traffic and the real-time road network information are obtainedaccording to a set alarm clock time, a set starting place and a set destination, the current traffic condition from the starting place to the destination is judged via cloud computing processing, a transfer route or a driving route is calculated, the necessary time is predicted, and a ringing time of the smart alarm clock is obtained according to the predicted time plus a reasonable preparation time and a reserved system error time. The smart alarm clock disclosed by the invention improves the experience and the practicability, the public traffic and real-time road network information are integrated, and the starting place and destination addresses and other information of all alarm clock users under big data are combined to guide the urban traffic, which is conducive to relieving the traffic jam, efficiently planning the travel of people and improving the city image.

The invention relates to a method specially used for drawing a datum plane of combined H-steel. The method includes the steps that first, a drawing device specially used for leading out datum lines of a middle flange plate is assembled; second, a drawing device specially used for leading out datum lines of side flange plates is assembled; third, datum lines of webs on the two sides of the middle flange plate of a combined H-steel component are drawn; fourth, the datum lines of the middle flange plate of the combined H-steel component are drawn; fifth, the datum lines of the upper half portions of the side flange plates are led out and drawn; sixth, the datum lines of the lower half portions of the side flange plates are led out and drawn; seventh, the datum lines of the lower portion of the middle flange plate of the combined H-steel component are drawn. The method specially used for drawing the datum plane of the combined H-steel is easy to machine and efficient in drawing, the drawing precision is improved, the drawing cost is reduced, and the assembly and installation quality of the component is effectively guaranteed.

The invention discloses a bus line generation method. The method comprises steps: a bus network model is built based on actual road network data; source stop information and destination stop information are acquired, and a source bus hub and a destination bus hub are determined; a bus line between the source stop and the source bus hub and a bus line between the destination stop and the destination bus hub are determined; according to the corresponding relationship between the bus hubs and the lines, a bus line between the source bus hub and the destination bus hub is determined; and accordingto the bus line between the source stop and the source bus hub, the bus line between the destination stop and the destination bus hub and the bus line between the source bus hub and the destination bus hub, a bus line between the source stop and the destination stop is outputted. The invention also provides a bus line generation device capable of realizing the above method. Thus, the bus line canbe generated quickly and efficiently.

The invention is applicable to the technical field of data set construction methods, and provides a data set construction method and device based on an unmanned aerial vehicle instruction sequence andterminal equipment, and the method comprises the steps: S1, obtaining the instruction sequence, and dividing the instruction sequence into N groups, N being a positive integer; S2, acquiring sensor data when the unmanned aerial vehicle executes the ith group of instruction sequences, i being a positive integer smaller than or equal to N, and an initial value of i being 1; S3, mapping the sensor data into a data image of a preset pixel, or mapping into a curve image taking time and the sensor data as variables; and S4, when i is smaller than N, enabling i to be equal to i + 1, returning to S2for circulation, obtaining a data image set and/or a curve image set after circulation is finished, and constructing the data set based on the instruction sequence of the unmanned aerial vehicle. According to the invention, the general data in the sensor can be converted into visual data, so that the sensor data of the unmanned aerial vehicle can accurately feed back an actual scene, and a reasonable unmanned aerial vehicle instruction sequence is favorably constructed.