69results about How to "Excellent path" patented technology

The invention relates to an airline routing algorithm of an unmanned plane in a large-range complicated three-dimensional space. The algorithm comprises the following steps: first dividing a three-dimensional space on the basis of a 2.5-dimensional grid (each grid point includes longitude, altitude and elevation information); improving the A* cost function by comprehensively considering the influence factors such as airline height, detected probability, airline distance under the constraint conditions of radar, disaster weather and forbidden areas, and determining an initial airline on the basis of an algorithm search flow; serially processing the initial airline to obtain a final flying airline for meeting the performance constraint of the unmanned plane (such as minimal step length, turning radius, climbing rate, safety height). The algorithm is good in stability and astringency, high in efficiency, capable of meeting the wide-range low-altitude airline routing requirement and applicable to relevant fields such as military, national defense, emergency relief.

The invention discloses a hazardous chemical substance transport scheduling method based on multi-target modeling optimization. The hazardous chemical substance transport scheduling method includes the steps of respectively building a path length model, a building time model, a vehicle fixed cost model and a risk model, carrying out per-unit and weighted processing on the four sub-models to obtain an evaluation function of hazardous chemical substance transport optimized scheduling, solving the models through an improved genetic algorithm including natural number coding, initial population recursion generation, an optimal storage strategy, improved matched intersecting and continuous three-time intersecting, and finally obtaining a hazardous chemical substance transport optimal path which is short in transport path, high in distribution efficiency, few in distribution vehicle and small in risk. According to the hazardous chemical substance transport scheduling method, four targets are considered at the same time, a decision maker can set different weight values according to self requirements, the searching direction of the genetic algorithm is determined through the weight values, fitness values are continuously iterated to be finally converged, and therefore the optimal path is obtained.

The invention discloses a milling tool path optimization method for low carbon. The milling tool path optimization method comprises the steps of firstly, building solving process of milling tool pathoptimization problem considering carbon emission by taking flat cavity processing as a research object; secondly, building processing time, carbon emission and a processing cost function of cavity milling process taking a tool path as a variable; and finally, building a multi-target tool path optimization model taking shortest processing time, minimum carbon emission and lowest processing as optimization targets, and optimizing the multi-target tool path optimization model by an improved genetic algorithm-based optimization solution method. The method comprehensively considers the targets of the processing time, the carbon emission and the processing cost, the actual application demand of an enterprise is satisfied, the tool path optimization solving process is simple and effective and iseasy to implement, the population convergence speed is rapid during path optimization solving by the proposed improved genetic algorithm, and the algorithm can be effectively prevented from being sunken to local optimal solution.

An obstacle avoidance method used for an underwater robot and based on distance and parallax information comprises steps as follows: a control device performs overall path planning on the underwater robot according to an operation task and nautical chart database information; a detection sonar and a camera are taken as overall and local obstacle measuring instruments respectively so as to obtain relative distance and parallax information of the underwater robot and an obstacle; then the control device judges whether obstacle avoidance is required and adopts predictive control to adjust an obstacle avoidance strategy; if the underwater robot arrives to a target point, the path planning is finished. The obstacle avoidance method has the advantages of capacity of dynamically adjusting the obstacle avoidance strategy, better path, good avoidance effect, high reliability and the like, can handle complex obstacles, and improves the reliability of the underwater robot for executing the tasks.

A wireless networking method of air conditioners comprises the steps of sending a networking request carrying parameters of the air conditioners; judging whether answering signals, allowing networking, fed back by other air conditioners are received or not; if the signals are not received, continuing to send the networking request; if the signals are received, screening all the received answering signals, and according to a screening result, selecting to-be-networked air conditioners serving as child nodes from other air conditioners; building network connection with the to-be-networked air conditioners. The invention further provides a wireless networking device of the air conditioners. By the adoption of the technical scheme, the beneficial effects that automatic networking is achieved in a wireless manner, parent-child nodes are built, and a tree-shaped structural network is formed; networking objects with the optical signals are automatically selected, the superior path is formed, and the networked communication network is high in expansibility and stable in communication; and when problems appear in the child nodes, the parent nodes can select the child nodes again and build connection.

The invention discloses a mechanical arm motion planning method. The method is specifically implemented according to the following steps that S1, a common space rule object is used for approximately enveloping an obstacle to carry out obstacle modeling; S2, an initial position and a target position of a mechanical arm are given, and an inverse solution of the target position is obtained through aninverse kinematics method; S3, a track is calculated through a p-rrt algorithm; S4, a seven-degree-of-freedom mechanical arm model is imported, a mechanical arm target position is given, a target position inverse solution is obtained through inverse kinematics, a path node of the obtained track serves as an input, and smooth optimization processing is carried out on a path by using a B spline curve; and S5, a simulation experiment is carried out in a Matlab, wherein simulation comparison optimized after the B spline curve is added compares path curves before and after smoothing, verifies effectiveness, and finishes mechanical arm motion planning, thereby solving the problem of poor smoothness of a planned path in the prior art.

The invention provides a robot path planning method based on an improved genetic algorithm. The robot path planning method comprises the following steps: when an optimal path exists, a robot executes an inspection task according to the optimal path, or else, the task is executed according to an approximate optimal path. At the same time, the robot path planning method provided by the invention is used for calculating a shortest path between two random inspection points, then taking the shortest path as basic data of the genetic algorithm to calculate the optimal path for the robot to do the inspection task next time, and continuously iterating like this, so that the path planned by the robot is more and more intelligent, and the reliability and the navigation accuracy of the system are maximized; since the path planning adopts the specially optimized genetic algorithm, as time goes on, the number of robot inspection times is increased, the planned path may become more and more excellent.

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 provides a method and device for costmap updating, a robot and a storage medium. The method comprises the steps that an obstacle position and obstacle passing data are obtained, whetherthe robot can pass through an obstacle or not is determined according to the obstacle passing data and passing capability parameters of the robot, and a costmap is updated according to a judgment result and the obstacle position. According to the method, when the costmap is updated, the influence of the obstacle on the passage of the robot is considered, so that the generated costmap is more accurate, and the robot plans a better path.

The invention discloses a method for tracing the odor of an unmanned aerial vehicle based on a 3D_Z_spiral upwind algorithm. The method comprises the following steps: adopting an anemometer to measurewind direction; and combining real-time gas concentration monitored by a multi-rotor unmanned aerial vehicle with algorithm logic upwind to search odor source. Specifically, an oblique motion (Z motion) biased to the upwind direction is performed for the unmanned aerial vehicle (UAV), and enough field source concentration across the entire odor source pollution area is obtained; after flying outof the foul-smelling contaminated area, the unmanned aerial vehicle (UAV) began to do a spiral motion (Spiral) and returned to the foul-smelling contaminated area; then move in a straight line (Surge)against the wind to find the source of the stench. Unmanned aerial vehicles (UAVs) continue to repeat the above three movements, gradually approaching the current plane odor pollution sources. The UAV descends to a certain altitude (3D) when it finds what is believed to be the current planar odor source. And the descending position as a new plane tracing the origin of the starting point, repeat the above three movements, to find the source of odor. Until the UAV descends to the lowest permissible altitude and finds the source of the odor at that altitude plane, it stops moving and assumes thelocation of the source of the odor is found.

The invention discloses a path computing method and unit in an optical network. The method comprises the following steps: releasing ring protection information of each link in the optical network by a routing protocol message, wherein the ring protection information comprises the identification of each link and the identification of a ring to which each link belongs; receiving the ring protectioninformation by the routing protocol message, and according to the ring protection information, combining the links with the same ring identification into a ring so as to obtain ring topology information; and according to the ring topology information, carrying out path computing. Compared with the prior art, an optimal path can be computed by using the method and unit provided by the invention.

The invention provides an inchworm-imitating climbing robot suitable for a truss structure. The robot comprises clamping device modules at the two ends, a joint module, a processor, a binocular imageacquisition module, an image processing module and a route calculation module. The joint module comprises an I-shaped joint module and a T-shaped joint module. Two cameras of a binocular stereoscopicvision module are installed on the two clamping device modules, and the binocular image acquisition module is used for acquiring environment image information and space coordinate information of eachpoint in an image; the image processing module is used for processing the image acquired by the binocular image acquisition module and separating an obstacle image in the image; and the route calculation module plans and screens multiple route distances between the robot and an obstacle according to the separated obstacle image. The inchworm-imitating climbing robot suitable for the truss structure has the beneficial effects of being scientific in design, capable of achieving automatic advancing and high in environment adaptive capacity and has obstacle crossing capacity.

The invention discloses an unmanned aerial vehicle track route planning method applied to community distribution. The method comprises the following steps: S100, generating a random sampling point tran with a RRT algorithm, and finding an unmanned aerial vehicle track route from a root node tini to a target point tgoa with the RRT algorithm; and S200, optimizing the selection of the random sampling point tran and the generation process of the random sampling point tran to obtain an optimized unmanned aerial vehicle track route. Through adoption of the unmanned aerial vehicle track route planning method applied to community distribution, high route result quality is achieved for the community distribution, and the route is optimal. From the four aspects of a step length, a deflection angleand a parent node selected for the random sampling point, as well as the influence of the community distribution characteristic on the step length and the deflection angle, the unmanned aerial vehicletrack route searching efficiency and accuracy are improved.

The embodiment of the invention provides back-to-source routing information generation and transmission methods, and related devices, used in the back-to-source process of a CDN. The generation method comprises the steps that: a first CDN cache server obtains the first network distance, the second network distance and the third network distance; the first CDN cache server determines that the first network distance is greater than the sum of the second network distance and the third network distance, generates back-to-source routing information, and sends the back-to-source routing information to a second CDN cache server; and a back-to-source routing path indicated by the back-to-source routing information passes through the first CDN cache server, the second CDN cache server and a source station. Visibly, in the embodiment of the invention, according to the network distance between the source station and the CDN cache server, when the fact that back-to-source routing in indirect back-to-source is superior to that in direct back-to-source is determined, indirect back-to-source routing is adopted; therefore, the back-to-source speed is increased; and furthermore, the back-to-source error rate is reduced.

The invention discloses an intelligent acousto-optic electronic tag. The electronic tag, which utilizes a microprocessor with a real-time communication function to communicate with a server and control the acousto-optic displayed number, is capable of timely and accurately displaying the storage location of to-be-shelved goods or the position and quantity information of sorted goods, realizing the dynamic optimization of the storage location, increasing the efficiency and reducing the error rate.

The invention provides an atmospheric pollutant tracing method based on a longicorn beard search algorithm. The atmospheric pollutant tracing method is used for quickly and accurately positioning atmospheric pollutants under the condition that wind direction information is unknown. At present, most existing smell source positioning algorithms need to depend on wind direction information upwind search to track smoke plume, the algorithms have strong dependence on wind direction information, the fluctuation amplitude of actual wind speed and wind direction is large, the diffusion of odor sourcesin the air is greatly influenced, so referring the wind direction information and positioning the odor sources by utilizing the wind tendency, the search effect is poor, the robot is easy to fall into local optimum in the search process, and the search efficiency is low. According to the atmospheric pollutant tracing method based on a longicorn beard search algorithm, gas sensors are carried at the left end and the right end of an unmanned aerial vehicle respectively, pollutant concentrations at the left end and the right end of the unmanned aerial vehicle are read in real time, the next position of the unmanned aerial vehicle is judged through the longicorn beard search algorithm, and then continuous iteration is performed to gradually approach a pollution source. According to the algorithm, under the condition of not depending on wind direction information, the unmanned aerial vehicle is effectively prevented from falling into local optimum in the searching process, and the positionof a pollution source is accurately and rapidly positioned.

The invention belongs to the field of robot motion planning, particularly relates to a space robot intelligent motion planning method, system and equipment based on multiple constraints, and aims to solve a problem of how to realize high-precision and high-accuracy path planning of a space robot so as to realize space target intersection approaching and capture autonomous flight control. The method comprises steps of performing optimal task allocation of the space robot based on an FM* genetic algorithm, obtaining a traversal sequence with the shortest path distance, and generating a first path of the space robot; adjusting the first path based on a path adjustment method of a Gaussian filter, and enabling the adjusted second path to accord with a maneuverability constraint condition based on environmental characteristics; and if distribution points of the unexecuted tasks are dynamically changed, path point re-planning being carried out through a perceptron neural network which balances the calculation cost and the path cost, and a third path being obtained. According to the method, an efficient high-quality path which is easy to track, avoids collision and is re-planned can be provided for the motion of the space robot.

The present invention provides a traceability method for air pollutants based on a longicorn beetle search algorithm, which is used to realize fast and accurate positioning of air pollutants when wind direction information is unknown. At present, most of the existing odor source location algorithms need to rely on wind direction information to search against the wind to track the plume. They are highly dependent on wind direction information, and the actual wind speed and wind direction fluctuate greatly, which affects the diffusion of odor sources in the air. Larger, at this time, referring to the wind direction information and using the wind direction to locate the odor source, the search effect is poor, and the robot in the search process is likely to fall into a local optimum, and the search efficiency is low. The air pollutant traceability method is based on the beetle's beard search algorithm. Gas sensors are installed at the left and right ends of the drone to read the pollutant concentrations at the left and right ends of the drone in real time. The position of the next step of the machine, and then continue to iterate, gradually approaching the source of pollution. Without relying on wind direction information, this algorithm effectively avoids the UAV from falling into a local optimum during the search process, and accurately and quickly locates the location of the pollution source.

A method, control unit and computer program product is disclosed for executing an evasive maneuver of a motor vehicle. If an obstacle is detected in the vehicle's path, the evasive maneuver is initiated and a nominal trajectory is calculated. Control devices of the motor vehicle are actuated in such a way that the motor vehicle drives along the nominal trajectory under normal road conditions. The evasive maneuver is executed as calculated if the motor vehicle moves along the nominal trajectory. An alternative trajectory, which is actually possible with respect to the driving dynamics under the given road conditions, is calculated based on the reaction of the motor vehicle to the actuation of its control devices if the motor vehicle does not move along the nominal trajectory. The evasive maneuver is executed along the alternative trajectory.

The invention discloses a multi-way parallel quick sorting method based on a spiral slide; and the method is applied to an express sorting system for synchronous sorting in multiple ways. The method comprises the following sorting steps: (S01) subsystems are divided in a slide type multilayer express sorting system according to the terminal region number; (S02) packages enter bagging output devices corresponding to sorting towers through respective sorting paths; (S03) the packages are bagged and output in the bagging output devices; and (S04) the bagged packages are discharged through the spiral slide. The method has the following advantages: multiple sorting subsystems independently operated without mutually interfering can be formed; and each sorting subsystem comprises the bagging output devices classified in all terminal regions. The multiple sorting subsystems can synchronously perform multi-way sorting; and compared with single-way sorting in a traditional express sorting system, the sorting efficiency is greatly improved.

A lightweight, plastic coated component is in the shape of a three-dimensional shaped part with a metal layer provided with access apertures through which the plastic may flow. The component includes stiffening ribs created by the plastic that are positioned within hollow areas of the three-dimensional shaped part, and whose plastic extends through the apertures of the metal insert. The component is formed as a metal insert spray-covered with plastic for the purposes of optimizing the plastic spray process and to achieve an inner bond between the metal insert and the stiffening ribs. The metal insert includes a large number of evenly-distributed holes, and these holes form a flow resistance and also a flow enabler for the molten mass of plastic during spraying. There are projections present at each of the holes that are covered by the plastic coating. The stiffening ribs facing away from the sprayed side have a connecting cross-section that extends into the metal insert via a number, or a large number, of holes in the metal insert.

The invention discloses a mining wireless communication relay method. The method comprises the following steps: a network node needing to be relayed broadcasts a relay request message to surrounding nodes; each intermediate node records the address and the relay probability of the next hop in a relay table of the intermediate node; when the request information reaches a destination node through a certain path, an optimal path is selected according to relay probabilities of different paths; the destination node initiates a relay response, and returns to the source node through the optimal path. According to the invention, the relay probability algorithm in the MESH relay technology is realized. The nodes in the network have a relay function, and the problem that a relay needs to be additionally arranged in a star-shaped network architecture is solved. Under the powerful support of the grid-shaped network topology structure and all the full-function network nodes, all the nodes in the method have the ad hoc network function, along with the change of the environment, the nodes can flexibly select relays according to the relay probability between all the nodes, and it is guaranteed that the path is optimal at any time and in any environment.

The invention relates to a full-automatic tomato picking and transporting integrated robot and a using method thereof. The full-automatic tomato picking and transporting integrated robot comprises a picking vehicle and a transport vehicle; the transport vehicle is provided with a collecting device; and the picking vehicle is provided with a nondestructive picking device and a conveying device, theoutput end of which extends to the collecting device. By adopting the full-automatic tomato picking and transporting integrated robot disclosed by the invention, whole-process automation of picking,transportation, loading and unloading of tomatoes is achieved; the picking vehicle is matched with the transport vehicle through reasonable configuration of an intermediate conveying device, so that whole-process automation of picking, transportation, loading and unloading of the tomatoes is realized, and the labor efficiency is improved; and nondestructive picking operation is realized, a conicalprotective shell of the adsorption type nondestructive picking device only sleeves one tomato at one time, nearby fruits cannot be damaged when a vacuum sucker starts to twist, and a net bag device adopts a flexible rope woven mesh at the same time, so that impact force on the surface of each tomato can be greatly lowered, and a speed of a destruction reduction roller brush when the tomatoes leave a conveyor belt and enter a collecting basket can be lowered to the lowest, so that impact of the collecting basket on the tomatoes is reduced.

The invention provides a two-wheel self-balancing trolley. The two-wheel self-balancing trolley comprises a trolley frame, wheels, a power storage device, a pedal device, a driving mechanism, a six-axis inertial sensor, a steering trigging device, a wireless communication module and a controller, the wheels are movably connected with the driving mechanism and arranged on the two sides of the trolley frame, the power storage device is fixedly mounted on a bottom plate of a rack, the pedal device is arranged on the upper top face of the trolley frame, the controller is fixedly connected with thetrolley frame and arranged inside the trolley frame, the wireless communication module comprises a receiving terminal and an emitting terminal, the six-axis inertial sensor is arranged on one side ofthe controller, the receiving terminal of the wireless communication module is arranged on the other side of the controller, the emitting terminal of the wireless communication module is fixedly mounted on the steering trigging device, and the steering trigging device and the balancing trolley are used in a paired mode. The two-wheel self-balancing trolley is stable in operation and reliable in control, the precise inclination angle value and the precise angular velocity value of the trolley can be obtained, and precise positioning control can further be achieved.

Disclosed in the embodiment of the present invention is a method and device for processing service continuity; an MME, by means of acquiring the service continuity information of a PDN connection of a UE, and on the basis of said service continuity information of the PDN connection, determines whether the PDN connection needs to maintain service continuity; if the PDN connection does not need to maintain service continuity, then the MME selects a new packet data gateway PGW for the UE, and if the PDN connection needs to maintain service continuity, then the MME maintains the original PGW connection. The present invention can ensure the normal service connection of a UE needing to maintain service continuity, and on the premise of not influencing the service connectivity of the service of a PDN connection, can select a more suitable PGW for a UE not needing to maintain service continuity, optimising the UE path and saving routing resources.

The invention provides an industrial robot path planning method and system based on a pseudo-distance function. The method includes the steps of carrying out the enveloping of a mechanical arm connecting rod and a working environment obstacle through a convex polyhedron, and recording the geometric shape of a mechanical arm and the environment obstacle in the form of the vertex of the convex polyhedron; carrying out path planning in a joint space of a robot on the basis of a traditional RRT algorithm, mapping joint parameters of the joint space into a geometric shape of a working space through a kinematic equation of the mechanical arm, and judging whether the mechanical arm collides with the environmental obstacle or not through a GJK algorithm; and if collision occurs, calculating the gradient of the pseudo distance of a collision point to each joint parameter, and correcting the collision point along the gradient direction as a new path point. According to the industrial robot path planning method and system based on the pseudo-distance function, a path generated by the method is better, the robustness is better, and the method has more obvious advantages in the environment with more obstacles or narrow channels.

The invention belongs to the technical field of an unmanned aerial vehicle, and discloses a multi-fire extinguishing water bomb device of a rotor unmanned aerial vehicle, a control system and method and the unmanned aerial vehicle. An operation parameter of the multi-fire extinguishing water bomb device of the rotor unmanned aerial vehicle is set by a key, image data of a flight environment is acquired by a camera, flight distance-measurement operation is performed on the rotor unmanned aerial vehicle by an infrared distance-measurement part, a wireless signal is emitted by a wireless emitter,a wireless remote controller is connected with the wireless signal to wirelessly control the rotor unmanned aerial vehicle, a rotor is used for controlling upgrading of the unmanned aerial vehicle, ejection fire-extinguishing operation is performed on airborne multi-fire extinguishing water bomb by an ejector, and the rotor unmanned aerial vehicle is controlled to do return operation by a returninstruction. The multi-fire extinguishing water bomb device is also relatively high in sensitivity and has relatively high universality; and meanwhile, the unmanned aerial vehicle can be enabled to fly under an environment with relatively large interference to a GPS multiple paths by a return module, and the unmanned aerial vehicle can be enabled to still accurately return.

The invention discloses a multi-policeman cooperative hunting task allocation and path planning method under road network constraints. The method comprises the following steps: 1) obtaining a road topology map G of a road network; 2) acquiring police officer distribution information and task target position information in a road network G; 3) determining a next possible node set of the task targetaccording to the position where the task target appears in combination with the road topological map; 4) obtaining the moving speed of each policeman and the task target; 5) determining a police officer set to be allocated according to the interception point set and the moving speeds of the police officers and the task targets; 6) calculating the congestion degree of each intersection in the interception point set; 7) establishing a multi-policeman cooperative hunting task allocation and path planning optimization model under road network constraints; 8) solving the optimization model to obtain a multi-policeman cooperative hunting task allocation and path planning scheme. According to the multi-policeman cooperative hunting task allocation and path planning method based on the road network constraint, the multi-policeman cooperative hunting task allocation and path planning scheme is obtained by establishing the multi-objective optimization model, the policeman is reasonably allocated to each hunting point, and the hunting efficiency is effectively improved.

The invention discloses a path planning method, which comprises the following steps of: based on a scene memory model, establishing an experience map and a corresponding scene cognition map by using a RatSLAM algorithm; extracting a road edge in the historical memory image through a Canny operator; converting a pixel coordinate system to a world coordinate system based on the road edge, and performing preliminary judgment on connectivity according to the slope of the road edge; continuously injecting energy into the potential path detection network according to continuous observation of the potential path so as to further judge the road connectivity; fusing the detected potential path with the original scene cognition map, and correspondingly updating an experience map; and performing path planning based on the updated scene cognitive map. According to the method, the potential safety path in the environment can be detected, and a better path is planned based on the updated scene memory model.

The invention discloses a traffic information distribution method capable of eliminating oscillation, which includes the steps of: 1) installing traffic flow detection equipments on all traffic monitoring stations to record the parameters of the traffic flow; 2) computing the vehicle traveling OD(Origin-Destination) information at traffic diversion junctions through the OD backstepping technique; 3) computing the expected load level of a road section and estimating and comparing the expected load of the road section with the load level of an alternative road section; and 4) computing the fluctuation of the distributed information through a driver stimulation reaction model and building an information distribution dynamic area to distribute the information. With the method, the routes of the travelers can be optimal, and the benefit of the road network can be the maximum at the same time, smooth traffic circulation of the road network is ensured in time and traffic oscillation is reduced as much as possible.