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68results about How to "Excellent path" patented technology

Hazardous chemical substance transport scheduling method based on multi-target modeling optimization

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.
Owner:CHONGQING UNIV

Strip-shaped robot path planning method based on self-learning ant colony algorithm

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.
Owner:HUAIAN COLLEGE OF INFORMATION TECH

A method for tracing odor of unmanned aerial vehicle based on 3D_Z_spiral upwind algorithm

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.
Owner:CHINA JILIANG UNIV +1

Atmospheric pollutant tracing method based on longicorn beard search algorithm

ActiveCN110927342AAccurate and fast traceabilityImprove search efficiencyMaterial analysisUncrewed vehicleSmoke plume
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.
Owner:CHINA JILIANG UNIV

Space robot intelligent motion planning method and system based on multiple constraints

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.
Owner:INST OF AUTOMATION CHINESE ACAD OF SCI

A Traceability Method of Air Pollutants Based on Longhorn Beetle Search Algorithm

ActiveCN110927342BAccurate and fast traceabilityImprove search efficiencyMaterial analysisAir pollutantsEngineering
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.
Owner:CHINA JILIANG UNIV

Full-automatic tomato picking and transporting integrated robot and using method thereof

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.
Owner:SHANDONG AGRICULTURAL UNIVERSITY

Two-wheel self-balancing trolley

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.
Owner:TIANHE COLLEGE GUANGDONG POLYTECHNIC NORMAL UNIV

Multi-fire extinguishing water bomb device of rotor unmanned aerial vehicle, control system and method and unmanned aerial vehicle

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.
Owner:王翊丞

Multi-policeman cooperative hunting task allocation and path planning method under road network constraint

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.
Owner:WUHAN UNIV OF SCI & TECH
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