21results about How to "Achieve autonomy" patented technology

The invention discloses a multi-sensor fusion unmanned aerial vehicle environment monitoring and early warning system, and relates to the technical field of environment monitoring and early warning, and the system comprises the following components: an unmanned aerial vehicle platform which is used as a carrying basis of sensors and data processing equipment and has excellent flight stability and strong cruising ability; according to the invention, by introducing a task planning mechanism based on autonomous learning, the unmanned aerial vehicle can continuously learn and optimize the flight strategy when executing the monitoring task, the innovation point significantly improves the efficiency of task execution, and the unmanned aerial vehicle can perform real-time monitoring according to the actual environment feedback and historical task data. The unmanned aerial vehicle can automatically adjust the parameters of the flight path, speed and height to avoid adverse factors and select the optimal path, and meanwhile, the unmanned aerial vehicle is endowed with strong scene adaptability by the autonomous learning ability, so that the unmanned aerial vehicle can quickly respond to a complicated and changeable natural environment or a sudden emergency, and smooth completion of a task is ensured.

The invention belongs to the technical field of artificial intelligence and magnetic levitation traffic, and discloses a multi-mode-based magnetic levitation operation control intelligent system which comprises a user subsystem, a user interface, an artificial intelligence subsystem, a ubiquitous perception subsystem, a magnetic levitation traffic physical subsystem and a communication subsystem. The user subsystem is used for submitting a transportation demand, a user demand and a transportation object, the artificial intelligence subsystem is used for completing a system-level safety-critical task, a vehicle-level safety-critical task and a vehicle-level non-safety-critical task, and the ubiquitous perception subsystem provides multi-modal perception information of the user subsystem and the artificial intelligence subsystem. The magnetic suspension traffic physical subsystem provides physical reality for completing transportation requirements, and the communication subsystem provides a ubiquitous interconnection basis for other subsystems. Potential implementation of multi-mode artificial intelligence in the field of safety critical requirements is effectively promoted, intelligent transformation of a magnetic levitation traffic system is accelerated, and deep fusion of calculation, information and physics is promoted.

The invention relates to the technical field of new energy power generation, in particular to a new energy fan master control system improvement method and system, and the method comprises the steps: collecting fault information of a new energy unit; performing electrical and program design according to the fault information; a fan unit is transformed on site according to electrical and program design; and carrying out performance test and acceptance on the transformed fan set. By improving the master control system of the new energy fan set, including upgrading the protection strategy and the control logic of the master control system, the fault probability of the set is reduced, the equipment maintenance time is shortened, the operation stability of the equipment is improved, the operation data and the state information can be monitored and analyzed in real time, and the management and the control of the operation state of the fan are enhanced. By technically improving the variable pitch system and optimizing the control logic of the variable pitch motor, frequent input of an electromagnetic brake, overcurrent of the motor and failure of a driver are avoided, the overall failure rate of the variable pitch system is reduced, the availability and the generating capacity of a unit are improved, and the electric quantity income is increased.

The invention relates to the technical field of offshore mooring systems, and discloses a mooring system initial design method based on a catenary equation, which comprises the following steps: determining basic parameters of a mooring system according to a multi-component catenary equation; based on the basic parameters and the central symmetry problem of the floating foundation, mooring parameters, the horizontal offset of the floating platform under different wind wave flow incidence angles, the load borne by the floating wind turbine generator and the value of the horizontal force borne by the top end of a mooring chain are determined; according to the mooring parameters, the horizontal force borne by the top end of the mooring chain and the load borne by the floating type wind turbine generator, horizontal force balance checking is conducted; the maximum offset of the floating platform is verified, if the maximum offset of the floating platform is equal to the allowable maximum offset of the floating platform, the horizontal length of a mooring chain is compared, and if the maximum offset of the floating platform is not equal to the allowable maximum offset of the floating platform, iterative optimization is carried out; and determining parameters for designing the mooring system according to the mooring parameters in the corresponding states when the horizontal length of the mooring chain is maximum so as to establish the mooring system.

The invention belongs to the technical field of overhead line operation and maintenance, and particularly discloses a tower-crossing control method, device and equipment for an overhead line inspection robot and a medium. A tower-crossing control method for an overhead line inspection robot comprises the following steps: acquiring image data of an overhead line in a preset area; inputting the image data into a preset image processing model to obtain a topographic map in a preset area; acquiring position data of the inspection robot, and generating a planning path according to the position data of the inspection robot and the topographic map; and controlling the inspection robot to cross the tower according to the planned path. The topographic map is generated by acquiring the image data for image recognition, and the planned path is generated according to the topographic map, so that the inspection robot is controlled to cross the tower, and compared with the prior art, mechanical arms and manual interference are not needed, and the cost is saved.

The application discloses an intelligent lifting type culture net cage integrated with environment sensing and adaptive depth adjustment, and belongs to the technical field of marine culture devices. The net cage main body comprises main columns and a net cover. The main columns are provided in plurality. A connecting rod is arranged between the side portions of two adjacent main columns. The periphery of the net cover is supported and tensioned by the main columns to form a closed culture space. A buoyancy adjusting mechanism is connected with the bottom of the main column and is used for adjusting the overall buoyancy of the net cage main body to vertically lift. A mooring positioning mechanism is connected with the buoyancy adjusting mechanism and is used for anchoring the net cage main body in a predetermined sea area and adapting the vertical lifting movement of the net cage main body. An environment sensing module is installed on the net cage main body. An intelligent control module is electrically connected with the environment sensing module and the buoyancy adjusting mechanism. The intelligent control module is internally provided with a decision algorithm, is used for receiving the data collected by the environment sensing module, and outputs a control instruction to the buoyancy adjusting mechanism according to a preset strategy to adaptively adjust the water depth where the net cage main body is located.

The invention is suitable for the field of meteorological prediction, and provides an El Nino power autonomous prediction method, device and equipment, and the method comprises the steps: obtaining historical reanalysis data and target surface sea temperature observation data; performing space-time matching on the target surface layer sea temperature observation data and historical reanalysis data to construct a target matching data set; pre-training the first neural network model, and establishing an initial mapping relation between the surface sea temperature and the deep sea temperature; carrying out transfer learning on a pre-trained first neural network model to obtain a second neural network model; inputting the target surface layer sea temperature observation data into the second neural network model, and reconstructing target three-dimensional sea temperature data; generating a target initial field based on an assimilation module of the El Nino power autonomous prediction model; and the El Nino power autonomous prediction model is driven by the target initial field to carry out prediction integration, and an El Nino prediction result is output. According to the method, the autonomy of the El Nino prediction is realized.

The invention discloses a generative instruction control robot method, device, equipment and medium, and relates to the technical field of robot control, the method uses TokenLearner to reduce tokens generated by a pre-trained model, only calculates the tokens once, and repeatedly uses the tokens in a subsequent network layer for future reasoning, so as to improve the efficiency of robot control. And the model reasoning speed is improved to be within 100ms. And the robot can smoothly receive the generated instruction to execute the subsequent task. According to the trained generative model, an autonomous instruction generation model is constructed based on transformer, and redundant robot logic control codes do not need to be written any more. According to the model training set, a training data set of a multi-modal robot is constructed by collecting large-batch task videos and drawing track sketches in three modes. The robot autonomy can be achieved, manual instruction issuing is gradually avoided to control the robot, and the robot can simulate human behaviors to execute some complicated tasks.

The application discloses a dynamic branch decision and response generation method and system for multi-round dialogue, and relates to the technical field of natural language processing. The method comprises the following steps: obtaining a semantic representation vector of current round user input; maintaining a current topic semantic anchor and a historical dialogue semantic anchor with different update rates, wherein the two are only updated according to the current round and the last round; determining an intention drift degree and a semantic retention degree, and obtaining a transition tendency degree with continuous values through continuous mapping; constructing a maintenance distribution with a preference to continue the current topic, and a transition distribution valued according to the relevance of candidates and input and the semantic accessibility of candidates and historical dialogue semantic anchors; continuously mixing the two distributions to obtain a branch decision distribution by taking the transition tendency degree as a weight, determining a topic trend and generating a response. The application has the advantages of not increasing the calculation and storage overhead with the increase of dialogue rounds, and autonomously and smoothly deciding the topic continuation and transition without user instructions, and keeping the coherence with the history after transition.

The invention belongs to the field of precision test technologies and instruments, and the traditional non-contact current detection meets the basic requirements of power monitoring to a certain extent, but the limitation gradually appears in the face of complex and changeable measurement environments and increasing measurement precision requirements. According to the non-switching high-precision wide-range current measuring device and the signal processing method, high-precision sampling of micro-current analog signals is achieved through the high-sensitivity signal sampling unit, and two-stage passive filter circuits are added to the signal sampling unit to filter most clutters in the analog signals, so that high-precision sampling of the micro-current analog signals is achieved. A digital signal processing method is used in the MCU to filter digital current data with higher precision, a digital signal processing technology is applied to the field of current detection, and high-precision and high-efficiency current measurement is realized by optimizing a detection circuit structure and a signal processing flow.

The invention discloses a park electricity, hydrogen, heat and cold storage coordinated optimization scheduling method and system. The method comprises the steps that a park multi-energy scheduling physical model is converted into an improved DDQN agent; the improved DDQN intelligent agent determines a first-step action, namely the action condition # imgabs2 # of all 0-1 variables, according to a behavior strategy # imgabs1 # based on an operation state # imgabs0 # given by an environment, and judges whether # imgabs3 # meets 0-1 variable constraints or not; if the # imgabs4 # meets the energy storage operation constraint, solving the second-step action # imgabs5 # and # imgabs6 # by using an interior point method, and judging whether the # imgabs7 # meets the energy storage operation constraint or not; if the # imgabs 8 # meets the condition, taking an upper limit value when the # imgabs 9 # exceeds the upper limit, and taking a lower limit value when the # imgabs 10 # exceeds the lower limit; judging whether # imgabs11 # meets other constraints or not; if the # imgabs12 # does not meet the condition, setting the reward value as a minimum value # imgabs13 # and feeding back the minimum value # imgabs13 # to the intelligent agent; and inputting the action of the # imgabs14 # intelligent agent at the current moment, the system state # imgabs15 # given by the environment and the uncertainty # imgabs16 # into a state conversion function # imgabs17 # to obtain the system state # imgabs18 # at the new moment. A high-dimensional continuous action space can be effectively processed, and the optimization scheduling problem of electric hydrogen heat cold storage coordination in the park can be better fitted.

The application relates to the technical field of subway passenger flow prediction, and discloses a space-time perception subway passenger flow prediction method based on a large model and multi-source information fusion, which comprises the following steps: constructing a data agent based on a large language model and a model context protocol, and generating text descriptions of subway stations and corresponding space context embedding vectors of the subway stations based on surrounding point-of-interest data of the subway stations by using the data agent; constructing an enhanced graph neural network according to the space context embedding vectors, and performing space-time joint prediction based on historical passenger flow data and the space context embedding vectors by using the enhanced graph neural network to obtain a preliminary passenger flow prediction result; and constructing a prompt word template, calibrating domain knowledge based on the prompt word template by using a pre-trained large language model, and obtaining a final passenger flow prediction result. The application significantly improves the performance, robustness and interpretability of the urban rail transit passenger flow prediction task through deep fusion of external multi-source information.

The invention discloses a Tokamak plasma vacuum cavity wall body layered embedded pipe gradient heat utilization device, which is characterized in that a Tokamak vacuum cavity wall body is provided with a three-layer structure of an inner wall, a middle wall and an outer wall, and a high-temperature heat exchange pipe group, a middle-temperature heat exchange pipe group and a low-temperature heat exchange pipe group which are in arc fit are respectively embedded in the three-layer wall body; the distance between the plasma and the inner wall of the vacuum cavity is regulated and controlled through magnetic confinement, accurate adjustment of heat flux density is achieved, plasma heat is conducted from inside to outside in a stepped mode, the inner wall high-temperature heat exchange pipe set generates ultrahigh-temperature high-pressure steam for large-scale power generation, and the middle-wall medium-temperature heat exchange pipe set generates medium-temperature high-pressure steam for small-scale power generation. The outer wall low-temperature heat exchange pipe set heats water through waste heat to supply heat, and the distillation drinking water heat exchange pipe set achieves self-driven circulation through water vaporization natural impulsive force and also serves as a vacuum cavity wall body cooling protection layer. According to the device, Tokamak plasma heat cascade full utilization is achieved, the heat conduction efficiency is extremely high, the structure is simple and easy to achieve, direct output of multi-level energy can be completed only through the three-layer embedded pipe design of the vacuum cavity wall body, and the technical core focuses on heat exchange and energy distribution of the vacuum cavity body and the layered embedded pipes; and high-efficiency commercial conversion of nuclear fusion heat energy is adapted.

The present invention belongs to the field of service robot grasping detection, and provides a service robot grasping method, system and robot based on knowledge-driven perception, which are used for robot autonomous grasping detection in different scenarios, and improve the generalization performance of the robot's grasping skills in unseen environments according to the robot's own capabilities, and can continue to work in changing scenarios through its embodied perception and knowledge retrieval capabilities. The present invention is based on the robot's autonomous collection of samples based on embodied perception capabilities in a new environment, and improves its own grasping ability with the help of the collected samples, so as to eliminate human intervention and achieve autonomy. Based on the collected pseudo-label samples and observation perspectives, the grasping detection process and knowledge injection model can be optimized.

The invention provides a wafer regeneration chemical mechanical polishing system and process, and belongs to the technical field of semiconductor manufacturing, and the wafer regeneration chemical mechanical polishing system comprises a buffer unit, a conveying unit, a polishing unit, a cleaning unit and a control unit, the conveying unit, the polishing unit and the cleaning unit are located on the same side of the buffering unit and are sequentially arranged along the first linear path, and the conveying unit is located between the polishing unit and the cleaning unit; the buffer unit comprises a plurality of wafer cassettes, an optical detection station located on one side of the plurality of wafer cassettes, and a transmission mechanism located on one side, close to the conveying unit, of the wafer cassettes; the conveying unit comprises a transfer disc moving along the second linear path; the polishing unit comprises a first polishing assembly and a second polishing assembly which are arranged along the second linear path. Each polishing assembly comprises at least two polishing discs and polishing heads corresponding to the polishing discs.

The invention provides a fire alarm mycelium material and a preparation method and application thereof, and belongs to the technical field of fire alarm materials, and the fire alarm mycelium material comprises hemp stalks, ganoderma lucidum, ethanethiol and the like. The preparation method of the mycelium material comprises the following steps: carrying out mixed culture on a hemp stalk culture material and ganoderma lucidum; dissolving polyvinyl alcohol and lauryl sodium sulfate in deionized water; adding ethanethiol and polymethyl methacrylate into an organic solvent; dropwise adding the water phase into the oil phase, and emulsifying to obtain ethanethiol microcapsules; and mixing the pure mycelium material with ethanethiol microcapsules, culturing, and demolding to obtain the fire alarm mycelium material. According to the invention, intrinsic integration of a material structure and an early warning function is realized through a mycelium biological assembly and microcapsule embedding and fixing technology, so that the material becomes a sensing unit. According to the material, rapid and active fire early warning without external energy is realized by utilizing the temperature-triggered fracture characteristic of the microcapsules and the extremely low odor threshold value of ethanethiol.

The present invention discloses a multi-sensor fusion underwater robot positioning method and system, which relates to the technical field of underwater positioning. By fusing multiple sensor information, including sonar data, accelerometers, gyroscopes, magnetic compasses and depth gauges, the positioning accuracy and stability of the underwater robot can be further improved; the sonar data provides three-dimensional information of the underwater environment, and the sensor integration provides the robot's own motion state. The combination of the two can further realize accurate monitoring of the robot's position and posture. By pre-constructing an underwater three-dimensional point cloud map and predicting the robot's state vector in advance, the real-time and adaptability of the positioning system can be enhanced. The pre-constructed point cloud map can be used as a reference to provide auxiliary information in the actual positioning process, and the state vector predicted in advance can be used to adjust the robot's motion trajectory to achieve more accurate navigation and control.

The application provides a method for breeding laying hens, and belongs to the field of breeding of breeding hens, and comprises the following steps: step one: selecting an experimental group A, and recording the basic data of the group; step two: calculating the average weight and standard deviation of the group A at the age of 11 weeks, determining the weight range of the group A at the age of 11 weeks under the optimal condition of production performance, and using the average weight ± N times of the standard deviation to represent the weight range standard of the target group to be bred, wherein the weight range standard of the target group to be bred is the average weight + [(−1 to 2) times of the standard deviation]; and step three: using the finally determined average weight + [(−1 to 2) times of the standard deviation] as a screening standard, and providing a basis for screening laying hens for other groups at the age of 9 to 12 weeks. According to the application, the fixed accounting method is used to replace the weight range for selection, the time node of the weight selection at the age of 10 weeks is expanded to the age of 9 to 12 weeks, the time range of the selection is expanded, and the problem of the selection time limit is effectively avoided.

The invention relates to the technical field of robot control, in particular to a task adaptive incremental cognitive map construction method and device for a mobile operation robot, electronic equipment and a storage medium. And processing the perception data to obtain an environment understanding result with a semantic tag. According to the method provided by the invention, the rasterized semantic cognition map fusing geometric, semantic and dynamic attributes is constructed and incrementally updated by fusing real-time multi-modal perception and semantic understanding, the attention weights of the attributes are dynamically adjusted based on the task types, and finally closed-loop optimization is formed through task execution feedback, so that the task performance is improved. Therefore, the robot can autonomously, reliably, efficiently and intelligently work in a complex dynamic scene.

The invention provides a vehicle escape method, device and system, and relates to the field of unmanned driving, automatic driving and unmanned vehicles. The vehicle escape method is applied to a decision-making end and comprises the steps that a takeover request of a target vehicle is received, and the takeover request comprises state information and / or environment information when the target vehicle is parked; based on the takeover request, a decision module built in the decision end is utilized to autonomously generate a target driving strategy; and sending the target driving strategy to the target vehicle, so that the target vehicle gets out of trouble according to the target driving strategy.

The present invention discloses a method for evaluating the dynamic performance of an offshore wind power structure. The evaluation method integrates the wind power structure dynamic performance evaluation technology based on a root system morphology model. The root system morphology model includes a main root layer, a lateral root layer and a fibrous root layer. The number of lateral root layers is greater than 1. The main root layer is integrated and evaluated according to the data of a first-level lateral root layer, the upper-level lateral root layer is integrated and evaluated according to the data of a lower-level lateral root layer, and the lateral root layer is integrated and evaluated according to the corresponding fibrous root layer data. When the variation range of structural dynamic performance evaluation data classified based on environmental conditions is very small, there is a phenomenon that the root system morphology model and the structural dynamic performance evaluation data based on data fusion are close to each other in peaks and troughs. It can be seen that the structural dynamic performance evaluation based on the environmental root system morphology model comprehensively considers the environmental monitoring data and the vibration response data, effectively avoids the uncertainty of a single type of sensor, and improves the reliability of the evaluation result.