54 results about "Local environment" patented technology

This invention discloses a method for reusing obstacle avoidance trajectory parameters based on local environmental geometric and motion constraint features. The method includes the following steps: acquiring a local point cloud to construct a local map; calculating the geometric residuals from points to planes based on the local map to obtain residual statistical features; calculating the plane normal distribution based on the local map to obtain structural orientation features; and constructing an information matrix based on the Jacobian matrix optimized by the direct method pose to obtain motion constraint features; combining the residual statistical features, structural orientation features, and motion constraint features into a local environmental feature descriptor; binding the local environmental feature descriptor with trajectory generation parameters of historical obstacle avoidance trajectories and storing it in a database; calculating the similarity between the current local environmental feature descriptor and the historical feature descriptors in the database, and selecting the corresponding historical trajectory generation parameters based on similarity matching; and using the historical trajectory generation parameters as the initial parameters for the current obstacle avoidance trajectory planning.

This application discloses a path planning method and system for a quadruped robot based on an improved Direct Weakening (DWA) algorithm. The method includes: acquiring a global path point sequence and the turning state of the previous control cycle; fusing multi-source sensor data to construct a local environment map and the robot's own state set; evaluating the scene complexity coefficient and determining the current tracking point; sampling candidate velocity combinations and predicting the trajectory; filtering candidates that meet stability conditions based on the turning state of the previous cycle, and eliminating collision trajectories; dynamically adjusting the evaluation function weights according to the tracking point distance, heading deviation, and scene complexity to select the optimal trajectory; smoothing the trajectory before execution, and monitoring and correcting deviations in real time. This application avoids attitude fluctuations caused by frequent switching through turning state constraints, achieves accurate approximation through distance grading and heading deviation linkage, and improves scene adaptability through multi-source fusion and dynamic weights. It solves the problems of poor attitude stability, low tracking accuracy, and insufficient robustness in complex scenes found in existing DWA algorithms.

The application discloses a UAV robust path planning method and system for uncertain dynamic environment, relates to the field of path planning, and realizes real-time tracking of dynamic obstacles by using EKF, and constructs a probability repulsive field based on Mahalanobis distance, effectively solves the sensing vulnerability and static model limitation of a traditional APF algorithm, and provides a robust dynamic obstacle avoidance guide for random tree expansion; secondly, a fuzzy logic adaptive step (FLC-AS) module is designed; the module intelligently adjusts the expansion step according to the risk degree of a local environment and an exploration stage, and realizes dynamic balance of exploration safety and search efficiency; comparison and analysis of the method and various mainstream algorithms show that the PFLS-RRT* algorithm has excellent adaptability in a complex environment, and achieves the best comprehensive performance in key indexes such as path quality, planning efficiency and robustness.

This invention discloses a robot autonomous consciousness realization system based on external perception mapping and an internal state machine, belonging to the fields of artificial intelligence, humanoid consciousness construction, and robot autonomous decision-making and control technology. It includes: an external perception module configured to collect real-time state data of the robot itself and its external environment; a mirror mapping module connected to the external perception module, configured to map the collected local environment and the robot's own state data, which are actually in contact with the robot, to the corresponding state of the internal state machine in real time; and an internal state machine module. By constructing a robot autonomous consciousness realization system based on external perception mapping and an internal state machine, it can solve problems in existing technologies such as the inability to autonomously construct internal mirrors, reliance on manual error handling, lack of process correction, storage redundancy, and disconnection from the framework, realizing fully autonomous closed-loop consciousness behavior of the robot from perception, mapping, detection, deduction, correction to memory purification.

The application provides an ultrasonic-guided medical adhesive dynamic curing control method, which comprises the following steps: collecting multi-dimensional parameters in the medical adhesive curing process by using an ultrasonic real-time monitoring module, and transmitting monitoring data to a central control module in real time; purifying and standardizing the ultrasonic monitoring data and preoperative parameters of a patient by using a multi-source data preprocessing module; realizing precise prediction and control strategy generation of the curing process by using a curing rate prediction and control model module; adjusting the spraying state of the medical adhesive by using a medical adhesive spraying execution module; and assisting in optimizing the curing rate of the medical adhesive by regulating the local environment of a wound through a local environment regulation module. In the above technical solution, the precise matching of the curing rate and the operation demand is ensured.

The application discloses a kind of to time data processing method and system, it is related to data processing technical field, the method includes: based on local environment data, acquisition acquisition cycle, collect high-precision time data and local perception data;Data characteristics of the same batch crystal are analyzed, and based on the high-precision time data and the local perception data, obtain time deviation;Based on the data characteristics analysis rationality of time deviation, obtain rationality analysis result, adjust the acquisition cycle, obtain optimized acquisition cycle;Based on the local environment data is combined mapping table to obtain correction value, and based on the time deviation and crystal data characteristics and the mutual influence correlation of time deviation, the mapping table is dynamically revised, to obtain revised mapping table, for the time data processing of next cycle.The application solves the technical problem that the prior art exists and time data processing effect is not good.

This invention provides a privacy-preserving intelligent agent cross-domain knowledge hybrid retrieval method and system, relating to the fields of artificial intelligence and data security technology. The method includes: responding to a query request initiated by a cloud-based intelligent agent, parsing the privacy tags embedded in the request workflow definition; and concurrently executing the following two operations through an asynchronous task scheduler: sending the public subquery to a cloud-based knowledge retrieval service, and routing the private subquery to a privacy computing agent client deployed in the target local environment; the privacy computing agent client executing the private subquery in a local private knowledge base; and at a cloud aggregation point, aggregating the decrypted ciphertext knowledge fragment set and the public knowledge fragment set into unified knowledge data, and returning it to the intelligent agent. This invention achieves efficient, secure, and integrated retrieval and utilization of distributed heterogeneous knowledge bases by a cloud-based intelligent agent while ensuring that the original privacy data does not leave the local security boundary.

This invention discloses an autonomous sensing robotic arm suitable for confined spaces. A lateral translation slide rail is mounted on the upper end of a compact equipment mounting base, allowing for reciprocating movement along the length of the base. A second-stage rotation unit is mounted on the first telescopic arm, enabling second-stage horizontal rotation adjustment of the second telescopic arm and cooperating with the first-stage rotation unit to achieve horizontal positioning. A binocular stereo vision sensor, mounted on the second telescopic arm, performs real-time 3D ranging, identifies unexpected obstacles within the work area, and generates a 3D point cloud of the local environment, providing environmental perception data for obstacle avoidance and path planning. This invention improves operational flexibility, ensures operational continuity, significantly increases overall operational efficiency, enhances operational reliability, and significantly reduces the requirements for operator skills and experience.

The present application relates to a kind of heuristic Q-learning-based multi-robot full coverage path planning method, including constructing global gridding map and dividing mutually non-overlapping connected sub-region by DARP algorithm;Each robot independent sub-environment is constructed and Q-learning agent is initialized;Agent uses the enhanced state definition of "absolute coordinate+local environment topological feature", and the optimal action is selected by heuristic strategy of unvisited priority and backtrack distance guidance;The Q value table is updated based on the comprehensive function of coverage reward, dynamic repeated access penalty and completion reward;Path is generated after iteration training to full coverage or reaching preset number.The present application reduces 23.8% of total moving steps under the premise of ensuring 100% coverage, reduces path repetition rate from 26.35% to 3.36%, reduces 44.1% of turning number, significantly improves work efficiency, and can be widely applied to collaborative work scenarios such as cleaning robot cluster and agricultural automatic harvester group.

This application discloses an adaptive inspection method and system for the interior of wind turbine blades. The method includes: determining the initial environmental feature information inside the wind turbine blades and generating a global reference frame; controlling an inspection robot to perform inspection operations along the global reference frame, and fusing multi-source sensor data in real time to output the pose sequence of the inspection robot and a local environment model relative to the inspection robot; extracting spatiotemporal features from the pose sequence and the local environment model to obtain multi-dimensional quantitative indicators, and forming a comprehensive performance score based on the multi-dimensional quantitative indicators; adjusting the motion control parameters of the inspection robot in real time based on the comprehensive performance score; constructing an inspection dataset; and generating an inspection report. Using the scheme of this application, by constructing a global reference frame and fusing multi-source sensor data, the positioning accuracy and environmental perception capability of the inspection robot in the complex enclosed space of wind turbine blades are significantly improved.

The application provides a robot trajectory generation method and system based on diffusion and rule inference, and relates to the technical field of autonomous navigation.The application proposes a novel conditional diffusion trajectory generation model based on architecture induction bias, which is not only dependent on loss function for result constraint, but also divides the complex trajectory generation task into two mutually coordinated technical processes:1, based on local environment graph construction, graph convolution propagation and graph level feature convergence, the inference of the overall passable structure and obstacle topological relationship within the scope of the current local environment graph is realized;2, based on node level scene representation, target feature continuous injection and prediction step by step context update, the fine-grained local maneuvering control of obstacle avoidance, turning and end convergence behavior at each future waypoint is realized, and the high-fidelity generation of the trajectory in the complex unstructured environment is ensured.Meanwhile, a GTGRU is designed, the end drift problem is solved by introducing time attention bias.

This invention discloses a method for predicting the severity of localized corrosion environments based on the surrounding environment. The method includes: constructing a semi-closed simulation test system to simulate the internal local environment of equipment; conducting accelerated corrosion tests under different external environmental conditions, collecting external environmental parameters, internal local environmental parameters, and corrosion response data of metal samples; constructing a time-series feature matrix from the external environmental parameters; calculating a comprehensive corrosion risk index based on the corrosion response data; constructing and training a correlation prediction model from the time-series feature matrix to the comprehensive corrosion risk index using an attention mechanism long short-term memory network; collecting external environmental parameters in real time and inputting them into the trained correlation prediction model; and outputting a predicted value for the severity of localized corrosion environments at the target location of the equipment. This invention enables accurate and rapid assessment of internal corrosion risk based solely on externally measurable data, solving the problem of difficulty in directly monitoring the internal or localized corrosion environment of equipment.

This invention discloses an indoor robot path planning method and system based on navigation feedback closed-loop calibration. The method includes: constructing an initial representation of the local semantic environment based on RGB images, depth images, robot pose information, and local obstacle observation information; generating a local path based on the current local environment representation and driving robot movement; using navigation behavior anomalies generated by the robot during actual operation as feedback signals to perform reverse calibration of the local environment representation; extracting topological information from the local passage space and dynamically adjusting semantic risks to form a total risk field for path planning; and performing gated replanning and adaptive adjustment based on the total risk field. By introducing a navigation execution feedback-driven closed-loop calibration mechanism, this invention not only improves the consistency between the local environment representation and the actual passage state but also, by combining dynamic adjustment of topological semantic risks and gated replanning control, further enhances the stability and safety of path planning in complex indoor environments.

This utility model relates to the field of environmental monitoring equipment technology, specifically proposing a biomimetic frog-inspired mobile platform, comprising: a platform body, front support legs, and rear support legs; two front support legs are symmetrically arranged on both sides of the front end of the platform body; two rear support legs are symmetrically arranged on both sides of the rear end of the platform body; the rear support legs have a three-section structure on the side closest to the front support legs, extending forward towards the front support legs to form a forward joint. This design simulates the basic shape and movement of frogs, improving mechanical freedom and propulsion, facilitating integration into the local environment and significantly reducing the impact on the habitat of local organisms. Furthermore, by simulating frogs, a lightweight overall structural design is achieved, greatly reducing damage to the local terrain and improving endurance, thus ensuring the efficiency of patrol work.

This invention discloses a smart ecosystem for desert soil degradation that synergizes photovoltaic desertification control with the resource utilization of concentrated brine in agriculture. In this invention, industrial solid waste is transformed into multifunctional ecological restoration materials, constructing a stable aggregate structure for desertified soil. Simultaneously, the scientific configuration of salt-tolerant vegetation rapidly establishes a vegetation community adapted to the local environment, effectively curbing wind and sand erosion. The shading effect of the photovoltaic array not only reduces surface water evaporation but also creates a suitable microclimate for vegetation growth, gradually forming a virtuous cycle of soil-vegetation-microorganisms. This fundamentally reverses the desertification process, improves the regional ecological environment, and achieves efficient recycling of various resources through the construction of a complete closed-loop synergistic system. Furthermore, the stable electricity provided by the photovoltaic system not only meets its own operational needs but also drives seawater desalination and concentrated brine separation treatment, transforming concentrated brine into valuable resources for vegetation irrigation and soil improvement, avoiding resource waste and secondary pollution.

The application relates to the technical field of intelligent auxiliary travel equipment, and particularly provides an obstacle avoidance early warning system suitable for an electric wheelchair. The system comprises a multi-sensor perception module for collecting multi-modal data of a surrounding environment; a data processing and risk assessment module for constructing a local environment dynamic map and performing multi-dimensional risk quantification; an intelligent early warning and decision module for executing hierarchical early warning and flexible active intervention such as vision, hearing and touch according to a risk level; and a personalized learning module for optimizing risk assessment parameters and early warning strategies through reinforcement learning based on user historical behaviors. The system can realize all-around obstacle identification and dynamic avoidance, has high adaptability and learning ability, significantly improves the driving safety and user experience of the electric wheelchair in a complex environment, and has good practicability and popularization prospect.

A system and method for mapping a user's gestural interactions (positional interactions and pointing interactions) from their environment to that of their avatar's environment. The system and method provide a multi-objective optimization (MO) process with the primary objective being to minimize the positional error between the end effector and goal target and the secondary objective being to preserve the original body pose while redirecting the end effector to the goal target. The primary and second objectives are addressed with a dynamic weight allocation approach that optimizes between the objectives of body joint redirection and preserving the body pose of the original interaction.

The application discloses a salt and alkali grassland grass seed adaptability screening method and system based on multispectral remote sensing, and particularly relates to the technical field of agricultural resource informatization management and evaluation, and is used for solving the problems that the existing salt and alkali grassland grass seed screening method is dependent on manual work, is inefficient, and the evaluation result is greatly affected by local environment variation of a test site; a germplasm database is established and a test plot is arranged; multispectral remote sensing images of the test area are acquired; mixed pixel decomposition is performed on the images to obtain the abundance proportion of different grass seeds in each pixel and pure end-member spectral information of the different grass seeds; an inversion model is established based on the end-member spectral information and ground measured biomass data; a biomass spatial distribution map is generated in combination with the abundance proportion and the inversion model, and grass seeds are adaptability screened according to the biomass spatial distribution map; large-area data are rapidly acquired through remote sensing means, and mixed pixel decomposition technology is used to strip off environmental interference, so that efficient, objective and accurate evaluation on adaptability of multiple grass seeds is realized.

The application relates to the technical field of intelligent control and concrete curing of building engineering, in particular to a building component curing control system based on parameter dynamic feedback, which is communicated and connected with local environment monitoring nodes, internal state sensing terminals, partition spraying devices and heating devices, and comprises a multi-source parameter acquisition interface module, a state evolution calculation engine and a local decoupling control module; through temperature and humidity data time sequence alignment, environment data sets and state data sets are formed, time differences of space curing reactions in different topological regions are analyzed, a dynamic temperature gradient change rate tolerance is established, after double interlocking arbitration, the target topological region is directionally adjusted in terms of spraying amount and heating power, complex component space asymmetric compensation control is realized, and micro crack initiation is inhibited.

This application discloses an automated application deployment method based on a hybrid architecture, aiming to solve the problems of high cost of fully cloud-hosted services, unsuitability of lightweight event-driven architecture for the full lifecycle management of complex applications, and low automation and chaotic version management in traditional hybrid architectures. The method is executed by a continuous integration and deployment orchestrator deployed in a local environment, and mainly includes: receiving build instructions, completing application building based on project source code and generating a container image; pushing the image to a designated cloud container image repository; automatically initiating a deployment instruction to the associated cloud container engine service in response to the image push completion event via a trigger preset in the image repository; and causing the cloud container engine service to respond to the instruction, pull the updated image, and complete the service update operation in the container cluster.

This invention belongs to the field of nozzle technology and discloses a steam humidification nozzle device and its usage method. It includes a humidification nozzle outer shell and a humidification nozzle inner shell. The humidification nozzle inner shell is disposed inside the humidification nozzle outer shell and the two shells are coaxially arranged. Several rotating nozzles are provided on both sides of the humidification nozzle inner shell. These rotating nozzles pass through the humidification nozzle outer shell to transport steam. The cavity between the humidification nozzle outer shell and the humidification nozzle inner shell is a first cavity. An outer shell air inlet is provided on one side of the humidification nozzle outer shell, communicating with the first cavity. An inner shell air inlet is fixedly connected to one end of the humidification nozzle inner shell. The transmission unit includes a first gear and a second gear. The second gear is fixedly installed on the outer surface of the inner shell air inlet, and the first gear is fixedly installed at the output end of the drive component. The rotating nozzles rotate with the humidification nozzle inner shell, expanding the humidification range and improving the humidity uniformity of the local environment.

The utility model relates to a kind of eel pond water body anoxia alarm device, comprising: alarm and dissolved oxygen detection mechanism, the first float block, second float block, third float block of dissolved oxygen detection mechanism are sequentially head-to-tail connection by first connecting rod, second connecting rod and third connecting rod, and vertically with first detection rod, second detection rod and third detection rod are respectively set to form three-dimensional detection frame, first oxygen sensor, second oxygen sensor and third oxygen sensor can stably three-dimensional array on first detection rod, second detection rod and third detection rod, different depth of different area of eel pond dissolved oxygen concentration can be detected in all directions, avoid the detection error caused by local environment difference, improve the accuracy and comprehensiveness of detection, when the oxygen-dissolving amount is lower than set value, the controller of alarm can control loudspeaker and flashing light work to carry out alarm, it is convenient for aquaculture personnel to timely manage the breeding environment of eel, guarantee the survival environment of eel.

The present invention relates to a system for smart agriculture biochar production, yield prediction, and measurement. The system utilizes real time remote sensing of the local environment, weather and related conditions, and data analysis on spatial and spectral imagery data captured from satellite sensors, aerial sensors, and agricultural drones. The system performs a field mapping of a target field having a biomass and obtaining spectral imagery data of the biomass. A mobile pyrolysis system is deployed about the target field and follows a path derived from the spectral imagery data.

This invention discloses a quantum-inspired adaptive crushing and spatiotemporal coordination mining method, belonging to the field of ore mining technology. It includes: real-time acquisition of ore and rock parameters during drilling to construct a three-dimensional dynamic barrier field characterizing the crushing difficulty; dynamic adjustment of the crushing equipment's operating frequency and energy waveform based on the barrier field value, achieving efficient crushing through coherent enhancement with the inherent frequency of the ore and rock; mapping crushing points to transportation units to construct spatiotemporal coordination unit pairs, defining the coupling relationship between discharge rate and arrival time using a preset state correlation function; maintaining a probabilistic superposition state of candidate paths for the mobile equipment, triggering probabilistic collapse decisions based on the local environment; and dynamically adjusting the coupling strength of the coordination unit pairs based on mining efficiency to evolve the optimal coordination mode. Inspired by quantum mechanics, this invention achieves on-demand energy supply, precise crushing-transportation coordination, and intelligent path decision-making through classical physics field simulation, significantly improving energy utilization, system robustness, and overall production efficiency.

The present application relates to the technical field of robot control, in particular to a kind of water reservoir bottom mud dredging robot gait planning method and system, comprising: based on the collection multimodal sensing information, constructs the environment semantic map of dredging robot;According to the environment semantic map, drive foot end actuator and water reservoir bottom mud environment interact, and according to the real-time force and motion data existing in the interaction process, obtain the local environment dynamics parameters of water reservoir bottom mud environment;According to local environment dynamics parameters and preset gait sequence instruction, predict the predicted joint control instruction on future period, and drive foot end actuator according to predicted joint control instruction;The execution parameter of foot end actuator is monitored, and when execution parameter exceeds preset safety execution parameter, generate fault-tolerant joint control instruction to drive foot end actuator, effectively solve the technical problems that existing gait planning method cannot guarantee the stable operation and efficient operation of dredging robot.

The application discloses a kind of methods for the cooperative detection of submersible formation and related products.Therein, the method comprises: obtaining the obstacle distribution map and target candidate list according to the acoustic data, optical data, depth perception data and hydrological environment data collected by the sensor;According to the obstacle distribution map, update the local environment map of the target submersible;For any target, if the confidence corresponding to the target is greater than the first confidence threshold, send the first target discovery message to other submersibles;In response to the target submersible receiving the second target discovery message sent by other submersibles, update the global state table information according to the second target discovery message;According to the state of target submersible, local environment map and global state table information, cooperative detection is carried out with other submersibles.The cooperative detection method of submersible formation in the embodiment of the application can improve the cooperative efficiency and dynamic adaptability between each submersible in the submersible formation.

This invention discloses a target object navigation method based on Transformer, comprising: inputting the current environment image and the name of the target object to obtain a local environment feature vector, a global environment feature vector, and a target object feature vector; inputting the three vectors into a target vector Transformer model to obtain the final target vector at the current time; inputting the final target vectors at the current time and the previous time step into a navigation direction vector Transformer model to obtain a navigation direction vector; inputting the navigation direction vector into an A3C reinforcement learning model to obtain the action probability distribution vector, action score vector, and reward value at the current time step, and then selecting the action with the highest probability in the action probability distribution vector for execution; repeating the above process until the robot completes the action, and updating the model weights according to the action score vector and reward value at different times. This invention can improve the navigation effect and generalization ability.

The application provides a kind of intersection decision method based on multi-agent deep reinforcement learning, each agent is interacted with environment, obtains observable agent information and local environment information, whole state information is transmitted to model for learning, all agents are trained collectively, according to environment, explore action, agent gives corresponding decision, finally is transmitted to the bottom control of agent vehicle. Each round gets current reward, according to current reward and next state, new round training is carried out, so as to complete model building. The advantage is to improve the deep neural network model, optimize the process of action exploration, reduce the exploration process of invalid action, enhance the robustness of decision model, increase the performance of model in complex scene, reduce the training difficulty of model. Through the reward function involving multiple constraints, the generalization ability of the model method in complex scene is increased.