564 results about "Waypoint" patented technology

The invention relates to the technical field of unmanned aerial vehicles, in particular to an intelligent flight path planning and energy management system and method for a long-endurance fixed-wing unmanned aerial vehicle. Comprising an environment sensing unit; the flight path planning unit is used for planning a flight path meeting task requirements, safety requirements and energy constraints based on the flight environment information of the unmanned aerial vehicle acquired by the environment sensing unit and pre-stored performance parameters of the unmanned aerial vehicle; and the energy management unit realizes energy dynamic management and optimization according to the real-time energy state of the unmanned aerial vehicle, the flight task and the planning result of the flight path planning unit. The flight path planning unit can call working condition energy consumption data such as navigational speed and height output by the energy management unit in real time, and dynamically adjust the weight of the path to avoid high-energy-consumption flight segments; the energy management unit synchronously and intelligently adjusts a main / standby battery charging and discharging strategy to optimize energy distribution according to a task time sequence (such as waypoint priority and track curvature) of a track.

The present disclosure belongs to a field of UAVs exploration technology, discloses a high-efficient autonomous exploration method, system, and terminal for UAVs, comprising: S1, heuristic waypoint generation: setting an exploration scope and waypoint spacing, and generating waypoints through waypoint generation algorithms; S2, global path planning: after generating heuristic waypoints, an A * algorithm is used to generate the global planning path; S3, real-time positioning and mapping: using point clouds for real-time positioning and mapping; S4, local B-spline trajectory generation: using B-spline parameterization method to generate local trajectories; S5, real-time obstacle avoidance and dynamic feasibility constraints: optimizing the trajectories to achieve fast convergence, generating smooth, collision-free, and dynamically feasible trajectories; S6, local real-time replanning: using a time sliding window for local replanning; S7, flight control: Using UAV control algorithms for controlling of UAVs robustly.

The invention provides an energy optimal path planning method and device for an unmanned surface vessel in a complex marine environment, and belongs to the technical field of path planning. The method provided by the invention comprises the following steps: constructing a comprehensive energy consumption model; constructing a hybrid enhanced particle swarm optimization algorithm; constructing a safety space set and an adjacent graph through a grid method, generating an initial optimal path by adopting an A * algorithm, and carrying out bounded random disturbance and safety correction on target particle waypoints; smoothing the path generated by iteration by adopting a B-spline technology, resampling the smoothed optimal solution, and then reinjecting the optimal solution into the population; adjusting an inertia weight and a learning factor based on the number of iterations, and introducing double guide factors to carry out secondary adjustment on a cognitive item of particle speed updating; and embedding the comprehensive energy consumption model as a fitness function into a hybrid enhanced particle swarm optimization algorithm, performing real-time energy consumption evaluation, individual and global optimal path updating and path smooth optimization on each candidate path in an algorithm iteration process, and outputting an optimal navigation path of the unmanned surface vessel.

The invention discloses an unmanned aerial vehicle cooperative inspection route optimization method and device and electronic equipment, and relates to the field of unmanned aerial vehicle inspection, and the method comprises the steps: carrying out the deep cleaning, anomaly detection, multi-source feature fusion and dimension reduction, space-time calculation and result mapping of multi-source heterogeneous data of a to-be-inspected region; carrying out fusion, electromagnetic interference evaluation and optimization on the generated dynamic environment probability map and the flight risk evaluation model, carrying out key waypoint segmentation extraction and trajectory adjustment on the improved route scheme, generating a dynamic route adjustment scheme, and carrying out cooperative distribution of multiple unmanned aerial vehicle tasks on the dynamic route adjustment scheme, so as to obtain a dynamic route adjustment scheme; and carrying out route optimization on the distributed multi-unmanned aerial vehicle cooperative inspection scheme, and carrying out multi-dimensional flyability analysis and adaptive optimization on the multi-unmanned aerial vehicle cooperative inspection scheme to obtain an unmanned aerial vehicle inspection route. According to the invention, the technical problem of low efficiency and quality of unmanned aerial vehicle inspection due to the fact that the unmanned aerial vehicle inspection route only focuses on optimization of a single factor in the prior art is solved.

The invention discloses a path planning method and device for an unmanned ship, a storage medium and equipment, and relates to the technical field of traffic ships, and the method comprises the steps: building an environment map according to the current position information of a ship, the position information of a destination, the state information of the ship and the position information of an obstacle; based on ship motion characteristic constraints, an initial path point sequence is generated through an improved progressive optimal fast exploration random tree algorithm, and the waypoint deviation risk is eliminated. And carrying out motion constraint perception path optimization processing on the initial path point sequence to generate a smooth path which can be directly and efficiently executed by a tracking controller. A plurality of groups of optimized path point sequences are obtained based on ship characteristic parameters with different constraint degrees, the limitation that a path is difficult to adapt to complex sea conditions under a single motion constraint working condition is broken through, finally, path quality multi-target comprehensive evaluation is performed on the plurality of groups of optimized path point sequences, and an optimal target planning path is obtained through screening. The problems of insufficient feasibility and low efficiency of ship path planning are solved.

The invention provides a transformer substation unmanned aerial vehicle three-dimensional route real-time planning and autonomous obstacle avoidance system, and relates to the technical field of non-electrical variable control or adjustment systems. Through cooperative work of a navigation mode switching module and a near-field navigation control module, an electric field of equipment is used as a natural navigation beacon; and high-precision autonomous flight is realized in a strong electromagnetic interference area with RTK signal failure, and the dependence on external positioning is eliminated, so that the inspection blind area is eliminated. Meanwhile, a fusion environment map containing multi-physics field information is constructed, the value of observation points is scientifically quantified according to waypoint inspection efficiency indexes, and a path planning algorithm aims at optimizing a comprehensive target fusing energy consumption, risks and inspection efficiency. The design not only ensures that the unmanned aerial vehicle can safely get close to the core equipment, but also enables the planned route to be the most valuable path rather than the shortest path, and finally fundamentally improves the safety, the operation efficiency and the data validity of substation inspection.

The invention discloses a substation unmanned aerial vehicle inspection dynamic route planning method and device. The method comprises the steps of collecting and constructing a substation 3DGS model, optimizing details, dividing areas, recognizing equipment parts, inversely calculating waypoint parameters, planning waypoints of a safety channel and a flight channel, generating a basic model data set, and dynamically generating an inspection route in combination with tasks. The device comprises a model construction module, a region division module and the like. On the basis of a 3DGS model and equipment part identification, through a multi-level waypoint system and a dynamic planning algorithm, full-process automation from model construction to route generation is achieved, it is ensured that unmanned aerial vehicle routing inspection is safe and efficient, equipment updating and task changing are adapted, the problems that traditional two-dimensional planning is insufficient in precision, and static route flexibility is poor are solved, and the unmanned aerial vehicle routing inspection efficiency is improved. And the automation and intelligence level of substation inspection is improved.

The invention provides a visual language navigation method and system for a continuous environment, and relates to the field of visual language navigation, based on a language instruction and an environment topological graph initialized to be null, an intelligent agent autonomously navigates to a specified position in an unknown continuous environment by adopting a step-by-step navigation mode, and the navigation efficiency is improved. The specific operation of each step-by-step navigation comprises the following steps: acquiring a local panoramic image and a current environment topological graph of the current position of the intelligent agent; deadlock detection is carried out based on meta-cognitive monitoring, candidate waypoints in the local panoramic image are identified if deadlock is not detected, node features of the candidate waypoints are generated and added to the current environment topological graph, and the optimal waypoint is selected from the current environment topological graph; generating a bottom action instruction of the current position of the intelligent agent through an active reasoning obstacle avoidance method based on a depth map; according to the invention, meta-cognitive monitoring, gating multi-modal fusion decision and inference-reaction active obstacle avoidance are organically combined, and a systematic solution is provided for visual language navigation in a continuous environment.

The invention relates to an air-ground collaborative exploration method in an unknown environment based on three-dimensional Gaussian splashing, and belongs to the field of air-ground robot collaborative exploration in a dangerous environment. The method comprises the following steps: S1, acquiring image data of a to-be-explored area by using an unmanned aerial vehicle, describing a complex scene and a differentiable rendering technology by using three-dimensional Gaussian distribution, accurately estimating a camera pose of the unmanned aerial vehicle and reconstructing a three-dimensional environment in real time by combining a simultaneous localization and mapping (SLAM) system, traversing a space and marking a series of key waypoints; step S2, the ground robot realizes accurate exploration of a local three-dimensional environment by using waypoints provided by the unmanned aerial vehicle and combining a collaborative mechanism of global planning and local planning; and S3, dynamically updating the path plan through the robot in the exploration process, and constructing a fine three-dimensional map of the exploration area. According to the invention, the air-ground robot can collaboratively explore the unknown environment and establish the environment map.

The invention relates to the technical field of electric power, in particular to an unmanned aerial vehicle route automatic planning method and system for a complex space of a transformer substation. Analyzing at least one inspection task instruction input by a user to obtain a task type corresponding to each inspection task instruction and a data acquisition requirement corresponding to the task type; according to a preset three-dimensional semantic map of the transformer substation and the data acquisition requirement of each inspection task instruction, a flight route of at least one unmanned aerial vehicle is automatically generated by adopting a path planning algorithm, and the flight route comprises a waypoint sequence, a flight height, a shooting angle and a holder action instruction; the three-dimensional semantic map comprises no-fly zone information in the transformer substation, a plurality of devices, the position of each device, the device type, the electrification attribute and the safety rule label. And controlling the corresponding unmanned aerial vehicle to inspect target equipment in the transformer substation according to the flight route of each unmanned aerial vehicle. And large-scale and standardized inspection operation is realized.

The invention provides an unmanned aerial vehicle route planning operation safety monitoring system and method based on virtual-real fusion, belongs to the technical field of unmanned aerial vehicle safety monitoring, and aims to solve the problems that the test training difficulty of an unmanned aerial vehicle is increased and the experiment cost of the unmanned aerial vehicle is high due to interference and terrain transformation in the task execution process of the unmanned aerial vehicle. The safety monitoring system comprises a ground distributed semi-physical virtual-real fusion simulation platform and an air experiment module. The ground distributed semi-physical virtual-real fusion simulation platform is used for constructing a virtual test scene of task execution of the unmanned aerial vehicle, optimizing a waypoint planning decision according to feedback information in a task execution process, and performing safety judgment and real-time obstacle avoidance on the current waypoint planning decision so as to optimize the waypoint planning decision; and the space-time experiment module is used for monitoring the flight state of the unmanned aerial vehicle and executing the optimized waypoint planning decision.

The invention relates to an end-to-end automatic driving system based on multi-modal fusion, and the system comprises an environment sensing module which comprises a plurality of types of sensors and is used for collecting environment information of different modals; the feature extraction module is used for carrying out feature extraction on the environment information of different modes and converting the environment information into aerial view space to obtain multi-mode BEV features; the feature fusion module is used for fusing the multi-modal BEV features to obtain fused features; the behavior planning module is used for outputting a future waypoint of the target vehicle and a prediction result of a control instruction according to the fusion features by adopting a trained behavior planning network; and the output fusion module is used for carrying out track prediction and multi-step control prediction and selecting an optimal driving behavior based on a situation strategy. Compared with the prior art, the method has the advantages that the environment sensing precision and decision generalization ability in a complex scene are effectively improved, error accumulation between modules is reduced, and a more efficient solution is provided for end-to-end automatic driving.

The invention discloses an intelligent navigation method and device of an unmanned aerial vehicle, equipment and a storage medium. The method comprises the following steps: acquiring point cloud data and motion data, and calibrating to obtain a relative position and time synchronization parameter; performing map construction on the point cloud data and the motion data to generate a three-dimensional point cloud map; analyzing the boundary coordinates of the flight area, the flight height and the route step length, and generating route planning parameters; the boundary of the target inspection area is defined by combining the three-dimensional point cloud map, and an optimized route and corresponding waypoint sequence data are generated through route planning; acquiring real-time pose data of the unmanned aerial vehicle, comparing the current position with the waypoint sequence, and triggering image acquisition when a preset waypoint reaches a tolerance range; inspection data is obtained; and integrating the real-time pose data, the three-dimensional point cloud map, the flight state and the inspection data to form an intelligent navigation route. According to the invention, high-precision positioning and linkage of waypoints and data acquisition are realized, and the navigation precision, the inspection efficiency and the operation safety are improved.

The invention provides an aircraft guidance control method under constraint of passing points. The method comprises the following steps: step 1, discretizing a guidance control process; step 2, carrying out segmentation processing on the guidance process of the limited passing point; 3, solving a state transition control sequence between the passing points; 4, solving the passing speed of the passing point; and step 5, calculating an overall guidance process, dividing the whole guidance process into k relatively independent guidance processes according to the step 1 when the positions and the speed states of all the passing points are known, and performing guidance control between two adjacent passing points. According to the method, aircraft guidance control under guidance time and passing point constraints is realized, the coupling problem which is difficult to effectively solve in the prior art in the guidance problem is solved, a guidance relative motion track and guidance control cost can be accurately given, the control track is smooth, and the guidance control precision is high. The method is suitable for various guidance control processes based on model prediction and inversion, and an engineering implementation method can be provided for guidance control tasks of various scenes.

The invention provides a self-adaptive accurate rust removal method and system based on unmanned aerial vehicle visual feedback, and relates to the technical field of large metal structure surface maintenance and anticorrosion treatment.The rust removal method comprises the steps that a global path is planned, and a global flight waypoint sequence is generated; a local image of the current to-be-derusted area is collected; the corrosion characteristics of the current to-be-derusted area are analyzed, and initial derusting parameters and initial derusting time are set; after each derusting operation is finished, a frame of intermediate result image is collected; based on the difference between the intermediate result image and the historical image, performing quantitative evaluation on the effect of the previous rust removal operation, and performing feature analysis on the residual rust region; self-adaptively adjusting and generating rust removal parameters of the next stage; and the steps of derusting operation, image collection, evaluation and parameter adjustment are repeatedly executed, and after the termination condition is met, the unmanned aerial vehicle is switched to the next to-be-derusted area.

The invention discloses a tilt rotor aircraft flight control method in a tilt transition stage, and the method comprises the steps: determining a reverse tilt state point which is a waypoint of which the to-be-fly distance to the starting point of a multi-rotor mode descent stage is greater than or equal to the shortest design deceleration distance and the height is H; and when the tilt rotor aircraft is located at the reverse tilt state point, controlling the tiltable rotors to tilt reversely according to the tilt angle instruction, and controlling the tilt rotor aircraft to fly forward according to the reverse tilt transition flight speed. In the reverse tilting transition stage, the tilting angle rate is calculated based on the to-be-fly distance, and corresponding flight control strategies are executed for different stages in the reverse tilting transition stage in combination with comparison of the to-be-fly distance and the forward distance threshold value and the tilting angle range, so that accurate control over the position of the aircraft in the reverse tilting transition stage is achieved.

The invention discloses a ship path planning method based on traffic flow feature point guidance, and the method comprises the steps: obtaining weighted fusion points based on the feature points of a ship position point, the feature points of a ship steering point, and the feature points of a ship route intersection point, and carrying out the filtering constraint, the directivity constraint, and the accessibility verification constraint of a space corridor. Filtering the weighted fused points to obtain an initial shortest route; the method comprises the following steps: establishing a first spatial corridor constraint, obtaining a guiding waypoint by adopting a first spatial corridor constraint, establishing a guiding area taking the guiding waypoint as a center, obtaining a guided path by adopting an improved Bi-RRT algorithm, and finally obtaining an optimized path, thereby completing ship path planning based on traffic flow feature point guidance. According to the method, the problem of deviation between the path planning result and the actual navigation demand can be greatly avoided, and as candidate waypoints are simplified, the calculation power is reduced, and meanwhile, the requirements of path optimization and collision avoidance are considered, the ocean traffic flow characteristics can be fully utilized.

A method for generating intermediate waypoints for a navigation system of a robot includes receiving a navigation route. The navigation route includes a series of high-level waypoints that begin at a starting location and end at a destination location and is based on high-level navigation data. The high-level navigation data is representative of locations of static obstacles in an area the robot is to navigate. The method also includes receiving image data of an environment about the robot from an image sensor and generating at least one intermediate waypoint based on the image data. The method also includes adding the at least one intermediate waypoint to the series of high-level waypoints of the navigation route and navigating the robot from the starting location along the series of high-level waypoints and the at least one intermediate waypoint toward the destination location.

An aquatic rescue vehicle formed by adding directional and speed controls to a watercraft along with an autonomous control system to guide the vehicle to specified waypoints is disclosed. The rescue vehicle includes search devices such as a radio direction finder (RDF) and an infrared sensor (or camera) to be used to narrow the search for an isolated person (IP). The rescue vehicle may be discharged from a larger watercraft or an airplane and autonomously set out on its rescue mission. The vehicle may first navigate to a designated waypoint near an IP, and then use signals gathered from the RDF and infrared sensor to finally locate, assist, and retrieve the IP. The vehicle also includes a self-righting mechanism so that the vehicle can complete its mission even under the most adverse conditions.

The invention discloses an unmanned aerial vehicle waypoint generation method and device, and relates to the technical field of unmanned aerial vehicles. Based on the bridge boundary point set, determining an inspection area topology boundary, and constructing a minimum closed inspection area; generating parallel scanning lines in the minimum closed enclosing rectangle of the minimum closed inspection area, obtaining intersection points of each scanning line and the boundary of the minimum closed inspection area and each side line of the obstacle polygon, and obtaining a safety interval and an obstacle interval on each scanning line by judging the positions of the intersection points; safety interval waypoints are generated in the safety interval on the scanning line, obstacle avoidance waypoints are generated at the boundary of the obstacle interval, and a preliminary waypoint sequence is formed; and generating a coverage path by adopting an alternate scanning mode, performing interpolation and de-duplication processing on the initial waypoint sequence, generating a final waypoint sequence, outputting the final waypoint sequence as a waypoint file, and docking with an unmanned aerial vehicle flight control system through an interface to realize autonomous inspection flight. The problems that in the prior art, waypoint setting efficiency is low, and potential safety hazards exist are solved.

A portable flight navigation tool has a tablet computer with GPS, and memory with an aviation database with international operating rules including transoceanic flight rules, a moving-map database with tracks, coastal airport identifiers and locations, and predefined reporting point locations for transoceanic operations. The navigation tool includes machine readable code for displaying the operating rules, reading locations from the GPS while indicating them on a moving map display, and a trip database with a planned transoceanic route for an individual flight configured by entry of waypoints or names and selection of predefined tracks. The tool has a checklist database and displays checklists for pre-departure, coast-out flight phase, waypoint-reached, and a coast-in flight phases; and may provide a heading and next-waypoint timing for rhumb-line routes from GPS failure locations to the next waypoint of the active route. The tool links as a primary / secondary pair with another like tool.

The invention provides an unmanned vehicle layered road network path planning method and system based on air-ground cooperation, and belongs to the technical field of unmanned equipment path planning. The method comprises the following steps: S1, carrying out preliminary global planning on a road network according to a satellite map so as to extract an ordered global road point set with an interval of n1; s2, the high-altitude unmanned aerial vehicle goes to all global road points in sequence to obtain a finer local map, two layers of road networks are aligned and fused, part of road network information is supplemented, and the road points are calculated and updated; s3, taking the working range of a sensor carried by the unmanned vehicle as a planning step length, considering dynamic constraint and local dynamic and static obstacle avoidance, performing local planning on the unmanned vehicle to obtain an unmanned vehicle road point, and smoothing to obtain a final expected track of the unmanned vehicle; and S4, moving according to the position of the unmanned vehicle, and continuously iterating the steps S2 and S3 until the unmanned vehicle reaches the target point. The method improves the planning success rate.

The invention discloses an unmanned aerial vehicle building inspection route adjustment method and system based on wind field constraint and a storage medium, and the method comprises the steps: carrying out the simulation calculation of a three-dimensional wind field distribution result of an outer contour model according to the outer contour model of a to-be-detected building and the meteorological data of the geographic position of the to-be-detected building; determining external wind field wind speed data of the to-be-detected building so as to obtain coordinate points of which the wind speed is greater than the maximum wind resistance speed of the unmanned aerial vehicle in the external wind speed data; determining a limited flight area with the wind speed greater than the maximum wind-resistant speed of the unmanned aerial vehicle in the three-dimensional wind field distribution result according to the coordinate points; obtaining a target waypoint falling in the limited flight area in an initial inspection route generated by the unmanned aerial vehicle for the outer contour model; and adjusting and updating the target waypoint according to the limited flight area to obtain a target inspection route. A limited flight area is generated through wind field simulation and wind resistance threshold constraint, and the waypoint position of the limited flight area is adjusted, so that the cruising stability and safety are improved.

The invention provides a vehicle deviation path detection method and device, relates to the technical field of vehicle path planning, is applied to a cloud server, and comprises the following steps: determining a target planning path pre-configured for a target vehicle, the target planning path comprising a plurality of path points; in the running process of the target vehicle, the current position of the target vehicle is obtained; in the plurality of waypoints, determining the waypoint closest to the current position of the target vehicle as a current target waypoint, the target waypoint being the waypoint closest to the position of the target vehicle; and under the condition that the distance between the current target path point and the current position of the target vehicle exceeds the maximum deviation distance, determining that the target vehicle deviates from the target planned path. According to the method, the sensitivity of static path comparison to positioning fluctuation is overcome, even if transient position jump of the vehicle occurs due to signal interference, stability judgment can still be performed by taking the dynamically anchored nearest path point as a reference, and the false alarm rate is reduced.

The invention discloses an unmanned aerial vehicle line-imitating flight waypoint searching method, an unmanned aerial vehicle line-imitating flight route planning method and an unmanned aerial vehicle line-imitating flight route planning system, and the method comprises the steps: firstly, obtaining a center line discrete point sequence of an inspection road, and setting a waypoint spacing of a line-imitating flight route; and then determining a direction vector of the broken line segment to be searched according to the center line discrete point sequence. And then, according to the current waypoint coordinate, the direction vector and the waypoint spacing, determining the coordinate of a candidate waypoint, and verifying whether the candidate waypoint is on the broken line segment to be searched or not. If yes, the candidate waypoints are included in the waypoint set, and the candidate waypoints serve as the current waypoint to continue to search for the next waypoint. And if not, calculating the remaining distance which needs to be moved subsequently after moving to the terminal point of the broken line segment to be searched, and searching out the target line segment. And finally, searching the waypoints meeting the waypoint spacing by combining the direction vector and the starting point coordinate of the target line segment and the residual distance. Therefore, the line-imitating routing inspection waypoints are automatically generated, and the line-imitating flight routing inspection route planning efficiency of the unmanned aerial vehicle on the long linear road is improved.

Systems and methods for implementing mobility foundation models in accordance with some embodiments of the invention are illustrated. One embodiment includes a method for operating a mobile device. The method receives initial state tokens, wherein each corresponds to data reflecting a previous state of a mobile device. The method determines a sub-task for the mobile device by applying an LLM to the initial state tokens. The method encodes sensor data into patch tokens. Each of the patch tokens reflects a recent state of the mobile device. The method updates the initial state tokens into updated state tokens, based on the patch tokens and the sub-task. The method produces navigation waypoints from the updated state tokens, wherein each of the navigation waypoints represents a distinct destination for the mobile device. The method controlling the mobile device according to the navigation waypoints.

A method is provided. An implementation solution includes: obtaining first information and a plurality of waypoint sequences of a target vehicle; performing, for each waypoint sequence of the plurality of waypoint sequences, trajectory prediction based on the first information under the guidance of the waypoint sequence to obtain a predicted trajectory corresponding to the waypoint sequence and a score for the predicted trajectory; and determining, based on respective scores for a plurality of predicted trajectories corresponding to the plurality of waypoint sequences, a target predicted trajectory among the plurality of predicted trajectories.

The invention discloses a method for filtering an abnormal planned path of an unmanned sweeper, and the method comprises the steps: carrying out the region division of a surrounding space of a vehicle, and obtaining a group of regions; acquiring and counting obstacle information in each area and evaluating the obstacle information to obtain a high-risk obstacle area; based on a vehicle planning path, taking the current vehicle position and the target point as key waypoints, selecting another two key waypoints between the current vehicle position and the target point through a waypoint sampling method, and calculating a circle center fitting point of the four key waypoints; whether the position of the fitting circle center is located in the effective area behind the rear axle of the vehicle or not is judged, and if yes, the current planning is invalid; starting a re-planning process for the invalid current plan; and recalculating the path according to the new waypoint information, and updating the motion plan of the vehicle. According to the invention, a trajectory evaluation mechanism is introduced to carry out secondary auditing on the path so as to ensure the driving safety of the unmanned grassland vehicle.

The invention discloses a real-time visual language navigation method based on frontier exploration and neural relationship inference. The method comprises the following steps: constructing an initial occupation grid map and a confidence value map; based on the occupied grid map, identifying a boundary between the explored area and the unexplored area, and generating a candidate leading edge waypoint set; a vision-language model is used for detecting instance objects existing in the current visual field, and points closest to the robot are extracted to serve as a candidate instance route point set; calculating visual language comprehensive scores of all waypoints in the candidate frontier waypoint set and the candidate instance waypoint set, and selecting the waypoint with the highest score as a next navigation target; and based on the selected target waypoint, calling a local path planner to generate a collision-free path, driving the robot to move, and updating the occupied grid map and the confidence value map in a rolling manner. Task specific training is not needed, vision and language semantic information can be efficiently fused, and intelligent exploration and target navigation in an unknown environment are achieved.

The invention discloses a method for generating a route of an autonomous inspection channel of an unmanned aerial vehicle, and the method is characterized in that the method comprises the steps: S1, channel selection and vectorization; s2, elevation processing mode decision making: calculating an elevation standard deviation in a frame selection area according to the imported DEM elevation data; dynamically adjusting the terrain clearance of the unmanned aerial vehicle according to the calculated elevation standard deviation; s3, automatic route planning comprises the steps of generating an initial waypoint, self-adaptive waypoint density and multi-angle coverage in a channel vector range; and S4, generating and verifying an air route file, wherein the air route file comprises standardized packaging and three-dimensional visual verification. An unmanned aerial vehicle inspection channel route is quickly generated through a two-dimensional plane map, and efficient and safe autonomous flight is realized by combining intelligent elevation processing and route optimization.