76 results about "3d positioning" patented technology

The invention discloses a global scanning image splicing and defect positioning system for an ultra-large-diameter quartz crucible, and relates to the technical field of quartz crucibles, and the system comprises a scanning control module which constructs a fusion model through multiple sensors, evaluates a risk coefficient, obtains the fusion model, dynamically plans a multi-arm path of a robot based on reinforcement learning, and sends the multi-arm path of the robot; adaptively adjusting the acquisition frequency of the corresponding area based on the risk coefficient, and outputting multi-modal data through a multi-round feedback iteration optimization acquisition process; the image splicing module is used for acquiring multi-modal data for local splicing, and generating a panoramic image in combination with a multi-arm path of the robot; the defect positioning module is used for constructing a quartz crucible model through the panoramic image, detecting defects in a layered manner by utilizing a YOLOv5 model, tracking the defects through extended state Kalman filtering, quantifying the defect volume and the hazard level by combining point cloud semantic segmentation, and performing 3D positioning and evaluation on the defects; the output data is ensured to always meet the subsequent image splicing and defect positioning requirements, and the system stability is guaranteed.

The invention provides a precise workpiece positioning method and system based on three-dimensional vision, and the method comprises the steps: obtaining a scene three-dimensional vision data set containing a target workpiece, carrying out the multi-modal data fusion processing of the scene three-dimensional vision data set, generating a fusion data set with aligned space coordinates, extracting a workpiece feature identifier set from the fusion data set, and carrying out the recognition of the workpiece feature identifier set. And feature matching association processing is carried out on the workpiece feature identifier set and a pre-stored standard workpiece feature template, a feature matching corresponding relation set is generated, three-dimensional positioning coordinate information of the target workpiece in the scene is calculated based on the feature matching corresponding relation set, and the three-dimensional positioning coordinate information comprises workpiece centroid coordinates and space attitude angle parameters. The precision of precision workpiece machining is improved, and the stability of the positioning process is ensured.

The invention discloses a raspberry fruit identification and positioning method based on RGB-D image and depth information fusion. The method comprises the following steps: synchronously acquiring an RGB image and a depth image of a raspberry fruit through an RGB-D camera; constructing an RGB-D data set containing a fruit mask and a fruit stem connection point mark; establishing a depth fusion model based on YOLO11, wherein the model comprises a depth feature encoder, a CGAFusionPro fusion module and a 3D positioning head; the training model realizes multi-task learning; inputting an RGB-D image to obtain a 2D detection frame, a fruit surface 3D coordinate, a fruit stem offset and depth information confidence; and performing surface normal vector correction and curvature compensation through a depth perception optimizer to generate accurate 3D coordinates of the stem connection points. The invention provides a raspberry fruit identification and positioning method based on RGB-D image and depth information fusion aiming at the problem of low raspberry fruit identification and positioning accuracy under different scales, through depth information fusion and physical perception optimization, the problems of registration dislocation and positioning deviation in a traditional method are solved, and the accuracy of raspberry fruit identification and positioning is improved. And the raspberry fruit identification and positioning accuracy is effectively improved.

A system (SYS) and related method for facilitating medical imaging of a patient by a medical imaging apparatus (IA). The system comprises an input interface (IN) for receiving measurements collected by shape sensing sensors (Sj) of an optical shape sensing device (SSD). The shape sensing sensors (Sj) are arrangeable relative to the patient's body, wherein the measurements are representative of a current posture of the patient's body. A posture determiner (PD) of the system (SYS) computes, based on the measurements, output data representative of whether the patient's body is in a predefined target posture.

The application discloses a kind of automobile paint surface defect detection and polishing method and system, the method includes: offline processing: detection station offline collection point planning is carried out, and the trajectory of multiple detection mechanical arms is planned;Detection station offline collection point calibration is carried out, and the paint surface imaging acquisition component and the 3D positioning camera external parameter of detection station are offline calibrated;Polishing station polishing mechanical arm and polishing station 3D positioning camera hand-eye calibration are carried out;Online processing: paint surface defect detection is carried out, and defect attribute and defect position positioning are obtained;Defect three-dimensional coordinates and normal are transmitted to automatic polishing component by visual positioning mode, and the paint surface defect is polished by automatic polishing component.Processing is carried out.The system is used to execute the above method.The application has the advantages of simple structure, wide application range, high degree of intelligence, high detection and polishing efficiency, etc.

The invention discloses a multi-scene high-precision positioning method based on near ultrasound, and relates to the technical field of positioning, and the method comprises the steps: obtaining deployment parameters and environment reference parameters, and constructing a standardized reference database; deploying a near ultrasonic base station and a positioning terminal, and cooperatively collecting a near ultrasonic signal and a Beidou signal; performing targeted cleaning and standardization processing on the near ultrasonic signal and the Beidou signal; extracting features of the cleaned near ultrasonic signal and the Beidou signal, and performing fusion positioning calculation to obtain a positioning result; a positioning result is corrected through a self-calibration algorithm and an AI deep optimization model, and multi-dimensional positioning feedback is realized; and outputting a multi-dimensional positioning result. In actual use, an AI-driven scene algorithm is adopted for positioning optimization, indoor and outdoor centimeter-level seamless positioning is achieved, the method is adaptive to complex scenes such as strong electromagnetism, strong noise and multi-reflection, the deployment cost is remarkably reduced, and 1D, 2D and 3D positioning results are accurately output according to service requirements.

An illustrative multi-view 3D positioning system assigns a respective 3D position estimate, with respect to a 3D space, to each of a plurality of detected instance datasets corresponding to objects present within the 3D space. Based on the 3D position estimates, the multi-view 3D positioning system sorts the plurality of detected instance datasets into a plurality of groupings corresponding to the objects so that each detected instance dataset is grouped together with other detected instance datasets corresponding to a same object. The multi-view 3D positioning system then determines a respective 3D position resolution, with respect to the 3D space, for each of the plurality of objects. These 3D position resolutions are determined based on the plurality of groupings of detected instance datasets and represent, with greater accuracy than the 3D position estimates, 3D positions of the objects within the 3D space. Corresponding methods and systems are also disclosed.

This invention relates to the field of orchard navigation technology, specifically a 3D method for orchard operations based on a grid map. The method includes: constructing an orchard point cloud map using a mapping algorithm; filtering the acquired 3D point cloud map and constructing a triangular grid map of the orchard, embedding the orchard's GPS information into the triangular grid map; based on the triangular grid map with GPS information, performing ICP registration between the point cloud data scanned by the LiDAR and the points on the triangular grid map using the RMCL 3D positioning algorithm, outputting the 3D pose of the operation robot in the orchard; updating the 3D pose of the operation robot in the orchard using GNSS information; planning the navigation path of the operation robot using grid navigation based on the GPS information of the target point; and controlling the operation robot to dynamically avoid obstacles and navigate to the target point. This invention enables precise positioning and autonomous navigation of the operation robot in hilly orchards, allowing it to complete tasks such as orchard inspection, plant protection, harvesting, and transportation.

The present application provides a kind of complex stratum structure and topographic effect considering slope microseismic event 3D positioning method, the technical scheme includes S1: the theoretical travel time model suitable for complex slope environment is built;S2: the actual travel time difference is extracted from slope monitoring data;S3: based on the 3D positioning of theoretical and observed travel time difference matching, the ambient noise surface wave tomography technology is applied to slope velocity modeling, without artificial seismic source, high resolution velocity structure can be obtained;Realize 3D ray tracing under the constraint of digital elevation model, ensure that wave propagation path meets physical law, positioning accuracy reaches 3 m, can reach 1.5 m in dense array coverage area, compared with traditional method, it is improved by one order of magnitude;Successfully applied to complex environment with more than 700m topographic relief and extreme velocity variation, can be applied to microseismic monitoring in various complex geological environments.

The invention provides an intelligent nuclear power embedded part detection and acceptance method based on a binocular camera, belongs to the technical field of detection and acceptance, is an intelligent detection algorithm based on binocular vision and a deformable attention mechanism, and aims to break through the technical bottleneck of three-dimensional positioning and multi-scale feature fusion of embedded parts in a complex scene. A three-dimensional pyramid network with reserved features is designed, multi-scale features are fused in a layered mode, binocular geometric consistency is kept, and the problem of information loss in cross-resolution feature fusion is effectively solved; parallax perception position coding is innovatively introduced, binocular parallax information and two-dimensional position coding are deeply fused, and the three-dimensional space perception capability is enhanced; a non-parametric anchor-based target query mechanism is provided, query embedding covered by dense space is generated by multiplexing low-resolution three-dimensional features, the model convergence efficiency and the detection precision are improved, the detection cost is reduced, the detection efficiency is improved, and the detection safety is guaranteed.

To accurately generate a drawing of a structural member including a plurality of bolt holes corresponding to a plurality of bolts installed on a foundation.SOLUTION: An information processing system 100 including at least one information processing apparatus 3 and 103 is configured to acquire point cloud data generated by measuring a plurality of bolts 10 installed on a foundation 11, to acquire three-dimensional models for positioning relating to outer shapes of the bolts, to determine positions of the three-dimensional models for positioning by performing fitting processing of the three-dimensional models for positioning to the point cloud data of the bolts, and to generate drawing data of the structural member in which the plurality of bolt holes are formed on the basis of the positions of the three-dimensional models for positioning.SELECTED DRAWING: Figure 1

The invention belongs to the technical field of mining machinery, and discloses a spiral roller end disc plane intelligent cutting system and method.The spiral roller end disc plane intelligent cutting system comprises a three-axis rotating positioner, a material fixing table is installed on the three-axis rotating positioner, and a material fixing table square hole is formed in the material fixing table; a lifting hole is formed in the side wall of the semi-finished roller product, a connecting disc square hole is formed in one end of the semi-finished roller product, an end disc is arranged at the other end of the semi-finished roller product, and the connecting disc square hole is matched with the material fixing table square hole; the flame cutting assembly is used for cutting the semi-finished roller product; and the 3D position finding device comprises a 3D camera, a laser position finding device and a control platform, and the three-axis rotating positioner, the 3D camera, the laser position finding device and the flame cutting assembly are all connected with the control platform. According to the technical scheme, the labor intensity is reduced, the cutting time is shortened, and the cutting efficiency and the cutting precision are improved.

The invention discloses a control method and device for cleaning equipment, and the method comprises the steps: controlling the cleaning equipment to clean a pool wall according to a preset path which at least comprises a plurality of preset cleaning cycle paths; acquiring obstacle information in the preset path; and adjusting a cleaning cycle path where the obstacle is located based on the obstacle information so as to avoid the obstacle. While the cleaning equipment is controlled to clean the pool wall according to the preset path, the obstacle information in the path is obtained in real time in the running process, so that the cleaning cycle path where the obstacle is located can be adjusted in advance based on the obstacle information, the cleaning equipment can avoid the obstacle when running to the cleaning cycle, and the cleaning efficiency is improved. Obstacle avoidance does not need to be carried out through 3D positioning information, obstacle sensing and obstacle avoidance are achieved through machine motion planning and obstacle information, and the method can be suitable for sensing and processing obstacles on most swimming pool walls.

The present invention belongs to the field of artificial intelligence monitoring technology and relates to a method and system for three-dimensional tracking of multiple pedestrians based on monocular vision. The method comprises the following steps: S1: extracting features from a training image set obtained by a monocular camera; S2: simultaneously detecting pedestrians and learning their ID embeddings based on the extracted features; S3: 3D positioning of pedestrians based on the pedestrian detection results; S4: re-identifying pedestrians based on the results of the ID embedding learning; and S5: determining the motion trajectory of each pedestrian based on the re-identification results and the pedestrian's 3D position, thereby tracking them in three dimensions. The method can accurately detect and associate identical pedestrians, accurately predict their 3D positions, and plot their 3D activity trajectories. It can also achieve real-time operational efficiency, improving the operational efficiency of the entire model while ensuring competitive tracking accuracy.

This application discloses a multimodal data collaborative intelligent detection and 3D localization method for maritime vessels, comprising: fine preprocessing of collected multi-source heterogeneous data and preliminary target detection; dynamic weighted fusion of the preprocessed multi-source heterogeneous data, combined with depth data from lidar, to achieve accurate coordinate recovery of the vessel target in 3D space; and prediction and updating of the motion state of the identified target based on a multi-tracking mechanism collaborative strategy. By fully utilizing the rich texture information of visible light images, the anti-interference capability of thermal imaging, and the precise spatial depth data of lidar through multimodal data perception and preliminary processing, heterogeneous data deep fusion and 3D localization, and advanced multi-target continuous tracking and state estimation, this method integrates a multi-tracking mechanism collaborative strategy to predict and update the motion state of the identified target, effectively addressing the problem of tracking interruption caused by nonlinear motion or temporary occlusion of maritime targets.

This invention provides a 3D laser SLAM fusion magnetic stripe inspection robot navigation and positioning method, belonging to the field of navigation and positioning technology. The method includes: initializing the robot by acquiring an initial pose and presetting a rectangular boundary for a dynamically changing region; determining in real time whether the current pose is within the dynamically changing region; if the current pose is outside the dynamically changing region, registering the current frame of laser data with a pre-constructed point cloud map to obtain a first positioning pose; if the current pose is within the dynamically changing region, performing laser fusion magnetic stripe positioning: acquiring the initial 3D positioning pose and initial magnetic stripe data; determining the initial vertical deviation distance; acquiring the real-time 3D positioning pose and real-time magnetic stripe data; determining the real-time vertical deviation distance; and correcting the pose output by the laser odometry through forced constraints to determine the final fused pose. According to this invention, interference in dynamically changing regions can be better addressed, achieving stable and reliable navigation and positioning.

This invention provides a method, system, and medium for three-dimensional positioning and displacement measurement that integrates microwave and vision technologies. The method includes: rigidly connecting at least one microwave sensor and at least one vision sensor as a joint sensing unit; establishing a spatial transformation relationship between the coordinate systems of the two sensors through calibration; fusing the target's radial distance and angle information provided by the microwave sensor with the target's two-dimensional imaging information provided by the vision sensor; and directly solving for the target's three-dimensional coordinates in the selected coordinate system using an optimization algorithm; further combining the high-precision one-dimensional displacement information from the microwave sensor with the two-dimensional displacement information from the vision sensor to reconstruct the target's complete displacement vector in three-dimensional space. This invention, through a compact heterogeneous sensor fusion architecture, effectively solves the problems of limited dimensionality of single-sensor modes, high cost of multi-sensor networking, system complexity, and poor engineering applicability, achieving high-precision, low-cost, and full-dimensional non-contact three-dimensional positioning and displacement measurement.

This invention discloses a multi-algorithm collaborative 3D positioning method based on UWB and IMU. The method includes: constructing a 3D Cartesian coordinate system based on multiple UWB base stations; measuring the distance between the tag and the UWB base stations through bilateral bidirectional ranging to obtain the corresponding distance variables; establishing a nonlinear equation system using a trilateration algorithm, substituting the distance variables to transform it into a linear error equation system, and obtaining a set of 3D coordinates of the tag using Newton's iteration method; obtaining a nonlinear equation system using the time difference of arrival, obtaining a linear error equation system based on Taylor expansion approximation, and obtaining another set of 3D coordinates of the tag using the least squares method; weighted averaging the two sets of 3D coordinates to obtain the initial 3D coordinates; constructing a state transition model based on the initial 3D coordinates, velocity components, and acceleration components; predicting the state at the next moment using Kalman filtering and updating the tag's 3D coordinates; and outputting the final 3D spatial positioning result. This invention can achieve high-precision 3D positioning.

This invention discloses a natural language interactive navigation, obstacle avoidance, and grasping method for a robotic dog based on a nine-grid large model. The method includes the following steps: Step S1: Parsing user commands to extract key information and publishing standardized ROS2 topics; Step S2: Processing radar point clouds and fusing multi-sensor data to establish a coordinate transformation chain; Step S3: Navigating and avoiding obstacles to the target location based on the SLAM and Nav2 framework; Step S4: Completing target recognition and precise 3D positioning using a wrist camera and YOLOv8; Step S5: Generating a grasping action sequence and achieving closed-loop control of the robotic arm through smooth trajectory planning. This invention integrates nine-grid large model semantic parsing and a hierarchical modular architecture with multiple core technologies to achieve natural language interactive driving for the robotic dog, as well as the coordinated completion of navigation, obstacle avoidance, and object grasping, significantly reducing the operational threshold and improving grasping accuracy and motion safety.

The invention relates to the technical field of glass curtain wall installation, and discloses a glass curtain wall intelligent installation collaborative operation system. The system comprises a data fusion unit, a control instruction generation unit, an error compensation unit and an augmented reality display unit. The data fusion unit performs fusion processing on the building information model data and the three-dimensional point cloud scanning data to generate a high-precision three-dimensional positioning map of the curtain wall unit; a control instruction generation unit generates a multi-robot collaborative operation control instruction through a dynamic path planning algorithm on the basis of the map; the error compensation unit adopts a self-adaptive error compensation algorithm to dynamically correct the positioning map according to real-time building structure deformation monitoring data; and the augmented reality display unit presents the corrected positioning map through special equipment to assist in carrying out field installation operation. The system can adapt to complex building scenes, assist standard installation links and reduce operation deviation.

A medical image processing device according to an embodiment comprises: a first image acquisition unit that acquires a first image captured in a first stage; a second image acquisition unit that acquires a second image captured in a second stage; a 3D-3D positioning execution unit that aligns the position of the second image with the position of the first image; a region information acquisition unit that acquires region information corresponding to a region of the first image; a region estimation unit that estimates a region corresponding to the region information in the second image; a tracking model acquisition unit that acquires a tracking model; a tracking unit that tracks an object in the second image using the tracking model; and an error calculation unit that calculates an error between a tracking position, which is the position of the object in the second image tracked by the tracking unit, and the position of the object in the second image.

The invention belongs to the field of intelligent robots, and discloses an automatic configuration method for an outdoor inspection robot, which comprises the following steps of: acquiring point cloud data and an environment texture image, judging an environment grade after preprocessing, constructing a three-dimensional electronic map and establishing a dynamic coordination rule; a robot walks along a planned route to trigger a dynamic coordination rule, after double cameras shoot inspection equipment, a suspected inspection target is primarily screened and framed, a type is labeled, a primary screening result table is generated, a corrected labeled target set is generated through manual recheck and correction, an environment weighting factor is introduced, shooting angle deviation is compensated, and a full-amount unified labeled photo set is generated; constructing an inspection recognition model, outputting frame selection coordinates, target categories and target confidence coefficients, and judging target frame selection consistency; constructing a three-dimensional constraint condition, removing the same target picture, marking an effective inspection target, and calculating and adjusting the attitude compensation amount of 3D positioning; a correlation mapping table is generated based on large auxiliary target positioning and small target candidate area amplification identification, and the inspection target identification precision and configuration efficiency are improved.

The invention relates to the technical field of building detection, and provides a house indoor defect intelligent detection and graphic file output method and system. The method comprises the following steps: acquiring millimeter-level three-dimensional point cloud data through handheld SLAM laser scanning, generating an orthoimage after preprocessing, carrying out defect identification and classification by adopting an unsupervised-weak supervised neural network in which a MobileNetV3-SOM and a stacked auto-encoder are connected in series, calculating three-dimensional coordinates and quantization parameters of a defect center through pixel-point cloud back projection, and carrying out defect identification and classification on the defect center. And finally generating a CAD vector file containing defect types, three-dimensional coordinates and quantization parameters. According to the method, only normal wall surface sample training is needed, the problem of insufficient model generalization caused by defect sample scarcity is solved, meanwhile, accurate three-dimensional positioning and complete parameter description of defects are achieved, the output standardized CAD file can be directly used for repairing design, the detection efficiency is improved, and the application range is widened.

Eyewear configured to identify movements of a remote physical object to provide a 3D painting interactive augmented reality experience. In an example, the eyewear uses the identified movements of the remote physical object as a virtual brush to create a three-dimensional (3D) virtual object on an eyewear display. The eyewear determines positional information of the remote physical object. The eyewear uses the positional information and responsively displays and edits the virtual object as a function of the relative 3D positioning of the remote physical object.

This invention discloses an integrated method for low-altitude UAV radio frequency positioning and intelligent trajectory control, relating to the cross-technical field of low-altitude UAV radio frequency positioning and trajectory control. The specific steps of this method are as follows: performing radio frequency synchronous calibration, with multiple ground base stations and an airborne radio frequency unit interacting to adjust parameters and output calibration datasets; positioning calculation and evaluation, outputting positioning results, evaluation data, and feedback interference characteristics; conducting trajectory feedforward control, generating and adjusting commands; optimizing flight control feedback, generating predicted values ​​to adjust algorithm parameters; and closed-loop iterative optimization, integrating parameters to adapt to low-altitude flight scenarios. This invention achieves dynamic adaptation of radio frequency signal parameters and acquisition strategies through collaborative calibration between multiple ground base stations and an airborne radio frequency unit, improving the accuracy and stability of UAV 3D positioning. Through integrated design of positioning calculation and trajectory control, a closed-loop iterative process is achieved, reducing system latency and errors, enhancing scenario adaptability, and ensuring operational safety and management efficiency.

The invention provides an indoor three-dimensional visual positioning system and method based on double cameras, and belongs to the technical field of indoor positioning, and the system comprises an image obtaining module which comprises two cameras and is used for obtaining a first image and a second image respectively; a target detection model is preset in the model detection module, and the model detection module is used for performing human body detection and human face detection and acquiring a first detection result for the first image and a second detection result for the second image; and the target position determination module is used for fusing the first image and the second image and sequentially performing binocular correction, parallax calculation and re-projection when the detection result contains the detection target so as to determine the three-dimensional coordinate of the detection target. The method has the beneficial effects that the monocular limitation is broken through based on double cameras, the method can adapt to complex scenes, and the target recognition performance of the model for small targets and long-distance targets is improved; meanwhile, the double cameras can be flexibly installed, parameters suitable for follow-up parallax calculation can be calculated through binocular correction, and accurate three-dimensional positioning is achieved.

The application provides a finger joint labeling method and device and electronic equipment, and relates to the technical field of computer vision. The method comprises the following steps: collecting a multi-view image set under the same time frame; the multi-view image set is synchronously captured by multiple cameras in a common view area; key point detection is performed on the multi-view image set to obtain the potential pixel position of each finger joint, and a potential box centered on the potential pixel position is generated; the corner points of each potential box are extracted, and the 3D position of each finger joint is determined according to the response degree of the corner points; the corner points are image feature points related to the finger joint; and each finger joint is labeled according to the 3D positions. The application breaks through the single-view limitation through multi-view fusion, improves the spatial positioning reliability, and improves the feature reliability and 3D positioning accuracy through the potential box and the response degree screening, so as to improve the accuracy of 3D finger joint labeling.

The invention relates to a multi-view combined tracking method for a complex target in an industrial production scene, and the method comprises the following steps: S1, carrying out the calibration of internal parameters and external parameters of all cameras, constructing a physical space 3D model of a target production region, and forming a factory coordinate system; s2, collecting a multi-view image frame through the calibrated camera, and carrying out the preprocessing of the multi-view image frame; s3, detecting the position of each frame of target by using a deep learning detection model Detectron2, performing monocular inter-frame association on the detected target to obtain a local trajectory, and extracting a depth feature vector for each target; s4, when the same target appears at a plurality of visual angles, fusing the space coordinates to obtain accurate 3D positioning, and obtaining a physical 3D space coordinate candidate set of each actual target; and S5, according to the physical 3D space coordinate candidate set, constructing a matching candidate set, and adopting a joint matching algorithm to realize trajectory merging to obtain a complete 3D trajectory. According to the invention, multi-target efficient and multi-view collaborative accurate tracking in a complex industrial scene is realized.

This invention provides a method and apparatus for visual detection and harvesting control of guava maturity, relating to the field of visual detection technology. It acquires multi-view time-series images from a drone and extracts individual guava image blocks and depth information to determine spatial location. A feature encoder extracts feature vectors and performs clustering to determine maturity levels. Then, an optimization problem is constructed to plan the harvesting path, aiming to maximize harvesting revenue per unit time. Finally, the drone and robotic arm are controlled for flexible harvesting. This method can achieve automatic identification of guava maturity, 3D positioning, revenue-driven target selection and path planning, and precise flexible harvesting even in the absence of numerous manual maturity labels. It forms an integrated autonomous harvesting system with a closed loop of perception, understanding, decision-making, and execution, effectively solving problems such as difficult feature extraction, high manual labeling costs, low planning efficiency, and fruit damage in greenhouse guava harvesting.

A smart Autonomous Vertical Farming System in an indoor farm comprising a Computer server, a Planning and Control system, a Library containing images and reference data, a plarlity of wireless routers for data transmission to and from all parts of the indoor farm. with routes for movement inside and through the Vertical Farming System. The indoor farm is provided with a plurality of racks with a plurality of racks with a plurality of trays of plants placed on the racks, wherein new data are gathered by a plurality of Autonomous Mobile Robots (AMR), said data including images of the plants, health condition and growth status of the plants obtained from the AMRs. The data transmitted through the wireless routers to the Computer Server, wherein the Computer Server schedules daily operations for the AMRS and maintenance works to be carried out by the AMRs autonomously transitted to each AMR. The 3D positioning tags, wireless beacons and designated landmarks in the indoor farm form a Route Guidance System, for movements of the AMRs for the daily operations and maintenance within the vertical farming system and the movements are planned and executed using the Route Guidance System.