Automatic three-dimensional laser scanning method and system based on robot

Abstract

The invention discloses an automatic three-dimensional laser scanning method and system based on a robot, and relates to the technical field of robot automation, and the robot comprises a mobile system, a sensor system, a mechanical arm and operation system, a visual system, a control system and a communication system. The robot performs system self-inspection and initializes each system, and receives a scanning task from the server; a sensor is used for sensing the environment, a map is constructed, an optimal scanning path is planned, a scanning task is carried out according to the planned path, control points are recognized through a visual system, and scanning dotting is executed. According to the method, the main clock signal is used in the main control system to trigger the activation process of all the subsystems, synchronous starting of all the subsystems is ensured, accurate environment data can still be obtained in a complex environment through combination of the laser radar, the ultrasonic sensor and the infrared sensor, and the accuracy of the environment data is improved. An environment map is dynamically constructed and updated by dividing a three-dimensional space and cooperating with an SLAM algorithm.

Description

Technical Field

[0001] The present invention relates to the field of robot automation technology, and in particular to an automated three-dimensional laser scanning method and system based on a robot. Background Art

[0002] With the continuous development of 3D scanning technology, the reality capture industry has higher and higher requirements for the efficiency and accuracy of data collection. As a high-precision and high-efficiency 3D laser scanner, wearable 3D laser scanners have been widely used in digital modeling and measurement of indoor and outdoor environments.

[0003] Although there are already some solutions for automated scanning and robot-assisted scanning, they usually have the following limitations: Limited degree of automation: Many existing systems still have limited degree of automation and require manual intervention or monitoring; Insufficient environmental adaptability: Some systems perform poorly in complex environments and cannot cope with changing environmental conditions; Data collection efficiency and accuracy need to be improved: Despite automation, some systems still have room for improvement in data collection efficiency and accuracy. Therefore, automation and intelligence have become important development trends in this field. Summary of the invention

[0004] In view of the problems existing in the above-mentioned existing robot-based automated three-dimensional laser scanning method and system, the present invention is proposed.

[0005] Therefore, the problem to be solved by the present invention is that although there are already some solutions for automated scanning and robot-assisted scanning, they usually have the following limitations: limited degree of automation: the degree of automation of many existing systems is still limited and requires manual intervention or monitoring; insufficient environmental adaptability: some systems perform poorly in complex environments and cannot cope with changing environmental conditions; data collection efficiency and accuracy need to be improved: although automation has been achieved, some systems still have room for improvement in data collection efficiency and accuracy. Therefore, automation and intelligence have become important development trends in this field.

[0006] To solve the above technical problems, the present invention provides the following technical solutions: a robot-based automated three-dimensional laser scanning method, comprising:

[0007] The robot performs system self-check and initializes each system, and receives scanning tasks from the server;

[0008] Use sensors to perceive the environment, build maps, and plan the optimal scanning path. Perform scanning tasks according to the planned path, identify control points through the visual system, and perform scanning and marking.

[0009] The data is transmitted to the server in real time, and data comparison and data backup are performed after the task is completed. A report template is generated and the task report is embedded based on the stored data.

[0010] As a preferred solution of the robot-based automated three-dimensional laser scanning method of the present invention, wherein: the robot includes a mobile system, a sensor system, a mechanical arm and an operating system, a visual system, a control system and a communication system;

[0011] The mobile system adopts high-precision motors and encoders;

[0012] The sensor system integrates laser radar, ultrasonic and infrared sensors;

[0013] The robotic arm and operating system are equipped with a multi-joint robotic arm;

[0014] The visual system uses a high-resolution camera to assist in positioning, and uses a computer vision algorithm to determine the location of the control point and the corresponding number. The operator observes the robot's environment in real time through a panoramic video.

[0015] The control system uses a high-performance computing unit for path planning, task scheduling and data processing;

[0016] The communication system exchanges data with the remote server, and the operator intervenes in the robot to control it through the communication system.

[0017] As a preferred solution of the robot-based automated three-dimensional laser scanning method of the present invention, the robot performs system self-check and initializes each system, and receives a scanning task from a server, including:

[0018] The master clock signal of the robot control system triggers and activates subsystems, including the mobile system, sensor system, manipulator system, vision system, control system and communication system;

[0019] The mobile system detects its stationary state through the built-in gyroscope and accelerometer. If any movement or tilt is detected, the system will send a warning signal and recalibrate the initial position;

[0020] The sensor system performs self-calibration, including measuring the distance or size of known reference objects in the environment and comparing it with a preset standard, and issuing a fault warning if an error occurs;

[0021] The robot arm system self-checks and performs angle tests on the joints. The sensors of the joints return the current angle position and torque, and calculate the expected torque and angle according to the motion model preset by the control system. If an error occurs, a fault warning is issued;

[0022] The visual system captures the surrounding environment image and determines the image contrast, color saturation, and edge detection data. If the image cannot be captured clearly, a fault warning is issued;

[0023] The control system performs self-checks on the internal processor, memory and I / O interface. If an abnormality is detected, the control system will automatically restart or switch to the backup system;

[0024] The communication system detects the quality of the connection with the external device, including signal strength, data transmission rate and error rate;

[0025] The self-test results of each subsystem will be transmitted to the main control system in real time. If all systems pass the self-test, the main control system will issue a system initialization command and put each subsystem into standby mode. At the same time, it will load the path planning algorithm and sensor data processing algorithm and receive the scanning task through the server.

[0026] As a preferred solution of the robot-based automated three-dimensional laser scanning method of the present invention, wherein: the use of sensors to perceive the environment, build a map, and plan the optimal scanning path includes:

[0027] Acquire environmental information through sensor systems, including lidar, ultrasonic sensors, and infrared sensors. Mark point data acquired by lidar with timestamps and spatial coordinates to form a point cloud map.

[0028] According to the ultrasonic sensor and infrared sensor, the distance information between the environment and the robot is measured, and the distance is calculated according to the received echo time;

[0029] The image data is collected by the camera of the visual system, and the data is synchronized based on the laser radar, ultrasonic sensor and infrared sensor, and a unified timestamp is added. The data is unified into a unified coordinate system through coordinate transformation, which is expressed as:

[0030] Pg=R·Ps+T;

[0031] Where Pg represents the point position in the global coordinate system, R represents the rotation matrix, which describes the rotation relationship between the sensor and the global coordinate system, T represents the translation vector, which describes the displacement relationship between the sensor and the global coordinate system, and Ps represents the point position in the sensor coordinate system;

[0032] The point cloud data generated by the lidar is combined with the distance data of the ultrasonic sensor and the infrared sensor. The accuracy of the point cloud is optimized through the data fusion algorithm of the Kalman filter. The fused point cloud data is processed into a three-dimensional grid, and the three-dimensional space is divided into a series of regular cube Voxels. Each Voxel stores the obstacle information in the area.

[0033] For each Voxel, the occupancy probability of the Voxel is calculated based on the detection results of the lidar, ultrasonic sensor and camera, and the probability of the Voxel being occupied is calculated using the Bayesian update formula, which is expressed as:

[0034]

[0035] Where P(OkZi:k) represents the probability that Voxel k is occupied when the observation value Zi:k is given, P(ZkOk) represents the probability that the sensor measures the Voxel when Voxel k is occupied, and P(OkZi:k- 1 ) represents the probability that Voxel k is occupied when the observation value Zi:k-1 is given, P(ZkZi:k- 1 ) represents the probability that the sensor measures the observation value Zk when the observation value Zi:k-1 is given;

[0036] The SLAM algorithm uses the robot's initial position as the origin to start building a map. The robot continuously updates its position and three-dimensional space data through the mobile system.

[0037] Based on the grid map of three-dimensional spatial data, the A-star algorithm is used for path planning.

[0038] As a preferred solution of the robot-based automated three-dimensional laser scanning method of the present invention, wherein: the scanning task is performed according to the planned path, the control points are identified by the visual system, and the scanning and marking are performed, including:

[0039] Based on path planning, the robot arm and the operating system move based on the current robot's mobile system based on the path planning. The path points in the path planning correspond to the target positions of the robot arm. The robot arm moves to the target positions in sequence through its motion control system.

[0040] The motion control system uses an inverse kinematics algorithm to calculate the angle of each joint, allowing the scanner at the end of the robotic arm to be accurately positioned at the predetermined spatial position;

[0041] After the robot reaches each scanning point, the 3D laser scanner emits a laser beam and receives the signal reflected from the surface of the scanned object. The scanner calculates the precise distance of the object surface by measuring the flight time TOF of the laser beam and generates 3D point cloud data.

[0042] The control points are identified by the visual system, and the robotic arm operates the wearable 3D laser scanner to mark the points.

[0043] As a preferred solution of the robot-based automated three-dimensional laser scanning method of the present invention, wherein: the real-time transmission data is stored in the server, and data comparison and data backup are performed after the task is completed, including:

[0044] The point cloud data is transmitted in real time to an external server through the robot’s internal communication system for storage and preliminary processing;

[0045] The communication system uses high-speed wireless networks for data transmission;

[0046] After receiving the point cloud data, the server pre-processes the data and records it in real time;

[0047] After the scanning task is completed, the 3D point cloud data of the scanning task is retransmitted and preprocessed;

[0048] At the same time, it is compared with the point cloud data transmitted in real time. If the data is consistent, it is stored in an external hard disk as backup data;

[0049] The server stores the collected data by timestamp and task number, and creates an index for the data. The index includes timestamp, task number, size of data block and storage location.

[0050] As a preferred solution of the robot-based automated three-dimensional laser scanning method of the present invention, wherein: the generated report template, embedded in the task report according to the stored data, includes:

[0051] Generate automated reports through the LaTeX document generation system and the Python script Jupyter Notebook;

[0052] Set up a standard LaTeX report template based on the LaTeX document generation system, including task overview, path record, data analysis, environmental complexity analysis and summary;

[0053] Extract the data received by the server and input it into the generated standard LaTeX report template, embedding it according to the placeholders in the template;

[0054] Compile the report template into the final PDF document through the LaTeX compiler.

[0055] Another object of the present invention is to provide a system for a robot-based automated three-dimensional laser scanning method, comprising:

[0056] System self-check module: the system performs self-check and initializes each subsystem to confirm the working status of all systems;

[0057] Task path planning module: The control system receives scanning tasks from the server, perceives the environment through the sensor system, builds a map, and plans the optimal scanning path;

[0058] Task execution module: the robot arm and operating system perform scanning tasks according to the planned path, the visual system identifies control points and performs precise point marking, and the point cloud data collected in real time is transmitted to the server through the communication system;

[0059] Data storage module: real-time transmitted data is stored on the server side. After the task is completed, the system will compare and back up the data to ensure data consistency and integrity;

[0060] The task report module controls the generation of report templates, embeds the stored data into the task report, and automatically generates a complete task execution report for operator review and analysis.

[0061] A computer device comprises: a memory and a processor; the memory stores a computer program, and the processor implements the steps of the above-mentioned robot-based automated three-dimensional laser scanning method when executing the computer program.

[0062] A computer-readable storage medium stores a computer program, which, when executed by a processor, implements the steps of the above-mentioned robot-based automated three-dimensional laser scanning method.

[0063] The beneficial effects of the present invention are as follows: by using the main clock signal in the main control system to trigger the activation process of all subsystems, it is ensured that each subsystem is started synchronously; by combining lidar, ultrasonic sensor and infrared sensor, it is ensured that accurate environmental data can still be obtained in complex environments; by dividing the three-dimensional space and cooperating with the SLAM algorithm, the environmental map is dynamically constructed and updated; the path points planned by the robot arm and the operating system are used as the target positions, and the function of collaborative movement is realized; at the same time, through the inverse kinematics algorithm, the robot arm can accurately calculate the angle of each joint, ensuring that the scanner at the end of the robot arm can be accurately positioned to the predetermined spatial position, realizing automatic dotting operations, and improving the automation level and overall quality of the task. BRIEF DESCRIPTION OF THE DRAWINGS

[0064] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the accompanying drawings required for use in the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other accompanying drawings can be obtained based on these accompanying drawings without paying creative work.

[0065] Figure 1 Schematic diagram of the process of robot-based automated 3D laser scanning method.

[0066] Figure 2 Schematic diagram of the structure of the robot-based automated 3D laser scanning system.

[0067] Figure 3 Schematic diagram of the overall structure of the robot-based automated 3D laser scanning system.

[0068] Figure 4 Schematic diagram of the mobile system structure of the robot-based automated 3D laser scanning system.

[0069] Figure 5 Schematic diagram of the visual system structure of the robot-based automated 3D laser scanning system.

[0070] Figure 6 Schematic diagram of the sensor system structure of the robot-based automated 3D laser scanning system.

[0071] Figure 7 Schematic diagram of the structure of the robotic arm and operating system of the robot-based automated 3D laser scanning system. DETAILED DESCRIPTION

[0072] In order to make the above-mentioned objects, features and advantages of the present invention more obvious and easy to understand, the specific embodiments of the present invention are described in detail below in conjunction with the accompanying drawings.

[0073] In the following description, many specific details are set forth to facilitate a full understanding of the present invention, but the present invention may also be implemented in other ways different from those described herein, and those skilled in the art may make similar generalizations without violating the connotation of the present invention. Therefore, the present invention is not limited to the specific embodiments disclosed below.

[0074] Secondly, the term "one embodiment" or "embodiment" as used herein refers to a specific feature, structure, or characteristic that may be included in at least one implementation of the present invention. The term "in one embodiment" that appears in different places in this specification does not necessarily refer to the same embodiment, nor is it a separate or selective embodiment that is mutually exclusive with other embodiments.

[0075] Example 1, reference Figure 1 , Figure 3 , Figure 4 , Figure 5 , Figure 6 and Figure 7 , which is the first embodiment of the present invention, and which provides a robot-based automated three-dimensional laser scanning method, the robot-based automated three-dimensional laser scanning method comprising:

[0076] S1, the robot includes a mobile system, a sensor system, a robotic arm and an operating system, a visual system, a control system, and a communication system;

[0077] Preferably, the robot includes a mobile system, a sensor system, a mechanical arm and an operating system, a visual system, a control system, and a communication system;

[0078] The mobile system uses high-precision motors and encoders, and also includes a load-bearing platform, mechanical legs, bending structures, and bottom support pads;

[0079] The mobile system can also be replaced by using a different type of mobile system such as a crawler type or a leg type to replace the mobile system in the original solution;

[0080] The sensor system integrates lidar, ultrasonic and infrared sensors to perceive the surrounding environment in real time, build environmental maps, and achieve obstacle avoidance.

[0081] The sensor system can further use depth cameras, RGB-D cameras or other types of sensors to enhance environmental perception capabilities;

[0082] The robot and operating system are equipped with a multi-joint robot that can flexibly grasp, move and operate the wearable 3D laser scanner, including a robot with a touch screen, a robot that grasps the scanner, and a robot that stabilizes the scanner and cooperates to measure control points;

[0083] The robotic arm and operating system can also be replaced with a flexible robotic arm to operate the NavVisVLX device in more complex environments;

[0084] The visual system uses high-resolution cameras to assist in positioning, and computer vision algorithms to determine the location and corresponding number of control points. The operator can observe the robot's environment in real time through panoramic video, so that effective braking measures can be taken in case of emergency.

[0085] The control system uses a high-performance computing unit for path planning, task scheduling, and data processing;

[0086] The communication system exchanges data with the remote server, and the operator intervenes in the robot to control it through the communication system. The communication system can also use self-organizing network technology: establish a self-organizing network between multiple robots to achieve collaborative work and data sharing between robots;

[0087] The robot can also be designed as a modular structure, which is convenient for quickly replacing different functional modules according to different task requirements;

[0088] The mobile system ensures the robot's stable movement and precise positioning in various complex terrains. The sensor system enables the robot to perceive the surrounding environment in real time and build an accurate environmental map. The robotic arm and operating system ensure the stability of the instrument during the scanning process, avoiding inaccurate scanning data due to robotic arm jitter or position error. The visual system enables the robot to accurately locate the control point. The control system ensures the robot's efficiency and accuracy when performing multiple tasks. The communication system provides flexible remote monitoring and operation functions to ensure that operators can intervene and adjust tasks in a timely manner in complex or emergency situations.

[0089] S2, the robot performs system self-check and initializes each system, and receives scanning tasks from the server;

[0090] Preferably, the robot performs a system self-check and initializes each system, receives a scanning task from the server,

[0091] include,

[0092] The master clock signal of the robot control system triggers and activates the subsystems, including the mobile system, sensor system, robotic arm system, vision system, control system and communication system, ensuring that all subsystems start working in a synchronized timing;

[0093] The mobile system detects its stationary state through the built-in gyroscope and accelerometer. If any movement or tilt is detected, the system will send a warning signal and recalibrate the initial position;

[0094] The sensor system performs self-calibration, which involves measuring the distance or size of known reference objects in the environment and comparing it to a preset standard, and if an error occurs, a fault warning is issued;

[0095] The robot arm system self-checks and performs angle tests on the joints. The sensors of the joints return the current angle position and torque, and calculate the expected torque and angle based on the motion model preset by the control system. If an error occurs, a fault warning is issued.

[0096] The visual system captures images of the surrounding environment and determines the image contrast, color saturation, and edge detection data. If the image cannot be captured clearly, a fault warning is issued;

[0097] The control system performs self-checks on the internal processor, memory, and I / O interface. If an abnormality is detected, the control system will automatically restart or switch to the backup system;

[0098] The communication system detects the quality of the connection with the external device, including signal strength, data transmission rate and error rate;

[0099] The self-test results of each subsystem will be transmitted to the main control system in real time. If all systems pass the self-test, the main control system will issue a system initialization command and put each subsystem into standby mode. At the same time, it will load the path planning algorithm and sensor data processing algorithm and receive the scanning task through the server.

[0100] By using the main clock signal in the main control system to trigger the activation process of all subsystems, it is ensured that each subsystem starts synchronously. By using the mobile system self-check, it can prevent path planning errors or scanning data deviations caused by abnormal initial status and ensure the accuracy of the task. The self-calibration of the sensor system helps to reduce data inaccuracies caused by sensor errors during the scanning process and improve the accuracy and reliability of data acquisition. By testing the angles and torques of each joint of the robotic arm, it is ensured that it can accurately position and move during the task execution. By comparing the image quality parameters of the visual system, it is ensured that the camera can work normally. The control system's detection of the processor, memory and I / O interface helps prevent task interruption or data loss caused by hardware failure and ensure the continuity of task execution. By testing the connection quality and automatically adjusting the parameters, the stability of data transmission of the communication system during the task execution is ensured. The self-check results of each subsystem are summarized in the main control system for analysis, which can ensure that all systems are in the best working condition during the initialization process.

[0101] S3, uses sensors to perceive the environment, builds maps, and plans the optimal scanning path. It performs scanning tasks according to the planned path, identifies control points through the visual system, and performs scanning and marking.

[0102] Preferably, sensors are used to sense the environment, build maps, and plan the optimal scanning path, including:

[0103] Acquire environmental information through sensor systems, including lidar, ultrasonic sensors, and infrared sensors. Mark point data acquired by lidar with timestamps and spatial coordinates to form a point cloud map.

[0104] According to the ultrasonic sensor and infrared sensor, the distance information between the environment and the robot is measured, and the distance is calculated according to the received echo time;

[0105] The image data is collected by the camera of the visual system, and the data is synchronized based on the laser radar, ultrasonic sensor and infrared sensor, and a unified timestamp is added. The data is unified into a unified coordinate system through coordinate transformation, which is expressed as:

[0106] Pg=R·Ps+T;

[0107] Where Pg represents the point position in the global coordinate system, R represents the rotation matrix, which describes the rotation relationship between the sensor and the global coordinate system, T represents the translation vector, which describes the displacement relationship between the sensor and the global coordinate system, and Ps represents the point position in the sensor coordinate system;

[0108] The point cloud data generated by the lidar is combined with the distance data of the ultrasonic sensor and the infrared sensor. The accuracy of the point cloud is optimized through the data fusion algorithm of the Kalman filter. The fused point cloud data is processed into a three-dimensional grid, and the three-dimensional space is divided into a series of regular cube Voxels. Each Voxel stores the obstacle information in the area.

[0109] For each Voxel, the occupancy probability of the Voxel is calculated based on the detection results of the lidar, ultrasonic sensor and camera, and the probability of the Voxel being occupied is calculated using the Bayesian update formula, which is expressed as:

[0110]

[0111] Where P(OkZi:k) represents the probability that Voxel k is occupied when the observation value Zi:k is given, and P(ZkOk) represents the probability that the sensor measures the Voxel when Voxel k is occupied. It can be obtained by counting the measurement error of the sensor on objects with known distances. 1 ) represents the probability that Voxel k is occupied when the observation value Zi:k-1 is given, P(ZkZi:k- 1 ) indicates the probability that the sensor measures the observation value Zk when the observation value Zi:k-1 is given, which can be obtained by integral calculation;

[0112] The SLAM algorithm uses the robot's initial position as the origin to start building a map. The robot continuously updates its position and three-dimensional space data through the mobile system.

[0113] Based on the grid map of three-dimensional spatial data, the A-star algorithm is used for path planning.

[0114] Through the combination of lidar, ultrasonic sensor and infrared sensor, the system can obtain environmental information from different dimensions and provide more comprehensive environmental perception capabilities. Lidar provides high-precision point cloud data, and ultrasonic and infrared sensors provide distance information to supplement, ensuring that accurate environmental data can still be obtained in complex environments, improving the accuracy and robustness of environmental modeling. Through unified timestamps and coordinate transformations, data from different sensors are synchronized to a unified coordinate system, ensuring the consistency and comparability of data from each sensor. The use of Kalman filtering to fuse and optimize point cloud data can effectively reduce noise and uncertainty in sensor data. By dividing the three-dimensional space into regular Voxel cubes and calculating the occupancy probability of each Voxel, the system can accurately represent the distribution of obstacles in the environment, enabling the robot to have stronger environmental perception and navigation capabilities in complex environments, and to better avoid obstacles and find the best path. Through the SLAM algorithm, the robot can dynamically build and update the environmental map with the initial position as the origin in an unknown environment.

[0115] Furthermore, the scanning task is performed according to the planned path, the control points are identified by the visual system, and the scanning and marking are performed, including:

[0116] Based on path planning, the robot arm and the operating system move based on the current robot's mobile system based on the path planning. The path points in the path planning correspond to the target positions of the robot arm. The robot arm moves to the target positions in sequence through its motion control system.

[0117] The motion control system uses an inverse kinematics algorithm to calculate the angle of each joint, allowing the scanner at the end of the robotic arm to be accurately positioned at the predetermined spatial position;

[0118] After the robot reaches each scanning point, the 3D laser scanner emits a laser beam and receives the signal reflected from the surface of the scanned object. The scanner calculates the precise distance of the object surface by measuring the flight time TOF of the laser beam and generates 3D point cloud data.

[0119] The control points are identified by the visual system, and the robotic arm operates the wearable 3D laser scanner to mark the points.

[0120] The robotic arm and the operating system use the path points planned by path planning as the target position to achieve the function of collaborative movement. At the same time, through the inverse kinematics algorithm, the robotic arm can accurately calculate the angle of each joint, ensuring that the scanner at the end of the robotic arm can accurately locate the predetermined spatial position, and cooperate with the 3D laser scanner to generate high-precision 3D point cloud data, ensuring that the scanner can capture the subtle features of the object surface, providing high-quality basic data for subsequent analysis and processing. The visual system can identify control points in real time and guide the robotic arm to operate the wearable 3D laser scanner for precise dotting, ultimately realizing automatic dotting operations and improving the automation level and overall quality of the task.

[0121] S4, real-time data transmission to the server for storage, and after the task is completed, data comparison and data backup are performed, and a report template is generated, and task reports are embedded according to the stored data;

[0122] Preferably, the data is transmitted to the server in real time and data comparison and data backup are performed after the task is completed, including:

[0123] The point cloud data is transmitted in real time to an external server through the robot’s internal communication system for storage and preliminary processing;

[0124] The communication system uses high-speed wireless networks for data transmission, such as Wi-Fi 6 or 5G, to ensure stable transmission of large amounts of data;

[0125] After receiving the point cloud data, the server pre-processes the data and records it in real time;

[0126] After the scanning task is completed, the 3D point cloud data of the scanning task is retransmitted and preprocessed;

[0127] At the same time, the data is compared with the point cloud data transmitted in real time. If the data is consistent, it is stored in an external hard disk as backup data. Distributed storage can also be used to store data in multiple nodes to improve data reliability and scalability.

[0128] The server stores the collected data by timestamp and task number, and creates an index for the data. The index includes timestamp, task number, size of data block and storage location.

[0129] The real-time transmission of point cloud data improves the efficiency and stability of data transmission, ensuring that data can be transmitted to the server for processing in a timely and secure manner during task execution. After receiving the point cloud data, the server immediately pre-processes and records the data in real time to prevent data loss and provide complete data records for subsequent analysis. By processing three-dimensional point cloud data and comparing and verifying it with real-time transmitted data, the reliability of data backup is improved, ensuring that accurate task data can be quickly restored when needed. By categorizing and storing the collected data by timestamp and task number, subsequent rapid retrieval and query are facilitated.

[0130] Further, a report template is generated to embed the task report according to the stored data, including,

[0131] Generate automated reports through the LaTeX document generation system and the Python script Jupyter Notebook;

[0132] Set up a standard LaTeX report template based on the LaTeX document generation system, including task overview, path record, data analysis, environmental complexity analysis and summary;

[0133] Extract the data received by the server and input it into the generated standard LaTeX report template, embedding it according to the placeholders in the template;

[0134] The task overview will embed basic information such as task number, scanning time, target area, etc.

[0135] The path record is inserted into the Python-generated robot motion path diagram, and a detailed description of the path is attached below the diagram;

[0136] Data analysis inserts the results of data analysis in the form of charts or text to explain the accuracy of point cloud data, key findings during scanning, etc.

[0137] Environmental complexity analysis: Generate an environmental complexity index based on sensor feedback and insert it into the report;

[0138] Summary: Automatically generate a summary paragraph based on the conclusions of the data analysis. The system will analyze the advantages of task execution and possible improvement suggestions;

[0139] Compile the report template into the final PDF document through the LaTeX compiler.

[0140] By generating automated reports, the time and error rate of manual operations are reduced, ensuring that each generated report has a unified format and standardized content. The standard LaTeX report template provides a clear framework that is easy to maintain and expand. By extracting the data received by the server and automatically inputting it into the LaTeX report template, it is embedded according to the placeholders of the template to ensure the accuracy and timeliness of the report content. The report template is compiled into a PDF document through the LaTeX compiler to ensure professional typesetting and high-quality output of the report.

[0141] Example 2, reference Figure 2 , which is the second embodiment of the present invention, and which is different from the previous embodiment, provides a system for an automated three-dimensional laser scanning method based on a robot, comprising:

[0142] System self-check module: the system performs self-check and initializes each subsystem to confirm the working status of all systems;

[0143] Task path planning module: The control system receives scanning tasks from the server, perceives the environment through the sensor system, builds a map, and plans the optimal scanning path;

[0144] Task execution module: the robot arm and operating system perform scanning tasks according to the planned path, the visual system identifies control points and performs precise point marking, and the point cloud data collected in real time is transmitted to the server through the communication system;

[0145] Data storage module: real-time transmitted data is stored on the server side. After the task is completed, the system will compare and back up the data to ensure data consistency and integrity;

[0146] The task report module controls the generation of report templates, embeds the stored data into the task report, and automatically generates a complete task execution report for operator review and analysis.

[0147] If the function is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention, or the part that contributes to the prior art, or the part of the technical solution, can be embodied in the form of a software product. The computer software product is stored in a storage medium and includes several instructions for a computer device (which can be a personal computer, a server, or a network device, etc.) to perform all or part of the steps of the method described in each embodiment of the present invention. The aforementioned storage medium includes: U disk, mobile hard disk, read-only memory (ROM, Read-Only Memory), random access memory (RAM, Random Access Memory), disk or optical disk, etc. Various media that can store program codes.

[0148] The logic and / or steps represented in the flowchart or otherwise described herein, for example, can be considered as an ordered list of executable instructions for implementing logical functions, and can be embodied in any computer-readable medium for use by an instruction execution system, device or apparatus (such as a computer-based system, a system including a processor, or other system that can fetch instructions from an instruction execution system, device or apparatus and execute instructions), or in conjunction with such instruction execution systems, devices or apparatuses. For the purposes of this specification, "computer-readable medium" can be any device that can contain, store, communicate, propagate or transmit a program for use by an instruction execution system, device or apparatus, or in conjunction with such instruction execution systems, devices or apparatuses.

[0149] More specific examples of computer-readable media (a non-exhaustive list) include the following: an electrical connection with one or more wires (electronic device), a portable computer disk case (magnetic device), a random access memory (RAM), a read-only memory (ROM), an erasable and programmable read-only memory (EPROM or flash memory), an optical fiber device, and a portable compact disk read-only memory (CDROM). In addition, the computer-readable medium may even be a paper or other suitable medium on which the program is printed, since the program may be obtained electronically, for example, by optically scanning the paper or other medium, followed by editing, deciphering or, if necessary, processing in another suitable manner, and then stored in a computer memory.

[0150] It should be understood that the various parts of the present invention can be implemented by hardware, software, firmware or a combination thereof. In the above embodiments, a plurality of steps or methods can be implemented by software or firmware stored in a memory and executed by a suitable instruction execution system. For example, if implemented by hardware, as in another embodiment, any one of the following technologies known in the art or a combination thereof can be used to implement: a discrete logic circuit having a logic gate circuit for implementing a logic function for a data signal, a dedicated integrated circuit having a suitable combination of logic gate circuits, a programmable gate array (PGA), a field programmable gate array (FPGA), etc.

[0151] It should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention rather than to limit it. Although the present invention has been described in detail with reference to the preferred embodiments, those skilled in the art should understand that the technical solutions of the present invention may be modified or replaced by equivalents without departing from the spirit and scope of the technical solutions of the present invention, which should all be included in the scope of the claims of the present invention.

Claims

1. A robot-based automated three-dimensional laser scanning method, characterized in that: include, The robot performs system self-check and initializes each system, and receives scanning tasks from the server; Use sensors to perceive the environment, build maps, and plan the optimal scanning path. Perform scanning tasks according to the planned path, identify control points through the visual system, and perform scanning and marking. The data is transmitted to the server in real time, and data comparison and data backup are performed after the task is completed. A report template is generated and the task report is embedded based on the stored data.

2. The robot-based automated three-dimensional laser scanning method according to claim 1, characterized in that: The robot includes a mobile system, a sensor system, a mechanical arm and an operating system, a visual system, a control system and a communication system; The mobile system adopts high-precision motors and encoders; The sensor system integrates laser radar, ultrasonic and infrared sensors; The robotic arm and operating system are equipped with a multi-joint robotic arm; The visual system uses a high-resolution camera to assist in positioning, and uses a computer vision algorithm to determine the location of the control point and the corresponding number. The operator observes the robot's environment in real time through a panoramic video. The control system uses a high-performance computing unit for path planning, task scheduling and data processing; The communication system exchanges data with the remote server, and the operator intervenes in the robot to control it through the communication system.

3. The robot-based automated three-dimensional laser scanning method according to claim 2, characterized in that: The robot performs system self-check and initializes each system, and receives scanning tasks from the server, including: The master clock signal of the robot control system triggers and activates subsystems, including the mobile system, sensor system, manipulator system, vision system, control system and communication system; The mobile system detects its stationary state through the built-in gyroscope and accelerometer. If any movement or tilt is detected, the system will send a warning signal and recalibrate the initial position; The sensor system performs self-calibration, including measuring the distance or size of known reference objects in the environment and comparing it with a preset standard, and issuing a fault warning if an error occurs; The robot arm system self-checks and performs angle tests on the joints. The sensors of the joints return the current angle position and torque, and calculate the expected torque and angle according to the motion model preset by the control system. If an error occurs, a fault warning is issued; The visual system captures the surrounding environment image and determines the image contrast, color saturation, and edge detection data. If the image cannot be captured clearly, a fault warning is issued; The control system performs self-checks on the internal processor, memory and I / O interface. If an abnormality is detected, the control system will automatically restart or switch to the backup system; The communication system detects the quality of the connection with the external device, including signal strength, data transmission rate and error rate; The self-test results of each subsystem will be transmitted to the main control system in real time. If all systems pass the self-test, the main control system will issue a system initialization command and put each subsystem into standby mode. At the same time, it will load the path planning algorithm and sensor data processing algorithm and receive the scanning task through the server.

4. The robot-based automated three-dimensional laser scanning method according to claim 3, characterized in that: The method of using sensors to perceive the environment, construct a map, and plan the optimal scanning path includes: Acquire environmental information through sensor systems, including lidar, ultrasonic sensors, and infrared sensors. Mark point data acquired by lidar with timestamps and spatial coordinates to form a point cloud map. According to the ultrasonic sensor and infrared sensor, the distance information between the environment and the robot is measured, and the distance is calculated according to the received echo time; The image data is collected by the camera of the visual system, and the data is synchronized based on the laser radar, ultrasonic sensor and infrared sensor, and a unified timestamp is added. The data is unified into a unified coordinate system through coordinate transformation, which is expressed as: P g =R·P s +T; Where P g represents the point position in the global coordinate system, R represents the rotation matrix, which describes the rotation relationship between the sensor and the global coordinate system, T represents the translation vector, which describes the displacement relationship between the sensor and the global coordinate system, and P s Represents the point position in the sensor coordinate system; The point cloud data generated by the lidar is combined with the distance data of the ultrasonic sensor and the infrared sensor. The accuracy of the point cloud is optimized through the data fusion algorithm of the Kalman filter. The fused point cloud data is processed into a three-dimensional grid, and the three-dimensional space is divided into a series of regular cube Voxels. Each Voxel stores the obstacle information in the area. For each Voxel, the occupancy probability of the Voxel is calculated based on the detection results of the lidar, ultrasonic sensor and camera, and the probability of the Voxel being occupied is calculated using the Bayesian update formula, which is expressed as: Where P(O k |Z i:k ) indicates that when giving the observation value Z i:k When Voxel k is occupied, P(Z k |O k ) represents the probability that the sensor measures the Voxel when Voxel k is occupied, P(O k |Z i:k-1 ) indicates that when giving the observation value Z i:k-1 When Voxel k is occupied, P(Z k |Z i:k-1 ) indicates that when giving the observation value Z i:k-1 When the sensor measures the observation value Z k The probability of The SLAM algorithm uses the robot's initial position as the origin to start building a map. The robot continuously updates its position and three-dimensional space data through the mobile system. Based on the grid map of three-dimensional spatial data, the A-star algorithm is used for path planning.

5. The robot-based automated three-dimensional laser scanning method according to claim 4, characterized in that: The scanning task is performed according to the planned path, the control points are identified by the visual system, and the scanning and marking are performed, including: Based on path planning, the robot arm and the operating system move based on the current robot's mobile system based on the path planning. The path points in the path planning correspond to the target positions of the robot arm. The robot arm moves to the target positions in sequence through its motion control system. The motion control system uses an inverse kinematics algorithm to calculate the angle of each joint, allowing the scanner at the end of the robotic arm to be accurately positioned at the predetermined spatial position; After the robot reaches each scanning point, the 3D laser scanner emits a laser beam and receives the signal reflected from the surface of the scanned object. The scanner calculates the precise distance of the object surface by measuring the flight time TOF of the laser beam and generates 3D point cloud data. The control points are identified by the visual system, and the robotic arm operates the wearable 3D laser scanner to mark the points.

6. The robot-based automated three-dimensional laser scanning method according to claim 5, characterized in that: The real-time transmission data is stored in the server, and data comparison and data backup are performed after the task is completed, including: The point cloud data is transmitted in real time to an external server through the robot’s internal communication system for storage and preliminary processing; The communication system uses high-speed wireless networks for data transmission; After receiving the point cloud data, the server pre-processes the data and records it in real time; After the scanning task is completed, the 3D point cloud data of the scanning task is retransmitted and preprocessed; At the same time, it is compared with the point cloud data transmitted in real time. If the data is consistent, it is stored in an external hard disk as backup data; The server stores the collected data by timestamp and task number, and creates an index for the data. The index includes timestamp, task number, size of data block and storage location.

7. The robot-based automated three-dimensional laser scanning method according to claim 6, characterized in that: The generated report template, embedded in the task report according to the stored data, includes: Generate automated reports through the LaTeX document generation system and the Python script Jupyter Notebook; Set up a standard LaTeX report template based on the LaTeX document generation system, including task overview, path record, data analysis, environmental complexity analysis and summary; Extract the data received by the server and input it into the generated standard LaTeX report template, embedding it according to the placeholders in the template; Compile the report template into the final PDF document through the LaTeX compiler.

8. A system based on the robot-based automated three-dimensional laser scanning method according to any one of claims 1 to 7, characterized in that: include, System self-check module: the system performs self-check and initializes each subsystem to confirm the working status of all systems; Task path planning module: The control system receives scanning tasks from the server, perceives the environment through the sensor system, builds a map, and plans the optimal scanning path; Task execution module: the robot arm and operating system perform scanning tasks according to the planned path, the visual system identifies control points and performs precise point marking, and the point cloud data collected in real time is transmitted to the server through the communication system; Data storage module: real-time transmitted data is stored on the server side. After the task is completed, the system will compare and back up the data to ensure data consistency and integrity; The task report module controls the generation of report templates, embeds the stored data into the task report, and automatically generates a complete task execution report for operator review and analysis.

9. A computer device comprising: A memory and a processor; the memory stores a computer program, wherein the processor implements the steps of the robot-based automated three-dimensional laser scanning method described in any one of claims 1 to 7 when executing the computer program.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the steps of the robot-based automated three-dimensional laser scanning method described in any one of claims 1 to 7 are implemented.

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