Intelligent inspection robot, intelligent inspection method, electronic equipment and medium

Abstract

The invention discloses an intelligent inspection robot, an intelligent inspection method, electronic equipment and a medium. The intelligent inspection robot comprises a GNSS module, an IMU module and an industrial personal computer; the GNSS module is used for determining the current position coordinates of the robot according to satellite signals received by the moving station and the base station respectively; the IMU module is used for acquiring motion information of the robot; and the industrial personal computer is used for generating current navigation data of the robot according to the current position coordinates, the motion information, a preset initial track and obstacle information returned by the rear-end server, and controlling a motion mechanism of the robot according to the current navigation data to realize automatic cruise. By adopting the technical scheme, the motion trail of the robot can be intelligently planned, so that the intelligent inspection robot can perform automatic inspection in an optimal motion mode, and the intelligent inspection efficiency is effectively improved.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of intelligent inspection equipment, and particularly relates to an intelligent inspection robot, an intelligent inspection method, an electronic device and a medium. BACKGROUND

[0002] The intelligent inspection robot is an intelligent device for replacing manual work to complete the detection and diagnosis of equipment running state in special environment, autonomous movement, image recognition, fault detection, equipment monitoring and the like through highly intelligent robot technology and image recognition technology. The intelligent inspection robot needs to have multiple functions such as full-coverage inspection of equipment area, security inspection, environmental monitoring and the like.

[0003] However, most of the existing intelligent inspection equipment relies on limited sensors such as cameras, temperature sensors, ultrasonic sensors and the like, and the control mode is relatively single, the comprehensiveness and accuracy of information collection are insufficient, the ability of multi-source data fusion is lacking, and thus there are problems such as low inspection efficiency, low intelligent degree and low flexibility of motion planning, and the monitoring is not comprehensive for larger working sites, so that the intelligent inspection equipment cannot adapt to the inspection work in complex environment. SUMMARY

[0004] The present application provides an intelligent inspection robot, an intelligent inspection method, an electronic device and a medium, which can intelligently plan the motion trajectory of the robot, so that the intelligent inspection robot automatically inspects in the optimal motion mode, and effectively improves the intelligent inspection efficiency.

[0005] According to an aspect of the present application, an intelligent inspection robot is provided, comprising a GNSS (Global Navigation Satellite System) module, an IMU (Inertial measurement unit) module and an industrial computer.

[0006] The GNSS module is configured to determine the current position coordinates of the robot according to satellite signals received by a flow station and a reference station respectively.

[0007] The IMU module is configured to obtain motion information of the robot.

[0008] The industrial computer is configured to generate current navigation data of the robot according to the current position coordinates, the motion information, a preset initial trajectory and obstacle information returned by a back-end server, and control a motion mechanism of the robot according to the current navigation data to realize automatic cruising.

[0009] According to another aspect of the present application, an intelligent inspection method is provided, which is executed by the intelligent inspection robot according to any one of the embodiments of the present application, and comprises the following steps.

[0010] determine the current position coordinates of the robot according to the satellite signals received by the flow station and the reference station respectively through the GNSS module;

[0011] acquire the motion information of the robot through the IMU module;

[0012] generate the current navigation data of the robot according to the current position coordinates, the motion information, the preset initial trajectory and the obstacle information returned by the back-end server through the industrial computer, and control the motion mechanism of the robot according to the current navigation data to realize automatic cruising.

[0013] According to another aspect of the present application, an electronic device is provided, which comprises:

[0014] at least one processor; and

[0015] a memory in communication connection with the at least one processor; wherein,

[0016] the memory stores a computer program executable by the at least one processor, and the computer program is executed by the at least one processor to enable the at least one processor to execute the intelligent inspection method according to any one of the embodiments of the present application.

[0017] According to another aspect of the present application, a computer readable storage medium is provided, which stores computer instructions for enabling a processor to execute the intelligent inspection method according to any one of the embodiments of the present application when executed.

[0018] The technical solution of the embodiments of the present application can accurately position the intelligent inspection robot in various inspection environments by configuring the GNSS module, the IMU module and the industrial computer in the intelligent inspection robot, effectively improve the inspection efficiency, improve the intelligent degree and the flexibility of motion planning of the inspection robot, and improve the comprehensiveness of monitoring, and can adapt to the inspection work in complex environments.

[0019] It should be understood that the content described in this part is not intended to identify the key or important features of the embodiments of the present application, nor is it used to limit the scope of the present application. Other features of the present application will become apparent from the following description. BRIEF DESCRIPTION OF DRAWINGS

[0020] In order to more clearly illustrate the technical solutions in the embodiments of the present application, the drawings needed in the embodiment description will be briefly introduced below. Obviously, the drawings in the following description are only some embodiments of the present application, and other drawings can be obtained by those skilled in the art without creative labor on the basis of these drawings.

[0021] Figure 1 is a structural schematic diagram of an intelligent inspection robot according to an embodiment of the present application;

[0022] Figure 2 is another structural schematic diagram of an intelligent inspection robot according to an embodiment of the present application;

[0023] Figure 3 is a structural schematic diagram of an intelligent inspection robot according to an embodiment of the present application;

[0024] Figure 4 is another structural schematic diagram of an intelligent inspection robot according to an embodiment of the present application;

[0025] Figure 5 is a flow chart of an intelligent inspection method according to an embodiment of the present application;

[0026] Figure 6 is a structural schematic diagram of an electronic device implementing an intelligent inspection method according to an embodiment of the present application. DETAILED DESCRIPTION

[0027] In order to make the personnel in the art better understand the present application, the technical solutions in the embodiments of the present application will be described clearly and completely below in conjunction with the drawings in the embodiments of the present application. Obviously, the described embodiments are only a part of the embodiments of the present application, but not all the embodiments. Based on the embodiments in the present application, all other embodiments obtained by those skilled in the art without creative labor should be within the scope of protection of the present application.

[0028] It should be noted that the terms "first", "second", and the like in the specification and claims of the present application and the above-described drawings are used to distinguish similar objects, and do not necessarily have to describe a specific order or sequence. It should be understood that the data thus used can be interchanged under appropriate circumstances, so that the embodiments of the present application described herein can be implemented in an order other than those illustrated or described herein. In addition, the terms "include" and "have" and any variations thereof are intended to cover non-exclusive inclusion, for example, a process, method, system, product or device including a series of steps or units does not have to be limited to those steps or units clearly listed, but can include other steps or units not clearly listed or inherent to these processes, methods, products or devices.

[0029] Embodiment One

[0030] Figure 1 is a structural schematic diagram of an intelligent inspection robot according to an embodiment of the present application. As shown in the figure, Figure 1As shown, the intelligent inspection robot includes a GNSS module 110 , an IMU module 120 and an industrial computer 130 .

[0031] The GNSS module 110 is used to determine the current position coordinates of the robot based on the satellite signals received by the rover and the base station respectively.

[0032] The IMU module 120 is used to obtain motion information of the robot.

[0033] The industrial computer 130 is used to generate the robot's current navigation data based on the current position coordinates, the motion information, the preset initial trajectory and the obstacle information returned by the back-end server, and control the robot's motion mechanism according to the current navigation data to achieve automatic cruising.

[0034] The technical solution of the embodiment of the present invention, by configuring a GNSS module, an IMU module and an industrial computer in the intelligent inspection robot, can accurately position the intelligent inspection robot in various inspection environments, effectively improve the inspection efficiency, improve the intelligence level of the inspection robot and the flexibility of motion planning, enhance the comprehensiveness of monitoring, and be able to adapt to inspection work in complex environments.

[0035] Optionally, the GNSS module 110 can not only provide precise outdoor positioning, but also meet the positioning requirements of indoor inspections. The differential positioning method adopted in the embodiment of the present invention can effectively overcome the errors caused by signal transmission and reception, and improve the positioning accuracy of the inspection robot.

[0036] Optionally, the GNSS module 110 is specifically configured to:

[0037] Determine a carrier phase and a pseudorange at a current position according to satellite signals received by the mobile station, and calculate a first position coordinate according to the carrier phase and the pseudorange;

[0038] A positioning error is determined according to the satellite signal received by the reference station, and the first position coordinate is corrected according to the positioning error to obtain the current position coordinate of the robot.

[0039] Optionally, if the position difference method is used, after the base station receives the satellite signal, it can determine the positioning error based on the base station's own high-precision positioning and the measured positioning calculated based on the satellite signal, and send the positioning error to the mobile station so that the mobile station can correct the first position coordinates based on the positioning error.

[0040] Optionally, for the GNSS system, the reference station can be arranged at a fixed point with accurate positioning coordinates, and the mobile station can be arranged in the intelligent inspection robot, and the reference station and the mobile station can interact with each other, and the reference station and the mobile station are essentially satellite signal receivers but are arranged at different positions.

[0041] Optionally, both the carrier phase and the pseudo-range can be obtained by satellite signal calculation, the carrier phase refers to the measurement value of the phase of the received satellite signal at the receiving time relative to the phase of the carrier signal generated by the receiver, and the pseudo-range refers to the distance measurement value between the satellite and the receiver at the receiving time, and according to the carrier phase and the pseudo-range, the coordinates of the position of the receiver can be calculated.

[0042] Optionally, the GNSS module 110 can also use carrier phase difference technology to achieve accurate positioning, and the GNSS module 110 can be specifically used for:

[0043] According to the satellite signal received by the reference station, a first carrier phase measurement value is obtained, and according to the satellite signal received by the mobile station, a second carrier phase measurement value is obtained;

[0044] According to the first carrier phase measurement value and the second carrier phase measurement value, a phase difference observation value is determined, and according to the phase difference observation value, a baseline vector is determined;

[0045] According to the baseline vector, the current position coordinates of the robot are obtained.

[0046] The advantage of such an arrangement is that it can effectively reduce the positioning error caused by atmospheric delay and other factors, and improve the positioning accuracy of the robot.

[0047] Optionally, the IMU module 120 can include a gyroscope and an accelerometer, and through analysis of the collected data, the acceleration, angular velocity and direction change of the intelligent inspection robot can be obtained, and then the data in the motion information can be calibrated and filtered to reduce errors and noise and improve the quality and stability of the data.

[0048] Figure 2 Another structure diagram of the intelligent inspection robot provided by the embodiment of the present application is shown in Figure 2 As shown in the figure, the industrial computer 130 of the intelligent inspection robot can include a first server 131 and a ROS unit 132.

[0049] Optionally, the first server 131 can also be used to obtain the obstacle information sent by the backend server and send the obstacle information to the ROS unit 132.

[0050] The ROS unit 132 can be used for:

[0051] The Kalman filtering method is used to fuse the current position coordinates and motion information, and according to the data fusion result and a preset initial trajectory, first navigation data of the robot is acquired.

[0052] The first navigation data is corrected according to the obstacle information returned by the backend server, current navigation data of the robot is generated, and the motion mechanism in the intelligent inspection robot is controlled according to the current navigation data, wherein the motion mechanism is a four-wheel omni-directional driving system.

[0053] Optionally, the first server 131 can be used for data interaction with the backend server, and the obstacle information sent by the backend processor is sent to the ROS unit 132, the first server 131 can also be used for initializing and checking the modules in the intelligent inspection robot after the intelligent inspection robot is powered on, and when it is determined that all the modules in the intelligent inspection robot are in a normal state, it is determined that the robot can start the inspection work, the ROS unit 132 is applied as a software architecture in the industrial computer 130, and can realize planning, operation, perception, control and other functions.

[0054] Optionally, the backend server can be a remote server, and the backend server and the intelligent inspection robot can constitute an intelligent inspection system, the intelligent inspection robot performs an inspection operation, a data acquisition operation and a simple positioning and control operation, and the backend server collects data and performs complex operations.

[0055] Optionally, the first navigation data can refer to initial navigation data obtained by the ROS unit 132 according to the data sent by the GNSS module 110 and the IMU module 120, the first navigation data is generally determined according to the inspection trajectory, but the obstacle situation is not considered, therefore, the first navigation data needs to be further corrected according to the obstacle information, so that the obstacle avoidance can be accurately and effectively performed on the basis of ensuring that the inspection trajectory is not deviated.

[0056] Optionally, by fusing the current position coordinates and motion information, more accurate state estimation data of the robot can be acquired, and the navigation data can include position coordinates, linear velocity, angular velocity and motion direction of the intelligent inspection robot at the next time step.

[0057] Optionally, when generating the navigation data, the ROS unit 132 can adopt a local path planning algorithm based on discrete optimization, that is, a cost function is used to respectively evaluate the safety, smoothness and other performance parameters of the candidate paths generated discretely, and then a local optimal path is obtained by weighted calculation according to the cost functions.

[0058] The intelligent inspection robot provided in the embodiment of the application can execute the intelligent inspection method provided in the third embodiment of the application.

[0059] Embodiment Two

[0060] Figure 3 A structural schematic diagram of an intelligent inspection robot provided for Embodiment Two of the present application, the present embodiment further illustrates the structure of the intelligent inspection robot on the basis of the above-mentioned embodiment. As shown in the figure, the intelligent inspection robot further comprises a thermal imaging dual-spectrum pan-tilt camera 140, a 3D camera module 150, a laser radar module 160, a lifting platform 170, and a power module 180. Figure 3

[0061] Optionally, the thermal imaging dual-spectrum pan-tilt camera 140 can be used to shoot thermal infrared images in the inspection environment under different spectral ranges.

[0062] Optionally, the 3D camera module 150 can be used to obtain three-dimensional point cloud data in the inspection environment.

[0063] Optionally, the laser radar module 160 can be used to obtain laser radar point cloud data in the inspection environment.

[0064] Optionally, the thermal imaging dual-spectrum pan-tilt camera 140 can perceive temperature information in the inspection environment through its thermal imaging technology, and then analyze the inspection environment in the backend server in combination with the temperature information, and also be able to obtain a temperature distribution map in the inspection environment from the thermal infrared images in the backend server.

[0065] The advantage of such an arrangement is that by using the thermal imaging technology in the thermal imaging dual-spectrum pan-tilt camera 140, the robot can also perform inspection at night or in low light conditions, without being limited by natural light conditions, thereby realizing all-weather inspection tasks and improving the flexibility and reliability of the application.

[0066] Optionally, the 3D camera module 150 can quickly obtain rich color images and depth information to determine the three-dimensional structure information of the inspection environment, but is seriously affected by light and has low depth information accuracy; the laser radar module 160 has high information accuracy and fast information acquisition speed, but has the problem of single data information acquisition, so the three-dimensional point cloud data and the laser radar point cloud data in the inspection environment can be obtained respectively, and then information fusion can be performed in the backend server, thereby improving the detection accuracy of the inspection environment.

[0067] Optionally, the laser radar module 160 can include a laser radar and a millimeter wave radar, and by mounting multiple radars, high-resolution obstacle detection can be realized.

[0068] ​Optionally, the first server 131 can be configured to collect information collected by the GNSS module 110, the IMU module 120, the thermal imaging dual-spectrum pan-tilt camera 140, the 3D camera module 150, and the laser radar module 160, and send the information to the backend server in real time, so that the backend server determines the obstacle information in the inspection environment and updates the map according to the information sent by the industrial computer.

[0069] Optionally, the backend server can obtain all the data collected by the intelligent inspection robot, and can perform data fitting according to the three-dimensional point cloud data and the laser radar point cloud data, to obtain the obstacle information in front of the motion trajectory of the intelligent inspection robot in real time. The obstacle information can include the coordinate range, size, temperature, and other data of the obstacle, which are not limited herein, and the obstacle information is fed back to the intelligent inspection robot through the first server 131. After receiving the obstacle information sent by the backend server, the first server 131 can send the obstacle information to the ROS unit 132.

[0070] Optionally, if the intelligent inspection robot is performing the inspection operation for the target inspection environment for the first time, an initial trajectory set by a user can be preloaded in the ROS unit 132, and the actual inspection trajectory is recorded during the inspection process and sent to the backend server to generate an inspection map.

[0071] Optionally, if the intelligent inspection robot is repeatedly performing the inspection operation for the target inspection environment, the inspection map generated by the backend server in advance can be used as the initial trajectory, and the initial trajectory is corrected according to the real-time obtained obstacle information.

[0072] Optionally, for a simple path or a path with known obstacles, the ROS unit 132 can also move according to the pre-set trajectory, and the obstacle problem can be ignored.

[0073] Optionally, the ROS unit 132 can also be combined with the screen of the industrial computer to provide a visual page for a user to control the intelligent inspection robot through the visual page.

[0074] Optionally, the ROS unit 132 can also be configured to:

[0075] detect an abnormal state of the target obstacle according to the obstacle information;

[0076] generate alarm information matched with the target obstacle when it is determined that the target obstacle belongs to an abnormal state.

[0077] Optionally, according to the preset obstacle index and the obstacle information, it is determined whether the obstacle exceeds the index range, if yes, it is determined that the obstacle is in an abnormal state, and if not, the obstacle is in a normal state.

[0078] Optionally, the obstacle index can include a temperature range and a coordinate range of the obstacle, for example, if the reasonable temperature of the obstacle is 100-120 degrees, but according to the obstacle information, it is determined that the current obstacle temperature is 180 degrees, it is determined that the obstacle is in an abnormal state, and then an alarm information is generated to prompt the user.

[0079] Optionally, the lifting platform 170 can be arranged at the front end of the intelligent inspection robot, and the thermal imaging dual-spectrum pan-tilt camera 140 is carried on the lifting platform 170.

[0080] The thermal imaging dual-spectrum pan-tilt camera 140 can include a temperature measurement thermal imager, a full high-definition visible light camera, and a 360-degree unlimited position outdoor pan-tilt.

[0081] The advantage of such an arrangement is that through the 360-degree unlimited position outdoor pan-tilt and the lifting platform 170, the thermal imaging dual-spectrum pan-tilt camera 140 can rotate in the horizontal and vertical directions, so that the intelligent inspection robot can capture information of the inspection environment at multiple angles.

[0082] Optionally, the power module 180 can be used to power the intelligent inspection robot.

[0083] The ROS unit 132 can also be used to:

[0084] record the inspection trajectory of the intelligent inspection robot in the current inspection process, and monitor the remaining power of the power module in real time;

[0085] When it is determined according to the remaining power of the power module that the robot meets the return charging condition, the robot is controlled to return to charging according to the inspection trajectory.

[0086] Figure 4 Another structure diagram of an intelligent inspection robot is provided for the embodiment of the present application. Figure 4As shown, the thermal imaging dual-spectrum pan-tilt camera 140, the 3D camera module 150, and the laser radar module 160 are installed at the front end of the intelligent inspection robot, the laser radar module 160 is also connected with a rotating motor, and the rotation of the laser radar module 160 in the horizontal direction is realized through the motor. The thermal imaging dual-spectrum pan-tilt camera 140 is carried on the lifting platform 170, and the rotation of the thermal imaging dual-spectrum pan-tilt camera 140 in the horizontal and vertical directions is realized through the lifting platform and the pan-tilt inside the thermal imaging dual-spectrum pan-tilt camera 140. The IMU module 120 is embedded in the center of the intelligent inspection robot to obtain accurate robot motion information, and the GNSS module 110 is installed at the top of the intelligent inspection robot to realize accurate positioning.

[0087] The advantages of such an arrangement are that through the cooperative collection of information by the GNSS module 110, the IMU module 120, the thermal imaging dual-spectrum pan-tilt camera 140, the 3D camera module 150, and the laser radar module 160, the collected information can be further fused and processed, the environment can be perceived in all directions, the inspection efficiency is effectively improved, and the possibility of missed inspection and false inspection is reduced.

[0088] Optionally, as shown in the bottom structure of the intelligent inspection robot, Figure 4 The bottom structure of the intelligent inspection robot adopts a four-wheel omnidirectional driving system, each wheel is driven by an independent motor, and the robot has high mobility.

[0089] The technical scheme of the embodiment of the application configures a GNSS module, an IMU module, a thermal imaging dual-spectrum pan-tilt camera, a 3D camera module, a laser radar module, a lifting platform, and a power module in the intelligent inspection robot, obtains multi-dimensional information of the intelligent inspection robot and the inspection environment, and fuses the information to realize the autonomous navigation and automatic inspection of the intelligent inspection robot. The intelligent inspection robot can realize automatic planning of an inspection path, automatic obstacle avoidance, autonomous charging, and the like, reduces the need for manual intervention, improves the automation level of the inspection system, can accurately position the intelligent inspection robot in various inspection environments, effectively improves the inspection efficiency, improves the intelligent degree and the flexibility of motion planning of the inspection robot, improves the comprehensiveness of monitoring, and can adapt to inspection work in complex environments.

[0090] Embodiment three

[0091] Figure 5 A flowchart of an intelligent inspection method provided by the third embodiment of the application, the embodiment can be applicable to accurate and efficient inspection in various different inspection environments, and the method can be executed by an intelligent inspection robot. As shown in Figure 5 The method comprises the following steps:

[0092] S310, determining the current position coordinate of the robot according to the satellite signals respectively received by the rover station and the reference station through the GNSS module.

[0093] Optionally, the determining of the current position coordinate of the robot according to the satellite signals respectively received by the rover station and the reference station through the GNSS module can comprise:

[0094] determining the carrier phase and the pseudo-range at the current position according to the satellite signals received by the rover station, and calculating the first position coordinate according to the carrier phase and the pseudo-range;

[0095] determining the positioning error according to the satellite signals received by the reference station, and correcting the first position coordinate according to the positioning error to obtain the current position coordinate of the robot.

[0096] Optionally, if the position difference method is adopted, after the reference station receives the satellite signals, the positioning error can be determined according to the high-precision positioning of the reference station itself and the measurement positioning calculated according to the satellite signals, and the positioning error is sent to the rover station for correcting the first position coordinate according to the positioning error.

[0097] Optionally, for the GNSS system, the reference station can be arranged at a fixed point with accurate positioning coordinates, and the rover station can be configured in the intelligent inspection robot. The reference station and the rover station can interact with each other, and both of them are essentially satellite signal receivers but are configured at different positions.

[0098] Optionally, both the carrier phase and the pseudo-range can be obtained by solving the satellite signals. The carrier phase is the measurement value of the phase of the received satellite signal at the receiving time relative to the carrier signal phase generated by the receiver, and the pseudo-range is the distance measurement value between the satellite and the receiver at the receiving time. According to the carrier phase and the pseudo-range, the coordinates of the position of the receiver can be solved.

[0099] Optionally, the determining of the current position coordinate of the robot according to the satellite signals respectively received by the rover station and the reference station through the GNSS module can further comprise:

[0100] obtaining a first carrier phase measurement value according to the satellite signals received by the reference station, and obtaining a second carrier phase measurement value according to the satellite signals received by the rover station;

[0101] determining a phase difference observation value according to the first carrier phase measurement value and the second carrier phase measurement value, and determining a baseline vector according to the phase difference observation value;

[0102] obtaining the current position coordinate of the robot according to the baseline vector.

[0103] S320, acquiring motion information of the robot through the IMU module.

[0104] Optionally, the IMU module can include a gyroscope and an accelerometer, and according to the collected data of the gyroscope and the accelerometer, the motion information such as acceleration, angular velocity and direction change of the intelligent inspection robot can be acquired.

[0105] Optionally, after acquiring the motion information of the robot, each data in the motion information can be calibrated and filtered to reduce errors and noises and improve the quality and stability of the data.

[0106] S330, generating current navigation data of the robot according to the current position coordinates, the motion information, the preset initial trajectory and the obstacle information returned by the back-end server through the industrial computer, and controlling the motion mechanism of the robot according to the current navigation data to realize automatic cruising.

[0107] Optionally, the industrial computer can include a first server and a ROS unit.

[0108] Optionally, generating the current navigation data of the robot according to the current position coordinates, the motion information, the preset initial trajectory and the obstacle information returned by the back-end server can include:

[0109] acquiring the obstacle information sent by the back-end server through the first server and sending the obstacle information to the ROS unit;

[0110] fusing the current position coordinates and the motion information by using the Kalman filtering method through the ROS unit, and acquiring first navigation data of the robot according to the data fusion result and the preset initial trajectory;

[0111] correcting the first navigation data according to the obstacle information returned by the back-end server through the ROS unit to generate the current navigation data of the robot, and controlling the motion mechanism in the intelligent inspection robot according to the current navigation data; wherein the motion mechanism is a four-wheel omnidirectional driving system.

[0112] Optionally, the back-end server can be a remote server, and the back-end server and the intelligent inspection robot can constitute an intelligent inspection system, wherein the intelligent inspection robot performs inspection operation, data collection operation and simple positioning and control operation, and the back-end server collects data and performs complex operation.

[0113] Optionally, the first navigation data can be initial navigation data obtained by the ROS unit according to the data sent by the GNSS module and the IMU module, and the first navigation data is generally determined according to the inspection track, but the situation of obstacles is not considered, therefore, the first navigation data needs to be further corrected according to the obstacle information, so that accurate and effective obstacle avoidance can be performed on the basis of ensuring that the inspection track is not deviated.

[0114] Optionally, by fusing the current position coordinates and motion information, more accurate state estimation data of the robot can be obtained, and the navigation data can include the position coordinates, linear velocity, angular velocity and motion direction of the intelligent inspection robot at the next time step.

[0115] The technical scheme of the embodiment of the application determines the current position coordinates of the robot according to the satellite signals received by the GNSS module from the flow station and the reference station respectively, the IMU module obtains the motion information of the robot, the industrial computer generates the current navigation data of the robot according to the current position coordinates, the motion information, the preset initial track and the obstacle information returned by the back-end server, and controls the motion mechanism of the robot according to the current navigation data, realizes the automatic cruising mode, can accurately position the intelligent inspection robot in various inspection environments, effectively improves the inspection efficiency, improves the intelligent degree and the flexibility of motion planning of the inspection robot, improves the comprehensiveness of monitoring, and can adapt to the inspection work in complex environments.

[0116] Embodiment four

[0117] Figure 6 A structural schematic diagram of an electronic device 10 that can be used to implement embodiments of the application is shown. The electronic device is intended to represent various forms of digital computers, such as laptops, desktops, tablets, personal digital assistants, servers, blade servers, mainframes, and other appropriate computers. The electronic device can also represent various forms of mobile devices, such as personal digital assistants, cellular telephones, smartphones, wearable devices (e.g., headsets, glasses, watches, etc.), and other similar computing devices. The components shown here, their connections and relationships, and their functions, are meant to be examples only, and are not intended to limit the implementations of the applications described and / or claimed in this document.

[0118] As Figure 6As shown, the electronic device 10 includes at least one processor 11, and a memory, such as a read-only memory (ROM) 12, a random access memory (RAM) 13, etc., which is communicatively connected to the at least one processor 11, wherein the memory stores a computer program that can be executed by the at least one processor, and the processor 11 can perform various appropriate actions and processes according to the computer program stored in the read-only memory (ROM) 12 or loaded from the storage unit 18 into the random access memory (RAM) 13. In the RAM 13, various programs and data required for the operation of the electronic device 10 can also be stored. The processor 11, the ROM 12, and the RAM 13 are connected to each other through a bus 14. An input / output (I / O) interface 15 is also connected to the bus 14.

[0119] A plurality of components in the electronic device 10 are connected to the I / O interface 15, including an input unit 16, such as a keyboard, a mouse, etc., an output unit 17, such as various types of displays, a loudspeaker, etc., a storage unit 18, such as a magnetic disk, an optical disk, etc., and a communication unit 19, such as a network card, a modem, a wireless communication transceiver, etc. The communication unit 19 allows the electronic device 10 to exchange information / data with other devices through a computer network, such as the Internet, and / or various telecommunication networks.

[0120] The processor 11 can be various general-purpose and / or special-purpose processing components with processing and computing capabilities. Some examples of the processor 11 include, but are not limited to, a central processing unit (CPU), a graphics processing unit (GPU), various special-purpose artificial intelligence (AI) computing chips, various processors running machine learning model algorithms, a digital signal processor (DSP), and any appropriate processor, controller, microcontroller, etc. The processor 11 performs various methods and processes described above, such as the intelligent patrol method as described in Embodiment Three of the present application. That is:

[0121] Determine the current position coordinates of the robot according to the satellite signals respectively received by the rover station and the reference station through the GNSS module;

[0122] Obtain the motion information of the robot through the IMU module;

[0123] Generate the current navigation data of the robot according to the current position coordinates, the motion information, the preset initial trajectory, and the obstacle information returned by the back-end server through the industrial computer, and control the motion mechanism of the robot according to the current navigation data to realize automatic cruising.

[0124] In some embodiments, the intelligent patrol method can be implemented as a computer program tangibly embodied in a computer readable storage medium, e.g., storage unit 18. In some embodiments, parts or all of the computer program can be loaded and / or installed onto electronic device 10 via, e.g., ROM 12 and / or communication unit 19. When the computer program is loaded onto RAM 13 and executed by processor 11, one or more steps of the intelligent patrol method described above can be performed. Alternatively, in other embodiments, processor 11 can be configured to perform the intelligent patrol method by other means, e.g., with the aid of firmware.

[0125] Various implementations of the systems and techniques described above can be realized in digital electronic circuitry, integrated circuitry, specially designed application specific integrated circuits (ASICs), field programmable gate arrays (FPGAs), computer hardware, firmware, software, and / or combinations thereof. These various implementations can include implementation in one or more computer programs that are executable and / or interpretable on a programmable system including at least one programmable processor, which can be special or general purpose, coupled to receive data and instructions from, and to transmit data and instructions to, a storage system, at least one input device, and at least one output device.

[0126] Computer programs used to implement the methods of the application can be written in any combination of one or more programming languages. These computer programs can be provided to a processor of a general purpose computer, special purpose computer, or other programmable data processing apparatus to produce a machine, such that the computer program, when executed by the processor of the machine, implements the functions / acts specified in the flowcharts and / or block diagrams. The computer program can be executed entirely on a machine, partially on a machine and partially on a remote machine or entirely on a remote machine or server.

[0127] In the context of the present application, a computer-readable storage medium can be a tangible medium that can contain or store a computer program for use by or in connection with an instruction execution system, apparatus, or device. A computer-readable storage medium can include, but is not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any suitable combination of the foregoing. Alternatively, a computer-readable storage medium can be a machine-readable signal medium. More specific examples of a machine-readable storage medium will include one or more lines of a program of instructions in a transitory signal, a portable computer diskette, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or Flash memory), an optical fiber, a portable compact disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing.

[0128] To provide for interaction with a user, the systems and techniques described here can be implemented on an electronic device having a display device (e.g., a CRT (cathode ray tube) or LCD (liquid crystal display) monitor) for displaying information to the user and a keyboard and a pointing device (e.g., a mouse or a trackball) by which the user can provide input to the electronic device. Other kinds of devices can be used to provide for interaction with a user as well; for example, feedback provided to the user can be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user can be received in any form, including acoustic, speech, or tactile input.

[0129] The systems and techniques described here can be implemented in a computing system that includes a back end component (e.g., as a data server), or that includes a middleware component (e.g., an application server), or that includes a front end component (e.g., a user computer having a graphical user interface or a Web browser through which a user can interact with an implementation of the systems and techniques described here), or any combination of such back end, middleware, or front end components. The components of the system can be interconnected by any form or medium of digital data communication (e.g., a communication network). Examples of communication networks include a local area network (LAN), a wide area network (WAN), a blockchain network, and the Internet.

[0130] The computing system can include clients and servers. A client and server are generally remote from each other and typically interact through a communication network. The relationship of client and server arises by virtue of computer programs running on the respective computers and having a client-server relationship to each other. The server can be a cloud server, also known as a cloud computing server or cloud host, which is a host product in the cloud computing service system, to solve the defects of large management difficulty and weak business scalability in traditional physical host and VPS service.

[0131] It should be understood that the various forms of flow shown above can be reordered, added to, or have steps deleted. For example, the steps described in the present application can be performed in parallel, in series, or in a different order, as long as the desired results of the technical solutions of the present application can be achieved, which are not limited herein.

[0132] The above detailed description does not constitute a limitation on the protection scope of the present application. Those skilled in the art should understand that various modifications, combinations, sub-combinations and substitutions can be made according to design requirements and other factors. Any modifications, equivalent replacements and improvements made within the spirit and principles of the present application shall be included in the protection scope of the present application.

Claims

1. An intelligent inspection robot, characterized in that: Including global navigation satellite system GNSS module, inertial measurement unit IMU module and industrial computer; The GNSS module is used to determine the current position coordinates of the robot based on the satellite signals received by the rover station and the base station respectively; The IMU module is used to obtain the motion information of the robot; The industrial computer is used to generate the robot's current navigation data based on the current position coordinates, the motion information, the preset initial trajectory and the obstacle information returned by the back-end server, and control the robot's motion mechanism according to the current navigation data to achieve automatic cruising.

2. The intelligent inspection robot according to claim 1, characterized in that: It also includes a thermal imaging dual-spectral gimbal camera, a 3D camera module, and a lidar module; The thermal imaging dual-spectrum pan-tilt camera is used to capture thermal infrared images in the inspection environment under different spectral ranges; The 3D camera module is used to obtain three-dimensional point cloud data in the inspection environment; The laser radar module is used to obtain laser radar point cloud data in the inspection environment; The industrial computer includes a first server, which is used to collect information collected by the GNSS module, IMU module, thermal imaging dual-spectrum pan-tilt camera, 3D camera module and lidar module, and send the information to the back-end server in real time, so that the back-end server can determine the obstacle information in the inspection environment and update the map based on the information sent by the industrial computer.

3. The intelligent inspection robot according to claim 1, characterized in that: The GNSS module is specifically used for: Determine a carrier phase and a pseudorange at a current position according to satellite signals received by the mobile station, and calculate a first position coordinate according to the carrier phase and the pseudorange; A positioning error is determined according to the satellite signal received by the reference station, and the first position coordinate is corrected according to the positioning error to obtain the current position coordinate of the robot.

4. The intelligent inspection robot according to claim 2, characterized in that: The industrial computer also includes a robot operating system ROS unit; The first server is further configured to obtain obstacle information sent by the backend server and send the obstacle information to the ROS unit; The ROS unit is used to: The Kalman filter method is used to fuse the current position coordinates and motion information, and the first navigation data of the robot is obtained based on the data fusion result and the preset initial trajectory; According to the obstacle information returned by the back-end server, the first navigation data is corrected to generate the current navigation data of the robot, and the motion mechanism in the intelligent inspection robot is controlled according to the current navigation data; wherein, the motion mechanism is a four-wheel omnidirectional drive system.

5. The intelligent inspection robot according to claim 4, characterized in that: The ROS unit is also used to: Performing abnormal state detection on the target obstacle according to the obstacle information; When it is determined that the target obstacle is in an abnormal state, an alarm message matching the target obstacle is generated.

6. The intelligent inspection robot according to claim 2, characterized in that: The front end of the intelligent inspection robot also includes a lifting platform; the lifting platform is equipped with the thermal imaging dual-spectrum pan-tilt camera; The thermal imaging dual-spectrum pan-tilt camera includes a temperature measuring thermal imager, a full-HD visible light camera, and a 360-degree unlimited outdoor pan-tilt camera.

7. The intelligent inspection robot according to claim 4, characterized in that: It also includes a power module for powering the intelligent inspection robot; The ROS unit is also used to: Record the inspection trajectory of the intelligent inspection robot during the current inspection process and monitor the remaining power of the power module in real time; When it is determined based on the remaining power of the power module that the robot meets the return charging condition, the robot is controlled to return to charge along the inspection track.

8. An intelligent inspection method, performed by the intelligent inspection robot according to any one of claims 1 to 7, characterized in that: include: The GNSS module determines the robot's current position coordinates based on the satellite signals received by the rover and base stations respectively; Obtain the robot's motion information through the IMU module; Through the industrial computer, the robot's current navigation data is generated according to the current position coordinates, the motion information, the preset initial trajectory and the obstacle information returned by the back-end server, and the robot's motion mechanism is controlled according to the current navigation data to achieve automatic cruising.

9. An electronic device, characterized in that: The electronic device comprises: at least one processor; and a memory communicatively connected to the at least one processor; wherein, The memory stores a computer program that can be executed by the at least one processor, and the computer program is executed by the at least one processor so that the at least one processor can execute the intelligent inspection method described in claim 8 of the present invention.

10. A computer-readable storage medium, characterized in that The computer-readable storage medium stores computer instructions, and the computer instructions are used to enable a processor to implement the intelligent inspection method of the many-core system according to claim 8 when executed.

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