Rail transit intelligent inspection robot, control method and device and storage medium

Abstract

The invention relates to a rail transit intelligent inspection robot, a control method and device and a storage medium. The method comprises the steps that a preset inspection task is acquired; controlling an environment sensing system to collect ground environment parameters; determining a target mobile platform according to the ground environment parameters; under the condition that the detachable mobile platform connected with the chassis driving system is a target mobile platform, the chassis driving system is controlled to drive the target mobile platform to move according to the inspection route according to a mobile control algorithm, and the environment sensing system is controlled to collect target detection parameters of a to-be-detected target according to the inspection control algorithm and perform fault detection; controlling an inspection execution system to execute an auxiliary task according to a mobile control algorithm or an inspection control algorithm; through modular design and intelligent perception and interaction, dynamic replacement of the mobile platform is realized in combination with the ground environment, so that a single robot can perform adaptive inspection in different ground environments, and the detection efficiency, reliability and multifunctionality of the inspection robot are remarkably improved.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of rail transit detection equipment, and in particular to a rail transit intelligent inspection robot, a control method and device, and a storage medium. BACKGROUND

[0002] With the rapid development of the motor train industry, the safety operation requirements for motor train tracks are becoming higher and higher. The motor train track is exposed to the natural environment for a long time and is affected by various complex environmental factors such as high and low temperature, rain and snow, wind and sand. The track surface may have problems such as wear, cracks, depressions, and the presence of gravel, which need to be regularly inspected to ensure the safe driving of the motor train.

[0003] At present, most of the existing motor train track inspection equipment adopts a single walking mode, such as a wheel type or a track type. However, in different ground environments, the adaptability of the single walking mode is poor. SUMMARY

[0004] Therefore, it is necessary to provide a rail transit intelligent inspection robot, a control method and device, and a storage medium that can switch the moving platform based on the ground environment, share the chassis and three quickly replaceable moving platforms (wheel type, track type, and bionic type), combine the mechanical arm actuator, the environment perception system, and the operation control unit, and realize efficient self-adaptive inspection, target grabbing, autonomous navigation and obstacle avoidance of different terrains, and real-time interaction with the diagnostic center.

[0005] In a first aspect, the present application provides a control method of a rail transit intelligent inspection robot. The rail transit intelligent inspection robot includes an operation control system, an environment perception system, a chassis driving system, an inspection execution system, a shared chassis, and a plurality of detachable moving platforms. The chassis driving system is in transmission connection with the detachable moving platforms. The method includes: acquiring a preset inspection task; wherein the preset inspection task includes an inspection route, a target to be detected, and a target detection parameter; controlling the environment perception system to collect ground environment parameters; determining a target moving platform according to the ground environment parameters; the target moving platform includes any one of a wheel type moving platform, a track type moving platform, and a bionic type moving platform; In the case that the detachable mobile platform connected to the chassis driving system is the target mobile platform, load the mobile control algorithm and the inspection control algorithm corresponding to the target mobile platform, and control the chassis driving system to drive the target mobile platform to move according to the inspection route according to the mobile control algorithm, control the environment perception system to collect the target detection parameter of the target to be detected and perform fault detection according to the inspection control algorithm, and control the inspection execution system to perform auxiliary tasks according to the mobile control algorithm or the inspection control algorithm; In the case that the detachable mobile platform connected to the chassis driving system is not the target mobile platform, control the chassis driving system to stop, generate platform replacement prompt information and upload it to the diagnosis center, until the detachable mobile platform connected to the chassis driving system is replaced by the target mobile platform.

[0006] In one of the embodiments, the environment perception system includes at least one of a visual perception component, an infrared perception component, an ultrasonic perception component, a laser perception component, and an inertial measurement component; the ground environment parameter includes ground texture, ground material, ground fluctuation standard deviation, and spatial size data; and the target mobile platform is determined according to the ground environment parameter, including: If the ground environment belongs to a first road surface condition according to the ground environment parameter, the target mobile platform is determined to be a wheeled mobile platform; and the first road surface condition is a flat road surface. If the ground environment belongs to a second road surface condition according to the ground environment parameter, the target mobile platform is determined to be a tracked mobile platform; and the second road surface condition is a train track or a gravel road surface. If the ground environment belongs to a third road surface condition according to the ground environment parameter, the target mobile platform is determined to be a bionic mobile platform; and the third road surface condition is a narrow pipeline.

[0007] In one of the embodiments, the chassis driving system is controlled to drive the target mobile platform to move according to the inspection route according to the mobile control algorithm, including: In the case that the target mobile platform is a wheeled mobile platform, the chassis driving system is controlled to drive the wheeled mobile platform to move according to the inspection route according to a first mobile control algorithm; and the first mobile control algorithm includes a first obstacle avoidance strategy. In the case that the target mobile platform is a tracked mobile platform, the chassis driving system is controlled to drive the tracked mobile platform to move according to the inspection route according to a second mobile control algorithm; and the second mobile control algorithm includes a second obstacle avoidance strategy. In the case where the target mobile platform is a bionic mobile platform, the chassis driving system is controlled to drive the wheeled mobile platform to move along the inspection route according to a third mobile control algorithm; the third mobile control algorithm comprises a third obstacle avoidance strategy.

[0008] In one of the embodiments, the method further comprises: In the case where the environment perception system detects a change in the ground environment, a change in the preset inspection task, or a change in the robot self-checking state, a platform replacement instruction is generated; The target mobile platform is re-determined according to the platform replacement instruction.

[0009] In one of the embodiments, the inspection execution system comprises a three-axis mechanical arm, a base of the three-axis mechanical arm is fixedly installed at a front end of the shared chassis, and a grabbing mechanism is arranged at an end of the three-axis mechanical arm, the grabbing mechanism is used to assist in removing track obstacles or grabbing a target to be detected; The control of the inspection execution system to perform the auxiliary task according to the mobile control algorithm or the inspection control algorithm comprises: The three-axis mechanical arm is controlled to assist in removing track obstacles according to the mobile control algorithm; The three-axis mechanical arm is controlled to grab the target to be detected according to the inspection control algorithm.

[0010] In one of the embodiments, the working mode of the inspection execution system comprises a remote instruction control mode, a local autonomous control mode, and a preset trajectory control mode; The method further comprises: In the case where the grabbing control instruction issued by the diagnosis center is received, the working mode of the inspection execution system is determined to be the remote instruction control mode, and the auxiliary task is performed according to the grabbing control instruction; the grabbing control instruction comprises grabbing coordinates, a clamping jaw force, and a movement speed; In the case where the communication with the diagnosis center is interrupted or a local control instruction is triggered, the working mode of the inspection execution system is determined to be the local autonomous control mode, a real-time grabbing trajectory is autonomously planned based on real-time environment data collected by the environment perception system, and the auxiliary task is performed according to the real-time grabbing trajectory; In the case where a standard task on the inspection route is triggered, the working mode of the inspection execution system is determined to be the preset trajectory control mode, a preset grabbing trajectory corresponding to the standard task is loaded, and the auxiliary task is performed according to the preset grabbing trajectory.

[0011] In one of the embodiments, the fault types of the target to be detected comprise a first type of fault and a second type of fault; The method further comprises: If a first type of fault is detected and it is determined from the ground environment parameters that the ground environment does not belong to the third road surface condition, the target detection parameters will be uploaded to the diagnostic center in real time. If a second type of fault is detected and the ground environment is determined to be a third road surface condition based on the ground environment parameters, the target detection parameters are stored in the local memory. After the ground environment changes to a first road surface condition or a second road surface condition, the target detection parameters in the local memory are uploaded to the diagnostic center. If a second type of fault is detected, a fault location movement trajectory, an alarm command, and a location upload command are generated in real time. Based on the fault location movement trajectory, the chassis drive system is controlled to drive the target mobile platform to the fault location. An audible and visual alarm is triggered based on the alarm command, and the fault location, fault type, and image data are uploaded to the diagnostic center based on the location upload command.

[0012] Secondly, this application also provides a control device for an intelligent rail transit inspection robot. The intelligent rail transit inspection robot includes an operation control system, an environmental perception system, a chassis drive system, an inspection execution system, a shared chassis, and multiple detachable mobile platforms, wherein the chassis drive system is transmissionally connected to the detachable mobile platforms; the device includes: The task acquisition module is used to acquire preset inspection tasks; wherein, the preset inspection tasks include inspection routes, targets to be inspected, and target detection parameters; The environmental sensing module is used to control the environmental sensing system to collect ground environmental parameters; The platform determination module is used to determine the target mobile platform based on the ground environment parameters; the target mobile platform includes any one of wheeled mobile platforms, tracked mobile platforms, and biomimetic mobile platforms. The inspection execution module is used to, when the detachable mobile platform connected to the chassis drive system is the target mobile platform, load the corresponding movement control algorithm and inspection control algorithm for the target mobile platform, and control the chassis drive system to drive the target mobile platform to move according to the inspection route according to the movement control algorithm; control the environmental perception system to collect target detection parameters of the target to be detected and perform fault detection according to the inspection control algorithm; and control the inspection execution system to perform auxiliary tasks according to the movement control algorithm or the inspection control algorithm. If the detachable mobile platform connected to the chassis drive system is not the target mobile platform, the module controls the chassis drive system to stop, generates a platform replacement prompt message and uploads it to the diagnostic center, until the detachable mobile platform connected to the chassis drive system is replaced with the target mobile platform.

[0013] Thirdly, this application also provides an intelligent inspection robot for rail transit, comprising: an operation control system, an environmental perception system, a chassis drive system, an inspection execution system, a common chassis, and multiple detachable mobile platforms, wherein the operation control system, the environmental perception system, the chassis drive system, and the inspection execution system are all mounted on the common chassis; the operation control system is connected to the environmental perception system, the chassis drive system, and the inspection execution system respectively, and the chassis drive system is drive-connected to the detachable mobile platforms; The operation control system is used to execute the steps of the control method for the intelligent inspection robot of rail transit described in the first aspect.

[0014] Fourthly, this application also provides a computer-readable storage medium having a computer program stored thereon, wherein the computer program, when executed by a processor, implements the steps of the control method for the intelligent inspection robot for rail transit described in the first aspect.

[0015] In summary, this application proposes an intelligent inspection robot for rail transit, a control method, a device, and a storage medium. The method includes: acquiring a preset inspection task; controlling an environmental perception system to collect ground environmental parameters; determining a target mobile platform based on the ground environmental parameters; when the detachable mobile platform connected to the chassis drive system is the target mobile platform, controlling the chassis drive system to drive the target mobile platform to move along the inspection route according to a motion control algorithm; controlling the environmental perception system to collect target detection parameters of the target to be inspected and perform fault detection according to an inspection control algorithm; and controlling the inspection execution system to perform auxiliary tasks according to a motion control algorithm or an inspection control algorithm. This application, through modular design and intelligent perception and interaction, combined with the ground environment, enables the mobile platform to be dynamically replaced, allowing a single robot to perform adaptive inspections in different ground environments, significantly improving the inspection efficiency, reliability, and multifunctionality of the inspection robot. Attached Figure Description

[0016] Figure 1 This is a schematic diagram of the structure of an intelligent inspection robot for rail transit in one embodiment; Figure 2 This is a schematic diagram of the structure of a rail transit intelligent inspection robot equipped with a wheeled mobile platform in one embodiment; Figure 3 This is a schematic diagram of the universal coupling of a wheeled mobile platform in one embodiment; Figure 4 This is a schematic diagram of the structure of an intelligent inspection robot for rail transit equipped with a tracked mobile platform in one embodiment. Figure 5 This is a schematic diagram of the structure of an intelligent rail transit inspection robot equipped with a biomimetic mobile platform in one embodiment. Figure 6 This is a schematic diagram of the bionic foot of a bionic mobile platform in one embodiment. Figure 7 This is a flowchart illustrating the control method of an intelligent inspection robot for rail transit in one embodiment; Figure 8 This is a flowchart illustrating the control method for an intelligent inspection robot for rail transit in another embodiment; Figure 9 This is a flowchart illustrating the process of a smart rail transit inspection robot performing a complete inspection task in one embodiment. Figure 10 This is a structural block diagram of the control device for an intelligent inspection robot for rail transit in one embodiment. Figure 11 This is an internal structural diagram of a computer device in one embodiment.

[0017] Summary of attached image labels: 1-Shared chassis, 2-Three-axis robotic arm, 3-High-definition camera, 4-Infrared thermal imager, 5-Ultrasonic detector, 6-LiDAR, 7-IMU, 8-Flange, 9-Drive motor shaft, 201-Bionic foot, 301-Wheel, 302-Universal coupling, 401-Track wheel, 402-Track body, 403-Auxiliary wheel, 404-Connecting rod. Detailed Implementation

[0018] To make the objectives, technical solutions, and advantages of this application clearer, the following detailed description is provided in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative and not intended to limit the scope of this application.

[0019] In related technologies, most high-speed rail inspection equipment adopts a single mode of locomotion, such as wheeled or tracked. However, a single locomotion mode has poor adaptability to different ground environments. For example, wheeled inspection equipment is efficient on flat surfaces, but it is prone to slipping when encountering train tracks and gravel surfaces. Tracked inspection equipment has good traversal on gravel surfaces, but its energy consumption is high on flat surfaces. Bionic devices are suitable for overcoming obstacles in narrow pipes, but their versatility is poor. Equipping different equipment for different surface environments (flat surfaces, train tracks / gravel surfaces, narrow pipes) would increase inspection costs and maintenance burden. At the same time, most rail inspection robots at present only have a single inspection function and lack environmental perception, actuators, and efficient interaction capabilities.

[0020] Therefore, there is an urgent need to develop an inspection robot that can flexibly switch mobile platforms, integrate actuators, intelligently sense and efficiently interact.

[0021] In one embodiment, such as Figure 1As shown, a smart inspection robot for rail transit based on a switchable mobile platform in a ground environment is provided, including: an on-board control unit (OCU), an environmental perception system, a chassis drive system, an inspection execution system, a common chassis 1, and multiple detachable mobile platforms. The on-board control unit, environmental perception system, chassis drive system, and inspection execution system are all mounted on the common chassis 1. The on-board control unit is connected to the environmental perception system, chassis drive system, and inspection execution system respectively, and the chassis drive system is drive-connected to the detachable mobile platforms.

[0022] In this embodiment, the detachable mobile platform includes at least three types of mobile platforms, such as wheeled mobile platforms, tracked mobile platforms, and biomimetic mobile platforms. The detachable platform is detachably connected to the common chassis 1. The common chassis 1 provided in this embodiment is equipped with a standard connection structure adapted to the three types of mobile platforms, including positioning holes and locking devices, for achieving precise positioning and stable connection.

[0023] In this embodiment, the chassis drive system includes a drive motor, which is fixedly mounted on a common chassis 1. The position of the drive motor shaft is fixed, and the mobile platform can be quickly connected and replaced with the chassis and drive motor shaft 9 through manual operation. The drive motor shaft 9 is provided with a standardized connection interface, and all three types of mobile platforms are provided with matching transmission connectors. For example, the output end of the drive motor shaft 9 is provided with a flange-type standard drive interface, which includes locating pin holes and bolt holes evenly distributed along the circumference. The wheeled mobile platform, tracked mobile platform, and bionic mobile platform are all provided with a driven flange 8 (driven interface) that matches the flange-type standard drive interface. The driven flange 8 (driven interface) is provided with a locating pin groove and a connecting bolt hole. The locating pin groove of the driven interface is clearance-fitted with the locating pin hole of the standard drive interface, and the connecting bolt hole of the driven interface is coaxially arranged with the bolt hole of the standard drive interface. The detachable connection with the drive motor shaft 9 is achieved by bolt tightening.

[0024] In this embodiment, as Figure 2 and Figure 3 As shown, the wheeled mobile platform also includes a universal coupling 302 and wheel sets 301. The universal coupling 302 is connected to the drive motor shaft 9 via a driven interface. The universal coupling 302 rotates synchronously with the drive motor shaft 9 and transmits the rotation synchronously to the wheels 301. All wheels 301 of the wheel set 301 are drive wheels and rotate synchronously with the universal coupling 302. They can be made of high-wear-resistant rubber and are suitable for high-speed cruising on flat roads. In a specific embodiment, the wheel 301 is made of high-wear-resistant rubber, which has good elasticity and wear resistance. The universal coupling 302 can transmit power while improving the robot's shared chassis 1 without changing the position of the drive shaft.

[0025] like Figure 4 As shown, the tracked mobile platform also includes track wheels 401, auxiliary wheels 403, track bodies 402 with anti-slip treads, and connecting rods 404. Track wheels 401 are connected to the drive motor shaft 9 via a driven interface. Connecting rods 404 connect the drive motor shaft 9 in the middle position of the shared chassis 1 to the auxiliary wheels 403. The auxiliary wheels 403 can be raised / lowered by rotating the drive motor in the middle position to overcome obstacles. In a specific embodiment, the tracks are made of high-strength, wear-resistant material, providing strong grip and passability. Furthermore, the front wheels can be raised by rotating the connecting rods 404 to overcome obstacles.

[0026] like Figure 5 and Figure 6 As shown, the biomimetic mobile platform includes a "C"-shaped biomimetic foot 201. The contact surface of the biomimetic foot 201 has protrusions and is connected to the drive motor shaft 9 via a driven interface. It adapts to narrow pipe environments through rolling motion. In a specific embodiment, the biomimetic mobile platform is suitable for narrow pipes (such as inside pipes or narrow spaces). The biomimetic foot 201 adopts a C-shaped structure, and the contact surface between the foot 201 and the ground has protrusions, which can increase grip. The robot moves forward by rolling with the C-shaped claw, and can flexibly cross obstacles.

[0027] It should be noted that the bionic foot 201 of the bionic mobile platform can also be replaced with other shapes of bionic feet 201 according to the needs of actual application scenarios to adapt to different types of narrow space scenarios. Furthermore, the materials of the aforementioned mobile platform can be adaptively replaced according to the needs of actual application scenarios.

[0028] In this embodiment, the environmental perception system integrates multiple inspection sensor components, including visual perception components, infrared perception components, ultrasonic perception components, laser perception components, and inertial measurement components. Furthermore, the environmental perception system incorporates Simultaneous Localization and Mapping (SLAM) technology, enabling it to autonomously plan movement paths and execute obstacle avoidance strategies.

[0029] In this embodiment, the visual sensing component can be a high-definition camera 3, the infrared sensing component can be an infrared thermal imager 4, the ultrasonic sensing component can be an ultrasonic detector 5, the laser sensing component can be a lidar 6, and the inertial measurement component can be an inertial measurement unit (IMU). Specifically, the high-definition camera 3, the infrared thermal imager 4, the ultrasonic detector 5, the lidar 6, and the IMU 7 can be configured as follows: Figure 1As shown, the sensors are installed on a common chassis 1. Each inspection sensor component sends data to the operation control system in real time via the CAN bus, or directly uploads data to the cloud diagnostic system to achieve multi-sensor (vision, infrared, ultrasound, laser) information fusion, so as to build an environmental map and accurately locate the device.

[0030] In this embodiment, the sensor components built into the shared chassis 1 can also be expanded into an intelligent navigation controller. This controller automatically loads control algorithms based on the current mobile platform type and environmental perception data. For example, it loads a first mobile control algorithm from a wheeled algorithm library to adapt to cruising on flat roads and plan obstacle avoidance paths. It loads a second mobile control algorithm from a tracked algorithm library to adapt to anti-skid cruising on train tracks / gravel roads and dynamically execute obstacle avoidance strategies. It loads a third mobile control algorithm from a biomimetic algorithm library to adapt to obstacle crossing in narrow pipes and run navigation algorithms in confined spaces. The operation control system provided in this embodiment can optimize the path in real time based on sensor fusion data, and automatically adjust the movement of the mobile platform or control the inspection execution system actions when encountering obstacles.

[0031] In this embodiment, the inspection execution system includes a three-axis robotic arm 2. The three-axis robotic arm 2 is mounted on a common chassis 1, with the robotic arm base fixed to the front end of the chassis. The end of the robotic arm is equipped with a gripping mechanism (gripper). The gripper adopts an adjustable design to support the gripping of track debris, samples, or small obstacles.

[0032] The Operation Control Unit (OCU) is integrated into the control module of the robot's shared chassis 1. It serves as a relay processing unit for local robot control and remote commands from the diagnostic center, acting as the core hub for interaction between the robot and the diagnostic center. In this embodiment, the OCU can employ an industrial-grade embedded processor, supporting multi-threaded processing to ensure real-time data transmission and command response. Its core functions include receiving commands from the diagnostic center and parsing the protocol (compatible with the CAN bus communication protocol); uploading pre-processed sensor data and robot status information (such as mobile platform type, robotic arm posture, energy consumption data, etc.) to the diagnostic center; and implementing the switching logic between local and remote control (default is remote control, switchable to local manual control in emergencies).

[0033] In summary, this embodiment provides an intelligent inspection robot for rail transit, employing a modular mobile platform design. Three platforms share a common chassis and a fixed-position drive motor shaft, allowing for rapid manual replacement and enabling the robot to flexibly select the appropriate movement mode based on the ground environment. The three-axis robotic arm actuator supports multi-functional operations, such as grasping obstacles or samples, enhancing the robot's practicality. The environmental perception system enables intelligent navigation and high-precision detection. The integration of the operation control unit strengthens the "perception-analysis-decision-execution" closed loop between the robot and the diagnostic center. Real-time interaction and encrypted transmission via 5G ensure the efficiency and security of remote operation and maintenance. The wheeled mobile platform travels quickly and energy-efficiently on flat surfaces, the tracked mobile platform traverses stably on train tracks and gravel roads, and the biomimetic mobile platform flexibly overcomes obstacles in narrow pipes. Combined with the remote interaction capabilities of the intelligent control and operation control unit, inspection efficiency, reliability, and adaptability are significantly improved. The elimination of the need for separate equipment for different environments reduces investment and maintenance costs, while sensor fusion technology and the data processing capabilities of the operation control unit ensure the comprehensiveness and accuracy of inspection data.

[0034] In one embodiment, such as Figure 7 As shown, a control method for an intelligent inspection robot for rail transit is provided, which is then applied to... Figure 1 Taking the operation and control system of the intelligent inspection robot for rail transit as an example, the following steps are included: S701, obtain preset inspection tasks.

[0035] In this embodiment, the preset inspection task includes the inspection route, the target to be inspected, and the target detection parameters. In a specific embodiment, the target to be inspected includes ground cracks, equipment appearance damage, foreign objects, outdoor high-speed rail tracks, gravel track beds, and reinforced concrete drainage pipes under the tracks, etc. The target detection parameters include, for example, track gauge deviation thresholds and crack width thresholds.

[0036] In this embodiment, the preset inspection tasks can be issued by the cloud diagnostic center or allocated by the inspection robot control center. This embodiment does not limit the process of issuing preset inspection tasks. According to the needs of the actual application scenario, the corresponding inspection tasks can be loaded into the inspection robot to plan the inspection route, inspection target and inspection parameters.

[0037] S702 controls the environmental sensing system to collect ground environmental parameters.

[0038] In this embodiment, after the inspection task begins, the operation control unit collects parameters such as ground texture, ground material, ground undulation standard deviation and spatial size data through multiple sensor components of the environmental perception system as ground environmental parameters.

[0039] For example, by activating a LiDAR and IMU, 3D point cloud data and attitude data of the ground can be collected, and the standard deviation of ground undulation can be calculated. Activating a high-definition camera can capture ground texture images, and image recognition algorithms can distinguish between flat road surface textures (such as cement / asphalt textures), gravel textures, track textures, and pipe inner wall textures. Activating an ultrasonic detector can collect spatial distance data to determine whether the environment is a narrow pipe; if the spatial diameter is ≤50cm, the ground environment is determined to be a narrow pipe environment. It should be noted that the judgment thresholds for different ground environments can be determined according to the needs of the actual application scenario.

[0040] S703 determines the target mobile platform based on ground environmental parameters. The target mobile platform includes any one of wheeled, tracked, and biomimetic mobile platforms.

[0041] In this embodiment, the type of ground environment in which the inspection robot is located can be determined by judging the ground environment parameters collected in the aforementioned steps and the parameter thresholds corresponding to different types of ground environments. Alternatively, the type of ground environment in which the inspection robot is located can be determined directly by combining image data collected by the environmental perception system with image analysis algorithms.

[0042] In one embodiment, the environmental perception system includes at least one of a visual perception component, an infrared perception component, an ultrasonic perception component, a laser perception component, and an inertial measurement component. Ground environmental parameters include ground texture, ground material, ground relief standard deviation, and spatial dimension data. Determining the target mobile platform based on the ground environmental parameters includes: If the ground environment parameters determine that the ground environment falls under the first road surface condition, then the target mobile platform is identified as a wheeled mobile platform. The first road surface condition is a flat road surface.

[0043] If the ground environment parameters determine that the ground environment falls under the second road surface condition, then the target mobile platform is identified as a tracked mobile platform. The second road surface condition is either train track or gravel road surface.

[0044] If the ground environment parameters determine that it falls under the third road surface condition, then the target mobile platform is identified as a biomimetic mobile platform. The third road surface condition is a narrow pipe.

[0045] For example, if the standard deviation of undulation is less than or equal to a preset threshold, and the road surface is free of gravel or pipe structures, then the ground environment is determined to be a flat surface, and the target mobile platform can be identified as a wheeled mobile platform. If the standard deviation of undulation is greater than the preset threshold, and the road surface has sleeper / gravel textures, then the ground environment is determined to be a train track or gravel road surface, and the target mobile platform can be identified as a tracked mobile platform. If the spatial diameter is less than or equal to a preset size, and the road surface texture has inner wall textures, then the ground environment is determined to be a narrow pipe, and the target mobile platform can be identified as a biomimetic mobile platform.

[0046] S704: When the detachable mobile platform connected to the chassis drive system is the target mobile platform, load the corresponding mobile control algorithm and inspection control algorithm for the target mobile platform, and control the chassis drive system to drive the target mobile platform to move according to the inspection route according to the mobile control algorithm. Control the environmental perception system to collect the target detection parameters of the target to be detected and perform fault detection according to the inspection control algorithm. Control the inspection execution system to perform auxiliary tasks according to the mobile control algorithm or the inspection control algorithm.

[0047] In this embodiment, the motion control algorithm can be called from the autonomous planning and obstacle avoidance strategy library built into the operation control system. This library includes wheeled algorithm libraries, tracked algorithm libraries, and biomimetic algorithm libraries. The inspection control algorithm corresponds to specific preset inspection tasks in actual application scenarios, including sensor sampling frequency, detection parameter thresholds, inspection routes, and inspection targets. Auxiliary tasks include grasping obstacles or samples to be inspected.

[0048] In this embodiment, after the preset inspection task begins execution, it is first determined whether the detachable mobile platform connected to the chassis drive system is the target mobile platform. If the detachable mobile platform connected to the chassis drive system is the target mobile platform, the corresponding movement control algorithm and inspection control algorithm for the target mobile platform are loaded. The movement control algorithm includes a first movement control algorithm, a second movement control algorithm, and a third movement control algorithm. The inspection control algorithm includes a first inspection control algorithm, a second inspection control algorithm, and a third inspection control algorithm.

[0049] When the target mobile platform is a wheeled mobile platform, the chassis drive system is controlled according to the first motion control algorithm to drive the wheeled mobile platform to move along the inspection route. The environmental perception system is controlled according to the first inspection control algorithm to collect target detection parameters of the target to be inspected and perform fault detection. The first motion control algorithm includes a first obstacle avoidance strategy.

[0050] When the target mobile platform is a tracked mobile platform, the chassis drive system is controlled according to the second motion control algorithm to drive the tracked mobile platform to move along the inspection route. The environmental perception system is controlled according to the second inspection control algorithm to collect target detection parameters of the target to be inspected and to perform fault detection. The second motion control algorithm includes a second obstacle avoidance strategy.

[0051] When the target mobile platform is a biomimetic mobile platform, the chassis drive system is controlled by the third motion control algorithm to drive the wheeled mobile platform to move along the inspection route. The environmental perception system is controlled by the third inspection control algorithm to collect target detection parameters and perform fault detection for the target to be inspected. The third motion control algorithm includes a third obstacle avoidance strategy.

[0052] For example, when the target mobile platform is a wheeled mobile platform, the first mobile control algorithm in the wheeled algorithm library is invoked to control the chassis drive system to drive the wheel assembly through the universal joint, traveling along the inspection route at a cruising speed of 3km / h±0.5km / h. Steering is achieved through differential control, and the IMU corrects the driving trajectory in real time. The first obstacle avoidance strategy can be to replan the movement path or control the three-axis robotic arm to remove obstacles.

[0053] When the target mobile platform is a tracked mobile platform, the second motion control algorithm in the tracked algorithm library is invoked to control the chassis drive system to drive the tracked wheels, traveling along the inspection route at a cruising speed of 1.5km / h±0.3km / h. When encountering obstacles, the linkage is controlled to raise the auxiliary wheels (the raising angle is fed back in real time by an angle sensor). The second obstacle avoidance strategy can be to control the linkage of the tracked mobile platform to raise the auxiliary wheels to move over obstacles or to control the three-axis robotic arm to remove obstacles.

[0054] When the target mobile platform is a biomimetic mobile platform, the third mobile control algorithm in the biomimetic algorithm library is invoked to control the chassis drive system to drive the "C"-shaped biomimetic foot, which moves along the inspection route through rolling motion. The IMU monitors the attitude in real time to avoid overturning. The third obstacle avoidance strategy can be to control the biomimetic foot to roll over obstacles or to control the three-axis robotic arm to remove obstacles.

[0055] S705, when the detachable mobile platform connected to the chassis drive system is not the target mobile platform, controls the chassis drive system to stop, generates a platform replacement prompt message and uploads it to the diagnostic center, until the detachable mobile platform connected to the chassis drive system is replaced with the target mobile platform. The platform replacement prompt message includes the inspection robot's positioning information.

[0056] In this embodiment, if it is determined that the detachable mobile platform connected to the chassis drive system is not the target mobile platform, the inspection robot is controlled to stay in place, and a platform replacement prompt message is generated and uploaded to the cloud diagnostic center to remind the staff to replace the detachable mobile platform at the designated location in time, so that the detachable mobile platform can conform to the target mobile platform and adapt to the road environment ahead of the inspection route, so as to continue to perform the inspection task.

[0057] In summary, this embodiment provides a control method for an inspection robot. It allows for rapid switching between three mobile platforms, covering multiple scenarios including flat roads, tracks, gravel areas, and pipelines, without requiring separate equipment. It integrates environmental perception, detection, robotic arm operation, and remote interaction functions to form a complete inspection closed loop. The wheeled platform's high-speed cruising improves inspection efficiency in flat areas, the tracked platform's high-precision detection ensures reliable track inspection, and the biomimetic platform flexibly overcomes obstacles, reducing overall procurement and maintenance costs. Furthermore, coordinated obstacle avoidance, fault alarms, and encrypted data transmission control steps ensure a safe and controllable inspection process.

[0058] In one embodiment, such as Figure 8 As shown, the control method for the intelligent inspection robot for rail transit also includes: S801 generates a platform replacement command when the environmental perception system detects changes in the ground environment, changes in the preset inspection task, or changes in the robot's self-inspection status. S802, redetermine the target mobile platform according to the platform replacement instruction.

[0059] In this embodiment, the replacement trigger conditions for the detachable mobile platform are mainly determined by the Environmental Perception System Cooperative Operation Control Unit (OCU) based on multi-source data, specifically including the following categories: First, changes in ground environmental characteristics trigger the system. High-definition cameras combined with image recognition algorithms analyze ground texture and material. For example, when a change in road surface texture from flat cement to irregular gravel is detected, a replacement command for the tracked or biomimetic platform is triggered. A 3D point cloud map constructed from LiDAR scanning data can also assist in the judgment. If the standard deviation of ground undulation exceeds a set threshold and persists for more than 5 seconds, it is determined to be an uneven road surface, and the platform switching process is initiated.

[0060] Second, changes in inspection task requirements trigger the diagnostic center to issue specific task instructions via the OCU based on the track facility maintenance plan or sudden malfunctions. For example, when switching from routine track surface inspection to track internal structure inspection, which requires navigating confined spaces, the OCU triggers a biomimetic platform replacement process. If rapid inspection of a large track area is required, the instruction is changed to a wheeled platform to improve movement speed.

[0061] Third, when the robot's self-check is triggered, if the motor current of the wheeled platform continuously exceeds the rated value by 20% and the vehicle speed is more than 30% lower than the set cruising speed for 10 seconds during operation, the OCU determines that the wheeled platform is obstructed on the current road surface and may need to switch to a tracked platform to improve its mobility. If the tracked platform experiences more than 5 track slippages per minute and the distance traveled is less than 50% of the expected distance, it should be considered for replacement with a platform more adaptable to the terrain.

[0062] It should be noted that changes in the ground environment, preset inspection tasks, or robot self-inspection status can all be customized according to the needs of the actual application scenario. Platform replacement instructions can include the specific type of the target mobile platform, or instruct the operation control unit to re-execute S702-S703.

[0063] In one embodiment, the inspection execution system includes a three-axis robotic arm. The base of the three-axis robotic arm is fixedly installed at the front end of a common chassis. The end of the three-axis robotic arm is provided with a gripping mechanism, which is used to assist in clearing obstacles on the track or gripping the target to be inspected.

[0064] The inspection execution system is controlled to perform auxiliary tasks based on the motion control algorithm or the inspection control algorithm, including: The three-axis robotic arm is controlled by a motion control algorithm to assist in clearing obstacles on the track.

[0065] The inspection control algorithm controls the three-axis robotic arm to grasp the target to be inspected.

[0066] In this embodiment, the auxiliary task of clearing obstacles from the track is typically triggered when the inspection robot is controlled to move along a specified path according to the motion control algorithm. The auxiliary task of grasping the target to be inspected is typically triggered when the inspection robot is controlled to identify faults in the target to be inspected according to the inspection control algorithm.

[0067] In this embodiment, the collaborative control of the three-axis robotic arm and the mobile platform is achieved through a closed-loop linkage between the intelligent navigation controller and the operation control unit (OCU) obtained by extending the environmental perception system built into the shared chassis. The core logic includes three levels: motion synchronization, motion planning, and obstacle avoidance coordination.

[0068] Motion synchronization is achieved by aligning the robotic arm and the mobile platform using the same time reference. For example, when the mobile platform executes a turning command, the OCU sends a "pause operation" signal to the robotic arm controller to prevent the robotic arm from deviating from its target position due to inertia during the turning process. Once the mobile platform has completed the turning (after the attitude has stabilized as reported by the IMU), the OCU then issues a command for the robotic arm to continue working.

[0069] The speed signal of the mobile platform is transmitted to the robotic arm controller in real time, serving as a reference for the robotic arm's movement speed. For example, when the mobile platform moves forward at 0.5 m / s, the extension / retraction speed of the robotic arm will automatically match to 0.3 m / s (a preset proportional coefficient) to ensure relative position stability when grasping the target.

[0070] Motion planning is based on a 3D environment map generated by the environmental perception system, which is simultaneously provided to the OCU to complete the path planning for the mobile platform and the trajectory planning for the robotic arm. For example, when an obstacle (such as gravel) is detected beside the track, the system first plans the stopping position of the mobile platform, and then calculates the grasping trajectory of the robotic arm based on that position. When the LiDAR detects an obstacle in front of the mobile platform, it simultaneously triggers the obstacle avoidance cooperative control logic. The cooperative control logic includes emergency braking of the mobile platform; rapid retraction of the robotic arm to a safe posture; and resumption of work by the robotic arm after the mobile platform has planned and executed the detour path.

[0071] In one embodiment, the inspection execution system operates in three modes: remote command control, local autonomous control, and preset trajectory control. The inspection robot control method further includes: Upon receiving the grasping control command issued by the diagnostic center, the working mode of the inspection execution system is determined to be remote command control mode, and auxiliary tasks are executed according to the grasping control command; the grasping control command includes grasping coordinates, gripper force and movement speed; In the event of communication interruption with the diagnostic center or triggering of local control commands, the working mode of the inspection execution system is determined to be the local autonomous control mode. Based on the real-time environmental data collected by the environmental perception system, the system autonomously plans the real-time capture trajectory and executes auxiliary tasks according to the real-time capture trajectory. When a standard task is triggered on the inspection route, the working mode of the inspection execution system is set to the preset trajectory control mode, and the preset grasping trajectory corresponding to the standard task is loaded to execute the auxiliary task according to the preset grasping trajectory.

[0072] In this embodiment, the control modes of the robotic arm are divided into remote command control (default), local autonomous control (emergency), and preset trajectory control (routine tasks). These three modes are seamlessly switched through the OCU. Remote command control receives sensor data from the diagnostic center via the OCU, generates a command packet containing "grasping coordinates, gripper force, and movement speed," encrypts it, and sends it to the OCU. The OCU decrypts the packet, verifies permissions, and forwards it to the robotic arm controller. The controller drives the motors of each joint to perform actions and simultaneously feeds back the joint angles to the OCU. The OCU then transmits this information back to the diagnostic center, forming a closed loop.

[0073] When communication is interrupted or the diagnostic center issues a "local control" command, the robotic arm automatically switches to local control mode, and the OCU makes independent decisions based on real-time data from the environmental perception system.

[0074] When performing highly repetitive and standardized tasks, such as the individual inspection of track bolts (requiring the robotic arm to carry an ultrasonic probe and align it with the bolt positions sequentially) or the circular scanning of the inner wall of a pipe (the robotic arm's end rotates 360° around its own axis), a preset trajectory control mode is used. The robotic arm works in conjunction with the mobile platform through a controller built into the chassis. For example, in a narrow pipe environment, the bionic mobile platform works with the robotic arm to achieve precise grasping and cleaning.

[0075] In one embodiment, the fault types of the target to be detected include a first type of fault and a second type of fault. In this embodiment, the first type of fault is a fault of lower severity, and the second type of fault is a fault of higher severity. The inspection control method provided in this embodiment further includes: If a Type I fault is detected and the ground environment is determined not to be a third road surface condition based on the ground environment parameters, the target detection parameters will be uploaded to the diagnostic center in real time.

[0076] In this embodiment, the target data (such as track gauge, crack width, and equipment temperature) collected by the sensors is preprocessed by the operation control unit and then uploaded to the diagnostic center every 2 seconds via the 5G network. It should be noted that the specific method and parameters for real-time uploading to the diagnostic center can be determined according to the needs of the actual application scenario.

[0077] If a second type of fault is detected and the ground environment is determined to be a third road surface condition based on the ground environment parameters, the target detection parameters are stored in the local memory. After the ground environment changes to a first or second road surface condition, the target detection parameters in the local memory are uploaded to the diagnostic center.

[0078] In this embodiment, if the vehicle is in a narrow pipe environment (where the 5G signal is weak), the operation control unit locally stores the inspection data and uploads it to the diagnostic center in batches after the vehicle leaves the pipe.

[0079] If a second type of fault is detected, the system generates a fault location movement trajectory, an alarm command, and a location upload command in real time. Based on the fault location movement trajectory, the system controls the chassis drive system to move the target mobile platform to the fault location. Based on the alarm command, the system issues an audible and visual alarm. Based on the location upload command, the system uploads the fault location, fault type, and image data to the diagnostic center.

[0080] In this embodiment, if a fault is detected (such as track gauge deviation ±3mm, crack width ≥10cm, equipment temperature ≥60℃), the operation control unit triggers a local audible and visual alarm, controls the robot to stop within 1m of the fault point, and uploads the fault location, type, and image data.

[0081] In one embodiment, after the inspection task is completed, the operation control unit can also generate an energy consumption report (including the energy consumption of each module and the remaining battery life) and upload it to the diagnostic center so that staff can keep track of the status information of the inspection robot in real time.

[0082] In summary, the inspection robot control method provided in this embodiment can achieve rapid replacement of the mobile platform through modular design, and achieve multi-scenario adaptive inspection by combining the environmental perception system and the operation control unit (OCU).

[0083] The following combines three typical environments and Figure 9 The inspection task execution procedure shown is explained in detail, outlining its specific implementation process.

[0084] In a more detailed embodiment, the inspection scheme of a wheeled mobile platform on a flat road surface (taking a high-speed railway station maintenance passage as an example) is described. This embodiment is aimed at the concrete maintenance passage, station square and flat transition section connecting the track in the high-speed railway station. The scene is open and unobstructed, and it is necessary to quickly cover a large area. The main inspection targets are: cracks in the passage ground, appearance damage to surrounding facilities (cable troughs, signal boxes), foreign objects on the surface (scattered parts, water accumulation) and abnormal equipment temperature (such as heat dissipation failure of signal boxes).

[0085] During the equipment preparation and installation phase, inspect the wheeled mobile platform for wear, ensure the universal coupling rotates freely, and confirm the locating pins and bolt holes match accurately. Install the wheeled platform, aligning the platform positioning components with the common chassis positioning holes. After initial positioning, align the driven interface of the universal coupling with the flange-type standard interface of the drive motor shaft, and tighten the bolts with a torque wrench to complete the power connection. Activate the OCU, start the OCU, and establish a 5G encrypted link connection with the diagnostic center. The default remote control mode automatically identifies the wheeled platform and loads the "Wheeled Algorithm Library."

[0086] During the environmental perception system startup phase, the lidar and IMU work together to construct a 3D environmental map and plan a patrol path along the centerline of the passage. Inspection sensors are activated, and a high-definition camera mounted at the front of the chassis captures one frame every 0.5 seconds, using edge detection algorithms to identify ground cracks and foreign objects with a diameter ≥5mm. An infrared thermal imager focuses on surrounding equipment, with a temperature measurement range of -20℃ to 150℃ and an over-temperature threshold set at 60℃ (the upper limit of the normal operating temperature of the signal box).

[0087] During the inspection execution phase, the robot travels along the planned path. The universal coupling synchronously transmits motor power to the wheels, and steering is achieved through differential control. The IMU corrects the driving trajectory in real time. The obstacle avoidance logic includes that when the lidar detects a dynamic obstacle (such as a person) within 10m ahead, the OCU instructs the robot to decelerate to 0.5m / s and detour (the detour distance is ≥ 1.5 times the diameter of the obstacle). After the sensor data is preprocessed by the OCU, it is uploaded to the diagnostic center every 2 seconds via 5G. If a ground crack ≥ 10cm wide is detected, the OCU triggers a local audible and visual alarm and stops within 1m of the potential hazard point.

[0088] After receiving the "Stop Inspection" command from the diagnostic center at the end of the mission, the robot travels to the endpoint and brakes. The OCU generates an energy consumption report and uploads it to the diagnostic center for reference in the next use.

[0089] Based on the above steps, the wheeled platform achieves efficient inspection of large flat areas by combining high-speed cruising (3km / h) with wide-field sensors, while taking into account driving stability and energy consumption optimization (range ≥4h).

[0090] In another more detailed embodiment, the inspection scheme of tracked mobile platform on train track and gravel road surface (taking outdoor railway section as an example) is described. This embodiment is for outdoor high-speed rail track, gravel track bed between tracks and transition gravel section, and needs to detect track cracks, track gauge deviation, missing / loose fasteners and track bed accumulation.

[0091] During the equipment preparation and installation phase, the tracked mobile platform was inspected. The tracks were found to be free of tears, the track wheels and auxiliary wheels rotated smoothly, and the angle sensor of the linkage obstacle-crossing mechanism was calibrated correctly. The tracked platform was installed, initially positioned with the chassis through the positioning holes. The driven interface of the track drive wheel and the flange of the transmission motor shaft were aligned, and the bolts were tightened. The tracks were then wrapped around the track wheels and auxiliary wheels, and the tension was adjusted. The OCU was activated, the "track algorithm library" was loaded, the cruising speed was 1.5 km / h, and the initial angle of the linkage obstacle-crossing mechanism was set to 0° (auxiliary wheel in contact with the ground). The angle data was uploaded to the diagnostic center in real time.

[0092] During the environmental perception system startup phase, a 3D map of the track is constructed using LiDAR and IMU, with a positioning accuracy of ±5cm, ensuring the robot travels along the track centerline (5cm±2cm from the inner side of the rail). Dedicated sensors are deployed: an ultrasonic detector emits a signal every 0.1 seconds to detect internal cracks in the rail; a dual-line laser displacement meter is installed on the side of the connecting rod, measuring the track gauge at a 10mm sampling interval, with an out-of-tolerance threshold set at ±3mm.

[0093] During the inspection phase, the tracked platform adapts to the gravel track bed by increasing its ground contact area. When encountering a depression between sleepers, the OCU instructs the central motor to rotate, and the connecting rod raises the auxiliary wheel to overcome the obstacle. The laser displacement gauge calculates the track gauge value in real time. When the deviation exceeds the limit, the OCU triggers an audible and visual alarm and stops, while a high-definition camera captures images of the abnormal area. The camera identifies missing or loose fasteners, and the infrared thermal imager monitors the temperature difference on the track surface. When gravel is detected on the track surface, the OCU instructs the three-axis robotic arm to grab and remove it, and transmits the operation images back to the diagnostic center.

[0094] At the end of the mission, the robot returns to the starting point and brakes. The OCU uploads track gauge deviation statistics, crack distribution, and energy consumption data to provide a reference for the next use.

[0095] The tracked platform adapts to complex terrains such as tracks and gravel roads through differential control and linkage obstacle-crossing mechanisms. Dedicated track gauge measurement and ultrasonic testing modules enable high-precision quantitative evaluation of track parameters.

[0096] In another detailed embodiment, a biomimetic mobile platform is used to illustrate an inspection scheme for narrow pipes (taking a drainage pipe under a track as an example). This embodiment is for a reinforced concrete drainage pipe under a track, where the space is narrow and it is necessary to inspect for corrosion on the inner wall (surface, blockages, and leakage at the joints).

[0097] During the equipment preparation and installation phase, inspect the bionic mobile platform. The "C"-shaped bionic feet, made of polyurethane, show no deformation in the height of the contact surface protrusions, and the joint bearings are well lubricated. Install the bionic platform, positioning it with the chassis via the positioning holes. Align the driven interface of the bionic feet with the transmission motor shaft flange, tighten the bolts, and complete the power transmission. Activate the OCU, load the "bionic algorithm library," and initiate attitude monitoring using the IMU.

[0098] During the initial phase of the environmental perception system, a map of the pipeline's interior is constructed using lidar and cameras. The cameras, mounted at the end of a robotic arm, capture images of the inner wall every 0.3 seconds, and image segmentation algorithms identify corroded areas and cracks. Miniature ultrasonic detectors are placed close to the inner wall to detect wall thickness; a reduction of ≥20% from the original 100mm thickness is considered excessive corrosion.

[0099] During the inspection process, when the lidar detects an obstruction ahead, the OCU commands the machine to stop, and the robotic arm extends to the obstruction. A camera then determines if the obstruction is removable; if so, it is grabbed and removed. When the 5G signal is weak inside the pipeline, the OCU stores the data locally and uploads it in batches to the diagnostic center after the vehicle exits the pipeline.

[0100] At the end of the mission, after the robot leaves the pipeline, the OCU uploads a corrosion area distribution map, crack location, and energy consumption report to provide a reference for the next use.

[0101] The biomimetic platform adapts to the confined space of narrow pipes through "C"-shaped foot tumbling and miniaturized sensors. Combined with the end effector of the robotic arm, it realizes the integrated operation of detecting defects in the inner wall of the pipe and removing small blockages.

[0102] It should be understood that although the steps in the flowcharts of the embodiments described above are shown sequentially according to the arrows, these steps are not necessarily executed in the order indicated by the arrows. Unless explicitly stated herein, there is no strict order restriction on the execution of these steps, and they can be executed in other orders. Moreover, at least some steps in the flowcharts of the embodiments described above may include multiple steps or multiple stages. These steps or stages are not necessarily completed at the same time, but can be executed at different times. The execution order of these steps or stages is not necessarily sequential, but can be performed alternately or in turn with other steps or at least some of the steps or stages of other steps.

[0103] Based on the same inventive concept, this application also provides an inspection robot control device for implementing the inspection robot control method described above. The solution provided by this device is similar to the solution described in the above method; therefore, the specific limitations in one or more embodiments of the inspection robot control device provided below can be found in the limitations of the inspection robot control method described above, and will not be repeated here.

[0104] In one embodiment, such as Figure 10 As shown, a control device 1000 for an intelligent inspection robot for rail transit is provided, comprising: a task acquisition module 1010, an environmental perception module 1020, a platform determination module 1030, and an inspection execution module 1040, wherein: The task acquisition module 1010 is used to acquire preset inspection tasks; wherein, the preset inspection tasks include inspection routes, targets to be detected, and target detection parameters; The environmental sensing module 1020 is used to control the environmental sensing system to collect ground environmental parameters; The platform determination module 1030 is used to determine the target mobile platform based on the ground environment parameters; the target mobile platform includes any one of a wheeled mobile platform, a tracked mobile platform, and a biomimetic mobile platform. The inspection execution module 1040 is used to, when the detachable mobile platform connected to the chassis drive system is the target mobile platform, load the movement control algorithm and inspection control algorithm corresponding to the target mobile platform, and control the chassis drive system to drive the target mobile platform to move according to the inspection route according to the movement control algorithm; control the environmental perception system to collect the target detection parameters of the target to be detected and perform fault detection according to the inspection control algorithm; and control the inspection execution system to perform auxiliary tasks according to the movement control algorithm or the inspection control algorithm. When the detachable mobile platform connected to the chassis drive system is not the target mobile platform, the module controls the chassis drive system to stop, generates a platform replacement prompt message and uploads it to the diagnostic center, until the detachable mobile platform connected to the chassis drive system is replaced with the target mobile platform.

[0105] Each module in the aforementioned inspection robot control device can be implemented entirely or partially through software, hardware, or a combination thereof. These modules can be embedded in or independent of the processor in a computer device, or stored in the computer device's memory as software, so that the processor can call and execute the corresponding operations of each module.

[0106] In one embodiment, a computer device is provided, which may be a terminal, and its internal structure diagram may be as follows: Figure 11As shown, the computer device includes a processor, memory, input / output interface, communication interface, display unit, and input device. The processor, memory, and input / output interface are connected via a system bus, and the communication interface, display unit, and input device are also connected to the system bus via the input / output interface. The processor provides computing and control capabilities. The memory includes non-volatile storage media and internal memory. The non-volatile storage media stores the operating system and computer programs. The internal memory provides an environment for the operation of the operating system and computer programs stored in the non-volatile storage media. The input / output interface is used for exchanging information between the processor and external devices. The communication interface is used for wired or wireless communication with external terminals; wireless communication can be achieved through Wi-Fi, mobile cellular networks, NFC (Near Field Communication), or other technologies. When the computer program is executed by the processor, it implements a control method for an intelligent inspection robot for rail transit. The display unit is used to form a visually visible image and can be a display screen, projection device, or virtual reality imaging device. The display screen can be an LCD screen or an e-ink screen. The input device of the computer device can be a touch layer covering the display screen, or buttons, trackballs, or touchpads set on the casing of the computer device, or external keyboards, touchpads, or mice, etc.

[0107] Those skilled in the art will understand that Figure 11 The structures shown are merely block diagrams of some structures related to the present application and do not constitute a limitation on the computer device to which the present application is applied. Specific computer devices may include more or fewer components than shown in the figures, or combine certain components, or have different component arrangements. It should be noted that... Figure 11 Solid boxes represent physical devices. Dashed boxes represent operating systems and computer programs that do not have physical components.

[0108] In one embodiment, a computer device is provided, including a memory and a processor, wherein the memory stores a computer program, and the processor executes the computer program to perform the following steps: Obtain preset inspection tasks; wherein, preset inspection tasks include inspection routes, targets to be inspected, and target detection parameters; The environmental sensing system is used to collect ground environmental parameters. The target mobile platform is determined based on ground environmental parameters; the target mobile platform includes any one of wheeled mobile platforms, tracked mobile platforms, and biomimetic mobile platforms. When the detachable mobile platform connected to the chassis drive system is the target mobile platform, the corresponding mobile control algorithm and inspection control algorithm of the target mobile platform are loaded. The chassis drive system is controlled to drive the target mobile platform to move according to the inspection route according to the mobile control algorithm. The environmental perception system is controlled to collect the target detection parameters of the target to be detected and perform fault detection according to the inspection control algorithm. The inspection execution system is controlled to perform auxiliary tasks according to the mobile control algorithm or the inspection control algorithm. If the detachable mobile platform connected to the chassis drive system is not the target mobile platform, the chassis drive system is shut down, a platform replacement prompt is generated and uploaded to the diagnostic center, until the detachable mobile platform connected to the chassis drive system is replaced with the target mobile platform.

[0109] In one embodiment, a computer-readable storage medium is provided having a computer program stored thereon, the computer program performing the following steps when executed by a processor: Obtain preset inspection tasks; wherein, preset inspection tasks include inspection routes, targets to be inspected, and target detection parameters; The environmental sensing system is used to collect ground environmental parameters. The target mobile platform is determined based on ground environmental parameters; the target mobile platform includes any one of wheeled mobile platforms, tracked mobile platforms, and biomimetic mobile platforms. When the detachable mobile platform connected to the chassis drive system is the target mobile platform, the corresponding mobile control algorithm and inspection control algorithm of the target mobile platform are loaded. The chassis drive system is controlled to drive the target mobile platform to move according to the inspection route according to the mobile control algorithm. The environmental perception system is controlled to collect the target detection parameters of the target to be detected and perform fault detection according to the inspection control algorithm. The inspection execution system is controlled to perform auxiliary tasks according to the mobile control algorithm or the inspection control algorithm. If the detachable mobile platform connected to the chassis drive system is not the target mobile platform, the chassis drive system is shut down, a platform replacement prompt is generated and uploaded to the diagnostic center, until the detachable mobile platform connected to the chassis drive system is replaced with the target mobile platform.

[0110] In one embodiment, a computer program product is provided, including a computer program that, when executed by a processor, performs the following steps: Obtain preset inspection tasks; wherein, preset inspection tasks include inspection routes, targets to be inspected, and target detection parameters; The environmental sensing system is used to collect ground environmental parameters. The target mobile platform is determined based on ground environmental parameters; the target mobile platform includes any one of wheeled mobile platforms, tracked mobile platforms, and biomimetic mobile platforms. When the detachable mobile platform connected to the chassis drive system is the target mobile platform, the corresponding mobile control algorithm and inspection control algorithm of the target mobile platform are loaded. The chassis drive system is controlled to drive the target mobile platform to move according to the inspection route according to the mobile control algorithm. The environmental perception system is controlled to collect the target detection parameters of the target to be detected and perform fault detection according to the inspection control algorithm. The inspection execution system is controlled to perform auxiliary tasks according to the mobile control algorithm or the inspection control algorithm. If the detachable mobile platform connected to the chassis drive system is not the target mobile platform, the chassis drive system is shut down, a platform replacement prompt is generated and uploaded to the diagnostic center, until the detachable mobile platform connected to the chassis drive system is replaced with the target mobile platform.

[0111] Those skilled in the art will understand that all or part of the processes in the above embodiments can be implemented by a computer program instructing related hardware. The computer program can be stored in a non-volatile computer-readable storage medium. When executed, the computer program can include the processes of the embodiments described above. Any references to memory, databases, or other media used in the embodiments provided in this application can include at least one of non-volatile and volatile memory. Non-volatile memory can include read-only memory (ROM), magnetic tape, floppy disk, flash memory, optical memory, high-density embedded non-volatile memory, resistive random access memory (ReRAM), magnetic random access memory (MRAM), ferroelectric random access memory (FRAM), phase change memory (PCM), graphene memory, etc. Volatile memory can include random access memory (RAM) or external cache memory, etc. By way of illustration and not limitation, RAM can take many forms, such as Static Random Access Memory (SRAM) or Dynamic Random Access Memory (DRAM). The databases involved in the embodiments provided in this application may include at least one type of relational database and non-relational database. Non-relational databases may include, but are not limited to, blockchain-based distributed databases. The processors involved in the embodiments provided in this application may be general-purpose processors, central processing units, graphics processing units, digital signal processors, programmable logic devices, quantum computing-based data processing logic devices, etc., and are not limited to these.

[0112] The technical features of the above embodiments can be combined in any way. For the sake of brevity, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0113] The embodiments described above are merely illustrative of several implementation methods of this application, and while the descriptions are specific and detailed, they should not be construed as limiting the scope of this patent application. It should be noted that those skilled in the art can make various modifications and improvements without departing from the concept of this application, and these all fall within the protection scope of this application. Therefore, the protection scope of this application should be determined by the appended claims.

Claims

1. A control method for an intelligent inspection robot for rail transit, characterized in that, The intelligent inspection robot for rail transit includes an operation control system, an environmental perception system, a chassis drive system, an inspection execution system, a shared chassis, and multiple detachable mobile platforms, wherein the chassis drive system is connected to the detachable mobile platforms via a transmission connection; the method includes: Obtain a preset inspection task; wherein, the preset inspection task includes an inspection route, a target to be inspected, and target detection parameters; The environmental sensing system is controlled to collect ground environmental parameters; The target mobile platform is determined based on the ground environment parameters; the target mobile platform includes any one of wheeled mobile platforms, tracked mobile platforms, and biomimetic mobile platforms. When the detachable mobile platform connected to the chassis drive system is the target mobile platform, a mobile control algorithm and an inspection control algorithm corresponding to the target mobile platform are loaded. The chassis drive system is controlled to drive the target mobile platform to move according to the inspection route according to the mobile control algorithm. The environmental perception system is controlled to collect the target detection parameters of the target to be detected and perform fault detection according to the inspection control algorithm. The inspection execution system is controlled to perform auxiliary tasks according to the mobile control algorithm or the inspection control algorithm. If the detachable mobile platform connected to the chassis drive system is not the target mobile platform, the chassis drive system is controlled to stop, a platform replacement prompt message is generated and uploaded to the diagnostic center, until the detachable mobile platform connected to the chassis drive system is replaced with the target mobile platform.

2. The method according to claim 1, characterized in that, The environmental perception system includes at least one of a visual perception component, an infrared perception component, an ultrasonic perception component, a laser perception component, and an inertial measurement component; the ground environmental parameters include ground texture, ground material, ground relief standard deviation, and spatial dimension data; The step of determining the target mobile platform based on the ground environment parameters includes: If the ground environment is determined to be a first road surface condition based on the ground environment parameters, the target mobile platform is determined to be a wheeled mobile platform; the first road surface condition is a flat road surface. If the ground environment is determined to be the second road surface condition based on the ground environment parameters, the target mobile platform is determined to be a tracked mobile platform; the second road surface condition is a train track or a gravel road surface. If the ground environment is determined to be a third road surface condition based on the ground environment parameters, the target mobile platform is determined to be a biomimetic mobile platform; the third road surface condition is a narrow pipe.

3. The method according to claim 2, characterized in that, The step of controlling the chassis drive system to drive the target mobile platform to move along the inspection route according to the motion control algorithm includes: When the target mobile platform is a wheeled mobile platform, the chassis drive system is controlled according to the first mobile control algorithm to drive the wheeled mobile platform to move along the inspection route; the first mobile control algorithm includes a first obstacle avoidance strategy; When the target mobile platform is a tracked mobile platform, the chassis drive system is controlled to drive the tracked mobile platform to move along the inspection route according to the second motion control algorithm; the second motion control algorithm includes a second obstacle avoidance strategy. When the target mobile platform is a biomimetic mobile platform, the chassis drive system is controlled according to the third mobile control algorithm to drive the wheeled mobile platform to move along the inspection route; the third mobile control algorithm includes a third obstacle avoidance strategy.

4. The method according to claim 2, characterized in that, The method further includes: When the environmental perception system detects changes in the ground environment, changes in the preset inspection task, or changes in the robot's self-inspection status, it generates a platform replacement command. The target mobile platform is re-determined based on the platform replacement instruction.

5. The method according to claim 1, characterized in that, The inspection execution system includes a three-axis robotic arm. The base of the three-axis robotic arm is fixedly installed at the front end of a common chassis. The end of the three-axis robotic arm is equipped with a gripping mechanism, which is used to assist in clearing obstacles on the track or gripping the target to be inspected. The step of controlling the inspection execution system to perform auxiliary tasks according to the motion control algorithm or the inspection control algorithm includes: The three-axis robotic arm is controlled according to the motion control algorithm to assist in clearing obstacles on the track. The inspection control algorithm is used to control the three-axis robotic arm to grasp the target to be inspected.

6. The method according to claim 5, characterized in that, The inspection execution system has three working modes: remote command control mode, local autonomous control mode, and preset trajectory control mode. The method further includes: Upon receiving the grasping control command issued by the diagnostic center, the working mode of the inspection execution system is determined to be the remote command control mode, and the auxiliary task is executed according to the grasping control command; the grasping control command includes grasping coordinates, gripper force, and movement speed; In the event of a communication interruption with the diagnostic center or the triggering of a local control command, the working mode of the inspection execution system is determined to be the local autonomous control mode. Based on the real-time environmental data collected by the environmental perception system, the system autonomously plans a real-time capture trajectory to execute the auxiliary task according to the real-time capture trajectory. When a standard task is triggered on the inspection route, the working mode of the inspection execution system is determined to be the preset trajectory control mode, and the preset grasping trajectory corresponding to the standard task is loaded to execute the auxiliary task according to the preset grasping trajectory.

7. The method according to claim 1, characterized in that, The fault types of the target to be detected include a first type of fault and a second type of fault; The method further includes: If a first type of fault is detected and it is determined from the ground environment parameters that the ground environment does not belong to the third road surface condition, the target detection parameters will be uploaded to the diagnostic center in real time. If a second type of fault is detected and the ground environment is determined to be a third road surface condition based on the ground environment parameters, the target detection parameters are stored in the local memory. After the ground environment changes to a first road surface condition or a second road surface condition, the target detection parameters in the local memory are uploaded to the diagnostic center. If a second type of fault is detected, a fault location movement trajectory, an alarm command, and a location upload command are generated in real time. Based on the fault location movement trajectory, the chassis drive system is controlled to drive the target mobile platform to the fault location. An audible and visual alarm is triggered based on the alarm command, and the fault location, fault type, and image data are uploaded to the diagnostic center based on the location upload command.

8. A control device for an intelligent inspection robot for rail transit, characterized in that, The intelligent inspection robot for rail transit includes an operation control system, an environmental perception system, a chassis drive system, an inspection execution system, a shared chassis, and multiple detachable mobile platforms. The chassis drive system is connected to the detachable mobile platforms via a transmission connection. The device includes: The task acquisition module is used to acquire preset inspection tasks; wherein, the preset inspection tasks include inspection routes, targets to be inspected, and target detection parameters; The environmental sensing module is used to control the environmental sensing system to collect ground environmental parameters; The platform determination module is used to determine the target mobile platform based on the ground environment parameters; the target mobile platform includes any one of wheeled mobile platforms, tracked mobile platforms, and biomimetic mobile platforms. The inspection execution module is used to, when the detachable mobile platform connected to the chassis drive system is the target mobile platform, load the corresponding movement control algorithm and inspection control algorithm for the target mobile platform, and control the chassis drive system to drive the target mobile platform to move according to the inspection route according to the movement control algorithm; control the environmental perception system to collect target detection parameters of the target to be detected and perform fault detection according to the inspection control algorithm; and control the inspection execution system to perform auxiliary tasks according to the movement control algorithm or the inspection control algorithm. If the detachable mobile platform connected to the chassis drive system is not the target mobile platform, the module controls the chassis drive system to stop, generates a platform replacement prompt message and uploads it to the diagnostic center, until the detachable mobile platform connected to the chassis drive system is replaced with the target mobile platform.

9. A smart inspection robot for rail transit, characterized in that, include: The system comprises an operation control system, an environmental perception system, a chassis drive system, an inspection execution system, a shared chassis, and multiple detachable mobile platforms. The operation control system, environmental perception system, chassis drive system, and inspection execution system are all mounted on the shared chassis. The operation control system is connected to the environmental perception system, chassis drive system, and inspection execution system, respectively. The chassis drive system is drive-connected to the detachable mobile platforms. The operation control system is used to execute the steps of the control method for the intelligent inspection robot of rail transit according to any one of claims 1 to 7.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by the processor, it implements the steps of the control method for the intelligent inspection robot of rail transit as described in any one of claims 1 to 7.

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