Mobile robot fault diagnosis method, device, equipment and storage medium

Abstract

The present invention discloses a mobile robot fault diagnosis method, apparatus, device, and storage medium. The method comprises the following steps: configuring corresponding fault diagnostic codes for different robot system levels, and configuring the fault diagnostic codes to be triggered at the corresponding robot system level when a fault occurs; real-time monitoring of the fault status of the mobile robot while it is performing a task; obtaining the triggered fault diagnostic code at the corresponding robot system level when a fault is detected in the mobile robot; and diagnosing the fault type and location of the current mobile robot fault based on the obtained fault diagnostic code. The robot system level includes a task layer, a status layer, a communication layer, and a device layer. The present invention has the advantages of simple implementation, high diagnostic efficiency, and the ability to quickly locate the fault location and obtain the cause of the fault.

Description

Technical Field

[0001] The present invention relates to the technical field of mobile robots, and in particular to a mobile robot fault diagnosis method, device, equipment and storage medium. Background Art

[0002] Mobile robots are capable of locomotion and autonomously performing tasks. They are highly customized and operate in complex environments, often requiring multi-system and multi-device interaction. These challenges can include operating in high-voltage environments, entering and exiting elevators, crossing railroad tracks, and man-machine and multi-robot collaboration. Consequently, mobile robots may encounter various complex faults while performing tasks in diverse operating environments, posing safety risks. Accurate diagnosis of these faults is essential, enabling tailored troubleshooting for each type.

[0003] In existing technologies, fault diagnosis methods typically detect operating signals such as voltage and current in the device, and determine whether the device is faulty based on the status of these signals. This type of diagnosis is only applicable to robotic devices that do not require movement. If applied to mobile robots, the following problems may arise:

[0004] 1. Low diagnostic efficiency makes it difficult to achieve real-time fault diagnosis, and thus unable to promptly identify the cause of equipment failures. Mobile robots have a short operating window. Once a fault occurs, it is necessary to quickly locate the problem, quickly identify the cause, and promptly address the fault. Traditional diagnostic methods that detect voltage and current working signals are unable to meet the needs of mobile robots for rapid fault location and fault cause identification.

[0005] 2. The types of faults that can occur in mobile robots are complex, with different faults occurring in different scenarios, and the same fault can also manifest differently in different environments. This means that the generation and diagnosis of faults are deeply coupled with the robot's application scenario. Traditional diagnostic methods that detect voltage and current operating signals can only simply determine the robot's fault status, but it is difficult to accurately locate the cause of the fault. Summary of the Invention

[0006] The technical problem to be solved by the present invention is: in response to the technical problems existing in the prior art, the present invention provides a mobile robot fault diagnosis method, device, equipment and storage medium that are simple to implement, real-time and have high diagnostic efficiency, can quickly locate the fault position and obtain the cause of the fault.

[0007] In order to solve the above technical problems, the technical solution proposed by the present invention is:

[0008] A mobile robot fault diagnosis method, comprising the following steps:

[0009] Configuring corresponding Robot Diagnostic Trouble Codes (RDTCs) for different robot system levels, and configuring such that the RDTCs for the corresponding robot system levels are triggered when a fault occurs;

[0010] Real-time monitoring of the fault status of mobile robots during mission execution;

[0011] When a fault is detected in the mobile robot, a fault diagnostic code corresponding to the robot system level is obtained;

[0012] diagnosing the fault type, fault location, and fault cause of the current fault of the mobile robot according to the acquired fault diagnostic code;

[0013] The robot system hierarchy includes a task layer corresponding to the task hierarchy, a status layer corresponding to the robot operation status hierarchy, a communication layer corresponding to the communication status hierarchy between the robot and internal devices, and a device layer corresponding to the robot internal device hierarchy. The fault diagnostic code includes fault information such as the fault type, fault location, and fault cause.

[0014] Furthermore, the task layer classifies all tasks of the mobile robot and decomposes each type of task according to the execution stage. Each stage is configured with a corresponding fault diagnostic code; when the mobile robot cannot execute the task when it reaches the target stage, the fault diagnostic code corresponding to the target stage is triggered.

[0015] Furthermore, the fault diagnosis code of the task layer is coupled with the fault diagnosis codes of the status layer, the communication layer and the device layer respectively.

[0016] Furthermore, when a fault diagnostic code of any one of the status layer, communication layer and device layer is triggered, if the mobile robot is performing a task, a corresponding task layer fault diagnostic code is triggered according to the task execution stage.

[0017] Furthermore, the fault diagnostic code also includes a fault code ID, a DTC fault code string, error code information, solution information, potential cause information, recoverability information, repair instructions, log information where the error is located, fault level, device type, source of device fault, device ID, device name, software version information corresponding to the fault code, and any one or more of the error code information.

[0018] Furthermore, after diagnosing the fault type and fault location based on the acquired fault diagnostic code, the method further includes performing fault processing based on the fault diagnosis result and the robot system level corresponding to the current fault, and different fault processing measures are configured corresponding to different robot system levels.

[0019] Furthermore, when the fault occurs at the task layer, the control re-executes the task of the current stage, or performs a reset, restarts the device, or reconnects the communication, or directly reports the fault and ends the task; when the fault occurs at any layer of the status layer, communication layer or device layer, the fault is handled by the task layer fault handling mechanism. If the current fault diagnostic code level is lower than the preset value or does not affect the task execution, the fault is only reported without any processing.

[0020] Furthermore, the real-time monitoring of the fault status of the mobile robot during the execution of a task also includes predicting whether the current robot has the conditions to execute the task and whether a fault will occur when executing the current task based on the task type of the currently received task, the status of the operation auxiliary equipment, the status of the robot main body equipment and the robot main body task status. When the prediction is that the conditions to execute the task are met and no fault will occur when executing the current task, the robot is controlled to execute the current task. The robot main body task status is the status of the robot executing the task.

[0021] Furthermore, after diagnosing the fault type and fault location of the current fault of the mobile robot according to the acquired fault diagnostic code, the method also includes reporting the fault according to the type of the fault diagnostic code, the corresponding fault level and the robot system level control.

[0022] Furthermore, when the fault diagnostic code is a type of fault diagnostic code that the robot cannot self-repair, or when the corresponding fault level is judged to be greater than the preset level based on the fault diagnostic code, the control reports the fault information to the robot's upper system; when the task is canceled or the robot is reset, the task layer fault diagnostic code is controlled not to be reported; when the fault in any layer of the status layer, communication layer and equipment layer is eliminated, the corresponding fault diagnostic code is controlled not to be reported, otherwise the fault diagnostic code continues to be reported, and the robot is controlled to stop executing new tasks.

[0023] A mobile robot fault diagnosis device, comprising:

[0024] a fault diagnostic code configuration module, configured to configure corresponding fault diagnostic codes for different robot system levels, and configured so that the fault diagnostic code of the corresponding robot system level is triggered when a fault occurs;

[0025] Fault monitoring module, used to monitor the fault status of the mobile robot in real time during the execution of tasks;

[0026] The RDTC acquisition module is used to obtain the fault diagnostic code of the corresponding robot system level when a fault is detected in the mobile robot;

[0027] A fault diagnosis module is used to diagnose the fault type and fault location of the mobile robot according to the acquired fault diagnostic code;

[0028] The robot system hierarchy includes a task layer corresponding to the task hierarchy, a status layer corresponding to the robot operation status hierarchy, a communication layer corresponding to the communication status hierarchy between the robot and internal devices, and a device layer corresponding to the robot internal device hierarchy. The fault diagnostic code includes fault information such as the fault type and the fault location.

[0029] Furthermore, it also includes a fault processing module connected to the fault diagnosis module, which is used to perform fault processing based on the fault diagnosis result and the robot system level corresponding to the current fault. Different robot system levels are configured with different fault processing measures.

[0030] Furthermore, it also includes a fault reporting module connected to the fault diagnosis module, which is used to report faults according to the type of fault diagnosis code, the corresponding fault level and the robot system level control.

[0031] Furthermore, it also includes a fault prediction module arranged at the input end of the fault monitoring module, which is used to predict whether the current robot has the conditions to perform the task and whether a fault will occur when performing the current task based on the task type of the currently received task, the status of the operation auxiliary equipment, the status of the robot main body equipment and the robot main body task status. When it is predicted that the conditions to perform the task are met and no fault will occur when performing the current task, the robot is controlled to perform the current task. The robot main body task status is the status of the robot performing the task.

[0032] An electronic device includes a processor and a memory, wherein the memory is used to store a computer program, and the processor is used to execute the computer program to perform the above method.

[0033] A computer-readable storage medium storing a computer program, wherein the computer program implements the above method when executed.

[0034] Compared with the prior art, the advantages of the present invention are:

[0035] 1. The present invention adopts a layered design approach to divide the robot system into a task layer, a status layer, a communication layer, and an equipment layer. The fault status of the robot system is monitored in real time during the robot's task execution. When a mobile robot fails, different layers will trigger corresponding fault diagnostic codes RDTC. The fault can be diagnosed in time through the triggering time and coupling relationship of RDTC, thereby decoupling complex faults. The fault diagnostic codes RDTC of different layers are triggered to achieve real-time, rapid, and accurate positioning of mobile robot faults, effectively improving the real-time and efficiency of diagnosis, timely analyzing the fault generation mechanism and determining the fault cause, and then correctly classifying and attributing the fault when the mobile robot fails.

[0036] 2. The present invention further enables, when the upper-level system issues a task to the robot, the task type, the status of the auxiliary operation equipment, the status of the robot's main equipment, and the status of the robot's main task to be comprehensively considered to determine whether the current robot has the conditions to perform the task, and whether a failure will occur if the task is performed. This allows the mobile robot to comprehensively judge the operating conditions and predict failures in advance before performing the task, and to quickly judge the task execution conditions when the mobile robot receives the task, thereby ensuring the safety of task execution and predicting risks in advance before the mobile robot operates.

[0037] 3. The present invention further enables the robot to automatically adopt appropriate processing mechanisms to handle faults based on the fault diagnosis results after triggering the RDTC, so that the robot can handle faults in a timely and automatic manner to ensure safety and smooth execution of tasks, thereby improving the success rate of the robot's task execution. BRIEF DESCRIPTION OF THE DRAWINGS

[0038] Figure 1 It is a schematic diagram of the implementation flow of the mobile robot fault diagnosis method according to embodiment 1 of the present invention.

[0039] Figure 2 It is a flowchart of implementing mobile robot fault diagnosis in a specific application embodiment of Example 1 of the present invention.

[0040] Figure 3 It is a flowchart of implementing mobile robot fault handling in a specific application embodiment of Example 1 of the present invention.

[0041] Figure 4 It is a flowchart of realizing mobile robot fault reporting in a specific application embodiment of Example 1 of the present invention.

[0042] Figure 5 It is a flowchart of realizing mobile robot fault prediction in the specific application embodiment of Example 2 of the present invention.

[0043] Figure 6 It is a flowchart of implementing mobile robot fault prediction, diagnosis and processing in a specific application embodiment of Example 3 of the present invention. DETAILED DESCRIPTION

[0044] The present invention will be further described below in conjunction with the accompanying drawings and specific preferred embodiments, but the scope of protection of the present invention is not limited thereby.

[0045] Example 1:

[0046] like Figure 1 As shown, the steps of the mobile robot fault diagnosis method of this embodiment include:

[0047] S01 for different robot system levels corresponding to the configuration of the fault diagnostic code RDTC, and configured so that when a fault occurs, the corresponding robot system level fault diagnostic code RDTC is triggered;

[0048] S02. Real-time monitoring of the fault status of the mobile robot during the execution of the task;

[0049] S03. When a mobile robot failure is detected, a fault diagnostic code RDTC corresponding to the robot system level is obtained.

[0050] S04. Diagnose the fault type and fault location of the mobile robot according to the acquired fault diagnostic code RDTC;

[0051] The above-mentioned robot system hierarchy includes a task layer corresponding to the task hierarchy, a status layer corresponding to the robot operation status hierarchy, a communication layer corresponding to the communication status hierarchy between the robot and internal devices, and a device layer corresponding to the robot internal device hierarchy. The fault diagnostic code RDTC includes fault information such as the fault type and fault location.

[0052] When a robot performs a task, it usually executes it in a hierarchical order. Each step will have a corresponding task-level fault diagnostic code RDTC, that is, there is a coupling relationship between the fault diagnostic codes RDTC. When an abnormality occurs during the execution of a step, the corresponding task-level fault diagnostic code RDTC will be triggered. The triggering time and coupling relationship of the fault diagnostic code RDTC can be used to diagnose the fault in a timely manner, and it is also convenient to locate the location of the fault.

[0053] Taking the robot performing the charging task as an example, the following steps need to be performed in sequence:

[0054] 1) The robot in the idle state starts to perform the charging task, and the task state switches to the moving state until it moves to the charging station;

[0055] 2) The charging station and the robot dock and start charging, and the mission state switches to charging state;

[0056] 3) When the charging termination conditions are met, the charging pile and the robot are disconnected, the charging task is completed, and the state is switched to idle state.

[0057] Each of the above steps has a corresponding task-level RDTC. For example, step 1) has RDTCs corresponding to movement failure and movement timeout, and step 2) has RDTCs corresponding to charging docking failure. Based on the task execution order, the RDTC in step 1) will be triggered first. After triggering, the charging task failure RDTC will be generated, and the charging task will be terminated, so that the RDTCs in subsequent steps will not be triggered, thus preventing the generation of incorrect RDTCs. The acquired RDTCs can then be used to diagnose the fault type and location.

[0058] This embodiment adopts a hierarchical design method to divide the robot system into four layers: task layer, status layer, communication layer, and equipment layer. The fault status of the robot system is monitored in real time during the robot's task execution. When the mobile robot fails, different fault diagnostic codes RDTC will be triggered at different levels. Due to the coupling relationship between RDTCs, the fault can be diagnosed in time through the triggering time and coupling relationship of RDTC, so that complex faults can be decoupled. The fault diagnostic codes RDTCs of different levels are triggered to realize real-time, fast and accurate positioning of mobile robot faults, effectively improving the real-time and efficiency of diagnosis, timely analyzing the fault generation mechanism and judging the fault cause, and then correctly classifying and attributing the fault when the mobile robot fails.

[0059] In specific application embodiments, task-level faults and state-level faults are further defined and associated, and different faults in different scenarios and the robot system status are combined to form fault diagnosis results that match different scenarios and faults. For example, a robot has two control modes: manual control mode and automatic control mode, which mainly perform simple forward and backward motion control; automatic control mode is a mode in which the robot is controlled by the upper-level software system and can execute complex business logic. Because manual control authority is higher than automatic control, when in manual control mode, the robot does not execute control instructions from the upper-level software. Therefore, when the robot is in manual mode and is controlled to move forward through remote control or buttons, the fault "robot is in manual mode" will not be determined as a fault. However, when the robot is in manual mode and control instructions are issued by the upper-level software, it will be determined as a fault.

[0060] In this embodiment, the task layer specifically categorizes all mobile robot tasks and decomposes each categorized task by execution phase. Each phase is assigned a corresponding fault diagnostic code (RDTC). If the mobile robot fails to execute the task at the target phase, the corresponding fault diagnostic code (RDTC) is triggered. Different tasks, and different phases of the same task, require different fault mechanisms. This embodiment divides the task layer, categorizes the mobile robot tasks, and decomposes the tasks by execution phase. The corresponding fault diagnostic code (RDTC) is triggered according to the execution phase at the time of the failure. The fault diagnostic code (RDTC) can be used to quickly locate the type of task being executed by the robot and the execution phase of the task.

[0061] Mobile robots operate in the form of tasks. Task execution requires a combination of the mobile robot itself, the operating environment, and auxiliary operating equipment. Different tasks and different stages of the same task require different fault mechanisms. Therefore, the source of the fault may not only be the robot itself, but also the robot's operating environment, that is, the auxiliary operating equipment. Even when the mobile robot is normal and the auxiliary operating equipment is abnormal, a fault may occur. This embodiment locates faults from a task perspective by dividing the task layer, so that even when the mobile robot is normal and the auxiliary operating equipment is abnormal, the corresponding fault can be diagnosed. For example, if the robot's main equipment is normal, but the charging equipment is abnormal, causing the robot to be unable to operate, it will be reported as a task-layer fault. In addition, when a task fails, the robot itself may not necessarily have a fault, but it is still necessary to perform fault diagnosis on the task execution failure to accurately locate the cause of the task failure. This embodiment combines the characteristics of robot operations and uses task-layer fault diagnosis. When a task fails, even if the mobile robot is not faulty, it is still possible to perform fault diagnosis on the environment and the interactive operating equipment to accurately locate the cause of the task failure.

[0062] In this embodiment, the fault diagnostic code RDTC of the task layer is coupled with the fault diagnostic code RDTC of the status layer, communication layer and device layer respectively, that is, there is a coupling relationship between the RDTCs of each layer, so that the fault can be diagnosed in time through the triggering time and coupling relationship of the RDTC. Among them, when the fault diagnostic code RDTC of any layer in the status layer, communication layer and device layer is triggered, if the mobile robot is performing a task, the corresponding task layer fault diagnostic code RDTC is triggered according to the task execution stage. The task layer fault is combined with the RDTC of other layers to generate the final fault diagnosis result, in which the fault of the status layer, device layer or communication layer will be triggered independently. For example, if the robot is in manual control state, or the robot communication is abnormal, combined with the fault of the task layer, the upper system can obtain fault information such as: "The robot is in manual control state, the movement timed out, and the charging task failed", indicating that the robot cannot move to the charging position because it is in manual control mode, resulting in the failure of the charging task.

[0063] In a specific application embodiment, the fault diagnostic code RDTC setting and coupling relationship configuration are as follows:

[0064] Task-layer RDTC: This layer categorizes all robot tasks. Each task is further broken down according to different execution stages, and each stage has a corresponding RDTC. When the robot reaches a certain stage and cannot perform the task, the RDTC for that stage is triggered. The task-layer RDTC indicates the direct cause of the fault and is coupled with the RDTCs of the status layer, communication layer, and device layer.

[0065] Status layer RDTC: This layer indicates a fault in the robot system's operating status, such as a software exception or the robot being in manual control mode. After the status layer RDTC is triggered, if the robot is executing a task, the corresponding task layer RDTC will be triggered based on the task execution stage.

[0066] Communication layer RDTC: This layer indicates communication failures between the robot and internal devices (such as drive motors) or external systems (such as upper-level scheduling systems). After a communication layer RDTC is triggered, if the robot is currently executing a task, the corresponding task layer RDTC will be triggered based on the task execution stage.

[0067] Device-layer RDTC: This layer indicates a failure in the robot's internal devices (such as the drive motor). After a device-layer RDTC is triggered, if the robot is currently executing a task, the corresponding task-layer RDTC will be triggered based on the task execution phase.

[0068] This embodiment specifically performs fault diagnosis based on the fault triggering sequence, fault code level, and the association between fault codes at different levels (task layer, state layer, communication layer, device layer). The coupling relationship between the RDTCs at each level and the fault code level are used to determine the final fault diagnosis result. The fault code level is used to define the importance of the fault code, so that the diagnosis results of faults at different levels can be adjusted or fault reporting can be performed according to actual needs. For example, in some cases, if a laser ranging sensor of a robot has a fault, but the fault does not affect the robot, its fault level can be set to a lower level (such as level 1). During fault diagnosis and reporting, the sensor fault is not displayed in the fault diagnosis results. In specific application embodiments, the fault level can also be used to adjust the fault generation mechanism. For example, a fault with a fault level of 2 requires more than 100 triggers in 1 minute to be considered valid, while a fault with a fault level of 5 is considered valid as long as it is triggered once. Furthermore, the fault level can be used to set the information permissions that users with different permissions can access. For example, a high-privilege user can see faults of all levels, while a low-privilege user can only view faults of some fault levels.

[0069] like Figure 2 As shown, in a specific application embodiment, after the fault diagnosis is started, if the mobile robot fails, the fault diagnostic code RDTC corresponding to the robot system level will be triggered, and diagnosis will be performed separately according to the robot system level (task layer, status layer, communication layer and device layer) corresponding to the fault diagnostic code RDTC. The fault diagnosis is mainly based on the triggering timing of the fault, the fault code level and the correlation between the fault codes at different levels (task layer, status layer, communication layer, device layer), and then corresponding fault processing is performed according to the diagnosis result.

[0070] In this embodiment, the diagnostic fault code (RDTC) includes the fault category and location information, as well as the fault code ID, DTC fault code string, error code information, solution information, potential cause information, recovery information, repair instructions, log information of the error, fault level, device type, device fault source, device ID, device name, software version information corresponding to the fault code, and error code information. In a specific application embodiment, the format of the robot fault code RDTC is shown in Table 1.

[0071] Table 1: Robot fault code format

[0072]

[0073]

[0074] In this embodiment, after diagnosing the fault type and location based on the acquired fault diagnostic code (RDTC), the process also includes performing fault handling based on the fault diagnosis results and the robot system level corresponding to the current fault. Different robot system levels are configured with different fault handling measures. Through these fault handling steps, when the robot triggers the RDTC, it can automatically implement appropriate handling mechanisms to address the fault based on the fault diagnosis results. This allows the robot to handle the fault promptly and automatically, ensuring safety and smooth mission execution, and improving the robot's success rate in executing tasks. If the robot cannot resolve the diagnosed fault on its own, the fault can be further reported.

[0075] like Figure 3 As shown, in a specific application embodiment, when fault processing is started, the fault diagnostic code RDTC is obtained, and fault processing is performed according to the robot system level corresponding to the fault diagnostic code RDTC. For example, for a task layer fault, the fault processing is performed according to the task layer fault processing mechanism; for a state layer fault, the fault processing is performed according to the state layer fault processing mechanism. After the fault processing is completed, the fault diagnostic code RDTC is reported.

[0076] In this embodiment, the fault handling steps specifically include: when the fault is at the task layer, the control re-executes the task of the current stage, or performs a reset, restarts the device, or reconnects the communication, or directly reports the fault and ends the task; when the fault is at any layer of the status layer, communication layer or device layer, the fault is handled by the task layer fault handling mechanism. If the current fault diagnostic code RDTC level is lower than the preset value or does not affect the task execution, the fault is only reported without processing.

[0077] In a specific application embodiment, the fault handling steps at each layer are:

[0078] Task layer fault handling: Based on the triggered task layer RDTC, either re-execute the task at that stage, reset or restart the device, reconnect the communication, or directly report the fault and end the task.

[0079] State layer fault handling: Based on the triggered state layer RDTC and the task execution status, the corresponding task layer RDTC is triggered, and the task layer fault handling mechanism handles the fault. If the state layer RDTC level is low or does not affect task execution, it is only reported through the fault reporting mechanism without any processing.

[0080] Communication layer fault handling: Automatically reconnect based on the triggered communication layer RDTC. If multiple reconnection failures occur, the corresponding task layer RDTC is triggered based on the task execution status. The task layer fault handling mechanism handles the fault. If the communication layer RDTC level is low or does not affect task execution, the fault is only reported through the fault reporting mechanism without any processing.

[0081] Device layer fault handling: Based on the triggered device layer RDTC and the task execution status, the corresponding task layer RDTC is triggered, and the task layer fault handling mechanism handles the fault. If the device layer RDTC level is low or does not affect task execution, it is only reported through the fault reporting mechanism without any processing.

[0082] In this embodiment, after diagnosing the fault type and location of the mobile robot's current fault based on the acquired fault diagnostic code RDTC, the system also includes performing fault reporting based on the type of the fault diagnostic code RDTC, the corresponding fault level, and the robot system hierarchical control. Through the above fault reporting steps, after triggering an RDTC that cannot be self-repaired by the robot, fault information can be reliably reported to the robot's upper-level system in real time. At the same time, the need for fault reporting can be determined based on the fault level determined by the fault diagnostic code RDTC, facilitating the identification of the fault cause and thereby achieving optimization and improvement of the robot.

[0083] In this embodiment, specifically when the fault diagnostic code RDTC is a fault diagnostic code RDTC of the type that the robot cannot self-repair, or when it is judged according to the fault diagnostic code RDTC that the corresponding fault level is greater than the preset level, that is, the fault level is greater than the level that needs to be reported, the control is to report the fault information to the upper system of the robot; when the task is canceled or the robot is reset, the task layer fault diagnostic code RDTC is controlled not to be reported; when the fault of any layer among the status layer, communication layer and device layer is eliminated, the corresponding fault diagnostic code RDTC is controlled not to be reported, otherwise the fault diagnostic code RDTC is continuously reported, and the robot is controlled to stop executing new tasks.

[0084] like Figure 4As shown, in a specific application embodiment, when the fault reporting process is started, the fault diagnostic code RDTC is obtained, and the corresponding fault level is determined to determine whether reporting is required. If reporting is required, an RDTC queue is generated, and the fault diagnostic code RDTC is reported in the order of the RDTC queue.

[0085] The mobile robot fault diagnosis device of this embodiment includes:

[0086] A fault diagnostic code RDTC configuration module is used to configure corresponding fault diagnostic codes RDTC for different robot system levels, and to configure so that the fault diagnostic code RDTC of the corresponding robot system level is triggered when a fault occurs;

[0087] Fault monitoring module, used to monitor the fault status of the mobile robot in real time during the execution of tasks;

[0088] The RDTC acquisition module is used to obtain the fault diagnostic code RDTC of the corresponding robot system level when a fault is detected in the mobile robot;

[0089] The fault diagnosis module is used to diagnose the fault type and fault location of the mobile robot according to the acquired fault diagnostic code RDTC;

[0090] The robot system level includes a task layer corresponding to the task level, a status layer corresponding to the robot operation status level, a communication layer corresponding to the communication status level between the robot and internal devices, and a device layer corresponding to the robot internal device level. The fault diagnostic code RDTC includes fault information such as the fault type and fault location.

[0091] This embodiment also includes a fault processing module connected to the fault diagnosis module, which is used to perform fault processing based on the fault diagnosis result and the robot system level corresponding to the current fault. Different robot system levels are configured with different fault processing measures.

[0092] In this embodiment, a fault reporting module connected to the fault diagnosis module is also included, which is used to report the fault according to the type of the fault diagnostic code RDTC, the corresponding fault level and the robot system level control.

[0093] In this embodiment, a fault prediction module is also included at the input end of the fault monitoring module, which is used to predict whether the current robot has the conditions to perform the task and whether a fault will occur when performing the current task based on the task type of the currently received task, the status of the work auxiliary equipment, the status of the robot main body equipment and the robot main body task status. When the prediction is that the conditions to perform the task are met and no fault will occur when performing the current task, the robot is controlled to perform the current task. The robot main body task status is the status of the robot performing the task.

[0094] The mobile robot fault diagnosis device of this embodiment corresponds one-to-one to the above-mentioned mobile robot fault diagnosis method, and will not be described in detail here.

[0095] This embodiment also provides an electronic device, including a processor and a memory, wherein the memory is used to store a computer program, and the processor is used to execute the computer program to perform the above method.

[0096] This embodiment also provides a computer-readable storage medium storing a computer program, which implements the above method when executed.

[0097] Example 2:

[0098] This embodiment is substantially the same as Embodiment 1, except that, considering that mobile robots operate in the form of tasks, different task environments correspond to different tasks, and the mobile robot performs operations according to different tasks. Furthermore, task execution must be combined with the mobile robot itself, the operating environment, and auxiliary work equipment. This embodiment, before real-time monitoring of the fault status of the mobile robot during task execution, also includes predicting whether the current robot has the conditions to execute the task and whether a fault will occur during the execution of the current task based on the task type of the currently received task, the status of the auxiliary work equipment, the status of the robot itself, and the task status of the robot itself, thereby implementing fault prediction for tasks issued by the robot's upper-level system. When it is predicted that the conditions for executing the task are met and that the execution of the current task will not cause a fault, the robot is controlled to execute the current task. The task status of the robot itself is the status of the robot executing the task.

[0099] Through the above-mentioned fault prediction steps, this embodiment can comprehensively consider the task type, the status of the auxiliary operation equipment, the status of the robot's main equipment and the robot's main task status when the upper system issues a task to the robot to determine whether the current robot has the conditions to perform the task, and whether a fault will occur if the task is performed. This allows the mobile robot to comprehensively judge the operating conditions and predict faults in advance before performing the task, and can quickly judge the task execution conditions when the mobile robot receives the task, ensuring the safety of task execution and predicting risks in advance before the mobile robot operates.

[0100] In this embodiment, when the robot's upper-level system issues a task, it first performs a fault prediction based on four variables: the task type, the status of the auxiliary work equipment, the robot's main equipment status, and the robot's main task status. This is done to determine whether the robot is currently equipped to perform the task and whether a fault will occur during the task. The definitions of task type, auxiliary work equipment status, robot's main equipment status, and robot's main task status are shown in Table 2. After fault prediction, three fault prediction results are obtained: 1. The robot meets the operating conditions and no fault is predicted; 2. The robot meets the operating conditions and a fault is predicted; 3. The robot does not meet the operating conditions and a fault is predicted. If the robot is predicted to meet the operating conditions and no fault is detected, the robot is controlled to perform the task. If a fault occurs during the task, fault diagnosis is performed according to Example 1.

[0101] Table 2: Failure prediction parameters

[0102]

[0103] like Figure 5 As shown, in a specific application embodiment, when fault prediction is started, the task type, auxiliary equipment status, robot main equipment status and robot task status are analyzed respectively, and the task type, auxiliary equipment status, robot main equipment status and robot task status are comprehensively used to determine whether the current robot has the conditions to perform the task, and whether a fault will occur if the task is performed. If a fault is predicted, it is further determined whether the task can be executed. If it is predicted that there is a fault, the robot can perform the task; otherwise, it is predicted that there is a fault and the robot cannot perform the task; if no fault is predicted, it is determined that the robot can perform the task.

[0104] In a specific implementation, the robot's subsystems communicate over TCP / IP and update their status. These subsystems interact with hardware driver software to obtain information such as device status. When a hardware failure occurs, this information is relayed to the subsystem, and the robot continuously updates the task status during execution. Fault prediction is performed based on the specific source and nature of the failure, determining whether the task can be performed.

[0105] This embodiment predicts the faults of tasks issued by the robot's upper-level system by integrating four variables: task type, work auxiliary equipment status, robot main body equipment status, and robot main body task status. It can predict the execution risk of tasks when assigning tasks to robots. Combined with the fault diagnosis steps, it can promptly diagnose the cause of the fault after the robot fails to perform the task, and take appropriate measures to solve the fault in a timely manner. At the same time, it can report the fault in a timely manner when the robot itself cannot solve the fault, which can effectively ensure the safety and reliability of the robot's task execution.

[0106] Fault conditions vary depending on the business scenario and hardware characteristics. For example, when a robot is in manual mode, it is manually defined so that it does not accept task commands from the upper-level system and only receives commands from buttons on the robot or remote control. In this case, the fault prediction mechanism determines whether the robot can execute the task based on whether the manual mode status is triggered when receiving tasks from the upper-level system.

[0107] This embodiment also utilizes fault prediction to shield specific fault types, such as those that do not affect task execution, preventing the robot from being disrupted by these faults. For example, if the robot's music playback function malfunctions, the robot can still move and collect data. In this case, the fault prediction result indicates that the robot is capable of operating, but has a fault.

[0108] Example 3:

[0109] This embodiment combines the fault diagnosis method in Example 1 with the fault prediction method in Example 2 to form a method that can fully realize the prediction, diagnosis, processing and reporting of mobile robot faults, so as to systematically handle mobile robot faults and improve the safety and reliability of the robot system equipment as a whole. Figure 6 As shown, after starting work, first perform fault prediction according to Example 2. If a fault is predicted, report the fault. If no fault is predicted, control the execution of the task. During the execution of the task, if a fault occurs, perform fault diagnosis according to Example 1, and perform fault processing and fault reporting according to the fault diagnosis result until the fault processing is completed.

[0110] The above description is merely a preferred embodiment of the present invention and does not constitute any form of limitation to the present invention. Although the present invention has been disclosed above with reference to the preferred embodiment, it is not intended to limit the present invention. Therefore, any simple modifications, equivalent variations, and modifications to the above embodiment that do not depart from the technical solution of the present invention and are based on the technical essence of the present invention shall fall within the scope of protection of the technical solution of the present invention.

Claims

1. A mobile robot fault diagnosis method, characterized in that the steps include: Configuring corresponding fault diagnostic codes for different robot system levels, and configuring so that when a fault occurs, the fault diagnostic codes of the corresponding robot system level are triggered, and a coupling relationship exists between the fault diagnostic codes of each level; Real-time monitoring of the fault status of mobile robots during mission execution; When a fault is detected in the mobile robot, a fault diagnostic code corresponding to the robot system level is obtained; Diagnosing the fault type, fault location, and fault cause of the current fault of the mobile robot according to the acquired fault diagnostic code, wherein the fault is diagnosed based on the triggering time and coupling relationship of the fault diagnostic code; The robot system hierarchy includes a task layer corresponding to the task hierarchy, a status layer corresponding to the robot operation status hierarchy, a communication layer corresponding to the communication status hierarchy between the robot and internal devices, and a device layer corresponding to the robot internal device hierarchy. The fault diagnostic code includes fault information such as the fault type, fault location, and fault cause.

2. The mobile robot fault diagnosis method according to claim 1, characterized in that: The task layer classifies all tasks of the mobile robot and decomposes each task according to the execution stage. Each stage is configured with a corresponding fault diagnosis code. When the mobile robot is unable to perform the task when it reaches the target stage, the fault diagnostic code corresponding to the target stage is triggered.

3. The mobile robot fault diagnosis method according to claim 2, characterized in that: The fault diagnosis code of the task layer is coupled with the fault diagnosis codes of the status layer, the communication layer and the device layer respectively.

4. The mobile robot fault diagnosis method according to claim 3, characterized in that: When a fault diagnostic code of any one of the state layer, communication layer and device layer is triggered, if the mobile robot is performing a task, a corresponding task layer fault diagnostic code is triggered according to the task execution stage.

5. The mobile robot fault diagnosis method according to claim 1, characterized in that: The fault diagnostic code also includes fault code ID, DTC fault code string, error code information, solution information, potential cause information, recoverability information, repair instructions, log information where the error is located, fault level, device type, device fault source, device ID, device name, software version information corresponding to the fault code, and any one or more of the error code information.

6. The mobile robot fault diagnosis method according to claim 1, characterized in that: After diagnosing the fault type and fault location according to the acquired fault diagnostic code, the method further includes performing fault processing according to the fault diagnosis result and the robot system level corresponding to the current fault, and different fault processing measures are configured correspondingly for different robot system levels.

7. The mobile robot fault diagnosis method according to claim 6, characterized in that: When the fault occurs at the task layer, the control re-executes the task of the current stage, or performs a reset, restarts the device, reconnects the communication, or directly reports the fault and ends the task. When the fault occurs at any layer of the status layer, communication layer or device layer, the task layer fault handling mechanism will handle the fault. If the current fault diagnostic code level is lower than the preset value or does not affect task execution, the fault will only be reported without any processing.

8. The mobile robot fault diagnosis method according to any one of claims 1 to 7, characterized in that: The real-time monitoring of the fault status of the mobile robot during the execution of a task also includes predicting whether the current robot has the conditions to execute the task and whether a fault will occur during the execution of the current task based on the task type of the currently received task, the status of the operation auxiliary equipment, the status of the robot main body equipment and the robot main body task status. When the prediction is that the conditions to execute the task are met and no fault will occur during the execution of the current task, the robot is controlled to execute the current task. The robot main body task status is the status of the robot executing the task.

9. The mobile robot fault diagnosis method according to any one of claims 1 to 7, characterized in that: After diagnosing the fault type and fault location of the current fault of the mobile robot according to the acquired fault diagnostic code, the method also includes reporting the fault according to the type of the fault diagnostic code, the corresponding fault level and the robot system level control.

10. The mobile robot fault diagnosis method according to claim 9, characterized in that: When the fault diagnostic code is a type that the robot cannot self-repair, or when the corresponding fault level is judged to be greater than the preset level according to the fault diagnostic code, the control reports the fault information to the robot's upper system; when the task is canceled or the robot is reset, the task layer fault diagnostic code is controlled not to be reported; when the fault in any layer of the status layer, communication layer and device layer is eliminated, the corresponding fault diagnostic code is controlled not to be reported, otherwise the fault diagnostic code continues to be reported, and the robot is controlled to stop executing new tasks.

11. A mobile robot fault diagnosis device, characterized in that: include: A fault diagnostic code configuration module is used to configure corresponding fault diagnostic codes for different robot system levels, and to configure so that when a fault occurs, the fault diagnostic code of the corresponding robot system level is triggered, and a coupling relationship exists between the fault diagnostic codes of each level; Fault monitoring module, used to monitor the fault status of the mobile robot in real time during the execution of tasks; The RDTC acquisition module is used to obtain the fault diagnostic code of the corresponding robot system level when a fault is detected in the mobile robot; a fault diagnosis module, configured to diagnose the type and location of a current fault of the mobile robot according to the acquired fault diagnostic code, wherein the fault is diagnosed according to the triggering time and coupling relationship of the fault diagnostic code; The robot system hierarchy includes a task layer corresponding to the task hierarchy, a status layer corresponding to the robot operation status hierarchy, a communication layer corresponding to the communication status hierarchy between the robot and internal devices, and a device layer corresponding to the robot internal device hierarchy. The fault diagnostic code includes fault information such as the fault type and the fault location.

12. The mobile robot fault diagnosis device according to claim 11, characterized in that: It also includes a fault processing module connected to the fault diagnosis module, which is used to perform fault processing according to the fault diagnosis result and the robot system level corresponding to the current fault. Different robot system levels are configured with different fault processing measures.

13. The mobile robot fault diagnosis device according to claim 11, characterized in that: It also includes a fault reporting module connected to the fault diagnosis module, which is used to report faults according to the type of fault diagnosis code, the corresponding fault level and the robot system level control.

14. The mobile robot fault diagnosis device according to claim 11, 12 or 13, characterized in that: It also includes a fault prediction module arranged at the input end of the fault monitoring module, which is used to predict whether the current robot has the conditions to perform the task and whether a fault will occur when performing the current task based on the task type of the currently received task, the status of the operation auxiliary equipment, the status of the robot main body equipment and the robot main body task status. When the prediction is that the conditions to perform the task are met and no fault will occur when performing the current task, the robot is controlled to perform the current task. The robot main body task status is the status of the robot performing the task.

15. An electronic device comprising a processor and a memory, wherein the memory is used to store a computer program, wherein: The processor is configured to execute the computer program to perform the method according to any one of claims 1 to 10.

16. A computer-readable storage medium storing a computer program, characterized in that: When the computer program is executed, the method according to any one of claims 1 to 10 is implemented.

Images