Robot self-diagnosis and self-recovery method and system

Abstract

The invention discloses a robot self-diagnosis and self-recovery method and system, and the method comprises the steps: 1, carrying out the fault detection of a robot, and obtaining the error information data if a fault error is detected; 2, the error reporting information data are matched with the content of a self-diagnosis and self-recovery data dictionary, and if the error reporting information data are matched with a certain item in the self-diagnosis and self-recovery dictionary, an error clearing processing mechanism corresponding to the item is called to carry out fault clearing processing on the robot; step 3, judging whether the fault is eliminated or not after the fault is cleared, and if the fault is eliminated, completing the self-diagnosis and self-recovery process of the robot; and if the fault is not eliminated, sequentially performing layer-by-layer progressive processing modes such as re-enabling processing, process restarting, system restarting and complete machine power-off restarting to eliminate the fault of the robot, and completing the self-diagnosis and self-recovery process of the robot. According to the method and the system, the system has expandability and universality of subsequent error report processing, and the customization cost can be effectively reduced.

Description

Technical Field

[0001] The present invention relates to the technical field of intelligent inspection robots, and in particular to a robot self-diagnosis and self-recovery method and system. Background Art

[0002] At present, intelligent inspection robots may encounter various occasional problems during autonomous operation, which may cause the robot to be unable to continue to complete the operation. The existing technical solutions are mainly implemented by the control unit collecting real-time data from each control unit; summarizing and analyzing the real-time data corresponding to each control unit; uploading the results of the summary analysis to the robot's decision-making unit, which performs another analysis based on the summary analysis results of all control units to obtain a robot diagnosis result report, and then pushes the robot diagnosis result report to the operation and maintenance personnel in real time or regularly based on the diagnosis results, and then manually handles the abnormalities based on the robot fault alarm information. The main problems are: It only collects and analyzes device data, does not establish a corresponding relationship between alarm data and robot recovery measures, and implements self-recovery through specific rules; There is no corresponding robot self-recovery solution for some faults that the robot itself cannot locate the cause of; When a corresponding alarm occurs, human intervention is required and self-recovery and intelligent continuous operation cannot be achieved. Summary of the invention

[0003] The purpose of the present invention is to overcome the shortcomings of the prior art intelligent inspection robot that when a fault occurs, there is a lack of a self-recovery scheme, human intervention is required, and the fault handling efficiency is low, which affects the normal operation of the intelligent inspection robot, and to provide a robot self-diagnosis and self-recovery method and system.

[0004] The purpose of the present invention is achieved through the following technical solutions: A robot self-diagnosis and self-recovery method comprises the following steps: Step 1: perform fault detection on the robot, and if a fault error is detected, obtain the error information data; Step 2, match the error information data with the contents of the self-diagnosis and self-recovery data dictionary. If the error information data matches an item in the self-diagnosis and self-recovery dictionary, call the error clearing processing mechanism corresponding to the item to perform fault clearing processing on the robot; Step 3, determine whether the fault is eliminated after the fault clearing processing. If the fault is eliminated, complete the robot self-diagnosis and self-recovery process; if the fault is not eliminated, perform secondary fault clearing processing to clear the robot's fault and complete the robot self-diagnosis and self-recovery process.

[0005] The design of this solution can self-diagnose the current fault cause or fault status of the robot in the event of a situation that affects the normal and continuous operation of the robot, and realize self-recovery by combining specific or general mechanism recovery logic. Since there are many kinds of robot failures, including software failures, hardware failures, etc., and the diversity of peripherals exacerbates the complexity of robot abnormality detection, it is necessary to collect and detect software and hardware failure information in a more comprehensive and specific manner and enrich the content of the data dictionary. For failures that cannot be self-diagnosed or for which a self-diagnosis model cannot be established, a general self-recovery solution is implemented based on the current state of the robot.

[0006] Preferably, the secondary fault clearing process includes sequentially performing re-enabling processing, process restarting, system restarting and whole machine power-off restarting.

[0007] Preferably, the fault error reporting includes hardware fault error reporting and software fault error reporting, the fault error reporting includes hardware fault error reporting and software fault error reporting, the self-diagnosis and self-recovery data dictionary corresponds to a hardware fault error reporting data dictionary and a software fault error reporting data dictionary, the hardware fault error reporting data dictionary is included according to the hardware device number, and the software fault error reporting data dictionary is included according to the software type number.

[0008] Preferably, the step 2 is specifically as follows: when a fault error is detected, first determine whether it is a hardware fault error or a software fault error. If it is a hardware fault error, obtain the hardware device number, find the error clearing mechanism corresponding to the hardware device number in the hardware fault error data dictionary, and perform fault clearing on the robot. If it is a software fault error, obtain the software type number, find the error clearing mechanism corresponding to the software type number in the software fault error data dictionary, and perform fault clearing on the robot.

[0009] Preferably, in the step 2, when a fault error is detected, the hardware device number or the software type number is not in the preset self-diagnosis and self-recovery data dictionary, a diagnostic model is first established, and the fault is cleared through the diagnostic model. The self-diagnosis and self-recovery data dictionary records the error clearing process and establishes a matching error clearing mechanism to complete the update of the self-diagnosis and self-recovery data dictionary.

[0010] Preferably, the robot self-diagnosis and self-recovery method also integrates the error clearing mechanism, analyzes the execution actions of all error clearing mechanisms, and if there are multiple error clearing mechanisms with the same execution actions, updates the self-diagnosis and self-recovery dictionary, integrating multiple hardware fault error reports or software fault error reports into a category of the data dictionary, corresponding to one error clearing mechanism.

[0011] Preferably, in the step 2, before the robot is subjected to fault clearing processing, it is determined whether the process has been restarted, the system has been restarted, and the whole machine has been powered off and restarted. If the process has not been restarted, the system has not been restarted, and the whole machine has not been powered off and restarted, then the fault clearing processing is performed. The prerequisite for restarting the system is that the fault error is still detected after the process has been restarted, and the prerequisite for powering off and restarting the whole machine is that the fault error is still detected after the system has been restarted. If the fault error is still detected after the whole machine is powered off and restarted, the robot stops working and reminds relevant personnel.

[0012] Preferably, the fault clearing process is executed m times. If the fault is still not eliminated after executing m times, it is determined whether it is a hardware fault error. If it is a hardware fault error, the hardware is re-enabled. If the fault is still not eliminated after trying to re-enable the hardware m times, the process is restarted. If it is not a hardware fault error, the process is directly restarted.

[0013] A robot self-diagnosis and self-recovery system, comprising: A fault detection unit, used for performing fault detection on the robot; A fault analysis unit is used to analyze the faults of the robot and output the corresponding fault handling method; The execution unit performs self-diagnosis and self-recovery processing on the robot according to the fault processing method obtained by the fault analysis unit; The system executes a robot self-diagnosis and self-recovery method during operation.

[0014] A computer-readable storage medium stores a computer program, wherein the computer-readable storage medium stores instructions, and when the instructions are executed on a computer or a processor, the computer or the processor executes the steps of the above method.

[0015] The beneficial effects of the present invention are as follows: the present invention enters the faults for which the robot system can establish a self-diagnosis model into the self-diagnosis and self-recovery data dictionary to uniformly plan the categories of hardware errors and software errors, so that the system has scalability and universality of subsequent error processing, which can effectively reduce customization costs; for faults for which a self-diagnosis model cannot be established, a step-by-step initialization scheme is adopted according to the current operating status of the robot, including re-enabling processing, process restarting, system restarting, and whole machine power off processing in a step-by-step manner, so as to restore the robot's autonomous operation at the lowest cost; an independent and complete self-diagnosis and self-recovery processing system realizes the decoupling of exception processing logic, improves the stability of the robot's operation, and does not require human intervention. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] Figure 1 It is a flow chart of the present invention. DETAILED DESCRIPTION

[0017] Example embodiments will now be described more fully with reference to the accompanying drawings. However, example embodiments can be implemented in a variety of forms and should not be construed as limited to the examples set forth herein; rather, these embodiments are provided so that this application will be more comprehensive and complete and fully convey the concept of the example embodiments to those skilled in the art.

[0018] In addition, described feature, structure or characteristic can be combined in one or more embodiments in any suitable manner. In the following description, many specific details are provided to provide a full understanding of the embodiments of the present application. However, those skilled in the art will appreciate that the technical scheme of the present application can be put into practice without one or more of the specific details, or other methods, components, devices, steps, etc. can be adopted. In other cases, known methods, devices, realizations or operations are not shown or described in detail to avoid blurring the various aspects of the application.

[0019] The flowcharts shown in the accompanying drawings are only exemplary and do not necessarily include all the contents and operations / steps, nor must they be executed in the order described. For example, some operations / steps can be decomposed, and some operations / steps can be combined or partially combined, so the actual execution order may change according to actual conditions.

[0020] Example: A robot self-diagnosis and self-recovery method, such as Figure 1 As shown, the following steps are included: Step 1: perform fault detection on the robot, and if a fault error is detected, obtain the error information data; Step 2, match the error information data with the contents of the self-diagnosis and self-recovery data dictionary. If the error information data matches an item in the self-diagnosis and self-recovery dictionary, call the error clearing processing mechanism corresponding to the item to perform fault clearing processing on the robot; Step 3, determine whether the fault is eliminated after the fault clearing processing. If the fault is eliminated, complete the robot self-diagnosis and self-recovery process; if the fault is not eliminated, re-enable processing, process restart, system restart, and whole machine power off and restart are performed in sequence to clear the robot's fault and complete the robot self-diagnosis and self-recovery process.

[0021] The method of this embodiment is particularly suitable for indoor wheeled, outdoor wheeled, and track-mounted intelligent inspection robots. In the event of a situation that affects the normal and continuous operation of the robot, the robot can self-diagnose the current fault cause or fault state, and realize self-recovery in combination with specific or general mechanism recovery logic. Since there are many kinds of robot failures, including software failures, hardware failures, etc., and the diversity of peripherals further increases the complexity of robot abnormality detection, it is necessary to collect and detect software and hardware fault information in a more comprehensive and specific manner to enrich the content of the data dictionary.

[0022] For faults that cannot be self-diagnosed or for which a self-diagnosis model cannot be established, a general self-recovery solution is implemented based on the current state of the robot. For example, a common robot fault phenomenon is "fault stops on the inspection road". The causes of the fault include deviating from the track, program crash, industrial computer crash, program pseudo-death, etc. For these faults, it is impossible to establish a self-diagnosis model. In this case, it is determined that the current robot is in the inspection motion state. If the motion state is detected to stop within a certain period of time, the robot software or system initialization solution is used to detect whether the robot has returned to the inspection motion state; for example, if the robot is in the charging state and an unknown fault occurs, the initialization solution is used to detect whether the robot has returned to the charging state.

[0023] The error clearing mechanism is, for example, a driving motor error, in which the motor is stopped first and then the software is cleared to determine whether the driving motor can recover by itself.

[0024] The fault error reporting includes hardware fault error reporting and software fault error reporting. The hardware devices are numbered from d1 to dn, and the software types are numbered from r1 to rn. The self-diagnosis and self-recovery data dictionary includes a hardware fault error reporting data dictionary [Ed1, Edm] and a software fault error reporting data dictionary [Er1, Erm]. The step 2 is specifically as follows: when a fault error is detected, first determine whether it is a hardware fault error reporting or a software fault error reporting. If it is a hardware fault error reporting, obtain the hardware device number, find the error clearing processing mechanism corresponding to the hardware device number in the hardware fault error reporting data dictionary, and perform fault clearing processing on the robot. If it is a software fault error reporting, obtain the software type number, find the error clearing processing mechanism corresponding to the software type number in the software fault error reporting data dictionary, and perform fault clearing processing on the robot.

[0025] In step 2, when a fault is detected, if the hardware device number or software type number is not in the preset self-diagnosis and self-recovery data dictionary, a diagnostic model is first established, and the fault is cleared through the diagnostic model. The self-diagnosis and self-recovery data dictionary records the process of clearing the error and establishes a matching clearing mechanism to complete the update of the self-diagnosis and self-recovery data dictionary. In the specific reference of this solution, for example, if the robot wheel slips, the speed difference and running distance between the driving wheels are generally detected, and the solution of first stopping and then running a distance in the opposite direction of travel and then moving forward to determine whether it is slipping and self-recovering.

[0026] The robot self-diagnosis and self-recovery method also integrates the error clearing and processing mechanisms, analyzes the execution actions of all error clearing and processing mechanisms, and updates the self-diagnosis and self-recovery dictionary if multiple error clearing and processing mechanisms have the same execution actions. Multiple hardware fault errors or software fault errors are integrated into a category of the data dictionary, corresponding to one error clearing and processing mechanism.

[0027] The design of this solution reasonably classifies software and hardware failures, and handles different failure phenomena but the same type of failure causes and the same type of failure solutions in a consistent manner, thereby avoiding redundant customization and achieving the purpose of reducing costs and universal processing. For example, when problems such as positioning timeout, mileage timeout, and gyroscope timeout occur, they can be classified as problems with the positioning and navigation software, and a series of logical rules such as error clearing and self-restarting of the positioning and navigation software can be used to solve the problems themselves.

[0028] In the step 2, before the robot is subjected to fault clearing processing, it is judged whether the process restart, system restart and whole machine power-off restart have been performed. If the process restart, system restart and whole machine power-off restart have not been performed, fault clearing processing is performed again. The prerequisite for system restart is that the fault error is still detected after the process restart. The prerequisite for whole machine power-off restart is that the fault error is still detected after the system restart. If the fault error is still detected after the whole machine is powered off and restarted, the robot stops working and reminds relevant personnel.

[0029] The fault clearing process is executed m times. If the fault is still not eliminated after executing m times, it is determined whether it is a hardware fault error. If it is a hardware fault error, the hardware is re-enabled. If the fault is still not eliminated after trying to re-enable the hardware m times, the process is restarted; if it is not a hardware fault error, the process is directly restarted.

[0030] The design of this solution avoids falling into an endless loop of repeated invalid operations when processing fault errors, and sets the processing priority, giving top priority to fault clearing and repairing the fault errors, and then re-enabling processing, process restart, system restart, whole machine power off and restart, etc., in a progressive manner, so as to restore the robot's autonomous operation at the lowest cost; the independent and complete processing system realizes the decoupling of exception handling logic and improves the stability of the robot's operation.

[0031] A robot self-diagnosis and self-recovery system, comprising: A fault detection unit, used for performing fault detection on the robot; A fault analysis unit is used to analyze the faults of the robot and output the corresponding fault handling method; The execution unit performs self-diagnosis and self-recovery processing on the robot according to the fault processing method obtained by the fault analysis unit; The system executes a robot self-diagnosis and self-recovery method during operation.

[0032] Those skilled in the art will readily appreciate other embodiments of the present application after considering the specification and practicing the embodiments disclosed herein. The present application is intended to cover any variations, uses or adaptations of the present application, which follow the general principles of the present application and include common knowledge or customary technical means in the art that are not disclosed in the present application.

[0033] It should be understood that the present application is not limited to the precise structures that have been described above and shown in the drawings, and that various modifications and changes may be made without departing from the scope thereof. The scope of the present application is limited only by the appended claims.

Claims

1. A robot self-diagnosis and self-recovery method, characterized in that: The following steps are involved: Step 1: perform fault detection on the robot, and if a fault error is detected, obtain the error information data; Step 2, matching the error information data with the contents of the self-diagnosis and self-recovery data dictionary. If the error information data matches an item in the self-diagnosis and self-recovery dictionary, the error clearing processing mechanism corresponding to the item is called to perform fault clearing processing on the robot; Step 3: After the fault clearing process is performed, determine whether the fault has been eliminated. If the fault has been eliminated, the robot self-diagnosis and self-recovery process is completed; If the fault is not eliminated, a secondary fault clearing process is performed to clear the robot's fault and complete the robot's self-diagnosis and self-recovery process.

2. A robot self-diagnosis and self-recovery method according to claim 1, characterized in that: The secondary fault clearing process includes re-enabling, process restart, system restart and whole machine power off and restart.

3. A robot self-diagnosis and self-recovery method according to claim 1, characterized in that: The fault error reports include hardware fault error reports and software fault error reports. The self-diagnosis and self-recovery data dictionary corresponds to a hardware fault error report data dictionary and a software fault error report data dictionary. The hardware fault error report data dictionary is recorded according to the hardware device number, and the software fault error report data dictionary is recorded according to the software type number.

4. A robot self-diagnosis and self-recovery method according to claim 3, characterized in that: The step 2 is specifically as follows: when a fault error is detected, first determine whether it is a hardware fault error or a software fault error. If it is a hardware fault error, obtain the hardware device number, find the error clearing processing mechanism corresponding to the hardware device number in the hardware fault error data dictionary, and perform fault clearing processing on the robot. If it is a software fault error, obtain the software type number, find the error clearing processing mechanism corresponding to the software type number in the software fault error data dictionary, and perform fault clearing processing on the robot.

5. A robot self-diagnosis and self-recovery method according to claim 4, characterized in that: In the step 2, when a fault error is detected, the hardware device number or the software type number is not in the preset self-diagnosis and self-recovery data dictionary, a diagnostic model is first established, and the fault is cleared through the diagnostic model. The self-diagnosis and self-recovery data dictionary records the error clearing process and establishes a matching error clearing mechanism to complete the update of the self-diagnosis and self-recovery data dictionary.

6. A robot self-diagnosis and self-recovery method according to claim 1, characterized in that: The error clearing and processing mechanisms are also integrated, and the execution actions of all error clearing and processing mechanisms are analyzed. If multiple error clearing and processing mechanisms have the same execution actions, the self-diagnosis and self-recovery dictionary is updated, and multiple hardware fault errors or software fault errors are integrated into a category of the data dictionary, corresponding to one error clearing and processing mechanism.

7. A robot self-diagnosis and self-recovery method according to claim 1, characterized in that: In the step 2, before the robot is subjected to fault clearing processing, it is judged whether the process restart, system restart and whole machine power-off restart have been performed. If the process restart, system restart and whole machine power-off restart have not been performed, fault clearing processing is performed again. The prerequisite for system restart is that the fault error is still detected after the process restart. The prerequisite for whole machine power-off restart is that the fault error is still detected after the system restart. If the fault error is still detected after the whole machine is powered off and restarted, the robot stops working and reminds relevant personnel.

8. A robot self-diagnosis and self-recovery method according to claim 7, characterized in that: The fault clearing process is executed m times. If the fault is still not eliminated after executing m times, it is determined whether it is a hardware fault error. If it is a hardware fault error, the hardware is re-enabled. If the fault is still not eliminated after trying to re-enable the hardware m times, the process is restarted; if it is not a hardware fault error, the process is directly restarted.

9. A robot self-diagnosis and self-recovery system, characterized in that: include: A fault detection unit, used for performing fault detection on the robot; A fault analysis unit is used to analyze the faults of the robot and output the corresponding fault handling method; The execution unit performs self-diagnosis and self-recovery processing on the robot according to the fault processing method obtained by the fault analysis unit; The system executes a robot self-diagnosis and self-recovery method as described in any one of claims 1 to 6 when running.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that: The computer-readable storage medium stores instructions, and when the instructions are executed on a computer or a processor, the computer or the processor executes the steps of the method according to any one of claims 1 to 8.

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