Remote control vehicle automatic reset method, reset system and readable storage medium

Abstract

The application belongs to the technical field of engineering elements, and particularly relates to a remote control vehicle automatic resetting method, a resetting system and a readable storage medium. The remote control vehicle automatic resetting method comprises the following steps: a controller calculates the variance of each sensing data in a current abnormal data group to determine whether a steering valve sensor is abnormal or whether resetting of the steering valve is to be confirmed; when it is determined that resetting of the steering valve is to be confirmed, the variance of each sensing data in a next abnormal data group is calculated to determine whether the steering valve sensor is abnormal or whether resetting of the steering valve is to be confirmed; and the controller compares the variance of each sensing data in the abnormal data group with a variance setting optimal value to adjust a first setting quantity. The application can offset random noise generated by the steering valve sensor, determine performance attenuation or abnormality of the steering valve sensor according to fluctuation of the abnormal data group, avoid frequent locking or resetting of the steering valve, accurately determine whether the steering is faulty, and enable the remote control vehicle to retain the steering function when no steering fault occurs.

Description

Technical Field

[0001] This invention belongs to the field of engineering components technology, specifically relating to steering valve devices, and more particularly to a remote-controlled vehicle automatic reset method, reset system, and readable storage medium. Background Technology

[0002] Traditional port automation equipment remote control systems need to meet the EN1175 certification standard. When the remote control vehicle malfunctions, all components, including the steering valve, will be forcibly locked.

[0003] However, because the standard is strict and lacks consideration for maintaining the basic steering function in the event of a failure, the steering function will still fail even in the event of a minor fault, leading to a series of dangerous situations. For example, in industrial automation production scenarios, it may lead to serious consequences such as equipment collisions and data loss.

[0004] Therefore, there is an urgent need to develop a new method, system and readable storage medium for automatic reset of remote-controlled vehicles to solve the technical problem of retaining basic steering function of remote-controlled vehicles in the event of non-steering failures, in order to bypass the EN1175 certification standard.

[0005] It should be noted that the information disclosed in this background section is only for understanding the background technology of the present application concept, and therefore, the above description is not considered to constitute prior art information. Summary of the Invention

[0006] This disclosure provides at least one method, system, and readable storage medium for automatically resetting a remotely controlled vehicle.

[0007] In a first aspect, embodiments of this disclosure provide a method for automatically resetting a remotely controlled vehicle, comprising: a controller acquiring and storing sensor data sets via a steering valve sensor, and calculating the average value of each sensor data set; when the average value exceeds a first preset threshold, the controller controls the steering valve to lock; when the average value does not exceed the first preset threshold, the controller selects all sensor data in each sensor data set that exceeds a second preset threshold, and sequentially forms an abnormal data set; the controller sets the number of sensor data in each abnormal data set to a first preset number, and calculates the variance of each sensor data in the abnormal data set, thereby controlling... The controller compares the variance of each sensor data in the abnormal data group with the set variance optimal value to adjust the first set quantity until the variance of each sensor data in the abnormal data group and the set variance optimal value tend to be consistent; and / or, the controller calculates the variance of each sensor data in the current abnormal data group to initially determine whether the steering valve sensor is in an abnormal state or the steering valve is in a reset pending confirmation state; wherein, when the controller determines that the steering valve is in a reset pending confirmation state, the controller calculates the variance of each sensor data in the next abnormal data group to verify whether the steering valve sensor is in an abnormal state or the steering valve is in a reset confirmation state.

[0008] In one alternative implementation, the controller sets a data processing cycle to acquire several sensing data collected by the steering valve sensor within the data processing cycle, thereby forming a sensing data set, and each sensing data is acquired by the steering valve sensor within one acquisition cycle.

[0009] In one optional implementation, the controller calculates the variance of each sensor data in the current abnormal data group and compares the variance of each sensor data in the current abnormal data group with a variance set threshold; when the variance of each sensor data in the current abnormal data group exceeds the variance set threshold, the controller determines that the steering valve sensor is in an abnormal state; when the variance of each sensor data in the current abnormal data group is within the variance set threshold, the controller determines that the steering valve is in a reset pending confirmation state.

[0010] In one optional implementation, when the controller determines that the steering valve is in a reset pending confirmation state, the controller calculates the variance of each sensor data in the next abnormal data group and compares the variance of each sensor data in the abnormal data group with a variance set threshold; when the variance of each sensor data in the abnormal data group exceeds the variance set threshold, the controller determines that the steering valve sensor is in an abnormal state; when the variance of each sensor data in the abnormal data group is within the variance set threshold, the controller determines that the steering valve is in a reset confirmation state.

[0011] In one optional implementation, when the variance of each sensor data in the abnormal data group is within the variance setting threshold and is inconsistent with the variance setting good value, the controller incrementally increases the first set number to obtain the corresponding abnormal data group, calculates the variance of each sensor data in the abnormal data, and compares the variance of each sensor data in the abnormal data group with the variance setting good value until the variance of each sensor data in the abnormal data group tends to be consistent with the variance setting good value, so as to redetermine the first set number.

[0012] In one optional implementation, when the variance of each sensor data in the abnormal data group is within the variance setting threshold and is inconsistent with the variance setting good value, the controller obtains the corresponding abnormal data group by step-decreasing the first set number, calculates the variance of each sensor data in the abnormal data, and compares the variance of each sensor data in the abnormal data group with the variance setting good value until the variance of each sensor data in the abnormal data group tends to be consistent with the variance setting good value, so as to redetermine the first set number.

[0013] Secondly, this disclosure also provides a remote-controlled vehicle automatic reset system, comprising: a controller and a steering valve sensor; the controller acquires and stores sensor data sets through the steering valve sensor, and calculates the average value of each sensor data set; when the average value exceeds a first preset threshold, the controller controls the steering valve to lock; when the average value does not exceed the first preset threshold, the controller selects all sensor data in each sensor data set that exceeds a second preset threshold, and sequentially forms an abnormal data set; the controller sets the number of sensor data in each abnormal data set to a first preset number, and calculates the value of each sensor data in the abnormal data set. The controller compares the variance of each sensor data in the abnormal data group with the set variance optimal value to adjust the first set quantity until the variance of each sensor data in the abnormal data group and the set variance optimal value tend to be consistent; and / or, the controller calculates the variance of each sensor data in the current abnormal data group to initially determine whether the steering valve sensor is in an abnormal state or the steering valve is in a reset pending confirmation state; wherein, when the controller determines that the steering valve is in a reset pending confirmation state, the controller calculates the variance of each sensor data in the next abnormal data group to verify whether the steering valve sensor is in an abnormal state or the steering valve is in a reset confirmation state.

[0014] In one alternative implementation, the remote vehicle automatic reset system is adapted to use the remote vehicle automatic reset method described above.

[0015] Thirdly, this disclosure also provides a non-transitory readable storage medium storing a computer program / instructions thereon, which, when executed by a processor, implements the steps of the above-described remote vehicle automatic reset method.

[0016] Fourthly, this disclosure also provides a computer program product, including a computer program / instructions, which, when executed by a processor, implement the steps of the above-described remote vehicle automatic reset method.

[0017] The beneficial effects of this invention are that it can offset the random noise generated by the steering valve sensor by calculating the average value of each sensor data group, and establish abnormal data groups to obtain data fluctuations. Based on the fluctuations of the abnormal data groups, it can determine whether the steering valve sensor performance is degraded or abnormal. If the steering valve sensor performance is degraded, an alarm will be triggered, and the steering valve will be reset. Otherwise, the steering valve will not be reset. Furthermore, the first set number is adjusted in real time according to the performance of the steering valve sensor to avoid the problem of frequent locking or resetting of the steering valve. It can accurately determine whether there is a steering fault and achieve the goal of exceeding the EN1175 certification standard when there is no steering fault, so that the remote-controlled vehicle retains the steering function.

[0018] Other features and advantages of the invention will be set forth in the following description, and will be apparent in part from the description, or may be learned by practicing the invention. The objects and other advantages of the invention are realized and obtained through the structures particularly pointed out in the description and the drawings.

[0019] To make the above-mentioned objects, features and advantages of the present invention more apparent and understandable, preferred embodiments are described below in detail with reference to the accompanying drawings. Attached Figure Description

[0020] To more clearly illustrate the specific embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the specific embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are some embodiments of the present invention. For those skilled in the art, other drawings can be obtained from these drawings without creative effort.

[0021] Figure 1 A flowchart illustrating a remote-controlled vehicle automatic reset method provided in this embodiment of the present disclosure; Figure 2 A flowchart for acquiring a group of sensor data provided in an embodiment of this disclosure; Figure 3 A flowchart illustrating a steering valve reset confirmation process provided in this embodiment of the present disclosure; Figure 4 A flowchart for confirming a steering valve reset is provided in an embodiment of this disclosure; Figure 5 A flowchart for re-determining a first predetermined quantity in a step-by-step increment is provided as an embodiment of this disclosure; Figure 6 A flowchart for re-determining a first predetermined quantity using a step-down approach is provided as an embodiment of this disclosure; Figure 7 This is a schematic diagram of a remote-controlled vehicle automatic reset system provided in an embodiment of the present disclosure. Detailed Implementation

[0022] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the technical solutions of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0023] The terminology used herein is for the purpose of describing specific exemplary configurations only and is not intended to be limiting. As used herein, the singular articles “a,” “an,” and “the” may also be intended to include plural forms unless otherwise clearly stated herein. The terms “comprising,” “including,” and “having” are inclusive and thus specify the presence of features, steps, operations, elements, and / or components, but do not preclude the presence or addition of one or more other features, steps, operations, elements, components, and / or combinations thereof. The method steps, processes, and operations described herein should not be construed as requiring them to be performed in the specific order discussed or shown, unless specifically identified as such. Additional or alternative steps may be employed.

[0024] As used herein, the phrases “in one embodiment,” “according to one embodiment,” “in some embodiments,” etc., generally refer to the fact that a particular feature, structure, or characteristic following the phrase can be included in at least one embodiment of this disclosure. Therefore, a particular feature, structure, or characteristic can be included in more than one embodiment of this disclosure, such that these phrases do not necessarily refer to the same embodiment. As used herein, the terms “example,” “exemplary,” etc., are used to “serve as an example, instance, or illustration.” Any implementation, aspect, or design described herein as “example” or “exemplary” is not necessarily to be construed as preferred or superior to other implementations, aspects, or designs. Rather, the use of the terms “example,” “exemplary,” etc., is intended to present concepts in a specific manner.

[0025] Research has revealed that traditional remote control systems for port automation equipment must meet the EN1175 certification standard. In the event of a malfunction in the remote-controlled vehicle, all components, including the steering valve, are forcibly locked. However, due to the stringent nature of this standard and its lack of consideration for maintaining basic steering functions in fault conditions, even minor malfunctions can cause steering failure, leading to a series of dangerous situations. For example, in industrial automation production scenarios, this could result in serious consequences such as equipment collisions and data loss.

[0026] Based on the above research, this disclosure provides a remote vehicle automatic reset method, reset system, and readable storage medium that can cancel out random noise generated by the steering valve sensor, determine the performance degradation or abnormality of the steering valve sensor based on the fluctuation of abnormal data sets, avoid the problem of frequent locking or reset of the steering valve, accurately determine whether it is a steering fault, and achieve the goal of bypassing the EN1175 certification standard when there is no steering fault, so that the remote vehicle retains the steering function.

[0027] The shortcomings of the above solutions are the result of the inventor's practical experience and careful research. Therefore, the discovery process of the above problems and the solutions proposed in this disclosure below should be considered as the inventor's contribution to this disclosure.

[0028] It should be noted that similar labels and letters in the following figures indicate similar items. Therefore, once an item is defined in one figure, it does not need to be further defined and explained in subsequent figures.

[0029] The following detailed description of some embodiments of the present invention is provided in conjunction with the accompanying drawings. Unless otherwise specified, the following embodiments and features can be combined with each other.

[0030] like Figures 1 to 6 As shown, at least one embodiment provides a method for automatically resetting a remotely controlled vehicle, comprising: a controller acquiring and storing sensor data sets via a steering valve sensor, and calculating the average value of each sensor data set; when the average value exceeds a first preset threshold, the controller controls the steering valve to lock; when the average value does not exceed the first preset threshold, the controller selects all sensor data in each sensor data set that exceeds a second preset threshold, and sequentially forms an abnormal data set; the controller sets the number of sensor data in each abnormal data set to a first preset number, and calculates the variance of each sensor data in the abnormal data set, thereby controlling... The controller compares the variance of each sensor data in the abnormal data group with the set variance optimal value to adjust the first set quantity until the variance of each sensor data in the abnormal data group and the set variance optimal value tend to be consistent; and / or, the controller calculates the variance of each sensor data in the current abnormal data group to initially determine whether the steering valve sensor is in an abnormal state or the steering valve is in a reset pending confirmation state; wherein, when the controller determines that the steering valve is in a reset pending confirmation state, the controller calculates the variance of each sensor data in the next abnormal data group to verify whether the steering valve sensor is in an abnormal state or the steering valve is in a reset confirmation state.

[0031] In at least one embodiment, the random noise generated by the steering valve sensor can be offset by calculating the average value of each sensor data group, and the data fluctuation situation can be obtained by establishing an abnormal data group. The performance degradation or abnormality of the steering valve sensor can be judged based on the fluctuation situation of the abnormal data group. If the performance degradation of the steering valve sensor causes an alarm, the steering valve is reset; otherwise, the steering valve is not reset. Furthermore, the first set number is adjusted in real time according to the performance of the steering valve sensor to avoid the problem of frequent locking or resetting of the steering valve. It can accurately determine whether there is a steering fault and achieve the goal of bypassing the EN1175 certification standard when there is no steering fault, so that the remote-controlled vehicle retains the steering function.

[0032] In at least one embodiment, please refer to Figure 2 The controller sets a data processing cycle to acquire several sensor data collected by the steering valve sensor within the data processing cycle, thereby forming a sensor data group. Each sensor data is acquired by the steering valve sensor within one acquisition cycle.

[0033] Specifically, the controller sets the data processing cycle based on its own performance, which can improve the processing speed of sensor data.

[0034] Specifically, constructing a sensor data set enables batch processing of sensor data. Due to noise interference or voltage fluctuations during the detection process of the steering valve sensor, some sensor data may be invalid. If the controller performs the entire judgment process for each sensor data, it will cause the steering valve to lock and reset frequently. This will cause excessive load on the controller and reduce the service life of the steering valve. By forming a sensor data set, the influence of individual invalid data can be offset by the averaging effect, thereby improving the control accuracy of the steering valve and ensuring its service life.

[0035] In at least one embodiment, please refer to Figure 3 The controller calculates the variance of each sensor data in the current abnormal data group and compares the variance of each sensor data in the current abnormal data group with the variance set threshold. When the variance of each sensor data in the current abnormal data group exceeds the variance set threshold, the controller determines that the steering valve sensor is in an abnormal state. When the variance of each sensor data in the current abnormal data group is within the variance set threshold, the controller determines that the steering valve is in a reset pending confirmation state.

[0036] Specifically, by calculating the variance of each sensor data in the current abnormal data group, the overall fluctuation of the current abnormal data group can be reflected. If the variance of each sensor data in the current abnormal data group exceeds the set variance threshold, it means that the fluctuation of each sensor data in the current abnormal data group is large, and the steering valve sensor is abnormal. If the variance of each sensor data in the current abnormal data group is within the set variance threshold, it means that the fluctuation of each sensor data in the current abnormal data group is small. The sensor data in the abnormal data group exceeding the second set threshold is due to the performance degradation of the steering valve sensor itself. The steering valve itself is not problematic, and it can be determined that the steering valve needs to be reset and confirmed.

[0037] In at least one embodiment, please refer to Figure 4 When the controller determines that the steering valve is in a reset pending confirmation state, the controller calculates the variance of each sensor data in the next abnormal data group and compares the variance of each sensor data in the abnormal data group with the variance set threshold. When the variance of each sensor data in the abnormal data group exceeds the variance set threshold, the controller determines that the steering valve sensor is in an abnormal state. When the variance of each sensor data in the abnormal data group is within the variance set threshold, the controller determines that the steering valve is in a reset confirmation state.

[0038] Specifically, after the controller determines that the steering valve reset needs to be confirmed, it needs to perform a secondary confirmation of the steering valve reset to ensure that the steering valve is in a normal state and improve safety.

[0039] Specifically, by calculating the variance of each sensor data in the next abnormal data group, the overall fluctuation of the abnormal data group can be reflected. If the variance of each sensor data in the abnormal data group exceeds the set variance threshold, it means that the fluctuation of each sensor data in the abnormal data group is large, and the steering valve sensor is abnormal. If the variance of each sensor data in the abnormal data group is within the set variance threshold, it means that the fluctuation of each sensor data in the abnormal data group is small. The sensor data in the abnormal data group exceeding the second set threshold is due to the performance degradation of the steering valve sensor itself. The steering valve itself is not problematic, and it can be determined that the steering valve reset is confirmed.

[0040] Specifically, an abnormal data group is established, and the data fluctuation of the abnormal data group is analyzed. Based on the fluctuation of the abnormal data group, it is determined whether the alarm is caused by the performance degradation of the steering valve sensor or by the steering valve sensor malfunction. If the alarm is caused by the performance degradation of the steering valve sensor, the steering valve can be reset. If the steering valve sensor is malfunctioning, the steering valve cannot be reset.

[0041] In at least one embodiment, please refer to Figure 5 When the variance of each sensor data in the abnormal data group is within the variance setting threshold and is inconsistent with the variance setting good value, the controller incrementally increases the first set number to obtain the corresponding abnormal data group, calculates the variance of each sensor data in the abnormal data, and compares the variance of each sensor data in the abnormal data group with the variance setting good value until the variance of each sensor data in the abnormal data group tends to be consistent with the variance setting good value, so as to redetermine the first set number.

[0042] Specifically, when collecting normal sensor data, abnormal data sets will be collected first according to a preset number (first set number), and the variance of the abnormal data sets will be calculated. If the variance of the abnormal data sets is changing (performance degradation of the steering valve sensor), the sensor data of the abnormal data sets need to be appropriately increased or decreased in order to better offset random noise through the averaging effect, avoid the controller from frequently controlling the steering valve to lock or reset, and at the same time judge the status of the steering valve sensor in a timely manner.

[0043] Specifically, by calculating the variance of each sensor data in the abnormal data group, the overall fluctuation of the abnormal data group can be reflected. If the variance of each sensor data in the abnormal data group is inconsistent with the set optimal value of variance, it means that the sensor data in the abnormal data group was collected under conditions of large fluctuations in the performance of the steering valve sensor. At the same time, if the variance of each sensor data in the abnormal data group is within the set variance threshold, the steering valve itself is functioning well. In order to match the fluctuation period of the steering valve sensor, the variance of each sensor data in the abnormal data group is increased step by step according to the first set number. When the variance of each sensor data in the abnormal data group tends to be consistent with the set optimal value of variance, the newly determined first set number can meet the requirements and can determine whether the steering valve sensor is abnormal at the fastest speed.

[0044] In at least one embodiment, please refer to Figure 6 When the variance of each sensor data in the abnormal data group is within the variance setting threshold and is inconsistent with the variance setting good value, the controller obtains the corresponding abnormal data group by step-decreasing the first set number, calculates the variance of each sensor data in the abnormal data, and compares the variance of each sensor data in the abnormal data group with the variance setting good value until the variance of each sensor data in the abnormal data group tends to be consistent with the variance setting good value, so as to redetermine the first set number.

[0045] Specifically, by calculating the variance of each sensor data in the abnormal data group, the overall fluctuation of the abnormal data group can be reflected. If the variance of each sensor data in the abnormal data group is inconsistent with the set optimal value of variance, it means that the sensor data in the abnormal data group was collected under conditions of large fluctuations in the performance of the steering valve sensor. At the same time, the variance of each sensor data in the abnormal data group is within the set variance threshold, and the steering valve itself is functioning well. In order to match the fluctuation period of the steering valve sensor, the variance of each sensor data in the abnormal data group is decreased step by step according to the first set number. When the variance of each sensor data in the abnormal data group tends to be consistent with the set optimal value of variance, the newly determined first set number can meet the requirements and can determine whether the steering valve sensor is abnormal at the fastest speed.

[0046] Based on the same technological concept, such as Figures 1 to 7 As shown, at least one embodiment also provides a remote-controlled vehicle automatic reset system, which includes: a controller and a steering valve sensor; the controller acquires and stores sensor data sets through the steering valve sensor, and calculates the average value of each sensor data set; when the average value exceeds a first preset threshold, the controller controls the steering valve to lock; when the average value does not exceed the first preset threshold, the controller selects all sensor data in each sensor data set that exceeds a second preset threshold, and sequentially forms an abnormal data set; the controller sets the number of sensor data in each abnormal data set to a first preset number, and calculates the value of each sensor data in the abnormal data set. The controller compares the variance of each sensor data in the abnormal data group with the set variance optimal value to adjust the first set quantity until the variance of each sensor data in the abnormal data group and the set variance optimal value tend to be consistent; and / or, the controller calculates the variance of each sensor data in the current abnormal data group to initially determine whether the steering valve sensor is in an abnormal state or the steering valve is in a reset pending confirmation state; wherein, when the controller determines that the steering valve is in a reset pending confirmation state, the controller calculates the variance of each sensor data in the next abnormal data group to verify whether the steering valve sensor is in an abnormal state or the steering valve is in a reset confirmation state.

[0047] In at least one embodiment, the remote vehicle automatic reset system is adapted to use the remote vehicle automatic reset method described above.

[0048] Based on the same technical concept, at least one embodiment also provides a non-transitory readable storage medium storing a computer program / instructions thereon, which, when executed by a processor, implements the steps of the above-described remote vehicle automatic reset method.

[0049] Based on the same technical concept, at least one embodiment also provides a computer program product, including a computer program / instructions that, when executed by a processor, implement the steps of the above-described remote vehicle automatic reset method.

[0050] In summary, this invention can offset the random noise generated by the steering valve sensor by calculating the average value of each sensor data group, and establish abnormal data groups to obtain data fluctuations. Based on the fluctuations of the abnormal data groups, it can determine whether the steering valve sensor performance has degraded or is abnormal. If the steering valve sensor performance degrades, an alarm will be triggered, and the steering valve will be reset; otherwise, the steering valve will not be reset. Furthermore, the first set number is adjusted in real time according to the steering valve sensor performance to avoid the problem of frequent locking or resetting of the steering valve. It can accurately determine whether there is a steering fault and achieve the goal of exceeding the EN1175 certification standard when there is no steering fault, so that the remote-controlled vehicle retains the steering function.

[0051] The disclosures and other solutions, examples, embodiments, modules, and functional operations described in this document can be implemented in digital electronic circuits, or computer software, firmware, or hardware, including the structures disclosed in this document and their structural equivalents, or combinations thereof. The disclosures and other embodiments can be implemented as one or more computer program products, i.e., one or more modules of computer program instructions encoded on a tangible and non-volatile computer-readable medium for execution by a data processing apparatus or for controlling the operation of the data processing apparatus. The computer-readable medium can be a machine-readable storage device, a machine-readable storage substrate, a storage device, a material composition that influences machine-readable propagated signals, or one or more of these. The terms "data processing unit" or "data processing apparatus" include all means, devices, and machines for processing data, including, for example, programmable processors, computers, or multiprocessors or computer groups. In addition to hardware, the apparatus may also include code that creates an execution environment for a computer program, such as code constituting processor firmware, a protocol stack, a database management system, an operating system, or combinations thereof. The propagated signals are artificially generated signals, such as machine-generated electrical, optical, or electromagnetic signals, which are generated to encode information for transmission to a suitable receiver device.

[0052] Computer programs (also known as programs, software, software applications, scripts, or code) can be written in any programming language (including compiled or interpreted languages) and can be deployed in any form, including as standalone programs or as modules, components, subroutines, or other units suitable for use in a computing environment. A computer program does not necessarily correspond to a file in a file system. A program can be stored in a portion of a file that holds other programs or data (e.g., one or more scripts stored in a markup language document), in a single file dedicated to that program, or in multiple coordinating files (e.g., a file storing one or more modules, subroutines, or portions of code). Computer programs can be deployed and executed on one or more computers located at a single site or distributed across multiple sites interconnected by a communication network.

[0053] The processing and logic flows described in this document can be executed by one or more programmable processors that execute one or more computer programs to perform functions by manipulating input data and generating outputs. The processing and logic flows can also be executed by special-purpose logic circuitry, and the devices can be implemented as special-purpose logic circuitry, such as FPGAs (Field-Programmable Gate Arrays) or ASICs (Application-Specific Integrated Circuits).

[0054] For example, processors suitable for executing computer programs include general-purpose and special-purpose microprocessors, as well as any one or more of any type of digital computer. Typically, the processor receives instructions and data from read-only memory or random access memory, or both. The basic components of a computer are a processor that executes instructions and one or more storage devices that store the instructions and data. Typically, a computer will also include one or more mass storage devices for storing data, such as magnetic disks, magneto-optical disks, or optical disks, or operatively coupled to receive data from or transfer data to mass storage devices, or both. However, a computer does not necessarily have such devices. Computer-readable media suitable for storing computer program instructions and data include all forms of non-volatile memory, media, and memory devices, including, for example, semiconductor memory devices such as erasable programmable read-only memory (EPROM), electrically erasable programmable read-only memory (EEPROM), and flash memory devices; magnetic disks, such as internal hard disks or removable disks; magneto-optical disks; and optical disc read-only memory (CD ROM) and digital versatile optical disc read-only memory (DVD-ROM). The processor and memory may be supplemented by dedicated logic circuitry or incorporated into dedicated logic circuitry.

[0055] While this patent document contains numerous details, it should not be construed as limiting the scope of any invention or claim, but rather as a description of features of specific embodiments of a particular invention. Certain features described in the context of individual embodiments may also be implemented in combination in a single embodiment. Conversely, various functions described in the context of a single embodiment may also be implemented individually in multiple embodiments, or in any suitable sub-combination. Furthermore, although the foregoing features may be described as functioning in certain combinations, or even initially claimed to be so, in certain circumstances, one or more features from a combination of claims may be removed from the combination, and a combination of claims may refer to a sub-combination or a variation of a sub-combination.

[0056] Similarly, although the operations are described in a specific order in the accompanying drawings, this should not be construed as requiring the specific order or sequence shown to perform such operations, or all the described operations, in order to obtain the desired result. Furthermore, the separation of various system components in the embodiments of this patent document should not be construed as requiring such separation in all embodiments.

[0057] Only some implementations and examples are described; other implementations, enhancements, and variations can be made based on the content described and illustrated in this patent document.

[0058] When no intermediate component exists other than a line, trace, or other medium between the first and second components, the first component is directly coupled to the second component. When an intermediate component other than a line, trace, or other medium exists between the first and second components, the first component is indirectly coupled to the second component. The term "coupling" and its variations include direct coupling and indirect coupling. Unless otherwise stated, the term "about" is used to mean a range including upper and lower 10% of the value.

[0059] While several embodiments are provided in this disclosure, it should be understood that the disclosed systems and methods may be embodied in many other specific forms without departing from the spirit or scope of this disclosure. The present examples are intended to be illustrative rather than restrictive and are not limited to the details given. For example, various elements or components may be combined or integrated into another system, or certain features may be omitted or not implemented.

[0060] In the several embodiments provided herein, it should be understood that the disclosed apparatus and methods can also be implemented in other ways. The apparatus embodiments described above are merely illustrative; for example, the flowcharts and block diagrams in the accompanying drawings illustrate the architecture, functionality, and operation of possible implementations of apparatus, methods, and computer program products according to various embodiments of the present invention. In this regard, each block in a flowchart or block diagram may represent a module, segment, or portion of code containing one or more executable instructions for implementing a specified logical function. It should also be noted that in some alternative implementations, the functions marked in the blocks may occur in a different order than those marked in the drawings. For example, two consecutive blocks may actually be executed substantially in parallel, and they may sometimes be executed in reverse order, depending on the functions involved. It should also be noted that each block in a block diagram and / or flowchart, and combinations of blocks in block diagrams and / or flowcharts, can be implemented using a dedicated hardware-based system that performs the specified function or action, or using a combination of dedicated hardware and computer instructions.

[0061] Furthermore, without departing from the scope of this disclosure, the discrete or individual technologies, systems, subsystems, and methods described and illustrated in the various embodiments may be combined or integrated with other systems, modules, technologies, or methods. Other items shown or discussed as coupled may be directly connected or indirectly coupled or communicated via some interface, device, or intermediate component in an electrical, mechanical, or other manner. Those skilled in the art can identify other examples of changes, substitutions, and modifications without departing from the spirit and scope of this disclosure.

Claims

1. A method for automatically resetting a remotely controlled vehicle, characterized in that, include: The controller acquires and saves sensor data sets through the steering valve sensor, and calculates the average value of each sensor data set; When the average value exceeds the first set threshold, the controller locks the steering valve. When the average value does not exceed the first set threshold, the controller selects all sensor data in each sensor data group that exceed the second set threshold and forms them into abnormal data groups in sequence. The controller sets the number of sensor data in each abnormal data group to a first set number and calculates the variance of each sensor data in the abnormal data group. The controller compares the variance of each sensor data in the abnormal data group with the set good value of variance to adjust the first set number until the variance of each sensor data in the abnormal data group and the set good value of variance tend to be consistent. The controller calculates the variance of each sensor data in the current abnormal data group and compares the variance of each sensor data in the current abnormal data group with a set variance threshold. When the variance of each sensor data in the current abnormal data group exceeds the set variance threshold, the controller determines that the steering valve sensor is in an abnormal state. When the variance of each sensor data in the current abnormal data group is within the set variance threshold, the controller determines that the steering valve is in a reset pending confirmation state. When the controller determines that the steering valve is in a reset pending confirmation state, the controller calculates the variance of each sensor data in the next abnormal data group and compares the variance of each sensor data in the abnormal data group with the variance set threshold. When the variance of each sensor data in the abnormal data group exceeds the set variance threshold, the controller determines that the steering valve sensor is in an abnormal state. When the variance of each sensor data in the abnormal data group is within the set variance threshold, the controller determines that the steering valve is in a reset confirmation state.

2. The remote-controlled vehicle automatic reset method as described in claim 1, characterized in that, The controller sets a data processing cycle to acquire several sensing data collected by the steering valve sensor within the data processing cycle, thereby forming a sensing data group, and each sensing data is acquired by the steering valve sensor within one acquisition cycle.

3. The remote-controlled vehicle automatic reset method as described in claim 1, characterized in that, When the variance of each sensor data in the abnormal data group is within the variance setting threshold and is inconsistent with the variance setting good value, the controller incrementally increases the first set number to obtain the corresponding abnormal data group, calculates the variance of each sensor data in the abnormal data, and compares the variance of each sensor data in the abnormal data group with the variance setting good value until the variance of each sensor data in the abnormal data group tends to be consistent with the variance setting good value, so as to redetermine the first set number.

4. The remote-controlled vehicle automatic reset method as described in claim 1, characterized in that, When the variance of each sensor data in the abnormal data group is within the variance setting threshold and is inconsistent with the variance setting good value, the controller obtains the corresponding abnormal data group by step-decreasing the first set number, calculates the variance of each sensor data in the abnormal data, and compares the variance of each sensor data in the abnormal data group with the variance setting good value until the variance of each sensor data in the abnormal data group tends to be consistent with the variance setting good value, so as to redetermine the first set number.

5. A remote vehicle automatic reset system suitable for using the remote vehicle automatic reset method as described in any one of claims 1-4, characterized in that, include: Controller and steering valve sensor; The controller acquires and saves sensor data sets through the steering valve sensor, and calculates the average value of each sensor data set; When the average value exceeds the first set threshold, the controller locks the steering valve. When the average value does not exceed the first set threshold, the controller selects all sensor data in each sensor data group that exceed the second set threshold and forms them into abnormal data groups in sequence. The controller sets the number of sensor data in each abnormal data group to a first set number and calculates the variance of each sensor data in the abnormal data group. The controller compares the variance of each sensor data in the abnormal data group with the set good value of variance to adjust the first set number until the variance of each sensor data in the abnormal data group and the set good value of variance tend to be consistent. The controller calculates the variance of each sensor data in the current abnormal data group to initially determine whether the steering valve sensor is in an abnormal state or the steering valve is in a reset pending confirmation state. When the controller determines that the steering valve is in a reset pending confirmation state, the controller calculates the variance of each sensor data in the next abnormal data group to verify whether the steering valve sensor is in an abnormal state or the steering valve is in a reset confirmation state.

6. A non-transitory readable storage medium storing computer programs / instructions thereon, characterized in that, When the computer program / instruction is executed by the processor, it implements the steps of the remote vehicle automatic reset method according to any one of claims 1-4.

7. A computer program product comprising a computer program / instructions, characterized in that, When the computer program / instruction is executed by the processor, it implements the steps of the remote vehicle automatic reset method according to any one of claims 1-4.

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