A tunnel robot positioning method, system, device and storage medium

Abstract

The application discloses a tunnel robot positioning method, system, device and storage medium, and comprises the following steps: in response to a received tunnel inspection request, determining a tunnel robot corresponding to the tunnel inspection request; driving the tunnel robot to travel along a preset sliding route through a sliding wheel; reading the ID numbers of each RFID combination through an RFID card reader within a preset distance threshold, obtaining position information corresponding to the ID numbers and storing the position information; calculating an optimal estimation value corresponding to a current label point according to the ID numbers and the position information corresponding to the ID numbers, and adjusting a wheeled odometer; and obtaining current position information corresponding to the tunnel robot through the wheeled odometer. The application solves the technical problem that existing robots cannot accurately identify the current position during the inspection process and cannot provide a specific position for a worker to enter for maintenance. The application adopts a tunnel robot to accurately position the positioning information of any position in the tunnel, and facilitates the worker to enter for maintenance according to the positioning information.

Description

Technical Field

[0001] This invention relates to the field of tunnel robot positioning technology, and in particular to a tunnel robot positioning method, system, device and storage medium. Background Technology

[0002] To ensure the safe and stable operation of cables in cable tunnels, regular inspections are necessary. Currently, cable tunnel inspections are gradually shifting from manual to mobile robot inspections. Robotic inspections require the robot to accurately identify its current location in order to achieve autonomous navigation and precise location of cable faults within the tunnel, facilitating access for maintenance personnel.

[0003] Therefore, the traditional method is to use a cable tunnel inspection robot and its positioning system based on marker positioning. This robot is equipped with a sensor to read the data within a certain effective range. However, RFID reading has a limited effective range, which is about 10cm. Since there is a 5cm gap between the robot and the RFID reader and the tag, the center of the reader on the robot can read the data when it is 5cm away from the center of the tag horizontally. The reading is 5cm ahead when moving forward and 5cm behind when moving backward. That is, the positioning error caused by the reader's reading range is about 10cm. As a result, the robot cannot accurately identify its current position during the inspection process, and it is difficult to provide a specific location for the staff to enter for maintenance. Summary of the Invention

[0004] This invention provides a method, system, device, and storage medium for locating tunnel robots, which solves the technical problem that existing robots fail to accurately identify their current location during inspections, making it difficult to provide a specific location for workers to enter and perform maintenance.

[0005] The first aspect of this invention provides a method for locating a tunnel robot, which relates to a tunnel robot including an RFID reader, pulleys, and a wheeled odometer. The method includes:

[0006] In response to a received tunnel inspection request, determine the tunnel robot corresponding to the tunnel inspection request;

[0007] The tunnel robot is driven to travel along a preset sliding route by the sliding wheels;

[0008] The RFID reader reads the ID number of each RFID combination at a preset distance threshold, obtains the location information corresponding to the ID number, and stores it.

[0009] Calculate the optimal estimate value corresponding to the current tag point based on the ID number and the location information corresponding to the ID number, and adjust the wheel odometer accordingly;

[0010] The current location information of the tunnel robot is obtained through the wheeled odometer.

[0011] Optionally, it also includes:

[0012] By setting multiple RFID combinations at equal intervals on the track, the ID number of the RFID corresponding to each RFID combination and the location information corresponding to the ID number are recorded;

[0013] An RFID tag list is generated and stored using each ID number and its corresponding location information.

[0014] Optionally, the RFID combination includes two adjacent RFID tags, which are arranged at equal intervals according to the tag points; the step of calculating the optimal estimate value corresponding to the current tag point based on the ID number and the location information corresponding to the ID number, and adjusting the wheel odometer, further includes:

[0015] The location information corresponding to two adjacent RFID tags is measured according to multiple preset measurement times to generate multiple measurement values;

[0016] Based on the multiple measured values, calculate the measured value of the current tag point corresponding to the RFID combination of two adjacent RFID tags, and generate multiple position measured values ​​corresponding to the current tag point;

[0017] According to the Kalman filter algorithm, the optimal estimated value corresponding to the current label point is calculated using multiple location measurements;

[0018] The wheel odometer is adjusted based on the optimal estimate.

[0019] Optionally, the step of calculating the measurement value of the current tag point corresponding to the RFID combination of two adjacent RFID tags based on the multiple measurement values, and generating the position measurement values ​​corresponding to the multiple current tag points, includes:

[0020] The ID numbers of the two RFID tags corresponding to the RFID combination are read at multiple preset distance locations, and the measurement values ​​corresponding to the ID numbers are obtained.

[0021] Calculate the initial position and value of the position measurement corresponding to the initial preset distance position and the final preset distance position, respectively;

[0022] The initial position and value are adjusted according to a preset multiple, and the position measurement value corresponding to the intermediate preset distance position is superimposed to generate the intermediate position and value;

[0023] Adjust the intermediate position and value according to the stated multiple to generate the position measurement value of the current tag point corresponding to the RFID combination.

[0024] Optionally, the step of calculating the optimal estimate corresponding to the current tag point using multiple location measurements according to the Kalman filter algorithm includes:

[0025] According to the Kalman filter algorithm, the estimated value of the previous measurement time is calculated using multiple position measurements;

[0026] The Kalman filter algorithm is adjusted according to the Kalman coefficients, and the estimated value of the current measurement time is calculated based on the estimated value corresponding to the previous measurement time, and determined as the optimal estimated value corresponding to the current label point.

[0027] Optionally, the tunnel robot further includes a motor controller, an MCU controller, and a power supply system, and the method further includes:

[0028] The MCU controller controls the motor controller to control the sliding wheel and the wheeled odometer;

[0029] The power system acquires power information in real time and inputs it into the MCU controller.

[0030] When the power information reaches a preset power threshold, the MCU controller outputs an alarm message.

[0031] Optionally, the wheel odometer includes an encoder; the step of adjusting the wheel odometer according to the optimal estimate includes:

[0032] The optimal estimated value corresponding to the current tag point at the current measurement time is input into the MCU controller;

[0033] The encoder is adjusted by the MCU controller.

[0034] A second aspect of the present invention provides a tunnel robot positioning system, wherein the tunnel robot includes an RFID reader, a pulley, and a wheeled odometer, and the system includes:

[0035] The tunnel robot module is used to respond to a received tunnel inspection request and determine the tunnel robot corresponding to the tunnel inspection request.

[0036] A sliding track module is used to drive the tunnel robot along a preset sliding track via the sliding wheels;

[0037] The location information acquisition module is used to read the ID number of each RFID combination through the RFID reader at a preset distance threshold, acquire the location information corresponding to the ID number, and store it.

[0038] The wheeled odometer module is used to calculate the optimal estimated value corresponding to the current tag point based on the ID number and the location information corresponding to the ID number, and to adjust the wheeled odometer.

[0039] The current location information module is used to obtain the current location information of the tunnel robot through the wheeled odometer.

[0040] A third aspect of the present invention provides an electronic device, including a memory and a processor, wherein the memory stores a computer program, and when the computer program is executed by the processor, the processor performs the steps of the tunnel robot positioning method as described in any of the preceding claims.

[0041] The fourth aspect of the present invention provides a computer-readable storage medium having a computer program stored thereon, which, when executed, implements the tunnel robot positioning method as described in any of the preceding claims.

[0042] As can be seen from the above technical solutions, the present invention has the following advantages:

[0043] This invention addresses the technical problem of existing robots failing to accurately identify their current location during inspections, making it difficult for personnel to access and perform maintenance. By responding to received tunnel inspection requests, the invention allows for the identification of a tunnel robot corresponding to the request. The robot is driven along a pre-defined gliding path via sliding wheels. An RFID reader reads the ID numbers of various RFID combinations at a preset distance threshold, obtaining and storing the corresponding location information. Based on the ID numbers and their location information, the optimal estimated value for the current tag point is calculated, and the wheeled odometer is adjusted accordingly. The current location information of the tunnel robot is then obtained through the wheeled odometer. This invention solves the problem of existing robots failing to accurately identify their current location during inspections, making it difficult to provide a specific location for maintenance personnel. The invention uses a tunnel robot to accurately locate any position within the tunnel, facilitating maintenance personnel to access the site based on this location information. Attached Figure Description

[0044] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0045] Figure 1 This is a flowchart illustrating the steps of a tunnel robot positioning method according to Embodiment 1 of the present invention.

[0046] Figure 2 This is a flowchart illustrating the steps of a tunnel robot positioning method according to Embodiment 2 of the present invention.

[0047] Figure 3 This is a schematic diagram of a track for tunnel robot sliding provided in Embodiment 2 of the present invention;

[0048] Figure 4 This is a schematic diagram illustrating the error range of an RFID tag according to Embodiment 2 of the present invention;

[0049] Figure 5 This is a measurement diagram illustrating the forward movement of a tunnel robot according to Embodiment 2 of the present invention;

[0050] Figure 6 This is a measurement diagram of a tunnel robot traveling in reverse, provided in Embodiment 2 of the present invention;

[0051] Figure 7 This is a schematic diagram of the structure of a tunnel robot provided in Embodiment 2 of the present invention;

[0052] Figure 8 This is a structural block diagram of a tunnel robot positioning system provided in Embodiment 3 of the present invention. Detailed Implementation

[0053] This invention provides a method, system, device, and storage medium for locating tunnel robots, which addresses the technical problem that existing robots fail to accurately identify their current location during inspections, making it difficult to provide a specific location for workers to access and maintain.

[0054] To make the objectives, features, and advantages of this invention more apparent and understandable, the technical solutions of the embodiments of this invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the embodiments described below are only some embodiments of this invention, and not all embodiments. Based on the embodiments of this invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this invention.

[0055] Please see Figure 1 , Figure 1 This is a flowchart illustrating the steps of a tunnel robot positioning method provided in Embodiment 1 of the present invention.

[0056] This invention provides a tunnel robot positioning method, which relates to a tunnel robot including an RFID reader, pulleys, and a wheeled odometer. The method includes the following steps:

[0057] Step 101: Respond to the received tunnel inspection request and determine the tunnel robot corresponding to the tunnel inspection request.

[0058] It should be noted that the tunnel inspection request refers to an inspection request for cable tunnels; the tunnel robot refers to an integrated robot including an RFID reader, pulleys, wheeled odometer, motor controller, MCU controller, and power system, as well as a camera, temperature measuring device, wireless network module, and alarm device. The camera can be a 360° rotating camera used to capture environmental video inside the tunnel and transmit it to the workbench or the mobile device of relevant personnel via the wireless network module; the temperature measuring device can be used to measure the temperature of the cable in real time, and the alarm device can issue an alarm sound according to the actual situation, such as in the event of a power outage, to facilitate the staff's search.

[0059] In a specific embodiment, when a tunnel inspection request is received, the tunnel robot to be inspected is determined, and the various operating data of the tunnel robot are adjusted to preset values. The preset values ​​are determined according to the actual situation and are not limited here.

[0060] Step 102: Drive the tunnel robot along the preset sliding route using sliding wheels.

[0061] It should be noted that the motor controller is connected to the pulley, the pulley is connected to the wheel-type odometer, and the motor controller controls the pulley to slide.

[0062] In a specific embodiment, the sliding wheel drives the tunnel robot to travel along a preset sliding line, which facilitates inspection. When the sliding wheel slides, the wheel-type odometer begins to follow the sliding wheel to calculate the distance slid by the tunnel robot.

[0063] Step 103: Use an RFID reader to read the ID number of each RFID combination at a preset distance threshold, obtain the location information corresponding to the ID number, and store it.

[0064] It should be noted that an RFID reader is an automatic identification device that can read data from electronic tags. Radio Frequency Identification (RFID) works by using non-contact data communication between the reader and the tag to identify the target. Each RFID tag has a unique ID number; RFID readers have a certain effective range, approximately 10cm, to read the RFID's radio frequency and corresponding ID number, hence the preset distance threshold is approximately 10cm.

[0065] In a specific embodiment, when the RFID reader follows the tunnel robot along the sliding line to reach the effective reading distance, the RFID reader reads the radio frequency and ID number of the two RFID tags in the RFID combination within the effective distance, obtains the location information recorded by the wheel odometer, and stores the ID number of the two RFID tags and the corresponding location information together.

[0066] Step 104: Calculate the optimal estimate value corresponding to the current tag point based on the ID number and the location information corresponding to the ID number, and adjust the wheel odometer.

[0067] It should be noted that when the tunnel robot slides, the mileage recorded by the wheel odometer may be inaccurate due to the possibility of slippage in the sliding wheels.

[0068] In a specific embodiment, by obtaining the ID number and repeatedly measuring the location information corresponding to the ID number using a wheeled odometer, the optimal estimated value corresponding to the current tag point is calculated using a Kalman filter algorithm, and the wheeled odometer is adjusted according to the optimal estimated value.

[0069] Step 105: Obtain the current location information of the tunnel robot through the wheeled odometer.

[0070] In a specific embodiment, by continuously adjusting the wheeled odometer, accurate position information is finally obtained, and the position information corresponding to each tag point is made into a tag lookup table so that the current position information of the tunnel robot can be measured in a timely manner during the subsequent sliding process.

[0071] This invention addresses the technical problem of existing robots failing to accurately identify their current location during inspections, making it difficult for personnel to access and perform maintenance. By responding to received tunnel inspection requests, the invention allows for the identification of a tunnel robot corresponding to the request. The robot is driven along a pre-defined gliding path via sliding wheels. An RFID reader reads the ID numbers of various RFID combinations at a preset distance threshold, obtaining and storing the corresponding location information. Based on the ID numbers and their location information, the optimal estimated value for the current tag point is calculated, and the wheeled odometer is adjusted accordingly. The current location information of the tunnel robot is then obtained through the wheeled odometer. This invention solves the problem of existing robots failing to accurately identify their current location during inspections, making it difficult to provide a specific location for maintenance personnel. The invention uses a tunnel robot to accurately locate any position within the tunnel, facilitating maintenance personnel to access the site based on this location information.

[0072] Please see Figures 2-7 , Figure 2 This is a flowchart illustrating the steps of a tunnel robot positioning method provided in Embodiment 2 of the present invention.

[0073] This invention provides a tunnel robot positioning method, which relates to a tunnel robot including an RFID reader, pulleys, and a wheeled odometer. The method includes the following steps:

[0074] Step 201: By setting multiple RFID combinations at equal intervals on the track, record the RFID ID number and the location information corresponding to the ID number of each RFID combination.

[0075] It should be noted that the tunnel robot's track consists of the track body and RFID; an RFID combination includes two RFID tags, which are respectively set 5cm to the left and right of the tag point.

[0076] In a specific embodiment, by Figure 3 As shown, the RFID combination includes RFID1 and RFID2, RFID3 and RFID4, RFID5 and RFID6; where RFID1, RFID2, RFID3, RFID4, RFID5 and RFID6 are ID numbers; RFID1 is set at 95cm of the track body, the tag point is set at 100cm of the track body, RFID2 is set at 105cm of the track body... RFID6 is set at 305cm of the track body.

[0077] Step 202: Use each ID number and the location information corresponding to the ID number to generate and store an RFID tag list.

[0078] In a specific embodiment, an RFID tag list is generated by combining each ID number and its corresponding location information, as shown in Table 1 below:

[0079]

[0080] Table 1

[0081] Step 203: Respond to the received tunnel inspection request and determine the tunnel robot corresponding to the tunnel inspection request.

[0082] In this embodiment of the invention, the specific implementation process of step 203 is similar to that of step 101, and will not be repeated here.

[0083] Step 204: Drive the tunnel robot along the preset sliding route using sliding wheels.

[0084] In this embodiment of the invention, the specific implementation process of step 204 is similar to that of step 102, and will not be repeated here.

[0085] Step 205: Use an RFID reader to read the ID number of each RFID combination at a preset distance threshold, obtain the location information corresponding to the ID number, and store it.

[0086] In this embodiment of the invention, the specific implementation process of step 205 is similar to that of step 103, and will not be repeated here.

[0087] Step 206: Calculate the optimal estimated value corresponding to the current tag point based on the ID number and the location information corresponding to the ID number, and adjust the wheel odometer.

[0088] Optionally, the RFID combination includes two adjacent RFID tags, which are arranged at equal intervals according to the tag points; step 206 includes the following steps S11-S14:

[0089] S11. Measure the location information of two adjacent RFID tags according to multiple preset measurement times, and generate multiple measurement values;

[0090] S12. Based on multiple measurement values, calculate the measurement value of the current tag point corresponding to the RFID combination of two adjacent RFID tags, and generate multiple location measurement values ​​corresponding to the current tag point.

[0091] S13. Calculate the optimal estimate of the current tag point using multiple location measurements based on the Kalman filter algorithm.

[0092] S14. Adjust the wheel odometer according to the optimal estimate.

[0093] It should be noted that multiple preset measurement times can be set according to actual conditions. They can be set to measure every 5 minutes, because an RFID tag has an error range of approximately 10cm when traveling in either the forward or reverse direction. Figure 4 As shown, this represents the error range of an RFID tag. Kalman filtering is an optimal estimation algorithm, and common optimal estimation algorithms include the "least squares method." Kalman filtering is also an iterator that predicts the estimated value at the next moment based on known prior values.

[0094] In this embodiment of the invention, multiple measurements are performed on two RFID tags in the same RFID combination to obtain multiple location measurement values. The measurement values ​​corresponding to the two RFID tags in the same measurement are extracted, and the location measurement value of the current tag point corresponding to the RFID combination of the two RFID tags is calculated. This process is repeated to extract the measurement values ​​corresponding to the two RFID tags for calculation, resulting in multiple location measurement values ​​corresponding to the current tag point. Using the Kalman filter algorithm, the optimal estimate value corresponding to the current tag point is calculated from the multiple location measurement values. This optimal estimate value is then used as the standard value to adjust the encoder of the wheel-type odometer.

[0095] Optionally, step S12 includes the following steps S121-124:

[0096] S121. Read the ID numbers of the two RFID tags corresponding to the RFID combination at multiple preset distance positions, and obtain the measurement value corresponding to the ID number;

[0097] S122. Calculate the initial position and value of the position measurement corresponding to the initial preset distance position and the final preset distance position, respectively;

[0098] S123. Adjust the initial position and value according to the preset multiple, and superimpose the position measurement value corresponding to the intermediate preset distance position to generate the intermediate position and value;

[0099] S124. Adjust the intermediate position and value according to the multiplier to generate the position measurement value of the current tag point corresponding to the RFID combination.

[0100] It should be noted that, as Figure 5 and Figure 6 As shown, the measurement results for the tunnel robot's forward and reverse travel are presented. During forward travel, the tunnel robot detected three critical states at several preset distance positions w1=90, w2=100, and w3=110cm: at w1, only RFID1 was detected; at w2, both RFID1 and RFID2 were detected; and at w3, only RFID2 was detected. The reverse travel effect is the opposite of the forward travel. Ideally, the relationship between the nearest points w1, w2, and w3 is such that the exact center of w1 and w3 is w2. The final calibration result is w2, which corresponds to the current tag point of the RFID combination. The preset multiplier is 2.

[0101] In specific embodiments, the actual situation is affected by factors such as processor latency. Since it is not equal to w2, the calibration result is averaged again from both to eliminate the delay instability factor, and finally the position measurement value of the current tag point is obtained. .

[0102] Optionally, step S13 includes the following steps S131-S132:

[0103] S131. Based on the Kalman filter algorithm, calculate the estimated value of the previous measurement time using multiple position measurements;

[0104] S132. Adjust the Kalman filter algorithm according to the Kalman coefficient, calculate the estimated value of the current measurement time based on the estimated value corresponding to the previous measurement time, and determine it as the optimal estimated value corresponding to the current label point.

[0105] It should be noted that the Kalman filter calculation formula is as follows:

[0106]

[0107] In the formula, and Let x and x-1 represent the position estimates corresponding to the measurement time x and the previous measurement time x-1, respectively, and k represent the k-th measurement time. These represent the positional measurements at measurement time 1, measurement time 2, ..., measurement time k-1, and measurement time k, respectively.

[0108] make , = (2);

[0109] In the formula, Kalman coefficients;

[0110] Therefore, the estimated value of the current measurement time is related to the estimated value of the previous measurement time, and the estimated value of the previous measurement time is related to the estimated value of the measurement time before that, which is a kind of recursion. Therefore, using Kalman filtering to calculate the estimated value of the current measurement time does not require data from a long time ago, but only the data from the previous time.

[0111] In this embodiment of the invention, multiple position measurement values ​​are applied to equation (1) to calculate the estimated value of the previous measurement time, and the Kalman coefficient is adjusted to obtain the most accurate and optimal estimated value. The estimated value corresponding to the previous measurement time is applied to equation (2) to calculate the estimated value of the current measurement time, and the estimated value is determined as the optimal estimated value corresponding to the current tag point.

[0112] Step 207: Obtain the current location information of the tunnel robot through the wheeled odometer.

[0113] In this embodiment of the invention, the specific implementation process of step 207 is similar to that of step 105, and will not be repeated here.

[0114] Optionally, the tunnel robot also includes a motor controller, an MCU controller, and a power supply system. The method further includes the following steps S21-S23:

[0115] S21. The MCU controller controls the motor controller to control the pulley and wheeled odometer;

[0116] S22. Obtain power information in real time through the power system and input it into the MCU controller;

[0117] S23. When the power information reaches the preset power threshold, the MCU controller outputs an alarm message.

[0118] It should be noted that, as Figure 7 As shown, the tunnel robot also includes a motor controller, an MCU controller, and a power system. The MCU controller is used to control the motor controller, wheel odometer, and power system. The power threshold can be set according to actual conditions and is not limited here.

[0119] In a specific embodiment, the MCU controller controls the motor controller, which in turn controls the sliding wheels and wheeled odometer to start or stop working. The power system acquires power information in real time to monitor the power status. When a certain power threshold is reached, there may be just enough power to support the tunnel robot to return to the starting point. The specific power threshold is determined by the distance of the tunnel robot from the starting point and the power required for the return. When this power threshold is reached, an alarm message needs to be issued to prompt the staff to adjust the tunnel robot to return, so as to avoid the tunnel robot running out of power halfway.

[0120] Optionally, the wheel-type odometer includes an encoder; step S14 includes the following steps S31-S32:

[0121] S31. Input the optimal estimated value corresponding to the current tag point at the current measurement time into the MCU controller;

[0122] S32. Adjust the encoder via the MCU controller.

[0123] It should be noted that different wheel diameters, changes in wheel contact points, non-uniform ground contact, and varying friction coefficients at different locations can all cause wheel odometers to slip, leading to encoder measurement errors.

[0124] In a specific embodiment, when the optimal estimated value of the current tag point corresponding to the current measurement time is calculated, the optimal estimated value is input to the MCU controller. The MCU controller adjusts the encoder based on the optimal estimated value, so that the tunnel robot can obtain accurate positioning data at any position on the track.

[0125] This invention addresses the technical problem of existing robots failing to accurately identify their current location during inspections, making it difficult for personnel to access and perform maintenance. By responding to received tunnel inspection requests, the invention allows for the identification of a tunnel robot corresponding to the request. The robot is driven along a pre-defined gliding path via sliding wheels. An RFID reader reads the ID numbers of various RFID combinations at a preset distance threshold, obtaining and storing the corresponding location information. Based on the ID numbers and their location information, the optimal estimated value for the current tag point is calculated, and the wheeled odometer is adjusted accordingly. The current location information of the tunnel robot is then obtained through the wheeled odometer. This invention solves the problem of existing robots failing to accurately identify their current location during inspections, making it difficult to provide a specific location for maintenance personnel. The invention uses a tunnel robot to accurately locate any position within the tunnel, facilitating maintenance personnel to access the site based on this location information.

[0126] Please see Figure 8 , Figure 8 This is a structural block diagram of a tunnel robot positioning system provided in Embodiment 3 of the present invention.

[0127] This invention provides a tunnel robot positioning system, relating to a tunnel robot. The tunnel robot includes an RFID reader, pulleys, and a wheeled odometer. The system includes:

[0128] The tunnel robot module 801 is used to respond to the received tunnel inspection request and determine the tunnel robot corresponding to the tunnel inspection request.

[0129] The sliding path module 802 is used to drive the tunnel robot to travel along a preset sliding path via sliding wheels;

[0130] The location information acquisition module 803 is used to read the ID number of each RFID combination at a preset distance threshold through an RFID reader, obtain the location information corresponding to the ID number and store it.

[0131] The wheel odometer module 804 is used to calculate the optimal estimate value corresponding to the current tag point based on the ID number and the location information corresponding to the ID number, and to adjust the wheel odometer.

[0132] The current location information module 805 is used to obtain the current location information of the tunnel robot through the wheeled odometer.

[0133] Optionally, this system also includes:

[0134] The RFID combination submodule is used to record the RFID ID number and the location information corresponding to the ID number of each RFID combination by setting multiple RFID combinations at equal intervals on the track.

[0135] The RFID tag list submodule is used to generate and store an RFID tag list using each ID number and its corresponding location information.

[0136] Optionally, the RFID array includes two adjacent RFID tags, which are arranged at equal intervals according to the tag points; the wheel odometer module 804 includes:

[0137] Multiple measurement value submodules are used to measure the location information of two adjacent RFID tags according to multiple preset measurement times and generate multiple measurement values;

[0138] The measurement value calculation submodule is used to calculate the measurement value of the current tag point corresponding to the RFID combination of two adjacent RFID tags based on multiple measurement values, and generate multiple location measurement values ​​corresponding to the current tag point.

[0139] The Kalman filter submodule is used to calculate the optimal estimate of the current tag point based on multiple location measurements using the Kalman filter algorithm.

[0140] The wheel odometer submodule is used to adjust the wheel odometer based on the optimal estimate.

[0141] Optionally, the submodule for calculating measured values ​​includes:

[0142] The ID numbering submodule is used to read the ID numbers of the two RFID tags corresponding to the RFID combination at multiple preset distance locations, and obtain the measurement value corresponding to the ID number.

[0143] The initial position and value submodule is used to calculate the initial position and value of the position measurement values ​​corresponding to the initial preset distance position and the final preset distance position, respectively.

[0144] The intermediate position and value submodule is used to adjust the initial position and value according to a preset multiple, and to superimpose the position measurement value corresponding to the intermediate preset distance position to generate the intermediate position and value;

[0145] The location measurement value submodule is used to adjust the intermediate position and value by a multiple to generate the location measurement value of the current tag point corresponding to the RFID combination.

[0146] Optionally, the Kalman filter submodule includes:

[0147] The previous measurement time submodule is used to calculate the estimated value of the previous measurement time using multiple location measurements based on the Kalman filter algorithm;

[0148] The Kalman coefficient submodule is used to adjust the Kalman filtering algorithm according to the Kalman coefficients, calculate the estimated value of the current measurement time based on the estimated value corresponding to the previous measurement time, and determine it as the optimal estimate corresponding to the current label point.

[0149] Optionally, the tunnel robot also includes a motor controller, an MCU controller, and a power supply system. This system also includes:

[0150] The MCU controller submodule is used to control the pulleys and wheeled odometer by controlling the motor controller through the MCU controller.

[0151] The power information acquisition submodule is used to acquire power information in real time from the power system and input it into the MCU controller.

[0152] The alarm information submodule is used to output alarm information by the MCU controller when the power level reaches a preset power threshold.

[0153] Optionally, the wheel odometer includes an encoder, and the wheel odometer submodule includes:

[0154] The optimal estimate submodule is used to input the optimal estimate value corresponding to the current tag point at the current measurement time into the MCU controller;

[0155] The encoder submodule is used to adjust the encoder via the MCU controller.

[0156] This invention addresses the technical problem of existing robots failing to accurately identify their current location during inspections, making it difficult for personnel to access and perform maintenance. By responding to received tunnel inspection requests, the invention allows for the identification of a tunnel robot corresponding to the request. The robot is driven along a pre-defined gliding path via sliding wheels. An RFID reader reads the ID numbers of various RFID combinations at a preset distance threshold, obtaining and storing the corresponding location information. Based on the ID numbers and their location information, the optimal estimated value for the current tag point is calculated, and the wheeled odometer is adjusted accordingly. The current location information of the tunnel robot is then obtained through the wheeled odometer. This invention solves the problem of existing robots failing to accurately identify their current location during inspections, making it difficult to provide a specific location for maintenance personnel. The invention uses a tunnel robot to accurately locate any position within the tunnel, facilitating maintenance personnel to access the site based on this location information.

[0157] Embodiment 4 of the present invention also provides an electronic device, including a memory and a processor, wherein the memory stores a computer program; when the computer program is executed by the processor, the processor performs the steps of the tunnel robot positioning method as described in any of the above embodiments.

[0158] Embodiment 5 of the present invention provides a computer-readable storage medium having a computer program stored thereon, wherein when the computer program is executed, it implements the steps of the tunnel robot positioning method as described in any embodiment of the present invention.

[0159] Those skilled in the art will clearly understand that, for the sake of convenience and brevity, the specific working processes of the systems, devices, and units described above can be referred to the corresponding processes in the foregoing method embodiments, and will not be repeated here.

[0160] In the several embodiments provided in this application, it should be understood that the disclosed systems, apparatuses, and methods can be implemented in other ways. For example, the apparatus embodiments described above are merely illustrative; for instance, the division of units is only a logical functional division, and in actual implementation, there may be other division methods. For example, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the coupling or direct coupling or communication connection shown or discussed may be an indirect coupling or communication connection between apparatuses or units through some interfaces, and may be electrical, mechanical, or other forms.

[0161] The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the units can be selected to achieve the purpose of this embodiment according to actual needs.

[0162] Furthermore, the functional units in the various embodiments of the present invention can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit. The integrated unit can be implemented in hardware or as a software functional unit.

[0163] If the integrated unit is implemented as a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention, in essence, or the part that contributes to the prior art, or all or part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods described in the various embodiments of the present invention. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks.

[0164] The above-described embodiments are only used to illustrate the technical solutions of the present invention, and are not intended to limit it. Although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features. Such modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. A method for locating a tunnel robot, characterized in that, The method relates to a tunnel robot, which includes an RFID reader, wheels, and a wheeled odometer. In response to a received tunnel inspection request, determine the tunnel robot corresponding to the tunnel inspection request; The tunnel robot is driven to travel along a preset sliding route by the sliding wheels; The RFID reader reads the ID number of each RFID combination at a preset distance threshold, obtains the location information corresponding to the ID number, and stores it. Calculate the optimal estimate value corresponding to the current tag point based on the ID number and the location information corresponding to the ID number, and adjust the wheel odometer accordingly; The current location information of the tunnel robot is obtained through the wheeled odometer; Also includes: By setting multiple RFID combinations at equal intervals on the track, the ID number of the RFID corresponding to each RFID combination and the location information corresponding to the ID number are recorded; A list of RFID tags is generated and stored using each ID number and its corresponding location information. The RFID array includes two adjacent RFID tags, which are spaced evenly at the same distance from each other. The step of calculating the optimal estimate for the current tag point based on the ID number and its corresponding location information, and adjusting the wheel odometer, further includes: The location information corresponding to two adjacent RFID tags is measured according to multiple preset measurement times to generate multiple measurement values; Based on the multiple measured values, calculate the measured value of the current tag point corresponding to the RFID combination of two adjacent RFID tags, and generate multiple position measured values ​​corresponding to the current tag point; According to the Kalman filter algorithm, the optimal estimated value corresponding to the current label point is calculated using multiple location measurements; The wheel odometer is adjusted based on the optimal estimate.

2. The tunnel robot positioning method according to claim 1, characterized in that, The step of calculating the measurement value of the current tag point corresponding to the RFID combination of two adjacent RFID tags based on the multiple measurement values, and generating the position measurement values ​​corresponding to the multiple current tag points, includes: The ID numbers of the two RFID tags corresponding to the RFID combination are read at multiple preset distance locations, and the measurement values ​​corresponding to the ID numbers are obtained. Calculate the initial position and value of the position measurement corresponding to the initial preset distance position and the final preset distance position, respectively; The initial position and value are adjusted according to a preset multiple, and the position measurement value corresponding to the intermediate preset distance position is superimposed to generate the intermediate position and value; Adjust the intermediate position and value according to the stated multiple to generate the position measurement value of the current tag point corresponding to the RFID combination.

3. The tunnel robot positioning method according to claim 1, characterized in that, The step of calculating the optimal estimate of the current tag point using multiple location measurements according to the Kalman filter algorithm includes: According to the Kalman filter algorithm, the estimated value of the previous measurement time is calculated using multiple position measurements; The Kalman filter algorithm is adjusted according to the Kalman coefficients, and the estimated value of the current measurement time is calculated based on the estimated value corresponding to the previous measurement time, and determined as the optimal estimated value corresponding to the current label point.

4. The tunnel robot positioning method according to claim 3, characterized in that, The tunnel robot also includes a motor controller, an MCU controller, and a power supply system; the method further includes: The MCU controller controls the motor controller to control the sliding wheel and the wheeled odometer; The power system acquires power information in real time and inputs it into the MCU controller. When the power information reaches a preset power threshold, the MCU controller outputs an alarm message.

5. The tunnel robot positioning method according to claim 4, characterized in that, The wheel odometer includes an encoder; the step of adjusting the wheel odometer according to the optimal estimate includes: The optimal estimated value corresponding to the current tag point at the current measurement time is input into the MCU controller; The encoder is adjusted by the MCU controller.

6. A tunnel robot positioning system, characterized in that, The tunnel robot includes an RFID reader, wheels, and a wheeled odometer; the system includes: The tunnel robot module is used to respond to a received tunnel inspection request and determine the tunnel robot corresponding to the tunnel inspection request. A sliding track module is used to drive the tunnel robot to travel along a preset sliding track via the sliding wheels; The location information acquisition module is used to read the ID number of each RFID combination through the RFID reader at a preset distance threshold, acquire the location information corresponding to the ID number, and store it. The wheeled odometer module is used to calculate the optimal estimated value corresponding to the current tag point based on the ID number and the location information corresponding to the ID number, and to adjust the wheeled odometer. The current location information module is used to obtain the current location information of the tunnel robot through the wheeled odometer; The system also includes: The RFID combination submodule is used to record the RFID ID number corresponding to each RFID combination and the location information corresponding to the ID number by setting multiple RFID combinations at equal intervals on the track. The RFID tag list submodule is used to generate and store an RFID tag list using each ID number and the location information corresponding to the ID number. The RFID array includes two adjacent RFID tags, which are arranged at equal intervals with their tag points. The wheel-type odometer module includes: Multiple measurement value submodules are used to measure the location information corresponding to two adjacent RFID tags according to multiple preset measurement times, and generate multiple measurement values; The measurement value calculation submodule is used to calculate the measurement value of the current tag point corresponding to the RFID combination of two adjacent RFID tags based on the multiple measurement values, and generate multiple position measurement values ​​corresponding to the current tag point; The Kalman filter submodule is used to calculate the optimal estimate value corresponding to the current tag point based on the Kalman filter algorithm and multiple position measurements. A wheel odometer submodule is used to adjust the wheel odometer based on the optimal estimate.

7. An electronic device, characterized in that, The system includes a memory and a processor, wherein the memory stores a computer program, and when the computer program is executed by the processor, the processor causes the processor to perform the steps of the tunnel robot positioning method as described in any one of claims 1-5.

8. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed, it implements the tunnel robot positioning method as described in any one of claims 1-5.

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