A remotely operated robot system and operation method for live dry ice cleaning of insulators

Abstract

This application relates to a remotely operated robot system and method for dry ice cleaning of insulators under energized conditions. The system comprises a complete robot system and a tracked insulated bucket truck. The complete robot system includes an RGB-D camera, a six-degree-of-freedom robotic arm, a dry ice machine subsystem, a monitoring camera, an industrial control computer, dry ice cleaning fixtures, a remote operator, a human-machine interface platform, and a power supply system. The remote operator connects to the human-machine interface platform via USB and then communicates with the robot's industrial control computer via WIFI. The complete robot system is mounted on the tracked insulated bucket truck, and the dry ice machine subsystem is installed at the end of the six-degree-of-freedom robotic arm for performing dry ice cleaning operations on the insulators. This application can perform high-quality and rapid cleaning of insulators of different diameters and uneven levels of contamination in an energized environment.

Description

Technical Field

[0001] This application relates to the field of live-line working robots for power distribution networks, specifically to a remote-operated robot system and operating method for live-line dry ice cleaning of insulators. Background Technology

[0002] With the rapid development of my country's economy, the demand for electricity is increasing, leading to a rapid expansion of the power grid. Substations, as a crucial component of the power grid, have electrical equipment (especially busbar insulators) that are frequently exposed to the elements, making them prone to contamination and flashover accidents, severely impacting the safe and stable operation of the equipment. To reduce power outages and ensure normal production and daily life, live-line maintenance of this equipment is necessary. However, currently, most substation equipment maintenance is done manually, requiring work in a power outage environment, resulting in significant economic losses. Furthermore, manual live-line work involves working at heights, is physically demanding, difficult, and carries the risk of falls. Therefore, utilizing robotic technology for live-line work is of great significance for live-line maintenance of substation equipment and ensuring personnel safety.

[0003] There are two main methods for cleaning insulators in live, high-altitude environments: one is manual or robotic cleaning using high-pressure water guns. This requires power outages, causing inconvenience to residents and is difficult to effectively clean stubborn oil stains, salt stains, and other dirt from insulators. The other is dry ice cleaning robots, which use rotating cleaning fixtures to clean insulators in a circular motion. However, the dry ice vaporizes and sublimates upon entering the rotating nozzle, and the rotating nozzles cannot target highly contaminated areas, resulting in poor cleaning performance. Summary of the Invention

[0004] The purpose of this application is to provide a remotely operated robot system and operation method for dry ice cleaning of insulators under energized conditions, which can complete high-quality and rapid cleaning of insulators of different diameters and uneven levels of contamination in an energized environment.

[0005] To achieve the above objectives, this application provides the following technical solution:

[0006] In a first aspect, this application provides a remote-operated robot system for cleaning live dry ice insulators, comprising a robot system and a tracked insulated bucket truck. The robot system includes an RGB-D camera, a six-degree-of-freedom robotic arm, a dry ice machine subsystem, a monitoring camera, an industrial control computer, dry ice cleaning fixtures, a remote operator, a human-machine interface platform, and a power supply system. The remote operator connects to the human-machine interface platform via USB and then communicates with the robot's industrial control computer via WIFI. Each joint of the tracked insulated bucket truck is equipped with an encoder or displacement measurement sensor, providing wireless remote control functionality and enabling real-time acquisition of the spatial coordinates of the bucket truck's end.

[0007] The tracked insulated bucket truck is equipped with a complete robot system, and the dry ice machine subsystem is installed at the end of the six-degree-of-freedom robotic arm to perform dry ice cleaning operations on the insulators.

[0008] Secondly, embodiments of this application provide a remotely operated robot method for cleaning insulators with live dry ice, comprising the following specific steps:

[0009] The tracked bucket truck is parked, the insulated bucket truck is remotely controlled and the distance between the position marked by the on-board laser and the reference object is observed in real time. The insulated bucket truck is then gradually driven to the parking area below the insulator to be cleaned.

[0010] The robot system is gradually transported to the insulator work station on the platform. At this time, the camera and dry ice cleaning equipment are facing the insulator.

[0011] Insulator weak texture target recognition and localization: an insulator fusion recognition and localization method based on RGB-D images, used to obtain high-precision spatial coordinate information of insulator skirts;

[0012] Based on remote operation, dry ice cleaning of insulators allows operators to control the remote operator in real time according to the information on the monitoring screen, thereby realizing the adaptive dry ice cleaning operation of the robot's dry ice cleaning nozzle on the insulator.

[0013] After the robot resets and completes the task of cleaning the energized insulators, the robotic arm retracts to its initial position, and the insulator lifting device is retracted.

[0014] The specific method for parking the tracked bucket truck involves installing four single-line blue lasers on the bucket truck, divided into two groups. The first group, A1 and A2, forms two parallel laser lines to indicate the maximum and minimum parking distances for the front and rear positions of the bucket truck. The second group, B1 and B2, forms two parallel laser lines to indicate the maximum and minimum parking distances for the left and right positions of the bucket truck. The operator remotely controls the insulated bucket truck according to the operating procedures and observes in real time the distance from the position marked by the onboard lasers to the reference object, gradually driving the insulated bucket truck to the parking area below the insulator to be cleaned.

[0015] Specifically, the above-ground platform entry workstation involves a remotely controlled boom truck operated by a human to gradually transport the robot system to the insulator workstation. At this point, both the camera and the dry ice cleaning fixture are facing the insulator. The nozzle of the dry ice cleaning fixture is directly connected to the dry ice tube. The high-speed dry ice particles in the dry ice tube come from the air compressor and pneumatic dry ice machine on the tracked vehicle, forming a mixed high-pressure dry ice gas. The air compressor provides high-speed, high-pressure gas, and its on / off state is controlled by a solenoid valve. Then, the high-pressure gas enters the pneumatic dry ice machine, driving the pneumatic motor to rotate and break up the dry ice particles inside the dry ice machine. Finally, the high-speed gas transports the dry ice to the insulator dry ice cleaning fixture to complete the cleaning operation.

[0016] The insulator weak texture target identification and positioning method specifically involves the robotic arm subsystem carrying an RGB-D camera to perform three-dimensional reconstruction of the target from different perspectives after the upper platform reaches the work station. The reconstruction results are then stitched together to obtain the color and depth information of the insulator. Based on the obtained RGB-D image information of the insulator, high-precision spatial positioning of the insulator skirt is achieved. The insulator fusion identification and positioning method based on RGB-D images has two modes: automatic algorithm recognition and manual selection recognition, which are used to obtain high-precision spatial coordinate information of the insulator skirt.

[0017] The insulator fusion identification and positioning method based on RGB-D images has two modes: automatic algorithm identification and manual selection identification. Specifically, it is used to obtain high-precision spatial coordinate information of the insulator skirts. In the automatic algorithm identification mode, to achieve insulator identification and spatial positioning, the first step is to use a robotic arm to rotate the RGB-D camera. The second step is to automatically complete the coarse positioning of the insulator based on the prior information that the insulator is in the center region of the camera and a distance-based bandpass filtering algorithm. The third step is to use PCA (Principal Component Analysis) to calculate and correct the insulator tilt angle. The fourth step is to further refine the image... After performing horizontal integration to complete the horizontal projection of the insulator point cloud map and obtain the insulator depth gradient map; the fifth step is to use the gradient detection operator to complete the segmentation of the insulator skirt and key point detection; the sixth step is to mark the key points on the color map, thus realizing the automatic identification and high-precision spatial positioning function of the insulator skirt; ② In the manually selected identification mode, the operator clicks on the insulator target p(x, y) in the two-dimensional image of the human-computer interaction system, and can obtain the spatial 3D coordinates P(X, Y, Z) of the insulator skirt to be cleaned through the depth map and the pinhole imaging model. The specific formula for calculating the 3D coordinates is:

[0018]

[0019] In the above formula, f is the focal length of the color camera, dx and dy are the pixel size, and u0 and v0 are the coordinates of the camera's optical center.

[0020] The weak texture target identification and localization of insulators also includes setting up virtual safety fences for insulators, which are used for safety protection during subsequent remote operation control of the robot. The specific calculation steps for the safety fence are as follows:

[0021] Coordinate acquisition: First, the coordinate set of key points of the insulator skirt is obtained by the RGB-D camera at the end of the six-degree-of-freedom robot arm. Let the coordinates of these key points in the robot's three-dimensional space be Pi=(xi,yi,zi), where i is the index of the key point;

[0022] Cylinder Fitting: Using these keypoint coordinates, an optimally fitted cylinder can be fitted. The centerline of the cylinder can be considered as the central axis of the insulator, and the radius R of the cylinder can be half the width of the skirt. Let the center coordinates of the cylinder be C = (xc, yc, zc). C and R can be solved by minimizing the sum of the squares of the distances from all keypoints to the centerline.

[0023] The equation of the cylinder can be expressed as: (x - xc) 2 +(y-yc) 2 =R 2 , where (x,y) are the projected coordinates of any point on the cylinder onto the horizontal plane;

[0024] Virtual safety fence setting: The virtual safety fence is formed by extending a certain safety distance d outward from the above cylinder. This safety distance is to ensure that the robot will not touch the insulator skirt during operation, thereby avoiding damage or accidents.

[0025] The equation for the expanded virtual security fence is: (x-xc) 2 +(y-yc) 2 ≤(R+d) 2 , where d is a value set according to operational safety requirements;

[0026] Safety protection is implemented as follows: During remote operation of the robot, the control system monitors the position of the robot's end effector, Probot = (xr, yr, zr), in real time. If Probot satisfies the following condition, the robot operation is safe: (x - xc) 2 +(y-yc) 2 >(R+d) 2 If the above conditions are not met, the control system will take measures to ensure the safety of operation.

[0027] The specific steps of insulator dry ice cleaning based on teleoperation are: ① Real-time acquisition of the joint angles of the teleoperator. ② The Monte Carlo method is used to solve for the teleoperator's motion space. The specific formula is as follows:

[0028] q i=q min i +(q max i -q min i Rand(j) (1)

[0029] Where i is the sequence number of each joint of the teleoperator (1, 2, 3…6); qmaxi and qmini are the maximum and minimum values ​​of the joint variable of the i-th joint, respectively; Rand() is a function to generate random numbers, ranging from 0 to 1; and j is the number of random numbers.

[0030] By automatically selecting 40,000 sets of random joint rotation angles, and based on the principal kinematics model, the point cloud map of the telemanipulator's workspace can be obtained, and then the minimum and maximum ranges of the telemanipulator in the x, y, and z directions can be obtained, which are (xmMin, xmMax), (ymMin, ymMax), and (zmMin, zmMax), respectively; similarly, the range of motion of the slave robotic arm can be obtained: (xsMin, xsMax), (ysMin, ysMax), and (zsMin, zsMax).

[0031] In actual calculations, the position (xm, ym, zm) of the teleoperator in the Cartesian coordinate system can be obtained in real time using the Monte Carlo method, and then mapped using the following spatial mapping function A:

[0032]

[0033] Where, k rx ~k rz x is the pose mapping coefficient from the teleoperator to the slave robot arm. s ~rz s The teleoperator, after applying the aforementioned spatial mapping function, requires the slave robot to reach the target spatial position; subsequently, the slave robot, based on the inverse kinematics algorithm of the robotic arm, can obtain the rotation angles of each joint. coordinates The data is sent to the motors of each joint in the robot body, ultimately enabling the joint movement and remote operation control of the robot from the end.

[0034] Operators can control the remote operator in real time based on the information on the monitoring screen, thereby realizing the adaptive dry ice cleaning operation of the dry ice cleaning nozzle of the robot on the insulator.

[0035] Compared with existing technologies, the beneficial effects of this invention are as follows: First, compared with existing manual or robotic high-pressure water gun cleaning methods, which require power outages during cleaning, causing inconvenience to residents, are difficult to clean stubborn stains, and result in wastewater pollution requiring further purification. Second, addressing the challenges of insulators' complex structures, varying dimensions, and unclear features in the central area, making precise positioning difficult, this method utilizes an RGB-D camera to acquire high-precision point cloud information. The dry ice cleaning fixture for insulators is designed to be safer, more efficient, and more direct, thus possessing greater practical application value. Attached Figure Description

[0036] To more clearly illustrate the technical solutions of the embodiments of this application, the accompanying drawings used in the embodiments of this application will be briefly introduced below. It should be understood that the following drawings only show some embodiments of this application and should not be regarded as a limitation of the scope. For those skilled in the art, other related drawings can be obtained based on these drawings without creative effort.

[0037] Figure 1 This is a hardware schematic diagram of the remotely operated robot system for cleaning live dry ice insulators according to this application;

[0038] Figure 2 This is a schematic diagram of the teleoperated robot system for live dry ice cleaning of insulators according to this application.

[0039] Figure 3 This is a flowchart of the remote-operated robot operation method for cleaning insulators with live dry ice, as described in this application.

[0040] Figure 4 This is a schematic diagram of the vehicle-mounted laser-assisted parking solution of this application;

[0041] Figure 5 This is a schematic diagram of the control structure of the dry ice machine according to this application;

[0042] Figure 6 This is an RGB-D image of an insulator from this application;

[0043] Figure 7 This is a flowchart of the insulator fusion identification and localization method based on RGB-D images according to this application;

[0044] Figure 8 This is a schematic diagram of the virtual safety fence for insulators in this application;

[0045] Figure 9 This is a schematic diagram of the insulator cleaning operation described in this application;

[0046] Figure 10 This is a schematic diagram of the robot reset in this application;

[0047] Figure 11 This is a flowchart of the teleoperator control method based on the Monte Carlo method of this application. Detailed Implementation

[0048] The technical solutions of the embodiments of this application will now be described with reference to the accompanying drawings. It should be noted that similar reference numerals and letters in the following drawings indicate similar items; therefore, once an item is defined in one drawing, it does not need to be further defined and explained in subsequent drawings.

[0049] The terms “comprising,” “including,” or any other variations thereof are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or apparatus. Without further limitation, an element defined by the phrase “comprising one…” does not exclude the presence of other identical elements in the process, method, article, or apparatus that includes said element.

[0050] The terms “first,” “second,” etc., are used only to distinguish one entity or operation from another, and should not be construed as indicating or implying relative importance, nor as requiring or implying any such actual relationship or order between these entities or operations.

[0051] Reference Figure 1 and Figure 2 The present invention provides a remote-operated robot system for dry ice cleaning of energized insulators, comprising a robot system and a tracked insulated bucket truck. The robot system includes an RGB-D camera, a six-degree-of-freedom robotic arm, a dry ice machine subsystem, a monitoring camera, an industrial control computer, dry ice cleaning fixtures, a remote operator, a human-machine interface platform, and a power supply system. The remote operator is connected to the human-machine interface platform via USB and then communicates with the robot's industrial control computer via WIFI. Each joint of the tracked insulated bucket truck is equipped with an encoder or displacement measurement sensor, providing wireless remote control functionality and real-time acquisition of the spatial coordinates of the bucket truck's end.

[0052] The tracked insulated bucket truck is equipped with a complete robot system, and the dry ice machine subsystem is installed at the end of the six-degree-of-freedom robotic arm to perform dry ice cleaning operations on the insulators.

[0053] like Figures 1-11 As shown,

[0054] The robot can perform dry ice cleaning of insulators through the following process, which mainly includes six steps: (1) parking the tracked bucket truck; (2) entering the work station on the platform; (3) identifying and locating weak texture targets on the insulator; (4) dry ice cleaning of the insulator based on remote operation; (5) robot reset; (6) proceeding to the next phase operation, such as Figure 3 As shown, Figure 3 Remotely operated robot system and operation method for live dry ice cleaning of insulators

[0055] The specific embodiments of the present invention are as follows:

[0056] (1) Parking of the tracked boom truck base. Before formal operation, the boom truck needs to be parked in a suitable area under the insulator.

[0057] To address the difficulty in manually estimating the parking position of the insulated carrier, this step employs a laser-assisted positioning solution, as follows: Four single-line blue lasers are installed on the boom truck, divided into two groups. Group 1, A1 and A2, forms two parallel laser lines to indicate the maximum and minimum parking distances for the front and rear positions of the boom truck. Group 2, B1 and B2, forms two parallel laser lines to indicate the maximum and minimum parking distances for the left and right positions of the boom truck. The laser installation effect is shown in the diagram below. Figure 4 A schematic diagram of a vehicle-mounted laser-assisted parking solution is shown.

[0058] In the above scheme, it is necessary to find fixed reference points on site for positioning. Optional targets include roadside curbs, insulators, and utility poles, and the specific choice needs to be flexible based on the site environment. In practice, when the bucket truck is parked, the operator follows the operating procedures, remotely controls the insulated bucket truck, and observes in real time the distance between the position marked by the onboard laser and the reference point. This allows the insulated bucket truck to be gradually driven to the parking area below the insulators to be cleaned.

[0059] (2) Enter the work station on the platform. The robot system can be gradually transported to the insulator work station by remotely controlling the bucket truck through manual operation. At this time, the camera and dry ice cleaning equipment are facing the insulator. The dry ice nozzle is hollow cylindrical and the end is connected to a dry ice hose fixed along the robotic arm. Above is a binocular camera for visual positioning.

[0060] The nozzle of the dry ice cleaning fixture is directly connected to the dry ice tube. The high-speed dry ice particles in the tube originate from the air compressor and pneumatic dry ice machine on the tracked vehicle, forming a mixed high-pressure dry ice gas. The specific control method of the dry ice machine is as follows: Figure 5 As shown.

[0061] First, an air compressor provides high-speed, high-pressure gas (typically 1 MPa), controlled by a solenoid valve. The high-pressure gas then enters the pneumatic dry ice machine, driving a pneumatic motor to break up the dry ice particles inside. Finally, the particles are transported by high-speed gas to the insulator dry ice cleaning fixture to complete the cleaning operation. The entire dry ice machine requires no electricity, making it low-cost and safer.

[0062] (3) Weak-texture target recognition and localization. After reaching the work station on the upper platform, the robotic arm subsystem, equipped with an RGB-D camera, performs 3D reconstruction of the target from different perspectives, and stitches the reconstruction results together to ultimately obtain the color and depth information of the insulator. For example... Figure 6 As shown.

[0063] Then, based on the obtained RGB-D image information of the insulator, high-precision spatial positioning of the insulator skirts is achieved. Specifically, this invention proposes an insulator fusion recognition and positioning method based on RGB-D images, which has two modes: automatic algorithm recognition and manual selection recognition. These modes can be used in combination to obtain high-precision spatial coordinate information of the insulator skirts, as detailed below:

[0064] In the automatic identification mode of the algorithm, to achieve the functions of insulator identification and spatial positioning, it is first necessary to use a robotic arm to rotate an RGB-D camera (typically RealSense D455).

[0065] The second step is to automatically perform coarse insulator localization based on the prior information that the insulator is in the center region of the camera and a distance-based bandpass filtering algorithm. The third step is to use Principal Component Analysis (PCA) to calculate and correct the insulator tilt angle. The fourth step is to perform horizontal integration on the image to complete the horizontal projection of the insulator point cloud map, obtaining the insulator depth gradient map. The fifth step is to use a gradient detection operator to segment the insulator skirts and detect key points. The sixth step is to mark the key points on the color map, thus achieving automatic identification and high-precision spatial localization of the insulator skirts. The specific steps are as follows:

[0066] 1) Coarse localization of insulators: Using prior information (the insulator is located in the center area of ​​the camera) and a distance-based bandpass filtering algorithm, coarse localization of the insulators is automatically completed. By setting distance thresholds Dmin to Dmax, pixels outside this range are filtered out, retaining only the approximate outline of the insulator.

[0067] 2) Insulator attitude detection and correction: Principal component analysis (PCA) is used to calculate the insulator's tilt and perform image correction. The edge contour of the insulator is analyzed using PCA to calculate the principal component direction, i.e., the insulator's tilt direction θ, and then the image is rotated for correction.

[0068] 3) Depth Horizontal Histogram Acquisition: Perform horizontal integration on the image to complete the horizontal projection of the insulator point cloud map and obtain the insulator depth gradient map (DHH).

[0069] 4) Segmentation and Key Point Detection of Insulator Skirts: The gradient detection operator is used to segment and detect key points of the insulator skirts. Specific operation: The gradient detection operator is applied to the DHH to identify peaks and troughs, corresponding to the left and right edges and center point of the insulator skirt.

[0070] 5) Key point marking: The detected key points are marked on the color map to achieve automatic identification and high-precision spatial positioning of the insulator skirts, which is used for subsequent positioning and operation guidance.

[0071] In the above steps, the insulator attitude detection and correction, depth and horizontal histogram acquisition, insulator skirt segmentation and key point detection, and key point marking are all innovative points of this invention, while the coarse positioning of the insulator is an innovative application of existing technology.

[0072] In the manually selected recognition mode, the operator clicks on the insulator target p(x, y) in the two-dimensional image of the human-computer interaction system. The operator can then obtain the spatial 3D coordinates P(X, Y, Z) of the insulator skirt to be cleaned through the depth map and pinhole imaging model. The specific formula for calculating the 3D coordinates is as follows:

[0073]

[0074] In the above formula, f is the focal length of the color camera, dx and dy are the pixel size, and u0 and v0 are the coordinates of the camera's optical center.

[0075] Specifically, the insulator fusion identification and positioning method is as follows: Figure 7 As shown:

[0076] In the above process, the automatic identification mode is characterized by fast and comprehensive identification. When the on-site positioning deviates, it switches to the manual selection identification mode, which determines the target by manually clicking on the surface of the insulator. This mode has stronger environmental adaptability and higher positioning accuracy.

[0077] Finally, based on the acquired insulator spatial coordinate information, a virtual safety fence can be set up with the insulator's central axis as the center and the insulator skirt width as the radius. This fence is used for safety protection during subsequent remote robot control. The specific calculation steps for the safety fence are as follows:

[0078] Coordinate Acquisition: First, the coordinate set of key points on the insulator skirt is acquired using an RGB-D camera at the end effector of the six-DOF robotic arm. Let the coordinates of these key points in the robot's three-dimensional space be Pi = (xi, yi, zi), where i is the index of the key point.

[0079] Cylinder Fitting: Using these keypoint coordinates, a best-fitting cylinder can be fitted. The centerline of the cylinder can be considered the central axis of the insulator, and the radius R of the cylinder can be half the width of the skirt. Let the center coordinates of the cylinder be C = (xc, yc, zc). C and R can be solved by minimizing the sum of the squares of the distances from all keypoints to the centerline.

[0080] The equation of the cylinder can be expressed as: (x - xc) 2 +(y-yc) 2 =R 2 , where (x,y) are the projected coordinates of any point on the cylinder onto the horizontal plane.

[0081] Virtual safety fence setup: The virtual safety fence is formed by extending a certain safety distance d outward from the aforementioned cylinder. This safety distance is to ensure that the robot will not touch the insulator skirts during operation, thereby avoiding damage or accidents.

[0082] The equation for the expanded virtual security fence is: (x-xc) 2 +(y-yc) 2 ≤(R+d) 2 , where d is a value set according to operational safety requirements.

[0083] Safety protection is implemented as follows: During remote operation of the robot, the control system monitors the position of the robot's end effector, Probot = (xr, yr, zr), in real time. The robot operation is safe if Probot satisfies the following condition: (x - xc). 2 +(y-yc) 2 >(R+d) 2 If the above conditions are not met, the control system will take measures (such as suspending operation, issuing an alarm, automatically adjusting the position, etc.) to ensure the safety of operation.

[0084] The virtual safety fence for insulators is as follows: Figure 8 As shown:

[0085] (4) Dry ice cleaning of insulators based on remote operation. Due to the confined space and complex lighting conditions at the power distribution network site, the quality of the RGB-D images acquired by the robot is easily affected, leading to a certain probability of positioning failure or abnormal movement. In this case, the automatic operation mode of the human-machine interface tablet can be manually switched to the remote operation control mode. Then, the ground control personnel hold the ground-based remote operator's hand while simultaneously observing the remote monitoring camera in real time. Based on the high-altitude site conditions, they remotely fine-tune the dual robotic arms and then send corresponding commands to complete the corresponding operation function in a human-machine collaborative manner. Here, a remote operator control method based on the Monte Carlo method is proposed, and the specific implementation process is as follows: Figure 11 :

[0086] like Figure 11 ① Real-time acquisition of the joint angles of the teleoperator ② The Monte Carlo method is used to solve for the teleoperator's motion space. The specific formula is as follows:

[0087] q i =q min i +(q max i -q min i Rand(j) (1)

[0088] Where i is the sequence number of each joint of the teleoperator (1, 2, 3…6); qmaxi and qmini are the maximum and minimum values ​​of the joint variable of the i-th joint, respectively; Rand() is a function to generate random numbers, ranging from 0 to 1; and j is the number of random numbers.

[0089] By automatically selecting 40,000 sets of random joint rotation angles, and based on the principal kinematics model, the point cloud map of the telemanipulator's workspace can be obtained, and then the minimum and maximum ranges of the telemanipulator in the x, y, and z directions can be obtained, which are (xmMin, xmMax), (ymMin, ymMax), and (zmMin, zmMax), respectively; similarly, the range of motion of the slave robotic arm can be obtained: (xsMin, xsMax), (ysMin, ysMax), and (zsMin, zsMax).

[0090] In actual calculations, the position (xm, ym, zm) of the teleoperator in the Cartesian coordinate system can be obtained in real time using the Monte Carlo method, and then mapped using the following spatial mapping function A:

[0091]

[0092] Where, k rx ~k rz x is the pose mapping coefficient from the teleoperator to the slave robot arm. s ~rz s The teleoperator, after applying the aforementioned spatial mapping function, requires the slave robot to reach the target spatial position; subsequently, the slave robot, based on the inverse kinematics algorithm of the robotic arm, can obtain the rotation angles of each joint. coordinates The data is sent to the motors of each joint in the robot body, ultimately enabling the joint movement and remote operation control of the robot from the end.

[0093] Operators can control the remote operator in real time based on the information displayed on the monitoring screen, thereby enabling adaptive dry ice cleaning of insulators by the robot's dry ice cleaning nozzles. (See diagram below.) Figure 9 As shown.

[0094] The robotic arm then moves the dry ice cleaning equipment upwards to begin cleaning the next stage of the insulator's skirts. This process is repeated until the skirts on the high-voltage side above the insulator are cleaned. Afterwards, a remotely controlled bucket truck transports the robotic platform to the next phase insulator to continue the dry ice cleaning operation.

[0095] (6) Robot Reset. After completing the live-line cleaning task of the insulator, the robotic arm retracts to its initial position, and the insulator lifting device is retracted. (See schematic diagram below.) Figure 10 As shown.

[0096] (7) Exit the work station. Manually control the boom truck to remove the upper platform from the work station and return the boom truck to the original position.

[0097] This invention designs a remote-operated robot system for cleaning live insulators with dry ice, comprising two parts: the main robot and a tracked insulated bucket truck. The main robot system includes subsystems such as a robotic arm, binocular camera, remote operator, and power supply, forming the entire operating system. By setting virtual fences, the robot can be controlled to avoid encountering the target during remote operation, ensuring safety.

[0098] This invention designs a dry ice cleaning fixture and method for insulators. The fixture includes a straight nozzle and a dry ice hose. A robotic arm drives the nozzle to move back and forth, up and down, and rotate, enabling comprehensive, all-around cleaning of the insulator's front surface. Compared to traditional high-pressure water gun cleaning methods, this invention proposes dry ice cleaning, which can be performed while the circuit is energized, and is more effective and efficient at cleaning stubborn stains. Furthermore, compared to existing robotic ring-shaped dry ice cleaning methods, the dry ice straight tube cleaning method proposed in this invention has the advantages of lower dry ice consumption, larger flow rate, and higher cleaning quality.

[0099] This invention proposes using a purely pneumatic dry ice machine for dry ice cleaning of insulators, reducing the power load required for electrically driven dry ice machines. The dry ice machine only requires 1MPA (1.5m³ / min) high-pressure gas to operate, and its operation is controlled by the on / off state of the gas path, resulting in lower cost and greater safety.

[0100] This invention proposes a robotic dry ice cleaning method for insulators, which mainly includes six steps: (1) parking the tracked boom truck; (2) entering the work station on the upper platform; (3) identifying and locating weak texture targets on the insulator; (4) dry ice cleaning of the insulator based on remote operation; (5) robot reset; and (6) proceeding to the next phase. This method effectively ensures the personal safety of operators and efficiently realizes live dry ice cleaning of insulators.

[0101] This invention further proposes an insulator fusion identification and positioning method based on RGB-D images, which has two modes: automatic identification and manual selection identification. The automatic identification mode is characterized by fast and comprehensive identification, while the manual selection identification mode has stronger environmental adaptability and higher positioning accuracy.

[0102] The above description is merely an embodiment of this application and is not intended to limit the scope of protection of this application. Various modifications and variations can be made to this application by those skilled in the art. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of this application should be included within the scope of protection of this application.

Claims

1. A remotely operated robot method for cleaning live insulators with dry ice, characterized in that, The specific steps include the following: The tracked bucket truck is parked, the insulated bucket truck is remotely controlled and the distance between the position marked by the on-board laser and the reference object is observed in real time. The insulated bucket truck is then gradually driven to the parking area below the insulator to be cleaned. The robot system is gradually transported to the insulator work station on the platform. At this time, the camera and dry ice cleaning equipment are facing the insulator. Insulator weak texture target recognition and localization: an insulator fusion recognition and localization method based on RGB-D images, used to obtain high-precision spatial coordinate information of insulator skirts; Based on remote operation, dry ice cleaning of insulators allows operators to control the remote operator in real time according to the information on the monitoring screen, thereby realizing the adaptive dry ice cleaning operation of the robot's dry ice cleaning nozzle on the insulator. After the robot resets and completes the task of cleaning the insulator while it is energized, the robotic arm retracts to its initial position, and the insulator lifting device is retracted. The insulator weak texture target identification and positioning method is as follows: after the upper platform reaches the work position, the robotic arm subsystem carries an RGB-D camera to perform three-dimensional reconstruction of the target from different perspectives, and stitches the reconstruction results to finally obtain the color and depth information of the insulator. Then, based on the obtained RGB-D image information of the insulator, high-precision spatial positioning of the insulator skirt is achieved. The insulator fusion identification and positioning method based on RGB-D images has two modes: automatic algorithm recognition and manual selection recognition, which are used to obtain high-precision spatial coordinate information of the insulator skirt. The insulator fusion identification and positioning method based on RGB-D images has two modes: automatic algorithm identification and manual selection identification. Specifically, it is used to obtain high-precision spatial coordinate information of the insulator skirts. In the automatic algorithm identification mode, to achieve insulator identification and spatial positioning, the first step is to use a robotic arm to rotate the RGB-D camera. The second step is to automatically complete the coarse positioning of the insulator based on the prior information that the insulator is in the center region of the camera and a distance-based bandpass filtering algorithm. The third step is to use PCA (Principal Component Analysis) to calculate and correct the insulator tilt angle. The fourth step is to perform horizontal integration on the image to complete the horizontal projection of the insulator point cloud map, obtaining the insulator depth gradient map. The fifth step is to use the gradient detection operator to complete the segmentation and key point detection of the insulator skirts; the sixth step is to mark the key points on the color map, thus realizing the automatic identification and high-precision spatial positioning function of the insulator skirts; ② In the manually selected identification mode, the operator clicks on the insulator target p(x, y) in the two-dimensional image of the human-computer interaction system, and obtains the spatial 3D coordinates P(X, Y, Z) of the insulator skirt to be cleaned through the depth map and the pinhole imaging model. The specific formula for calculating the 3D coordinates is: (1) In the above formula, f is the focal length of the color camera, dx and dy are the pixel size, and u0 and v0 are the coordinates of the camera's optical center.

2. The remote-operated robot operation method for live-line dry ice cleaning of insulators according to claim 1, characterized in that, The specific method for parking the tracked bucket truck involves installing four single-line blue lasers on the bucket truck, divided into two groups. The first group, A1 and A2, forms two parallel laser lines to indicate the maximum and minimum parking distances for the front and rear positions of the bucket truck. The second group, B1 and B2, forms two parallel laser lines to indicate the maximum and minimum parking distances for the left and right positions of the bucket truck. The operator remotely controls the insulated bucket truck according to the operating procedures and observes in real time the distance from the position marked by the onboard lasers to the reference object, gradually driving the insulated bucket truck to the parking area below the insulator to be cleaned.

3. The remote-operated robot operation method for live-line dry ice cleaning of insulators according to claim 1, characterized in that, Specifically, the above-platform entry into the work station involves a remotely controlled boom truck operated by a human to gradually transport the robot system to the insulator work station. At this point, both the camera and the dry ice cleaning fixture are facing the insulator. The nozzle of the dry ice cleaning fixture is directly connected to the dry ice tube. The high-speed dry ice particles in the dry ice tube come from the air compressor and pneumatic dry ice machine on the tracked vehicle, forming a mixed high-pressure dry ice gas. The air compressor provides high-speed, high-pressure gas, and its on / off state is controlled by a solenoid valve. Then, the high-pressure gas enters the pneumatic dry ice machine, driving the pneumatic motor to rotate and break up the dry ice particles inside the dry ice machine. Finally, the high-speed gas transports the dry ice to the insulator dry ice cleaning fixture to complete the cleaning operation.

4. The remote-operated robot operation method for live-line dry ice cleaning of insulators according to claim 1, characterized in that, The weak texture target recognition and localization of insulators also includes setting up virtual safety fences for insulators, which are used for safety protection during subsequent remote operation control of the robot. The specific calculation steps for the safety fence are as follows: Coordinate acquisition: First, the coordinate set of key points of the insulator skirt is obtained by the RGB-D camera at the end of the six-degree-of-freedom robot arm. Let the coordinates of these key points in the robot's three-dimensional space be Pi=(xi,yi,zi), where i is the index of the key point; Cylinder Fitting: Using these key point coordinates, fit an optimally matched cylinder. The centerline of the cylinder is considered to be the central axis of the insulator. The radius R of the cylinder is half the width of the skirt. Let the center coordinates of the cylinder be C=(xc,yc,zc). Solve for C and R by minimizing the sum of the squares of the distances from all key points to the centerline. The equation of the cylinder is expressed as: (x−xc) 2 +(y−yc) 2 =R 2 , where (x,y) are the projected coordinates of any point on the cylinder onto the horizontal plane; Virtual safety fence setting: The virtual safety fence is formed by extending a certain safety distance d outward from the above cylinder. This safety distance is to ensure that the robot will not touch the insulator skirt during operation, thereby avoiding damage or accidents. The equation for the expanded virtual security fence is: (x−xc) 2 +(y−yc) 2 ≤(R+d) 2 , where d is a value set according to operational safety requirements; Safety protection is implemented as follows: During remote operation of the robot, the control system monitors the position of the robot's end effector, Probot=(xr,yr,zr), in real time. If Probot satisfies the following condition, the robot operation is safe: (x−xc) 2 +(y−yc) 2 >(R+d) 2 If the above conditions are not met, the control system will take measures to ensure the safety of operation.

5. A remotely operated robot operation method for live dry ice cleaning of insulators according to claim 1, characterized in that, The specific steps of insulator dry ice cleaning based on teleoperation are: ① Real-time acquisition of the joint angles of the teleoperator. ② The Monte Carlo method is used to solve for the teleoperator's motion space. The specific formula is as follows: (1) Where i is the sequence number of each joint of the teleoperator (1, 2, 3...6); qmaxi and qmini are the maximum and minimum values ​​of the joint variable of the i-th joint, respectively; Rand() is a function to generate random numbers, ranging from 0 to 1; and j is the number of random numbers. By automatically selecting 40,000 sets of random joint angles, and based on the master kinematics model, the point cloud map of the telemanipulator's workspace is obtained, thereby obtaining the minimum and maximum ranges of the telemanipulator in the x, y, and z directions, which are (xmMin, xmMax), (ymMin, ymMax), and (zmMin, zmMax), respectively. Similarly, the range of motion of the slave manipulator is obtained: (xsMin, xsMax), (ysMin, ysMax), and (zsMin, zsMax). In actual calculations, the position (xm, ym, zm) of the teleoperator in the Cartesian coordinate system is obtained in real time using the Monte Carlo method, and then the following spatial mapping function A is used: （2） in, For the pose mapping coefficient from the teleoperator to the slave robot arm, The teleoperator, after applying the aforementioned spatial mapping function, requires the slave robot to reach the target spatial position; subsequently, the slave robot, based on the inverse kinematics algorithm of the robotic arm, obtains the joint angles. ; coordinates The data is sent to the motors of each joint in the robot body, ultimately enabling remote control of the robot's joint movements. Based on the information displayed on the monitoring screen, the operator controls the remote manipulator in real time, thereby enabling the robot's dry ice cleaning nozzle to perform adaptive dry ice cleaning operations on the insulators.

6. A remotely operated robot system for cleaning live insulators with dry ice, used to implement the method of claim 1, characterized in that, The system consists of two parts: a complete robot system and a tracked insulated bucket truck. The complete robot system includes an RGB-D camera, a six-degree-of-freedom robotic arm, a dry ice machine subsystem, a monitoring camera, an industrial control computer, dry ice cleaning equipment, a remote operator, a human-machine interface platform, and a power system. The remote operator connects to the human-machine interface platform via USB and then communicates with the robot's industrial control computer via WIFI. Each joint of the tracked insulated bucket truck is equipped with an encoder or displacement measurement sensor, which has wireless remote control function and can simultaneously acquire the spatial coordinates of the bucket truck's end in real time.

7. A remotely operated robot system for live dry ice cleaning of insulators according to claim 6, characterized in that, The tracked insulated bucket truck is equipped with a complete robot system, and the dry ice machine subsystem is installed at the end of the six-degree-of-freedom robotic arm to perform dry ice cleaning operations on the insulators.

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