Multi-mode navigation control method and system for high-altitude cable de-icing robot

Abstract

The application discloses a multi-mode navigation control method and system of a high-altitude cable deicing robot, and belongs to the field of navigation control. The multi-mode navigation control method of the high-altitude cable deicing robot comprises the following steps: collecting data by using a multi-sensor fusion system carried by the robot, generating a dynamic multi-dimensional risk map based on the collected data, and marking the moving path of the robot, the large slope area, the cable dancing area and the stain influence area on the multi-dimensional risk map; when predicting that the robot is about to enter the large slope area, controlling the robot to be in a brake priority mode; compared with the prior art, the application has the beneficial effects that: by constructing a multi-dimensional risk map, the moving path of the robot is divided into a conventional area, a large slope area, a cable dancing area and a stain influence area, and different control modes are adopted for different areas, so that the environmental adaptability of the high-altitude cable deicing robot is significantly improved.

Description

Technical Field

[0001] This invention belongs to the field of navigation and control, and in particular relates to a multi-mode navigation and control method and system for a high-altitude cable de-icing robot. Background Technology

[0002] High-altitude cable de-icing robots are automated devices used to remove ice from the surface of high-voltage transmission lines. They prevent excessively thick ice layers from causing cable breakage or power outages, thus ensuring the stable operation of the power grid in frigid environments.

[0003] Existing high-altitude cable de-icing robots have significant shortcomings in adapting to complex environments, specifically:

[0004] 1. Stability defects under wind interference: When strong winds occur, the cable will generate low-frequency, large-amplitude wave-like motion, making the robot operate as if it were on a swaying swing. This violent shaking will disrupt its balance control, increase the risk of derailment, and even lead to mission interruption.

[0005] 2. The impact of special attachments: (1) Bird droppings: Damp bird droppings have high adhesion, which will not only reduce the friction between the wheel and the cable instantly, but may also adhere to the wheel and form continuous resistance, affecting the subsequent movement efficiency. (2) Dust and salt stains: A thick layer of dust will significantly reduce the coefficient of friction. If it encounters a damp environment, it may turn into mud, further hindering the robot's movement, and even causing slippage or jamming problems.

[0006] In summary, existing high-altitude cable de-icing robots have an imperfect environmental adaptation mechanism and need improvement. Summary of the Invention

[0007] Therefore, it is necessary to provide a multi-mode navigation control method and system for high-altitude cable de-icing robots to address the above-mentioned problems.

[0008] The present invention is implemented as follows: a multi-mode navigation control method for a high-altitude cable de-icing robot includes the following steps:

[0009] The robot utilizes a multi-sensor fusion system (such as lidar and stereo vision cameras) to precisely scan the cable's geometry, calculate its slope angle and sag in real time, and detect low-frequency, high-amplitude cable galloping; simultaneously, the vision system, specially trained, can identify abnormal reflections and textures on the cable surface, thus marking areas contaminated by damp bird droppings, thick dust, or salt stains; induction coils and torque sensors continuously monitor the robot's contact state and adhesion with the cable) to collect data. Based on the collected data, a dynamic multi-dimensional risk map is generated, marking the robot's movement path, steep slope areas, cable galloping areas, and areas affected by contamination (bird droppings, mud, etc.).

[0010] When it is predicted that the robot is about to enter a steep slope area, the robot's movement mode is controlled to brake priority mode; when it is predicted that the robot is about to enter a cable galloping area, the robot's movement mode is controlled to active balancing mode; when it is predicted that the robot is about to enter a stained area, the robot's movement mode is controlled to low-speed creep mode.

[0011] When the robot is moving in areas with steep slopes, swaying cables, or areas affected by dirt, its actual movement status is continuously monitored by its own sensors (such as encoders, IMUs, inclinometers, and torque sensors). This monitoring is compared with the expected state of the robot's current mode. When an anomaly is detected (e.g., unexpected acceleration on a steep slope, indicating insufficient braking; body posture angle exceeding the safety threshold during swaying, posing a risk of tipping over; mismatch between drive wheel speed and body speed, resulting in severe slippage), a fault-tolerance mechanism is triggered (the fault-tolerance mechanism includes instantly increasing braking force, tightening all grippers to enter a "lock-up" safety mode, and switching to a more conservative crawling gait to attempt to escape). The real-time status data is then fed back to the multi-dimensional risk map for updates.

[0012] In one embodiment, the present invention provides a multi-mode navigation control method for a high-altitude cable de-icing robot. The steps of controlling the robot's movement mode to a braking priority mode when it is predicted that the robot is about to enter a steep slope area; controlling the robot's movement mode to an active balancing mode when it is predicted that the robot is about to enter a cable galloping area; and controlling the robot's movement mode to a low-speed creeping mode when it is predicted that the robot is about to enter a soiled area, specifically include:

[0013] When it is predicted that the robot is about to enter a steep slope area, the robot's movement mode is controlled to brake priority mode. When descending a steep slope, the robot's power system is controlled to perform regenerative electromagnetic braking, and intermittent braking intervention is performed according to the real-time tilt angle and acceleration to prevent loss of control. When ascending a steep slope, the left and right drive wheels are controlled to perform independent torque precise distribution and anti-slip control to provide sufficient traction and prevent single wheel slippage.

[0014] When it is predicted that the robot is about to enter the area where the cable is swaying, the robot's movement mode is controlled to be active balancing mode. Through movable joints or control torque gyroscopes, a compensating torque opposite to the cable swaying is generated to stabilize the robot body in the inertial space.

[0015] When predicting that the robot is about to enter a contaminated area, the robot's movement mode is controlled to be a low-speed creeping mode. The gait parameters are adjusted to reduce the rhythm and amplitude of the alternating movements of the gripping mechanism to reduce the risk of dynamic slippage. The gripping force is increased, and the output positive pressure of the gripping mechanism is appropriately increased during the clamping phase to improve the reliability of the grip. The cleaning function is activated, and the cleaning device (such as high-pressure air jet or rotating brush) is linked to clean the surface of the cable to be contacted and the mechanism body in real time during the interval of the gripping mechanism's movement to restore effective friction as much as possible.

[0016] In one embodiment, the present invention provides a multi-mode navigation control method for a high-altitude cable de-icing robot, further comprising:

[0017] The robot continuously compares real-time environmental data (such as current slope, cable sway amplitude, robot stability, and cable surface adhesion) with preset safety thresholds to determine whether the environment is stable or dangerous. If it is a stable environment, the robot continues to perform the de-icing task; if it is a dangerous environment, the robot stops the de-icing task and navigates to a preset safe area (such as the nearest tower or a cable section that has been confirmed to be stable and has a gentle slope) and enters a low-power standby mode to continuously monitor the environment and wait for the environment to change to a stable environment.

[0018] In one embodiment, the present invention provides a multi-mode navigation control method for a high-altitude cable de-icing robot, further comprising:

[0019] When the robot enters a regular area, on flat, unobstructed cable sections, it selects the wheeled movement mode to move (the braking priority mode is an improvement of the wheeled movement mode in special environments). When encountering obstacles (insulators, clamps, etc., which are different from areas affected by dirt, where dirt is in patches and obstacle-crossing mode can cause the robotic arm and grippers to become dirty, posing a risk of falling), the robot switches to obstacle-crossing mode. If severe icing of the cable is detected, causing a decrease in adhesion, the robot switches to crawling mode (the low-speed crawling mode is an improvement of the crawling mode in special environments) to provide greater gripping force and stability.

[0020] In one embodiment, the present invention provides a multi-mode navigation control method for a high-altitude cable de-icing robot, further comprising:

[0021] As the robot moves along the cable, it continuously measures and records the actual friction coefficient of different sections of the road using the robot's own sensors (wheel torque, slippage status), obtains friction data, and feeds the friction data back to the multi-dimensional risk map for updates, so as to adjust the robot's movement path planning.

[0022] In one embodiment, the present invention provides a multi-mode navigation control system for a high-altitude cable de-icing robot, comprising:

[0023] The multi-dimensional risk map construction module utilizes the robot's multi-sensor fusion system (such as lidar and stereo vision cameras) to accurately scan the cable's geometry, calculate the cable's slope angle and sag in real time, and detect the presence of low-frequency, high-amplitude cable galloping; simultaneously, the vision system, specially trained, can identify abnormal reflections and textures on the cable surface, thereby marking areas contaminated by damp bird droppings, thick dust, or salt stains; induction coils and torque sensors continuously monitor the robot's contact status and adhesion with the cable) to collect data. Based on the collected data, a dynamic multi-dimensional risk map is generated, which marks the robot's movement path, steep slope areas, cable galloping areas, and areas affected by contamination (bird droppings, mud, etc.).

[0024] The multi-mode adjustment module is used to control the robot's movement mode to braking priority mode when it is predicted that the robot is about to enter a steep slope area; to control the robot's movement mode to active balancing mode when it is predicted that the robot is about to enter a cable galloping area; and to control the robot's movement mode to low-speed creep mode when it is predicted that the robot is about to enter a soiled area.

[0025] The protection and update module is used to continuously monitor the robot's actual movement status through its own sensors (such as encoders, IMUs, inclinometers, and torque sensors) when the robot is moving in areas with steep slopes, cable galloping, or areas affected by dirt. The module compares the robot's actual movement status with the expected status of the current mode. When an anomaly is detected (e.g., unexpected acceleration on a steep slope, i.e., insufficient braking; body posture angle exceeding the safety threshold during galloping, posing a risk of tipping over; mismatch between drive wheel speed and body speed, resulting in severe slippage), the module triggers a fault-tolerance mechanism (which includes instantly increasing braking force, tightening all grippers to enter a "lock-up" safety mode, and switching to a more conservative crawling gait to attempt to escape). The real-time status data is then fed back to the multi-dimensional risk map for updating.

[0026] In one embodiment, the present invention provides a multi-mode navigation control system for a high-altitude cable de-icing robot, the multi-mode adjustment module comprising:

[0027] The braking priority mode working unit is used to control the robot's travel mode to braking priority mode when it is predicted that the robot is about to enter a steep slope area. When descending a steep slope, it controls the robot's power system to perform regenerative electromagnetic braking and performs intermittent braking intervention based on real-time tilt angle and acceleration to prevent loss of control. When ascending a steep slope, it controls the left and right drive wheels to perform independent torque precise distribution and anti-slip control to provide sufficient traction and prevent single wheel slippage and freewheeling.

[0028] The active balancing mode working unit is used to control the robot's movement mode to active balancing mode when it is predicted that the robot is about to enter the cable galloping area. Through movable joints or control torque gyroscopes, it generates a compensating torque that is opposite to the cable swaying, stabilizing the robot body in the inertial space.

[0029] The low-speed creep mode working unit is used to control the robot's movement mode to a low-speed creep mode when it is predicted that the robot is about to enter a contaminated area. It adjusts the gait parameters and reduces the rhythm and amplitude of the alternating movement of the gripping mechanism to reduce the risk of dynamic slippage; it enhances the gripping force by appropriately increasing the output positive pressure of the gripping mechanism during the clamping phase to improve the reliability of the grip; and it activates the cleaning function, linking with cleaning devices (such as high-pressure air jets or rotating brushes) to clean the surface of the cable to be contacted and the mechanism body in real time during the intervals of the gripping mechanism's movement, in order to restore effective friction as much as possible.

[0030] In one embodiment, the present invention provides a multi-mode navigation control system for a high-altitude cable de-icing robot, further comprising:

[0031] The de-icing task termination module continuously compares real-time environmental data (such as current slope, cable sway amplitude, robot stability, and cable surface adhesion) with preset safety thresholds to determine whether the environment is stable or dangerous. If it is a stable environment, the robot continues to perform the de-icing task; if it is a dangerous environment, the robot stops the de-icing task and navigates to a preset safe area (such as the nearest tower or a cable section that has been confirmed to be stable and has a gentle slope) and enters a low-power standby mode to continuously monitor the environment and wait for the environment to change to a stable one.

[0032] In one embodiment, the present invention provides a multi-mode navigation control system for a high-altitude cable de-icing robot, further comprising:

[0033] The standard area passage module is used to select the robot's wheeled movement mode for travel on flat, unobstructed cable sections when the robot enters a standard area (the braking priority mode is an improvement of the wheeled movement mode in special environments). When encountering obstacles (insulators, clamps, etc., which are different from areas affected by dirt, where dirt is in patches and obstacle-crossing mode can cause the robotic arm and grippers to become dirty, posing a risk of falling), the robot switches to obstacle-crossing mode. If severe cable icing is detected, causing a decrease in adhesion, the robot switches to a crawling mode (the low-speed crawling mode is an improvement of the crawling mode in special environments) to provide greater gripping force and stability.

[0034] In one embodiment, the present invention provides a multi-mode navigation control system for a high-altitude cable de-icing robot, further comprising:

[0035] The friction coefficient update module is used to continuously measure and record the actual friction coefficient of different road sections through the robot's body sensors (wheel torque, slippage) when the robot is moving on the cable, obtain friction data, and feed the friction data back to the multi-dimensional risk map for updating, so as to adjust the robot's movement path planning.

[0036] Compared with the prior art, the beneficial effects of the present invention are: by constructing a multi-dimensional risk map, the present invention divides the robot's movement path into regular areas, steep slope areas, cable galloping areas, and areas affected by dirt, and adopts different control modes for different areas, thereby significantly improving the environmental adaptability of the high-altitude cable de-icing robot. Attached Figure Description

[0037] Figure 1 This is a schematic diagram of the first part of the multi-mode navigation control method for a high-altitude cable de-icing robot provided in an embodiment of the present invention.

[0038] Figure 2 This is a flowchart illustrating the process of selecting different modes for different regions in an embodiment of the present invention.

[0039] Figure 3 This is a schematic diagram of the second part of the multi-mode navigation control method for a high-altitude cable de-icing robot provided in an embodiment of the present invention.

[0040] Figure 4 This is a schematic diagram of the third part of the multi-mode navigation control method for a high-altitude cable de-icing robot provided in an embodiment of the present invention.

[0041] Figure 5 This is a schematic diagram of the fourth part of the multi-mode navigation control method for a high-altitude cable de-icing robot provided in an embodiment of the present invention.

[0042] Figure 6This is a schematic diagram of the first part of the multi-mode navigation control system for a high-altitude cable de-icing robot provided in an embodiment of the present invention.

[0043] Figure 7 This is a schematic diagram of a multi-mode adjustment module provided in an embodiment of the present invention.

[0044] Figure 8 This is a schematic diagram of the second part of the multi-mode navigation control system for the high-altitude cable de-icing robot provided in an embodiment of the present invention.

[0045] Figure 9 This is a schematic diagram of the third part of the multi-mode navigation control system for the high-altitude cable de-icing robot provided in an embodiment of the present invention.

[0046] Figure 10 This is a schematic diagram of the fourth part of the multi-mode navigation control system for the high-altitude cable de-icing robot provided in an embodiment of the present invention. Detailed Implementation

[0047] To make the objectives, technical solutions, and advantages of this invention clearer, the invention will be further described in detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative and not intended to limit the invention.

[0048] In one embodiment, such as Figure 1 As shown, the multi-mode navigation control method for a high-altitude cable de-icing robot includes the following steps:

[0049] Step S1: The robot utilizes a multi-sensor fusion system (such as lidar and stereo vision cameras) to precisely scan the cable's geometry, calculate the cable's slope angle and sag in real time, and detect the presence of low-frequency, high-amplitude cable galloping; simultaneously, the vision system, specially trained, can identify abnormal reflections and textures on the cable surface, thereby marking areas contaminated by damp bird droppings, thick dust, or salt stains; induction coils and torque sensors continuously monitor the contact state and adhesion between the robot and the cable) to collect data. Based on the collected data, a dynamic multi-dimensional risk map is generated, which marks the robot's movement path, steep slope areas, cable galloping areas, and areas affected by contaminants (bird droppings, mud, etc.).

[0050] Step S2: When it is predicted that the robot is about to enter a steep slope area, the robot's movement mode is controlled to brake priority mode; when it is predicted that the robot is about to enter a cable galloping area, the robot's movement mode is controlled to active balancing mode; when it is predicted that the robot is about to enter a stain-affected area, the robot's movement mode is controlled to low-speed creep mode.

[0051] Step S3: If the robot is moving in a steep slope area, a cable galloping area, or an area affected by dirt, the robot's actual motion state is continuously monitored by its own sensors (such as encoders, IMUs, inclinometers, and torque sensors) and compared with the expected state of the robot's current mode. When an anomaly is detected (e.g., unexpected acceleration is detected on a steep slope, i.e., insufficient braking; the body posture angle exceeds the safety threshold during galloping, posing a risk of overturning; the speed of the drive wheels does not match the speed of the body, resulting in severe slippage), a fault tolerance mechanism is triggered (the fault tolerance mechanism includes instantly increasing braking force, tightening all grippers to enter a "lock-up" safety mode, and switching to a more conservative crawling gait to attempt to escape); the real-time status data is fed back to the multi-dimensional risk map for updating.

[0052] In step S1, generating a dynamic multidimensional risk map refers to the system fusing and processing heterogeneous data collected by multiple sensors (such as LiDAR, vision systems, torque sensors, etc.) to construct an environmental model that is continuously updated in time and space. This map not only includes the geometric path of the cable but also uses a semantic layer to label areas with different risk attributes: for example, it identifies areas with steep slopes based on slope angle calculations, marks areas of cable galloping by detecting low-frequency cable vibrations, and delineates areas affected by stains such as bird droppings and salt deposits using visual recognition results. Each area is associated with a corresponding risk level and response strategy, enabling the robot to perceive environmental characteristics ahead in advance, providing a core basis for subsequent pattern decisions and path planning. The multidimensional risk map is dynamically updated, meaning it refreshes in real time as the robot moves and the environment changes, ensuring that navigation decisions are always based on the latest on-site conditions.

[0053] In step S2, the steep slope area is a dynamically defined category relative to the robot's climbing ability and stability threshold. The core criterion is the cable's slope angle, which is measured and calculated in real-time by sensors on the robot (such as LiDAR and inclinometers). Specifically, when the detected slope angle exceeds a preset threshold (e.g., 30 degrees), the cable segment is marked as a steep slope area. This threshold is not fixed but is determined by comprehensively considering the robot's physical limits (such as the maximum torque of the drive wheels and the adhesion of the gripping mechanism) and safety redundancy. Operationally, this area can be further subdivided into steep uphill and steep downhill zones, and risk levels may be further classified based on the severity of the slope (such as the slope angle and continuous slope length) to trigger different levels of braking or power distribution strategies.

[0054] In one embodiment, such as Figure 2As shown, the multi-mode navigation control method for a high-altitude cable de-icing robot includes the following steps in step S2: when it is predicted that the robot is about to enter a steep slope area, the robot's travel mode is controlled to brake priority mode; when it is predicted that the robot is about to enter a cable galloping area, the robot's travel mode is controlled to active balancing mode; and when it is predicted that the robot is about to enter a soiled area, the robot's travel mode is controlled to low-speed creeping mode.

[0055] Step S21: When it is predicted that the robot is about to enter a steep slope area, the robot's travel mode is controlled to brake priority mode. When descending a steep slope, the robot's power system is controlled to perform regenerative electromagnetic braking. The robot intervenes with intermittent braking based on the real-time tilt angle and acceleration to prevent loss of control. When ascending a steep slope, the left and right drive wheels are controlled to perform independent torque precise distribution and anti-slip control to provide sufficient traction and prevent single wheel slippage.

[0056] Step S22: When it is predicted that the robot is about to enter the cable dancing area, the robot's movement mode is controlled to be active balancing mode. Through movable joints or control torque gyroscope, a compensating torque opposite to the cable swaying is generated to stabilize the robot body in the inertial space.

[0057] Step S23: When it is predicted that the robot is about to enter the area affected by the stain, the robot's movement mode is controlled to a low-speed creeping mode, the gait parameters are adjusted, and the rhythm and amplitude of the alternating movement of the gripping mechanism are reduced to reduce the risk of dynamic slippage; the gripping force is increased, and the output positive pressure of the gripping mechanism is appropriately increased during the clamping phase to improve the reliability of the grip; the cleaning function is activated, and the cleaning device (such as high-pressure air spray or rotating brush) is linked to perform immediate cleaning on the surface of the cable to be contacted and the mechanism body during the interval of the gripping mechanism's movement to restore effective friction as much as possible.

[0058] In step S22, to ensure the active balancing mode is achieved, high-speed closed-loop control is relied upon. First, a high-precision inertial measurement unit (IMU) detects the angular velocity and acceleration of the cable's swaying in real time at millisecond frequencies and calculates the phase and amplitude of the swaying. Subsequently, the controller immediately calculates the compensation torque required to counteract the swaying, in the opposite direction, based on this dynamic data. Finally, this command is sent to the actuator: if a movable joint is used, it drives the joint (such as the pitch joint in the middle of the robot's body) to move rapidly in the opposite direction of the cable's swaying, generating a reaction force; if a control torque gyroscope (CMG) is used, a strong gyroscopic torque is generated through the precession of a high-speed flywheel to resist tilting. This forms a negative feedback loop, ensuring the stability of the robot body relative to the ground (inertial space), rather than swaying with the cable.

[0059] In one embodiment, such as Figure 3 As shown, the multi-mode navigation control method for the high-altitude cable de-icing robot also includes:

[0060] Step S4: Continuously compare real-time environmental data (such as current slope, cable sway amplitude, machine stability, and cable surface adhesion) with preset safety thresholds to determine whether the environment is stable or dangerous. If it is a stable environment, control the robot to continue performing the de-icing task; if it is a dangerous environment, control the robot to stop the de-icing task and navigate to a preset safe area (such as the nearest iron tower or a cable section that has been confirmed to be stable and has a gentle slope) to enter a low-power standby mode, continuously monitor the environment, and wait for the environment to change to a stable environment.

[0061] The robot primarily employs a combination of mechanical crushing and thermal assistance for de-icing. Mechanically, a high-frequency impact hammer or rotating ice-breaking blade is typically used to break or scrape away the ice covering the cable surface through instantaneous mechanical force. Thermally, low-power resistance heating or a hot air gun may be used to soften and melt thin or stubborn ice layers, reducing the load on the mechanical de-icing process. The de-icing device operates synchronously with the robot's movement, and the broken ice fragments naturally fall off under gravity. This combined de-icing method aims to efficiently remove ice while minimizing potential damage to the cable itself.

[0062] In one embodiment, such as Figure 4 As shown, the multi-mode navigation control method for the high-altitude cable de-icing robot also includes:

[0063] Step S5: When the robot enters a normal area, on flat, unobstructed cable sections, select the robot's wheeled movement mode to move (the braking priority mode is an improvement of the wheeled movement mode in special environments); when encountering obstacles (insulators, clamps, etc., which are different from areas affected by dirt, where dirt is in patches, and obstacle-crossing mode can also cause the robotic arm and grippers to get dirty, posing a risk of falling), control the robot to switch to obstacle-crossing mode; if severe cable icing is detected, causing a decrease in adhesion, control the robot to switch to crawling mode (the low-speed crawling mode is an improvement of the crawling mode in special environments) to provide greater gripping force and stability.

[0064] Wheeled movement is the robot's basic and efficient locomotion mode. In this mode, the robot primarily moves along the cable by rotating its drive wheels. In obstacle-crossing mode, the robot adjusts its body posture, using a robotic arm or specific gripping mechanism to first release the rear gripper, then cross the obstacle and re-grip the cable, achieving a crawling motion similar to an inchworm. The creeping mode is a highly stable and traction-based locomotion mode. In this mode, multiple gripping mechanisms perform alternating tightening and loosening movements in a specific sequence, generating a wave-like propulsion force similar to an inchworm, thus moving slowly and steadily. This mode is naturally suitable for scenarios with insufficient global traction, such as slippery or icy areas. Throughout the process, attitude adjustment mechanisms (such as counterweights or gyroscopes) continuously work to counteract wind loads and swaying caused by its own movement, maintaining the robot's balance. This is a balancing behavior, while the active balancing mode simply uses a more powerful actuator (torque gyroscope) to achieve the same but more advanced goal.

[0065] In one embodiment, such as Figure 5 As shown, the multi-mode navigation control method for the high-altitude cable de-icing robot also includes:

[0066] Step S6: When the robot is moving on the cable, the actual friction coefficient of different road sections is continuously measured and recorded by the robot's body sensors (wheel torque, slippage) to obtain friction data. The friction data is then fed back to the multi-dimensional risk map for updating so as to adjust the robot's movement path planning.

[0067] When planning a movement path, the robot can prioritize paths with high adhesion, even if they are not the geometrically shortest path. For routes that are traversed repeatedly (such as inspection routes), based on multiple friction data, it can determine which sections are permanent low-adhesion areas (such as below bird habitats) and which are temporary (such as those recently washed away by rain). This allows the robot to further mark permanent risk areas in a multi-dimensional risk map, enabling it to switch to the safest mode in advance each time.

[0068] In one embodiment, such as Figure 6 As shown, the multi-mode navigation control system of the high-altitude cable de-icing robot includes:

[0069] The multi-dimensional risk map construction module 1 is used to collect data using the robot's multi-sensor fusion system (such as lidar and stereo vision cameras to accurately scan the geometry of the cable, calculate the cable's slope angle and sag in real time, and detect the presence of low-frequency, large-amplitude cable galloping phenomena; at the same time, the vision system is specially trained to identify abnormal reflections and textures on the cable surface, thereby marking areas contaminated by damp bird droppings, thick dust, or salt stains; induction coils and torque sensors continuously monitor the contact state and adhesion between the robot and the cable) and generate a dynamic multi-dimensional risk map based on the collected data. The multi-dimensional risk map marks the robot's movement path, steep slope areas, cable galloping areas, and areas affected by contamination (bird droppings, mud, etc.).

[0070] The multi-mode adjustment module 2 is used to control the robot's travel mode to braking priority mode when it is predicted that the robot is about to enter a steep slope area; to control the robot's travel mode to active balancing mode when it is predicted that the robot is about to enter a cable galloping area; and to control the robot's travel mode to low-speed creep mode when it is predicted that the robot is about to enter a soiled area.

[0071] The protection and update module 3 is used to continuously monitor the robot's actual motion status through its own sensors (such as encoders, IMUs, inclinometers, and torque sensors) when the robot is moving in areas with steep slopes, cable galloping, or areas affected by dirt. It compares the robot's actual motion status with the expected status of the robot's current mode. When an anomaly is detected (e.g., unexpected acceleration on a steep slope, i.e., insufficient braking; body posture angle exceeding the safety threshold during galloping, posing a risk of tipping over; mismatch between drive wheel speed and body speed, resulting in severe slippage), a fault tolerance mechanism is triggered (the fault tolerance mechanism includes instantly increasing braking force, tightening all grippers to enter a "lock-up" safety mode, and switching to a more conservative crawling gait to attempt to escape). The real-time status data is then fed back to the multi-dimensional risk map for updating.

[0072] The real-time status data feedback to the multi-dimensional risk map in the protection and update module 3 refers to the process by which the robot compares its real-time motion status monitoring data (such as wheel speed, body posture, slippage, etc.) with the expected status at the corresponding location in the multi-dimensional risk map and corrects the map information accordingly. For example, when the robot detects low-frequency, high-amplitude cable galloping in a region marked as a steep slope, the system will increase the risk level of that region, changing it to a steep slope region + cable galloping region. This feedback based on the robot's own sensors forms a closed-loop system, enabling the multi-dimensional risk map to not only reflect the pre-scanned static features of the environment but also integrate dynamic verification data from the robot's actual environment. This allows for online calibration and adaptive optimization of map information, improving the accuracy and safety of subsequent navigation and mode switching.

[0073] In one embodiment, such as Figure 7 As shown, the multi-mode navigation control system of the high-altitude cable de-icing robot includes a multi-mode adjustment module 2 comprising:

[0074] The braking priority mode working unit 21 is used to control the robot's travel mode to braking priority mode when it is predicted that the robot is about to enter a steep slope area. When descending a steep slope, it controls the robot's power system to perform regenerative electromagnetic braking and performs intermittent braking intervention based on real-time tilt angle and acceleration to prevent loss of control. When ascending a steep slope, it controls the left and right drive wheels to perform independent torque precision distribution and anti-slip control to provide sufficient traction and prevent single wheel slippage.

[0075] The active balancing mode working unit 22 is used to control the robot's movement mode to active balancing mode when it is predicted that the robot is about to enter the cable dancing area. It generates a compensating torque opposite to the cable swaying through movable joints or control torque gyroscopes to stabilize the robot body in the inertial space.

[0076] The low-speed creep mode working unit 23 is used to control the robot's movement mode to a low-speed creep mode when it is predicted that the robot is about to enter the area affected by the stain. It adjusts the gait parameters, reduces the rhythm and amplitude of the alternating movement of the gripping mechanism, so as to reduce the risk of dynamic slippage; enhances the gripping force, and appropriately increases the output positive pressure of the gripping mechanism during the clamping phase to improve the reliability of the grip; activates the cleaning function, and links the cleaning device (such as high-pressure air spray or rotating brush) to clean the surface of the cable to be contacted and the mechanism body in real time during the interval of the gripping mechanism's movement, so as to restore the effective friction as much as possible.

[0077] When facing steep slopes, the braking priority mode uses regenerative electromagnetic braking and precise torque distribution to convert the robot's gravitational potential energy into controllable braking or traction force. This effectively prevents the robot from stalling and sliding downhill while ensuring sufficient traction force when going uphill, fundamentally eliminating the risk of slippage and overturning due to insufficient power or braking on steep slopes.

[0078] In areas where cables sway, the active balancing mode allows the robot to stabilize itself within the inertial space through reverse compensation torque. Its direct benefit is that it decouples the robot body from the cable swaying, which not only prevents the robot from derailing or overturning due to violent swaying, but also provides a stable working platform for de-icing operations, ensuring the ability to perform tasks in adverse weather conditions.

[0079] For areas affected by stains, the low-speed creeping mode uses a combination of strategies, including slowing down the pace, increasing clamping, and coordinated cleaning. This strategy adapts to the current low-friction environment with a conservative gait and actively improves the contact surface through immediate cleaning. In this way, it ensures reliable gripping while gradually creating conditions for returning to the normal movement mode.

[0080] In one embodiment, such as Figure 8 As shown, the multi-mode navigation control system of the high-altitude cable de-icing robot also includes:

[0081] The de-icing task selection abort module 4 is used to continuously compare real-time environmental data (such as current slope, cable galloping amplitude, machine stability, and cable surface adhesion) with preset safety thresholds to determine whether the current environment is stable or dangerous. If it is a stable environment, the robot continues to perform the de-icing task; if it is a dangerous environment, the robot stops the de-icing task and navigates to a preset safe area (such as the nearest tower or a cable section that has been confirmed to be stable and has a gentle slope) and enters a low-power standby mode to continuously monitor the environment and wait for the current environment to change to a stable environment.

[0082] In hazardous environments, such as when the cable swing exceeds the safety threshold or the robot body tilts continuously due to strong winds, the robot should be immediately suspended or prohibited from starting the de-icing operation. This is because operating in this state is not only inefficient, but may also cause the robot to become unstable or damage the cable due to the impact reaction force.

[0083] In one embodiment, such as Figure 9 As shown, the multi-mode navigation control system of the high-altitude cable de-icing robot also includes:

[0084] The regular area passage module 5 is used to select the robot's wheeled movement mode for travel on flat, unobstructed cable sections when the robot enters a regular area (the braking priority mode is an improvement of the wheeled movement mode in special environments). When encountering obstacles (insulators, clamps, etc., which are different from areas affected by dirt, where dirt is in patches and obstacle-crossing mode can cause the robotic arm and grippers to become dirty, posing a risk of falling), the robot is controlled to switch to obstacle-crossing mode. If severe cable icing is detected, causing a decrease in adhesion, the robot is controlled to switch to crawling mode (the low-speed crawling mode is an improvement of the crawling mode in special environments) to provide greater gripping force and stability.

[0085] On flat terrain, wheeled movement fully leverages its speed advantage, maximizing travel efficiency and conserving energy. When encountering obstacles, switching to obstacle-crossing mode ensures the robot has the physical ability to bypass or traverse mechanical barriers, avoiding the risk of getting stuck or interrupting the de-icing task. When faced with severe icing, switching to crawling mode prevents unstable gripping that could affect de-icing.

[0086] In one embodiment, such as Figure 10 As shown, the multi-mode navigation control system of the high-altitude cable de-icing robot also includes:

[0087] The friction coefficient update module 6 is used to continuously measure and record the actual friction coefficient of different road sections through the robot's body sensors (wheel torque, slippage) when the robot is moving on the cable, obtain friction data, and feed the friction data back to the multi-dimensional risk map for updating, so as to adjust the robot's movement path planning.

[0088] Continuous updates to the multidimensional risk map enhance the accuracy and safety of robot navigation. By measuring and recording the actual friction coefficients of different road sections in real time, the robot updates the multidimensional risk map with valuable data from the actual environment. This process transforms the map from a static predictive map relying on the initial scan into a dynamic empirical map that incorporates real-time ground truth. The direct benefits are: subsequent path planning can more accurately avoid actual high-slip areas, and mode control parameters (such as clamping force and torque distribution) can be pre-optimized based on historical friction data, thereby reducing the overall risk of slippage and stalling.

[0089] It should be understood that although the steps in the flowcharts of the various embodiments of the present invention are shown sequentially according to the arrows, these steps are not necessarily executed in the order indicated by the arrows. Unless explicitly stated herein, there is no strict order restriction on the execution of these steps, and they can be executed in other orders. Moreover, at least some steps in the various embodiments may include multiple sub-steps or multiple stages. These sub-steps or stages are not necessarily completed at the same time, but can be executed at different times. The execution order of these sub-steps or stages is not necessarily sequential, but can be performed alternately or in turn with other steps or at least a portion of the sub-steps or stages of other steps.

[0090] The technical features of the above embodiments can be combined in any way. For the sake of brevity, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0091] The embodiments described above are merely illustrative of several implementations of the present invention, and while the descriptions are specific and detailed, they should not be construed as limiting the scope of the present invention. It should be noted that those skilled in the art can make various modifications and improvements without departing from the concept of the present invention, and these modifications and improvements all fall within the scope of protection of the present invention. Therefore, the scope of protection of this patent should be determined by the appended claims.

[0092] The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, and improvements made within the spirit and principles of the present invention should be included within the protection scope of the present invention.

[0093] Furthermore, it should be understood that although this specification describes embodiments, not every embodiment contains only one independent technical solution. This narrative style is merely for clarity. Those skilled in the art should consider the specification as a whole, and the technical solutions in each embodiment can also be appropriately combined to form other embodiments that can be understood by those skilled in the art.

Claims

1. A multi-mode navigation control method for a high-altitude cable de-icing robot, characterized in that, The multi-mode navigation control method for the high-altitude cable de-icing robot includes the following steps: Data is collected using a multi-sensor fusion system on the robot, and a dynamic multi-dimensional risk map is generated based on the collected data. The multi-dimensional risk map marks the robot's movement path, steep slope areas, cable galloping areas, and areas affected by stains. When it is predicted that the robot is about to enter a steep slope area, the robot's movement mode is controlled to brake priority mode; when it is predicted that the robot is about to enter a cable galloping area, the robot's movement mode is controlled to active balancing mode; when it is predicted that the robot is about to enter a stained area, the robot's movement mode is controlled to low-speed creep mode. When the robot is moving in areas with steep slopes, areas with dancing cables, or areas affected by dirt, its own sensors continuously monitor the robot's actual movement status and compare it with the expected status of the robot's current mode. When an anomaly is detected, a fault tolerance mechanism is triggered, and the real-time status data is fed back to the multi-dimensional risk map for updating. The steps of controlling the robot's movement mode to braking priority mode when predicting that the robot is about to enter a steep slope area; controlling the robot's movement mode to active balancing mode when predicting that the robot is about to enter a cable galloping area; and controlling the robot's movement mode to low-speed creeping mode when predicting that the robot is about to enter a soiled area specifically include: When it is predicted that the robot is about to enter a steep slope area, the robot's movement mode is controlled to brake priority mode. When descending a steep slope, the robot's power system is controlled to perform regenerative electromagnetic braking, and intermittent braking intervention is performed according to the real-time tilt angle and acceleration to prevent loss of control. When ascending a steep slope, the left and right drive wheels are controlled to perform independent torque precise distribution and anti-slip control to provide sufficient traction and prevent single wheel slippage. When it is predicted that the robot is about to enter the area where the cable is swaying, the robot's movement mode is controlled to be active balancing mode. Through movable joints or control torque gyroscopes, a compensating torque opposite to the cable swaying is generated to stabilize the robot body in the inertial space. When predicting that the robot is about to enter a contaminated area, the robot's movement mode is controlled to be a low-speed creeping mode, and the gait parameters are adjusted to reduce the rhythm and amplitude of the alternating movement of the gripping mechanism in order to reduce the risk of dynamic slippage; the gripping force is increased, and the output positive pressure of the gripping mechanism is appropriately increased during the clamping phase to improve the reliability of the grip; the cleaning function is activated, and the cleaning device is linked to perform immediate cleaning on the surface of the cable to be contacted and the mechanism body during the interval of the gripping mechanism's movement to restore effective friction as much as possible.

2. The multi-mode navigation control method for the high-altitude cable de-icing robot according to claim 1, characterized in that, Also includes: The system continuously compares real-time environmental data with preset safety thresholds to determine whether the environment is stable or dangerous. If it is a stable environment, the robot continues to perform the de-icing task. If it is a dangerous environment, the robot stops the de-icing task and navigates to a preset safe area to enter a low-power standby mode, continuously monitoring the environment and waiting for it to change to a stable environment.

3. The multi-mode navigation control method for the high-altitude cable de-icing robot according to claim 1, characterized in that, Also includes: When the robot enters a regular area, on flat, unobstructed cable sections, select the robot's wheeled movement mode to move; when encountering obstacles, control the robot to switch to obstacle-crossing mode; if severe icing of the cable is detected, causing a decrease in adhesion, control the robot to switch to crawling mode to provide greater grip and stability.

4. The multi-mode navigation control method for a high-altitude cable de-icing robot according to any one of claims 1 to 3, characterized in that, Also includes: As the robot moves along the cable, it continuously measures and records the actual friction coefficient of different sections using its own sensors to obtain friction data. This friction data is then fed back to the multidimensional risk map for updates, allowing for adjustments to the robot's movement path planning.

5. A multi-mode navigation control system for a high-altitude cable de-icing robot, characterized in that, The multi-mode navigation and control system of the high-altitude cable de-icing robot includes: The multi-dimensional risk map construction module is used to collect data using the multi-sensor fusion system on the robot and generate a dynamic multi-dimensional risk map based on the collected data. The multi-dimensional risk map marks the robot's movement path, steep slope areas, cable galloping areas, and areas affected by stains. The multi-mode adjustment module is used to control the robot's movement mode to braking priority mode when it is predicted that the robot is about to enter a steep slope area; to control the robot's movement mode to active balancing mode when it is predicted that the robot is about to enter a cable galloping area; and to control the robot's movement mode to low-speed creep mode when it is predicted that the robot is about to enter a stained area. The protection and update module is used to continuously monitor the robot's actual movement status through the robot's own sensors when the robot is moving in areas with steep slopes, cable galloping, or areas affected by dirt, and compare it with the expected state of the robot's current mode. When an anomaly is detected, the fault tolerance mechanism is triggered; and the real-time status data is fed back to the multi-dimensional risk map for updating. The multi-mode adjustment module includes: The braking priority mode working unit is used to control the robot's travel mode to braking priority mode when it is predicted that the robot is about to enter a steep slope area. When descending a steep slope, it controls the robot's power system to perform regenerative electromagnetic braking and performs intermittent braking intervention based on real-time tilt angle and acceleration to prevent loss of control. When ascending a steep slope, it controls the left and right drive wheels to perform independent torque precise distribution and anti-slip control to provide sufficient traction and prevent single wheel slippage and freewheeling. The active balancing mode working unit is used to control the robot's movement mode to active balancing mode when it is predicted that the robot is about to enter the cable galloping area. Through movable joints or control torque gyroscopes, it generates a compensating torque that is opposite to the cable swaying, stabilizing the robot body in the inertial space. The low-speed creep mode working unit is used to control the robot's movement mode to a low-speed creep mode when it is predicted that the robot is about to enter a contaminated area. It adjusts the gait parameters and reduces the rhythm and amplitude of the alternating movement of the gripping mechanism to reduce the risk of dynamic slippage; it enhances the gripping force by appropriately increasing the output positive pressure of the gripping mechanism during the clamping phase to improve the reliability of the grip; and it activates the cleaning function, linking with the cleaning device to clean the surface of the cable to be contacted and the mechanism body in real time during the interval of the gripping mechanism's movement to restore effective friction as much as possible.

6. The multi-mode navigation control system for the high-altitude cable de-icing robot according to claim 5, characterized in that, Also includes: The de-icing task selection and abort module is used to continuously compare real-time environmental data with preset safety thresholds to determine whether the current environment is stable or dangerous. If it is a stable environment, the robot continues to perform the de-icing task; if it is a dangerous environment, the robot stops the de-icing task and navigates to a preset safe area to enter a low-power standby mode, continuously monitoring the environment and waiting for the current environment to change to a stable environment.

7. The multi-mode navigation control system for the high-altitude cable de-icing robot according to claim 5, characterized in that, Also includes: The regular area passage module is used to select the robot's wheeled movement mode to move when the robot enters a regular area, on flat and unobstructed cable sections; when encountering obstacles, it controls the robot to switch to obstacle-crossing mode; if severe icing of the cable is detected, causing a decrease in adhesion, it controls the robot to switch to crawling mode to provide greater grip and stability.

8. The multi-mode navigation control system for the high-altitude cable de-icing robot according to any one of claims 5 to 7, characterized in that, Also includes: The friction coefficient update module is used to continuously measure and record the actual friction coefficient of different road sections through the robot's body sensors when the robot is moving on the cable, obtain friction data, and feed the friction data back to the multi-dimensional risk map for updating, so as to adjust the robot's movement path planning.

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