Calibration method for positioning and attitude determination of heading machine

Abstract

The invention relates to the technical field of engineering construction measurement and control, and discloses a calibration method for positioning and attitude determination of a heading machine, which comprises the following steps: constructing a data acquisition module, a route making module, a real-time dynamic monitoring module, an execution module, a feedback module and an optimization module; the data acquisition module is used for completing comprehensive acquisition of multi-source data of the heading machine, a route, an environment and an obstacle, the route making module is used for fusing the multi-source data to carry out path planning and error compensation, and the real-time dynamic monitoring module is used for realizing heading machine pose tracking and emergency correction through visual marking points and a laser scanner. The execution module is used for converting an optimal tunneling path into a driving motor control instruction, the feedback module is used for collecting deviation data of an actual operation pose and a planned path in real time and returning the deviation data, the optimization module realizes long-term self-adaptive optimization of the system, and finally, precision, safety and high efficiency of the tunneling operation of the tunneling machine in a complex underground environment are realized.

Description

Technical Field

[0001] This invention relates to the field of engineering construction surveying and control technology, specifically a calibration method for positioning and attitude determination of a tunneling machine. Background Technology

[0002] In the field of tunnel and underground engineering, tunnel boring machines (TBMs) are core equipment, and their positioning and attitude determination accuracy directly affects the quality of tunnel formation, construction safety, and project progress. However, traditional TBM positioning technology has long faced the following technical bottlenecks: First, due to the limitations of the equipment's own mechanical characteristics, the cumulative errors caused by factors such as track slippage, joint clearance, and equipment aging are difficult to effectively suppress, causing positioning accuracy to decrease with the duration of operation. Second, complex geological environments (such as sudden changes in rock hardness and high humidity conditions) significantly interfere with the tunneling path, and traditional path planning lacks dynamic environmental adaptability, easily leading to over-excavation and under-excavation problems. Third, when sudden obstacles (such as landslides and temporary equipment) appear, there is a lack of rapid response mechanisms, making it difficult to simultaneously meet the dual requirements of emergency avoidance and subsequent operational accuracy. In addition, existing technologies mostly adopt a single-sensor positioning mode, failing to form a data-driven closed-loop control system, resulting in prominent problems such as lagging environmental perception, coarse error compensation, and slow emergency decision-making. Therefore, there is an urgent need for an intelligent calibration method that integrates multi-source heterogeneous data, has active mechanical error compensation, dynamic environmental adaptation and emergency avoidance capabilities, in order to break through the positioning and attitude determination bottleneck of traditional tunneling machines in complex underground environments and achieve precision, safety and efficiency in tunneling operations. Summary of the Invention

[0003] (a) Technical problems to be solved To address the shortcomings of existing technologies, this invention provides a calibration method for positioning and attitude determination of a tunneling machine, which has the advantages of high-precision positioning and attitude determination, strong environmental adaptability, and rapid emergency response. It solves the problems of low positioning and attitude determination accuracy, poor environmental adaptability, and weak ability to respond to emergencies in traditional tunneling machines.

[0004] (II) Technical Solution To achieve the above objectives, the present invention provides the following technical solution: a calibration method for positioning and attitude determination of a tunneling machine, comprising the following steps: Step 1: Establish an intelligent tunneling machine calibration system, which includes a data acquisition module, a route planning module, a real-time dynamic monitoring module, an execution module, a feedback module, and an optimization module. Step 2: The data acquisition module is responsible for collecting multi-source data, including the tunneling machine's own characteristic data, route map information, environmental data, and obstacle data. Step 3: The route planning module performs path planning and error compensation based on multi-source data, integrates global map constraints and local working condition corrections, and generates an initial tunneling path; Step 4: The real-time dynamic monitoring module uses visual markers and laser scanners installed at key locations on the tunneling machine cutterhead and body to perform pose tracking and emergency corrections, generating the optimal tunneling path. Step 5: Based on the collaborative output of the route planning module and the real-time dynamic monitoring module, the execution module converts the optimal tunneling path into control commands for the drive motor, and synchronously coordinates the advance speed, the cutting arm angle and the action of the support mechanism. Step Six: The feedback module is responsible for monitoring the deviation data between the actual operating posture of the tunneling machine and the planned path online, and transmitting it back to the execution module via a wireless communication link; Step 7: The evaluation and optimization module is responsible for analyzing and evaluating the long-term operating data of the system and iteratively optimizing the comprehensive pose offset. Calculation model, environmental offset compensation coefficient Formula and Emergency Escape Path Correction algorithm.

[0005] Preferably, the data acquisition module includes a tunneling machine feature data acquisition unit, a tunneling machine route map information unit, an environmental data acquisition unit, and an obstacle monitoring unit, and the route planning module includes a tunneling machine mechanical structure deviation analysis unit, a tunneling environment offset compensation unit, and an initial tunneling path planning unit.

[0006] Preferably, the tunneling machine feature data acquisition unit acquires feature data of the tunneling machine's own posture, speed, tilt angle, body vibration frequency, track tension, and robotic arm posture angle through an airborne vision sensor and an IMU.

[0007] Preferably, the tunneling machine route map information unit obtains the tunneling machine's route map information through lidar and a pre-constructed underground tunnel point cloud map, and highlights the tunnel turning point coordinates, slope change ranges, support structure locations, and clearance width boundaries.

[0008] Preferably, the environmental data acquisition unit acquires environmental data at the location the tunneling machine is about to enter through environmental sensors, including air humidity, dust concentration, harmful gas concentration, tunnel wall temperature, rock moisture content, and air velocity.

[0009] Preferably, the obstacle monitoring unit acquires obstacle data at the location the tunneling machine is about to enter through millimeter-wave radar and infrared sensors, including the obstacle's three-dimensional coordinates, obstacle's volume and size, obstacle's material hardness, the real-time distance between the obstacle and the tunneling machine, the obstacle's relative speed, the obstacle's surface flatness, and the obstacle's duration of existence. It also highlights easily movable piles of rubble, piles of support materials, and temporary equipment.

[0010] Preferably, the tunneling machine mechanical structure deviation analysis unit dynamically compensates for structural deviations generated during equipment operation based on a preset correction formula for the tunneling machine's own mechanical structure deviation. The calculation formula is as follows: In the formula, This represents the overall pose offset. This indicates the current travel speed of the tunneling machine. This indicates the real-time tilt angle of the tunneling machine. and These represent the mechanical error coefficients that change with the increase of service life. This represents the constant bias caused by mechanical wear and assembly clearance factors.

[0011] Preferably, the tunneling environment offset compensation unit calculates the environmental offset compensation coefficient based on environmental data. The calculation formula is as follows: In the formula, Indicates the environmental offset compensation coefficient. This represents the baseline value of the compensation coefficient under the basic environment. Indicates the hardness of the rock strata. This indicates the offset of rock layer hardness. Indicates humidity. This indicates the weight of the influence of rock layer hardness on the compensation coefficient. This indicates the weight of the influence of humidity on the compensation coefficient. Indicates the humidity sensitivity coefficient; The initial tunneling path planning unit performs preliminary route planning based on the data acquired by the data acquisition module, combined with the comprehensive pose offset. Environmental offset compensation coefficient Then, an initial tunneling path is generated, and obstacles and interference during the advancement process are eliminated in real time through the dynamic monitoring of the subsequent real-time dynamic monitoring module.

[0012] Preferably, the real-time dynamic monitoring module installs visual markers and laser scanners at key locations on the tunneling machine's cutterhead and body to monitor the tunneling machine's position and posture in real time. When encountering temporary obstacles, it performs a secondary path correction on the initially planned route using an emergency avoidance calculation formula, which is as follows: In the formula, This indicates the amount of adjustment for emergency evacuation routes. Indicates deceleration. Indicates response time. This indicates the displacement caused by deceleration during the braking phase. Indicates the current speed of travel. It represents the inertial sliding distance traveled at the original speed within the response time. This indicates the safety distance offset.

[0013] Preferably, the route planning module determines the route based on the comprehensive pose offset. Optimize and adjust the tunneling path; The route planning module uses an environmental offset compensation coefficient. To adapt the tunneling path to the environment; The real-time dynamic monitoring module adjusts the amount based on the emergency evacuation path. It is responsible for the dynamic adjustment of the tunneling machine's position and attitude, the execution of emergency avoidance operations, and the tracking and emergency correction of position and attitude.

[0014] Compared with the prior art, the present invention provides a calibration method for positioning and attitude determination of a tunneling machine, which has the following beneficial effects: 1. This invention integrates pose offset. Environmental offset compensation coefficient The calculation includes the comprehensive pose offset. This is used to quantify the positional deviations of tunneling machines caused by track slippage, mechanical clearance, and inherent mechanical factors such as equipment aging. It is used to compensate in advance for the impact of equipment defects on positioning and attitude accuracy, providing a basis for mechanical error correction in path planning; and through environmental offset compensation coefficients... The calculations are performed to adapt the path to different rock hardness and humidity conditions, quantitatively correct the impact of environmental factors on tunneling accuracy, and optimize tunneling parameters (such as advance speed and cutting force) based on environmental parameters. Risk prediction and path adjustment are carried out in extreme environments (such as high humidity and high hardness rock strata). Finally, the dual impact of equipment error and environmental interference on tunneling accuracy is reduced, and the matching degree between the initial tunneling path and the actual working conditions is improved.

[0015] 2. This invention corrects the emergency escape path amount. The calculations precisely quantify the path length adjustments required in emergency situations (including braking, coasting, and safety redundancy distance), providing a clear basis for path correction to the real-time dynamic monitoring module, ensuring the safety and rationality of emergency braking and path adjustments; and adjusting the emergency escape path correction amount. It is applied to the process of emergency escape path correction, corrects the superimposed impact of the equipment's own mechanical deviation on braking distance and inertial sliding distance, calibrates the deviation between the emergency escape path and the initial planned path, and accurately resets the equipment's posture after the escape operation. It coordinates sudden obstacle avoidance and long-term precision control, and finally achieves the effect of quickly generating a safe and accurate escape path when encountering temporary obstacles, avoiding collision risks, and ensuring the accuracy of subsequent tunneling operations.

[0016] 3. This invention, through the collaborative operation of the route planning module and the real-time dynamic monitoring module, ensures that the tunneling machine can achieve precise positioning and stable attitude in complex and ever-changing underground environments. Simultaneously, it can react quickly to emergencies, guaranteeing the safety and efficiency of tunneling operations. This is achieved by comprehensively measuring the attitude offset. Optimization adjustment and environmental offset compensation coefficient The environmental adaptability modifications enable the tunneling machine to initially adapt to different underground environmental conditions, while the dynamic adjustment of the real-time dynamic monitoring module and the execution of emergency avoidance operations provide the necessary safety guarantee for the tunneling machine. Attached Figure Description

[0017] Figure 1 This is a flowchart of the method of the present invention. Detailed Implementation

[0018] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0019] Please see Figure 1 A calibration method for positioning and attitude determination of a tunneling machine includes the following steps: Step 1: Establish an intelligent tunneling machine calibration system, which includes a data acquisition module, a route planning module, a real-time dynamic monitoring module, an execution module, a feedback module, and an optimization module. Step 2: The data acquisition module is responsible for collecting multi-source data, including tunneling machine's own characteristic data (such as mechanical dimensions and joint parameters), route map information (preset trajectory coordinates), environmental data (geological conditions and surface topography), and obstacle data, to achieve real-time perception of the tunneling machine's own status, environment, and obstacles. Step 3: The route planning module performs path planning and error compensation based on multi-source data. By integrating global map constraints and local working condition corrections, it generates an optimal tunneling path that is both feasible and robust, which is used to generate a preliminary corrected tunneling path. Step 4: The real-time dynamic monitoring module uses visual markers and laser scanners installed at key locations on the tunneling machine cutterhead and body to perform pose tracking and emergency correction, generating the optimal tunneling path to ensure safety and accuracy during the tunneling process. Step 5: Based on the collaborative output of the route planning module and the real-time dynamic monitoring module, the execution module converts the optimal tunneling path into control commands for the drive motor, and synchronously coordinates the advance speed, cutting arm angle and support mechanism actions to drive the tunneling machine to move along the planned path. Step 6: The feedback module is responsible for collecting the deviation data between the actual operating posture (3D coordinates, pitch / roll angle) of the tunneling machine and the planned path in real time, and transmitting it back to the execution module through the wireless communication link to provide control deviation information to support system adjustment; Step 7: The evaluation and optimization module is responsible for analyzing and evaluating the long-term operating data of the system and iteratively optimizing the comprehensive pose offset. Calculation model, environmental offset compensation coefficient Formula and Emergency Escape Path Correction Algorithms are used to achieve long-term adaptive optimization of systems.

[0020] The advantages are: by constructing a data acquisition module, a route planning module, a real-time dynamic monitoring module, an execution module, a feedback module, and an optimization module, the data acquisition module is used to comprehensively collect multi-source data on the tunnel boring machine itself, the route, the environment, and obstacles, providing basic data support for subsequent path planning and control; the route planning module is used to integrate multi-source data for path planning and error compensation, generating a preliminary corrected tunneling path that is both feasible and robust; the real-time dynamic monitoring module is used to achieve tunnel boring machine posture tracking and emergency correction through visual markers and laser scanners, ensuring the safety and accuracy of the tunneling process; the execution module is used to convert the optimal tunneling path into... The drive motor control commands coordinate the actions of various mechanisms of the tunneling machine, driving the equipment to move along the planned path; the feedback module is used to collect and transmit the deviation data between the actual operating posture and the planned path in real time, providing control deviation information for system adjustment; the optimization module is used to analyze and evaluate long-term operating data, iteratively optimize the posture calculation model and algorithm, and realize long-term adaptive optimization of the system. Through the hierarchical collaboration, real-time data interaction and dynamic correction of the above-mentioned multiple modules, the problems of low positioning and posture accuracy, poor environmental adaptability and weak ability to respond to emergencies of traditional tunneling machines are finally solved, thereby realizing the precision, safety and efficiency of tunneling operations in complex underground environments.

[0021] The data acquisition module includes a tunneling machine feature data acquisition unit, a tunneling machine route map information unit, an environmental data acquisition unit, and an obstacle monitoring unit. The route planning module includes a tunneling machine mechanical structure deviation analysis unit, a tunneling environment offset compensation unit, and an initial tunneling path planning unit.

[0022] The tunneling machine feature data acquisition unit acquires feature data such as the tunneling machine's own posture, speed, tilt angle, body vibration frequency, track tension, and robotic arm attitude angle through airborne vision sensors (such as binocular cameras) and IMU (inertial measurement unit). Through dynamic parameter calibration, the accuracy of data in long-term operation is improved, providing feature data that can accurately reflect the real-time status of the tunneling machine, and providing equipment status basis for subsequent mechanical structure deviation analysis and path planning.

[0023] The tunneling machine route map information unit acquires the route map information of the tunneling machine through lidar and a pre-built underground tunnel point cloud map, and highlights the coordinates of tunnel turning points, slope change ranges, support structure locations and clearance width boundaries. Through dynamic updates of the route map information, it adapts to the dimensional changes after tunnel support, and provides accurate route map data containing detailed key node information that conforms to the actual tunnel working conditions, providing a spatial constraint basis for initial path planning.

[0024] The environmental data acquisition unit acquires environmental data (such as "weather" data, but actually refers to underground environmental parameters) at the location the tunneling machine is about to enter through environmental sensors (temperature, humidity, and gas concentration sensors). This includes air humidity, dust concentration, harmful gas concentration (such as methane and carbon monoxide), tunnel wall temperature, rock moisture content, and air velocity. Through time-series analysis of environmental parameters, it predicts environmental change trends (such as the impact of rising humidity on rock stability) and provides dynamic data that reflects the safety of the underground environment and its impact on tunneling operations. This provides an environmental basis for environmental offset compensation calculations and operational safety early warnings.

[0025] The obstacle monitoring unit acquires obstacle data at the location the tunneling machine is about to enter using millimeter-wave radar and infrared sensors. This data includes the obstacle's three-dimensional coordinates, size, material hardness, real-time distance between the obstacle and the tunneling machine, relative speed, surface smoothness, and duration of presence. It also prioritizes easily movable rock piles, support material accumulations, and temporary equipment (such as welding machines and ventilation ducts). Through multi-sensor complementary detection (radar for distance measurement + infrared for material measurement), the accuracy and comprehensiveness of obstacle identification are improved. Real-time updates and classification of obstacle parameters differentiate between fixed equipment and moving rock obstacles of different risk types. Relative motion trajectory prediction helps identify potential collision risks in advance. The unit provides complete data including detailed obstacle attributes, dynamic status, and risk level, supporting obstacle information for path avoidance correction and emergency evacuation operations.

[0026] The tunneling machine mechanical structure deviation analysis unit uses the following formula to correct for deviations in the tunneling machine's own mechanical structure (such as track slippage and mechanical clearance): In the formula, This represents the overall pose offset, which is the overall pose offset caused by deviations in the tunneling machine's own mechanical structure (such as track slippage or mechanical backlash). This indicates the current travel speed of the tunneling machine. This indicates the real-time tilt angle of the tunneling machine. and These represent the mechanical error coefficients that change with the number of years of use, used to quantify the impact of equipment aging on the deviations in speed and tilt angle measurements. This represents the constant bias caused by mechanical wear and assembly clearance factors.

[0027] The tunneling environment offset compensation unit calculates the environmental offset compensation coefficient based on environmental data (such as rock hardness and humidity). The calculation formula is as follows: In the formula, Indicates the environmental offset compensation coefficient. This represents the baseline value of the compensation coefficient under the basic environmental conditions (standard hardness, humidity). Indicates the hardness of the rock strata. This indicates the offset of rock layer hardness. Indicates humidity. This indicates the weight of the influence of rock layer hardness on the compensation coefficient. This indicates the weight of the influence of humidity on the compensation coefficient. This represents the humidity sensitivity coefficient (which controls the correlation between humidity and the compensation coefficient). The initial tunneling path planning unit performs preliminary route planning based on data acquired by the data acquisition module, combined with comprehensive pose offset. Environmental offset compensation coefficient Then, an initial tunneling path is generated, and obstacles and interference during the advancement process are eliminated in real time through the dynamic monitoring of the subsequent real-time dynamic monitoring module.

[0028] The advantage is that it integrates the pose offset. Environmental offset compensation coefficient The calculation includes the comprehensive pose offset. This is used to quantify the positional deviations of tunneling machines caused by track slippage, mechanical clearance, and inherent mechanical factors such as equipment aging. It is used to compensate in advance for the impact of equipment defects on positioning and attitude accuracy, providing a basis for mechanical error correction in path planning; and through environmental offset compensation coefficients... The calculations are performed to adapt the path to different rock hardness and humidity conditions, quantitatively correct the impact of environmental factors on tunneling accuracy, and optimize tunneling parameters (such as advance speed and cutting force) based on environmental parameters. Risk prediction and path adjustment are carried out in extreme environments (such as high humidity and high hardness rock strata). Finally, the dual impact of equipment error and environmental interference on tunneling accuracy is reduced, and the matching degree between the initial tunneling path and the actual working conditions is improved.

[0029] The real-time dynamic monitoring module installs visual markers and laser scanners at key locations on the tunnel boring machine's cutterhead and body to monitor the machine's position and attitude in real time. When encountering temporary obstacles, it performs a secondary path correction on the initially planned route using an emergency avoidance calculation formula. The calculation formula is as follows: In the formula, This indicates the amount of emergency escape path correction, which is the total path length that needs to be adjusted (including braking distance, coasting distance, and safety redundancy). This represents the deceleration, the magnitude of the acceleration (negative value, unit: m / s²) during emergency braking of the tunneling machine, reflecting its braking performance. Represents response time, the time window from obstacle detection to the start of braking (in seconds), including system latency and decision-making time. This indicates the displacement caused by deceleration during the braking phase (if aa is negative, this term is positive). Indicates the current speed of travel. It represents the inertial sliding distance traveled at the original speed within the response time. It represents the safety distance offset, which is the proactively added safety redundancy. It is the minimum safe distance (unit: meters) reserved to avoid obstacles and prevent secondary damage after a collision.

[0030] The advantage is: adjustment amount through emergency evacuation path. The calculations precisely quantify the path length adjustments required in emergency situations (including braking, coasting, and safety redundancy distance), providing a clear basis for path correction to the real-time dynamic monitoring module, ensuring the safety and rationality of emergency braking and path adjustments; and adjusting the emergency escape path correction amount. It is applied to the process of emergency escape path correction, corrects the superimposed impact of the equipment's own mechanical deviation on braking distance and inertial sliding distance, calibrates the deviation between the emergency escape path and the initial planned path, and accurately resets the equipment's posture after the escape operation. It coordinates sudden obstacle avoidance and long-term precision control, and finally achieves the effect of quickly generating a safe and accurate escape path when encountering temporary obstacles, avoiding collision risks, and ensuring the accuracy of subsequent tunneling operations.

[0031] The route planning module uses the comprehensive pose offset. Optimize and adjust the tunneling path; The route planning module uses environmental offset compensation coefficients. To adapt the tunneling path to the environment; The real-time dynamic monitoring module adjusts the amount based on the emergency evacuation path. It performs dynamic adjustment of the tunneling machine's position and attitude, executes emergency avoidance operations, and is responsible for position tracking and emergency correction to ensure safety and accuracy during the tunneling process. The advantages are: through the collaboration of the route planning module and the real-time dynamic monitoring module, the tunneling machine can achieve precise positioning and stable attitude in complex and ever-changing underground environments. Simultaneously, it can react quickly to emergencies, ensuring the safety and efficiency of tunneling operations. This is achieved through comprehensive positional offset measurement. Optimization adjustment and environmental offset compensation coefficient The environmental adaptability modifications enable the tunneling machine to initially adapt to different underground environmental conditions, while the dynamic adjustment of the real-time dynamic monitoring module and the execution of emergency avoidance operations provide the necessary safety guarantee for the tunneling machine.

[0032] Although embodiments of the invention have been shown and described, it will be understood by those skilled in the art that various changes, modifications, substitutions and alterations can be made to these embodiments without departing from the principles and spirit of the invention, the scope of which is defined by the appended claims and their equivalents.

Claims

1. A calibration method for positioning and orienting a heading machine, characterized in that, Comprising the following steps: Step one, establish intelligent tunneling machine calibration system, the system includes data acquisition module, route planning module, real-time dynamic monitoring module, execution module, feedback module and optimization module; Step two, the data acquisition module is responsible for the multi-source data acquisition of the tunneling machine's own characteristic data, route map information, environmental data and obstacle data; Step three, the route planning module plans the path and compensates for errors based on multi-source data, fuses global map constraints and local working condition correction, and generates an initial tunneling path; Step four, the real-time dynamic monitoring module performs pose tracking and emergency correction through visual marker points and laser scanners installed at key positions of the tunneling machine cutter and machine body, and generates an optimal tunneling path; Step five, the execution module converts the optimal tunneling path into control instructions for the drive motor based on the collaborative output results of the route planning module and the real-time dynamic monitoring module, and synchronously coordinates the advancing speed, cutting arm angle and support mechanism action; Step six, the feedback module is responsible for online monitoring of the deviation data between the actual running pose of the tunneling machine and the planned path, and returns the data to the execution module through a wireless communication link. Step seven, the evaluation and optimization module is responsible for analyzing and evaluating the long-term running data of the system, and iteratively optimizing the comprehensive pose offset Computing model, environmental offset compensation coefficient Formula and emergency avoidance path correction amount Algorithm.

2. The calibration method for positioning and orientation of the heading machine according to claim 1, characterized in that: The data acquisition module includes a tunneling machine characteristic data acquisition unit, a tunneling machine route map information unit, an environmental data acquisition unit and an obstacle monitoring unit.

3. The calibration method for positioning and orientation of the heading machine according to claim 2, characterized in that: The tunneling machine characteristic data acquisition unit acquires the tunneling machine's own pose, speed, inclination, machine body vibration frequency, track tension and mechanical arm attitude angle characteristic data through onboard visual sensors and IMU.

4. The calibration method for positioning and orientation of the heading machine according to claim 2, characterized in that: The tunneling machine route map information unit acquires the route map information of the tunneling machine through laser radar and the pre-constructed underground tunnel point cloud map, and performs key identification of tunnel inflection point coordinates, slope change interval, support structure position and limit width boundary.

5. The calibration method for positioning and orientation of the heading machine according to claim 2, characterized in that: The environmental data acquisition unit acquires environmental data in the position about to be entered by the tunneling machine through environmental sensors, including air humidity, dust concentration, harmful gas concentration, tunnel wall temperature, rock water content and air flow rate.

6. The calibration method for positioning and orientation of the heading machine according to claim 2, characterized in that: The obstacle monitoring unit acquires obstacle data in the position about to be entered by the tunneling machine through millimeter wave radar and infrared sensors, including obstacle three-dimensional coordinates, obstacle volume size, obstacle material hardness, real-time distance between the obstacle and the tunneling machine, obstacle relative motion speed, obstacle surface flatness and obstacle existence duration, and performs key identification of movable gravel piles, support material accumulation bodies and temporary equipment.

7. The calibration method for positioning and orientation of the heading machine according to claim 1, characterized in that: The tunneling machine mechanical structure deviation analysis unit dynamically compensates for structural deviations generated during equipment operation according to a pre-set tunneling machine mechanical structure deviation correction formula, whose calculation formula is: In the formula, represents the comprehensive pose offset amount, represents the current advancing speed of the heading machine, represents the real-time inclination angle of the heading machine, and respectively represent the mechanical error coefficients that change with the increase of the service life, represents the constant bias amount caused by the mechanical wear and the assembly gap factor.

8. The calibration method for positioning and orientation of the heading machine according to claim 1, characterized in that: The tunneling environment offset compensation unit calculates an environment offset compensation coefficient according to the environment data The calculation formula is: In the formula, represents the environmental offset compensation coefficient, represents the compensation coefficient reference value under the basic environment, represents the rock hardness, represents the rock hardness offset, represents the humidity, represents the influence weight of the rock hardness on the compensation coefficient, represents the influence weight of the humidity on the compensation coefficient, represents the humidity sensitivity coefficient; The initial tunneling path planning unit performs preliminary route planning based on the data obtained by the data acquisition module, and combines the comprehensive pose offset With environmental offset compensation coefficient After that, the initial tunneling path is generated, and the dynamic monitoring of the subsequent real-time dynamic monitoring module is used to eliminate the obstacle interference in the advancing process in real time.

9. The calibration method for positioning and orientation of the heading machine according to claim 1, characterized in that: The real-time dynamic monitoring module installs visual markers and laser scanners at key positions of the tunneling machine cutter and machine body, and monitors the tunneling machine pose in real time. When encountering temporary obstacles, it performs secondary path correction on the initial planned route through an emergency avoidance calculation formula, whose calculation formula is: In the formula, represents an emergency escape path correction amount, represents a deceleration, represents a response time, represents a displacement due to deceleration in the braking phase, represents a current travel speed, represents an inertial coasting distance at the original speed within the response time, represents a safety distance offset amount.

10. The calibration method for positioning and orientation of the heading machine according to claim 1, characterized in that: The route planning module performs optimization adjustment on the excavation path according to the comprehensive pose offset ​ The route planning module performs environmental adaptability modification of the excavation path according to the environmental offset compensation coefficient , performs environmental adaptability modification of the excavation path according to the environmental offset compensation coefficient The real-time dynamic monitoring module performs dynamic adjustment of the pose of the heading machine and execution of the emergency escape operation according to the emergency escape path correction amount , performs dynamic adjustment of the pose of the heading machine and execution of the emergency escape operation, and is responsible for pose tracking and emergency correction.

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