Multi-mode-based obstacle avoidance and path planning system for special wind power vehicle

Abstract

The invention discloses a multi-mode-based obstacle avoidance and path planning system for a wind power special vehicle, and the system comprises a wind power transport vehicle which is used for transporting wind power blades; the detection system is used for detecting the condition of a transportation path through laser measurement, ultrasonic detection and an image acquisition multi-mode sensing system, and assisting in path planning and obstacle avoidance of the wind power transportation vehicle; and the general control system dispatches the detection system, detects the transportation path condition and the obstacle condition through the detection system, plans the wind power blade transportation path of the wind power transportation vehicle according to the path condition and the obstacle condition, and guides the wind power transportation vehicle to transport. The system has the advantages that the transportation path condition and obstacles are detected through laser measurement, ultrasonic detection and image acquisition multi-mode perception pre-detection and auxiliary real-time obstacle avoidance, intelligent dispatching of wind power transportation vehicles is carried out, obstacle avoidance is reliable, the construction transportation efficiency of land and sea wind power blades is improved, and power is supplied to new energy system vehicles through solar energy.

Description

Technical Field

[0001] The present invention relates to the fields of offshore and onshore wind power construction, laser ultrasonic measurement image acquisition, and new energy technology, and more specifically, to a multi-modal obstacle avoidance and path planning system for wind power vehicles. Background Art

[0002] Currently, during the transportation of wind turbine blades for both onshore and offshore wind turbine construction, whether on mountain roads for onshore wind turbine construction or offshore wind turbine construction, wind turbine transport vehicles must navigate complex terrain and environments. Existing transport vehicles present numerous challenges when transporting wind turbine blades. For example, effective obstacle avoidance is difficult, and collisions with obstacles are common, resulting in damage to the blades and even safety accidents.

[0003] Most current transport vehicles are only equipped with simple obstacle avoidance systems and have poor adaptability to complex road conditions. Especially when facing narrow roads, mountain roads, and special sections with a large number of obstacles, they are unable to accurately perceive obstacle information in advance and make reasonable avoidance decisions.

[0004] In addition, existing transport vehicles also have shortcomings in route planning. They are unable to adjust the transport route in time according to real-time road conditions and obstacles. After entering the transport route, if the road conditions and obstacles make it impassable, they are unable to turn around and return, causing transportation obstruction, low transportation efficiency, and increased transportation costs and time costs.

[0005] Most existing wind power transport vehicles do not consider comprehensive perception and analysis of environmental information along the transport route, and lack monitoring and response measures for factors such as weather and light. In severe weather or insufficient light, transport safety cannot be effectively guaranteed.

[0006] In summary, there is at least one of the following technical problems: In the current construction and transportation of offshore and onshore wind turbine blades, most transport vehicles are only equipped with simple self-obstacle avoidance systems, which have poor adaptability to complex road conditions. Especially when facing narrow roads, mountain roads, and special sections with a large number of obstacles, they are unable to accurately perceive obstacle information in advance and make reasonable avoidance decisions. They lack multimodal perception systems that include laser measurement, ultrasonic detection, and image acquisition.

[0007] In the current construction and transportation of offshore and onshore wind turbine blades, existing transport vehicles are unable to adjust the transport route in a timely manner according to real-time road conditions and obstacles in terms of route planning. After entering the transport route, if the road conditions and obstacles make it impassable, they are unable to turn around and return, causing transportation obstruction, low transportation efficiency, and increased transportation costs and time costs.

[0008] In the current construction and transportation of offshore and onshore wind turbine blades, most existing wind turbine transport vehicles do not consider comprehensive perception and analysis of environmental information along the transportation route, and lack monitoring and response measures for factors such as weather and light. In the case of severe weather or insufficient light, transportation safety cannot be effectively guaranteed.

[0009] During the current construction and transportation of offshore and onshore wind turbine blades, the detection system relies on the vehicle's own power supply, which can easily lead to battery depletion. New energy vehicles can also lead to power consumption, and solar energy and new energy sources are not fully utilized. Summary of the Invention

[0010] The primary objective of this invention is to provide a multimodal obstacle avoidance and path planning system for specialized wind turbine vehicles. This system addresses the existing problem in the transport of offshore and onshore wind turbine blades, where most transport vehicles are equipped with only simple obstacle avoidance systems. These systems are inadequate for complex road conditions, particularly on narrow roads, mountainous roads, and sections with numerous obstacles. These vehicles are unable to accurately perceive obstacles in advance and make appropriate avoidance decisions. Furthermore, they lack a multimodal perception system that combines laser measurement, ultrasonic detection, and image acquisition. Furthermore, during the transport of offshore and onshore wind turbine blades, existing transport vehicles are unable to adjust their routes in real-time based on road conditions and obstacle counts. Once on a route, if the route becomes impassable due to road conditions or obstacles, they are unable to turn around and return, hindering transportation efficiency and increasing transportation costs and time. Furthermore, during the transport of offshore and onshore wind turbine blades, most existing transport vehicles fail to comprehensively perceive and analyze environmental information along the transport route and lack monitoring and response measures for factors such as weather and light. Consequently, transport safety cannot be effectively guaranteed in inclement weather or low light conditions. During the current construction and transportation of offshore and onshore wind turbine blades, the detection system needs to rely on the vehicle's own power supply, which can easily lead to battery depletion. New energy vehicles can easily lead to power consumption, and this is at least one technical problem in not fully utilizing solar energy, a new energy source.

[0011] To achieve the above objectives, according to one aspect of the present invention, a multi-modal obstacle avoidance and path planning system for a wind power vehicle is provided, comprising: A wind turbine transport vehicle, which is used to transport wind turbine blades; A detection system, which uses a multimodal perception system including laser measurement, ultrasonic detection, and image acquisition to detect transport path conditions, assisting in path planning and obstacle avoidance for wind power transport vehicles; A master control system, which dispatches a detection system and detects the transport path and obstacle conditions through the detection system, and plans the transport path of wind turbine blades by wind turbine transport vehicles and guides the transport of wind turbine blades according to the path and obstacle conditions; The new energy power supply system is provided, wherein the wind power transport vehicle and the detection system are equipped with a solar power generation device, and the solar power generation device is used to provide power for the wind power transport vehicle and the detection system.

[0012] Preferably, the master control system includes a first central processing unit, a first data calculation module, a first data processing module, a first image processing module, a comparison module, a path planning module, a first simulation demonstration module, a first map navigation module, a scheduling module, a first wireless transmission module, a first wireless receiving module, a calibration module, a detection trolley control module, a wind power transport vehicle control module, a first data storage module, a first path guidance detection unit control module, a front detection unit control module, a rear detection unit control module, an intelligent sensor control module and a first display module, and the first data calculation module, the first data processing module, the first image processing module, the comparison module, the path planning module, the first simulation demonstration module, the first map navigation module, the scheduling module, the first wireless transmission module, the first wireless receiving module, the calibration module, the detection trolley control module, the wind power transport vehicle control module, the first data storage module, the first path guidance detection unit control module, the front detection unit control module, the rear detection unit control module, the intelligent sensor control module and the first display module are respectively connected to the first central processing unit.

[0013] Preferably, the multimodal perception system includes a second central processing unit and a multimodal perception system, a first laser measurement unit, a first image acquisition unit, a first ultrasonic detection unit, a second wireless transmission module, a second wireless receiving module, a second data storage module, an angle control module, a trolley path guidance module, a second data calculation module and a second data processing module. The multimodal perception system, the first laser measurement unit, the first image acquisition unit, the first ultrasonic detection unit, the second wireless transmission module, the second wireless receiving module, the second data storage module, the angle control module, the trolley path guidance module, the second data calculation module and the second data processing module are respectively connected to the second central processing unit.

[0014] Preferably, the wind power transport vehicle control system includes a third central processing unit, a wind power transport vehicle control system, a third wireless receiving module, a third wireless transmitting module, a hydraulic system control module, a second laser measurement module, a second image acquisition module, a second ultrasonic detection unit, a second display module, a second map navigation module, a second simulation demonstration module, an alarm module, a second path guidance unit control module and an intelligent sensing module. The wind power transport vehicle control system, the third wireless receiving module, the third wireless transmitting module, the hydraulic system control module, the second laser measurement module, the second image acquisition module, the second ultrasonic detection unit, the second display module, the second map navigation module, the second simulation demonstration module, the alarm module, the second path guidance unit control module and the intelligent sensing module are respectively connected to the third central processing unit.

[0015] Preferably, the detection system includes a path guidance detection unit, a front detection unit and a rear detection unit. According to the transportation path from near to far, the required number of wind power transport vehicles and map navigation selection, the path guidance detection unit is used to pre-detect the traffic conditions, road data and obstacle data of the selected path and transmit them to the main control system. The main control system performs modeling and simulation demonstration based on the data detected by the path guidance detection unit, and plans the transportable path and whether the front detection unit and the rear detection unit need to be matched. For paths with narrow roads and many obstacles, the front detection unit and the rear detection unit are configured, wherein the path guidance detection unit, the front detection unit and the rear detection unit use small detection vehicles or drones.

[0016] Preferably, if the master control system simulates and demonstrates that the wind turbine transport vehicle has difficulty passing through narrow transport paths and obstacles through its own obstacle avoidance system, the master control system is required to dispatch the front detection unit and the rear detection unit to accompany the wind turbine transport vehicle, and when the wind turbine transport vehicle passes through the obstacle, the front detection unit and the rear detection unit respectively perform real-time obstacle avoidance detection on the left and right sides, and transmit the detection data to the master control system and the wind turbine transport vehicle control system. The master control system models and simulates the data to demonstrate the passing method, and transmits it to the wind turbine transport vehicle system. The wind turbine transport vehicle system displays the simulation demonstration transmitted by the master control system through the display, and can also display the real-time images detected by the front detection system and the rear detection system, and use its own obstacle avoidance system to avoid obstacles.

[0017] Preferably, the multimodal perception system integrates laser measurement, image acquisition and ultrasonic detection to obtain the dimensional data of the wind turbine transport vehicle and after loading the wind turbine blades, and uses laser measurement, image acquisition and ultrasonic detection through the front detection system to detect the width data, obstacle data and traffic condition data of the transportation path; through the front detection unit and the rear detection unit, laser measurement, image acquisition and ultrasonic detection are used to obtain real-time data and direct distance data of the wind turbine transport vehicle when passing through obstacles, and feedback is given to the main control system and the wind turbine transport vehicle system in real time.

[0018] Preferably, the wind turbine transport vehicle's own obstacle avoidance system includes a laser measurement system, an image acquisition system, an ultrasonic detection system and a high-flow hydraulic system. The high-flow hydraulic system is connected to the adjustment frame, and the adjustment frame is adjusted by the high-flow hydraulic system to adjust the inclination angle and posture of the wind turbine blades to avoid obstacles.

[0019] Preferably, the master control system also includes a risk assessment module, which is connected to the first central processing unit; the risk assessment module is used to perform risk level assessment on the planned path based on the transportation path status and obstacle status data obtained by the detection system, combined with historical transportation data and a preset risk assessment model; when the assessed risk level exceeds a preset threshold, the risk assessment module generates risk warning information and transmits the information to the first central processing unit, and the first central processing unit controls the first display module to display a warning. When the path is unique, the detection system is simultaneously dispatched to perform a secondary detection of the path to obtain more accurate data, and re-perform path planning and risk assessment.

[0020] Preferably, the detection system also includes an environmental perception unit, which includes a meteorological sensor and a light sensor; the meteorological sensor is used to monitor the weather conditions on the transportation path in real time, including but not limited to wind speed, rainfall, and snowfall data; the light sensor is used to detect the light intensity of the transportation environment; the environmental perception unit transmits the monitored meteorological and light data to the master control system; the master control system intelligently adjusts the detection parameters of the multimodal perception system according to the environmental data, and when the light intensity is low, enhances the fill light function and image clarity processing algorithm of the image acquisition unit; when the wind speed is high, the laser measurement and ultrasonic detection data are corrected for the influence of wind resistance in combination with the meteorological data, and at the same time adjusts the driving speed and path planning strategy of the wind power transport vehicle according to the weather conditions.

[0021] The application of the technical solution of the present invention has the following technical effects: During the construction and transportation of offshore and onshore wind turbine blades, the obstacle avoidance capability of wind turbine transport vehicles has been improved. The vehicles can effectively predict and avoid obstacles, and can perceive obstacle information and road conditions on the transportation routes to offshore and mountain wind turbine blade construction in real time, and provide feedback to the master control system. Through the simulation demonstration of the master control system, precise obstacle avoidance is achieved, ensuring the safe transportation of wind turbine blades.

[0022] In the construction and transportation of offshore and onshore wind turbine blades, intelligent path planning of wind turbine transport vehicles on the transportation routes for offshore wind turbine blade construction and mountain wind turbine blade construction has been realized. According to the pre-detected road conditions and obstacles, the transportation routes are adjusted in time, which improves transportation efficiency and flexibility and reduces transportation costs.

[0023] During the construction and transportation of offshore and onshore wind turbine blades, the adaptability of wind turbine transport vehicles to the transportation environment has been enhanced. Through comprehensive perception and analysis of environmental factors such as weather and light, the detection parameters and transportation strategies are automatically adjusted to ensure safe and stable transportation in various environments.

[0024] It has improved the overall performance and intelligence level of wind turbine transport vehicles, making them more reliable and competitive in the field of wind turbine blade transportation, and promoting the development of the wind power industry. BRIEF DESCRIPTION OF THE DRAWINGS

[0025] The accompanying drawings, which constitute part of this application, are intended to provide a further understanding of the present invention. The exemplary embodiments of the present invention and their descriptions are intended to explain the present invention and do not constitute an undue limitation of the present invention. In the accompanying drawings: Figure 1 A schematic structural diagram of a multi-modal obstacle avoidance and path planning system for a wind power vehicle according to the present invention is shown; Figure 2 Shown Figure 1 The overall control system structure diagram of the wind power vehicle obstacle avoidance and path planning system based on multi-modality; Figure 3 Shown Figure 1 The multimodal perception system structure diagram of the multimodal wind power vehicle obstacle avoidance and path planning system; Figure 4 Shown Figure 1 The structural diagram of the wind power transport vehicle obstacle avoidance system based on the multi-modal wind power vehicle obstacle avoidance and path planning system; Figure 5 Shown Figure 1 The structural view of the wind power transport vehicle based on the multi-modal obstacle avoidance and path planning system for wind power special vehicles; Figure 6 Shown Figure 1 Path scheduling view of the multi-modal obstacle avoidance and path planning system for wind power vehicles; Figure 7 Shown Figure 1 Detection views of the front and rear detection units of the wind power vehicle obstacle avoidance and path planning system based on multi-modality; Figure 8 Shown Figure 1 Detection view of the path guidance detection unit of the multi-modal obstacle avoidance and path planning system for wind power special vehicles; Figure 9 Shown Figure 1 A view of wind turbine transport vehicle size detection in the multimodal obstacle avoidance and path planning system for wind turbine vehicles.

[0026] The above drawings include the following reference numerals: Wind power transport vehicle 1; general control system 2; detection vehicle 3; first central processing unit 4; first data calculation module 5; first data processing module 6; first image processing module 7; comparison module 8; path planning module 9; first simulation demonstration module 10; first map navigation module 11; scheduling module 12; first wireless transmission module 13; first wireless receiving module 14; calibration module 15; detection vehicle control module 16; wind power transport vehicle control module 17; first data storage module 18; first path guidance detection unit control module 19; front detection unit control module 20; rear detection unit control module 21; intelligent sensor control module 22; first display module 23; risk assessment module 24; environment perception unit control module 25; second central processing unit 26; multimodal perception system 27; first laser measurement unit 28; first image acquisition unit 29; first Ultrasonic detection unit 30; second wireless transmission module 31; second wireless receiving module 32; second data storage module 33; angle control module 34; trolley path guidance module 35; second data calculation module 36; second data processing module 37; third central processing unit 38; wind power transport vehicle obstacle avoidance system 39; third wireless receiving module 40; third wireless transmission module 41; hydraulic system control module 42; second laser measurement module 43; second image acquisition module 44; second ultrasonic detection unit 45; second display module 46; second map navigation module 47; second simulation demonstration module 48; alarm module 49; second path guidance unit control module 50; intelligent sensing module 51; path 52; obstacle 53; origin 54; destination 55; path guidance detection unit 56; front detection unit 57; rear detection unit 58; wind turbine blade 59. DETAILED DESCRIPTION

[0027] It should be noted that, in the absence of conflict, the embodiments and features of the embodiments in this application can be combined with each other. The present invention will be described in detail below with reference to the accompanying drawings and in combination with the embodiments.

[0028] As shown in Figures 1 to 9, an embodiment of the present invention provides a multi-modal obstacle avoidance and path planning system for a wind power special vehicle, including: a wind power transport vehicle 1, wherein the wind power transport vehicle 1 is used to transport wind power blades 59; a detection system, wherein the detection system detects the status of the transportation path 52 through a multi-modal perception system 27 of laser measurement, ultrasonic detection, and image acquisition, and assists in path planning and obstacle avoidance of the wind power transport vehicle 1; a master control system 2, wherein the master control system 2 dispatches the detection system, and detects the status of the transportation path 52 and the status of obstacles 53 through the detection system, and plans the path 52 for the wind power transport vehicle 1 to transport the wind power blades 59 and guides the wind power transport vehicle 1 to transport according to the status of the path 52 and the status of the obstacles 53; a new energy power supply system, wherein the wind power transport vehicle 1 and the detection system are equipped with a solar power generation device, and the solar power generation device is used to provide power for the wind power transport vehicle 1 and the detection system for detection.

[0029] In this embodiment, a wind turbine transport vehicle 1 is used to transport wind turbine blades 59. The wind turbine transport vehicle control system includes a third central processing unit 38, a wind turbine transport vehicle control system, a third wireless receiving module 40, a third wireless transmitting module 41, a hydraulic system control module 42, a second laser measurement module 43, a second image acquisition module 44, a second ultrasonic detection unit 45, a second display module 46, a second map navigation module 47, a second simulation demonstration module 48, an alarm module 49, a second path guidance unit control module 50, and an intelligent sensing module 51. Each of these modules is connected to the third central processing unit 38. The wind turbine transport vehicle 1's own obstacle avoidance system includes a laser measurement system, an image acquisition system, an ultrasonic detection system, and a high-flow hydraulic system. The high-flow hydraulic system is connected to an adjustment frame. The adjustment frame is adjusted by the high-flow hydraulic system, thereby adjusting the tilt angle and posture of the wind turbine blades 59 to avoid obstacles.

[0030] In this embodiment, the detection system detects the condition of the transport path 52 through a multimodal perception system 27 of laser measurement, ultrasonic detection, and image acquisition, and assists in path planning and obstacle avoidance of the wind power transport vehicle 1; the detection system includes a second central processor 26 and a multimodal perception system 27, a first laser measurement unit 28, a first image acquisition unit 29, a first ultrasonic detection unit 30, a second wireless transmission module 31, a second wireless receiving module 32, a second data storage module 33, an angle control module 34, a trolley path guidance module 35, a second data calculation module 36 and a second data processing module 37, and the above modules are respectively connected to the second central processor 26. The detection system includes a path guidance detection unit 56, a front detection unit 57 and a rear detection unit 58. According to the transportation path 52 from near to far, the required number of wind power transport vehicles 1 and map navigation selection, the path guidance detection unit 56 pre-detects the traffic conditions, road data and obstacle 53 data of the selected path 52 and transmits them to the main control system 2. The main control system 2 performs modeling and simulation demonstration based on the data detected by the path guidance detection unit 56, and plans the transportable path 52 and whether the front detection unit 57 and the rear detection unit 58 need to be matched. For paths 52 with narrow roads and many obstacles 53, the front detection unit 57 and the rear detection unit 58 are configured, among which the path guidance detection unit 56, the front detection unit 57 and the rear detection unit 58 use small detection vehicles 3 or drones. The detection system also includes an environmental perception unit, which includes a meteorological sensor and a light sensor; the meteorological sensor is used to monitor the weather conditions on the transportation path 52 in real time, including but not limited to wind speed, rainfall, and snowfall data; the light sensor is used to detect the light intensity of the transportation environment; the environmental perception unit transmits the monitored meteorological and light data to the master control system 2; the master control system 2 intelligently adjusts the detection parameters of the multimodal perception system 27 according to the environmental data, and when the light intensity is low, enhances the fill light function and image clarity processing algorithm of the image acquisition unit; when the wind speed is high, the laser measurement and ultrasonic detection data are combined with the meteorological data to correct the wind resistance effect, and at the same time adjusts the driving speed and path planning strategy of the wind power transport vehicle 1 according to the weather conditions.

[0031] In this embodiment, the master control system 2 dispatches the detection system, and detects the status of the transportation path 52 and the status of the obstacles 53 through the detection system, and plans the path 52 for the wind turbine transport vehicle 1 to transport the wind turbine blades 59 and guides the wind turbine transport vehicle 1 for transportation according to the status of the path 52 and the status of the obstacles 53; the master control system 2 includes a first central processing unit 4, a first data calculation module 5, a first data processing module 6, a first image processing module 7, a comparison module 8, a path planning module 9, a first simulation demonstration module 10, a first map navigation module 11, a scheduling module 12, a first wireless transmission module 13, a first wireless receiving module 14, a calibration module 15, a detection vehicle control module 16, a wind turbine transport vehicle control module 17, a first data storage module 18, a first path guidance detection unit control module 19, a front detection unit control module 20, a rear detection unit control module 21, an intelligent sensor control module 22 and a first display module 23, and the above modules are respectively connected to the first central processing unit 4.

[0032] The master control system 2 also includes a risk assessment module 24, which is connected to the first central processor 4; the risk assessment module 24 is used to perform risk level assessment on the planned path 52 based on the transportation path 52 status and obstacle 53 status data obtained by the detection system, combined with historical transportation data and a preset risk assessment model; when the assessed risk level exceeds the preset threshold, the risk assessment module 24 generates risk warning information and transmits the information to the first central processor 4, and the first central processor 4 controls the first display module 23 to display a warning. When the path 52 is unique, the detection system is dispatched to perform a secondary detection of the path 52 at the same time to obtain more accurate data and re-perform path planning and risk assessment. If the master control system 2 simulates and demonstrates that the wind power transport vehicle 1 has difficulty passing through the narrow transport path 52 and the obstacle 53 through its own obstacle avoidance system, the master control system 2 needs to dispatch the front detection unit 57 and the rear detection unit 58 to accompany the wind power transport vehicle 1, and when the wind power transport vehicle 1 passes through the obstacle 53, the front detection unit 57 and the rear detection unit 58 respectively perform real-time obstacle avoidance detection on the left and right sides, and transmit the detection data to the master control system 2 and the wind power transport vehicle control system. The master control system 2 models the data to simulate and demonstrate the passing method, and transmits it to the wind power transport vehicle 1 system. The wind power transport vehicle 1 system displays the simulation demonstration transmitted by the master control system 2 through the display, and can also display the real-time images detected by the front detection system and the rear detection system, and use its own obstacle avoidance system to avoid obstacles. The multimodal sensing system 27 integrates laser measurement, image acquisition, and ultrasonic detection to obtain dimensional data of the wind turbine transport vehicle 1 and after loading the wind turbine blades 59. The front detection system uses laser measurement, image acquisition, and ultrasonic detection to detect the width of the transport path 52, obstacle 53 data, and traffic conditions. The front detection unit 57 and the rear detection unit 58 use laser measurement, image acquisition, and ultrasonic detection to obtain real-time data and the direct distance to the obstacle 53 when the wind turbine transport vehicle 1 passes through the obstacle 53, and provide real-time feedback to the master control system 2 and the wind turbine transport vehicle 1 system. In this embodiment, in the new energy power supply system, the wind turbine transport vehicle 1 and the detection system are equipped with a solar power generation device, which provides power for the wind turbine transport vehicle 1 and the detection system for detection.

[0033] Specifically: the wind turbine transport vehicle 1 transports the wind turbine blades 59, which is equipped with its own detection system and related control system. The detection system is dispatched by the master control system 2 to plan the transportation route 52 and guide the wind turbine transport vehicle 1 for transportation. The detection vehicle 3 or the drone is used as part of the detection system to perform the path guidance detection task. The first central processor 4 processes the data and instructions in the master control system 2 and coordinates the operation of each module. The detection data is calculated and processed by the first data calculation module 5. The detection data is preliminarily processed and analyzed by the first data processing module 6. The image data collected by the detection system is processed by the first image processing module 7. The detection data is compared with the safety standard by the comparison module 8 to judge the danger of the transportation route 52. The transport path 52 is planned according to the detection data and risk assessment results through the path planning module 9, the planned path 52 is simulated and demonstrated through the first simulation demonstration module 10 to verify its feasibility, the map information is provided through the first map navigation module 11 to assist in path planning, the actions of the detection system and the wind power transport vehicle 1 are coordinated through the scheduling module 12, the wireless data transmission between the master control system 2 and other devices is realized through the first wireless transmission module 13, the data sent by other devices is received through the first wireless receiving module 14, the detection system is calibrated through the calibration module 15 to ensure the accuracy of the data and calibrate the position of the obstacle 53, and the operation and detection operation of the detection vehicle 3 are controlled by the detection vehicle control module 16. The operation and obstacle avoidance operation of the wind power transport vehicle 1 are controlled by the wind power transport vehicle control module 17, the data and related information processed by the master control system 2 are stored by the first data storage module 18, the detection task and operation status of the path guidance detection unit 56 are controlled by the first path guidance detection unit control module 19, the detection task and operation status of the front detection unit 57 are controlled by the front detection unit control module 20, the detection task and operation status of the rear detection unit 58 are controlled by the rear detection unit control module 21, the operation and data collection of the intelligent sensor are controlled by the intelligent sensor control module 22, the related information and data of the master control system 2 are displayed by the first display module 23, and the risk assessment module 24 is used to determine the detection task and operation status of the path guidance detection unit 56 according to the detection task and operation status of the front detection unit 57. The system uses the data and historical transportation data to assess the risk level and generate risk warning information. The environment perception unit control module 25 controls the operation and data collection of the environment perception unit. The second central processor 26 processes the data and instructions in the multimodal perception system 27 and coordinates the operation of each module. The multimodal perception system 27 uses laser measurement, image acquisition, ultrasonic detection and other technologies to obtain various data information of the transportation path 52 and obstacles 53. The first laser measurement unit 28 performs laser measurement to obtain data such as distance and size. The first image acquisition unit 29 collects image data of the transportation path 52 and obstacles 53. The first ultrasonic detection unit 30 uses ultrasonic waves to detect the distance and position information of the obstacle 53.The second wireless transmitting module 31 realizes wireless data transmission between the multimodal sensing system 27 and other devices, the second wireless receiving module 32 receives data sent by other devices, the second data storage module 33 stores data and related information processed by the multimodal sensing system 27, the angle control module 34 controls the detection angle of the detection unit to optimize the detection effect, the vehicle path guidance module 35 controls the driving path of the detection vehicle 3, the second data calculation module 36 calculates and processes the data collected by the multimodal sensing system 27, the second data processing module 37 performs preliminary processing and analysis on the data collected by the multimodal sensing system 27, and the third central processing module 38 performs the processing of the data collected by the multimodal sensing system 27. The processor 38 processes the data and instructions in the control system of the wind power transport vehicle 1, coordinates the operation of each module, controls the operation and obstacle avoidance operation of the wind power transport vehicle 1 through the wind power transport vehicle control system, receives data sent by other devices through the third wireless receiving module 40, realizes wireless data transmission between the control system of the wind power transport vehicle 1 and other devices through the third wireless transmitting module 41, controls the operation of the high-flow hydraulic system through the hydraulic system control module 42, adjusts the posture and angle of the wind turbine blades 59, performs laser measurement through the second laser measurement module 43, assists the obstacle avoidance operation of the wind power transport vehicle 1, collects image data around the wind power transport vehicle 1 through the second image acquisition module 44, and uses the second ultrasonic The wave detection unit 45 uses ultrasonic waves to detect the distance and position information of the obstacle 53 to assist the obstacle avoidance operation of the wind power transport vehicle 1. The second display module 46 displays the information and data of the wind power transport vehicle 1 control system. The second map navigation module 47 provides map information to assist the operation of the wind power transport vehicle 1. The second simulation demonstration module 48 simulates the obstacle avoidance and transportation process of the wind power transport vehicle 1. The alarm module 49 sends an alarm signal when a dangerous or abnormal situation occurs. The second path guidance unit control module 50 controls the operation and operation of the path guidance unit of the wind power transport vehicle 1. The intelligent sensor module 51 collects various sensor information during the operation of the wind power transport vehicle 1. Data, path 52 is the planned route for transporting wind turbine blades 59, obstacles 53 are objects on transport path 52 that may hinder wind turbine transport vehicle 1 and wind turbine blades 59, origin 54 is the departure point of wind turbine transport vehicle 1, and destination 55 is the final destination of wind turbine transport vehicle 1. Path guidance detection unit 56 performs preliminary detection of transport path 52 to obtain information on road conditions and obstacles 53. Front detection unit 57 performs real-time detection of obstacles 53 in front of wind turbine transport vehicle 1, and rear detection unit 58 performs real-time detection of obstacles 53 behind wind turbine transport vehicle 1. Wind turbine blades 59 are core components that need to be transported during wind turbine generator system manufacturing.

[0034] Working Principle: The path guidance detection unit 56, front detection unit 57, and rear detection unit 58 in the detection system, each employing a small detection vehicle 3 or drone, conduct preliminary detection of the transport path 52 using multimodal sensing technologies such as laser measurement, ultrasonic detection, and image acquisition. This assists the wind turbine transport vehicle 1 in its obstacle avoidance process. These units acquire data such as road width, traffic conditions, and the size, location, and shape of obstacles 53, and transmit this data to the master control system 2. Upon receiving the data from the detection system, the master control system 2 analyzes and processes the data using the first data calculation module 5, the first data processing module 6, and the first image processing module 7. The comparison module 8 compares the real-time detection data with pre-set safety standards to determine whether the transport path 52 is potentially hazardous. Based on the processed data and risk assessment results, combined with map information provided by the first map navigation module 11, the path planning module 9 plans the optimal transport path 52. The first simulation demonstration module 10 then simulates the planned path 52 to verify its feasibility. At the same time, the master control system 2 coordinates the actions of the detection system and the wind turbine transport vehicle 1 through the dispatching module 12 to ensure the smooth progress of the transportation process. The wind turbine transport vehicle 1 is equipped with a solar power generation device to provide energy support for itself and the detection system. During the transportation process, the laser measurement system, image acquisition system and ultrasonic detection system in its own obstacle avoidance system perceive the surrounding environment information in real time and feed the data back to the control system of the wind turbine transport vehicle 1. Based on these data and the instructions transmitted by the master control system 2, the control system adjusts the high-flow hydraulic system, and then controls the adjustment frame to adjust the inclination angle and posture of the wind turbine blades 59 to achieve the obstacle avoidance function. In addition, the wind turbine transport vehicle 1 is also equipped with a second display module 46, a second map navigation module 47 and a second simulation demonstration module 48, which are used to display the simulation demonstration results, real-time images and its own operating status transmitted by the master control system 2 to assist the driver in operation.

[0035] From the above description, it can be seen that the above embodiments of the present invention achieve the following technical effects: During the construction and transportation of offshore and onshore wind turbine blades 59, the wind turbine transport vehicle 1 has enhanced its obstacle avoidance capabilities, enabling effective pre-sense and obstacle avoidance. The vehicle real-time senses obstacles 53 and road conditions along the transport routes 52 for offshore and mountain wind turbine blade construction, and provides feedback to the master control system 2. Through simulation demonstrations by the master control system 2, precise obstacle avoidance is achieved, ensuring the safe transportation of wind turbine blades 59. During the construction and transportation of offshore and onshore wind turbine blades 59, intelligent path planning is implemented for the wind turbine transport vehicle 1 along the transport routes 52 for offshore and mountain wind turbine blade construction. Based on pre-detected road conditions and obstacles 53, the transport route 52 is adjusted in a timely manner, improving transportation efficiency and flexibility while reducing transportation costs.

[0036] During the construction and transportation of offshore and onshore wind turbine blades 59, the wind turbine transporter 1 has enhanced its adaptability to the transport environment. By comprehensively sensing and analyzing environmental factors such as weather and sunlight, it automatically adjusts detection parameters and transportation strategies to ensure safe and stable transportation in various environments. This has improved the overall performance and intelligence level of the wind turbine transporter 1, making it more reliable and competitive in the field of transporting wind turbine blades 59, and promoting the development of the wind power industry.

[0037] The foregoing description is merely a preferred embodiment of the present invention and is not intended to limit the present invention. Those skilled in the art will readily appreciate that various modifications and variations of the present invention are possible. Any modifications, equivalent substitutions, or improvements made within the spirit and principles of the present invention are intended to be within the scope of protection of the present invention.

Claims

1. A wind power vehicle obstacle avoidance and path planning system based on multi-modality, characterized in that: include: A wind turbine transport vehicle, which is used to transport wind turbine blades; A detection system, which uses a multimodal perception system including laser measurement, ultrasonic detection, and image acquisition to detect transport path conditions, assisting in path planning and obstacle avoidance for wind power transport vehicles; A master control system, which dispatches a detection system and detects the transport path and obstacle conditions through the detection system, and plans the transport path of wind turbine blades by wind turbine transport vehicles and guides the transport of wind turbine blades according to the path and obstacle conditions; The new energy power supply system is provided, wherein the wind power transport vehicle and the detection system are equipped with a solar power generation device, and the solar power generation device is used to provide power for the wind power transport vehicle and the detection system.

2. The multi-modal obstacle avoidance and path planning system for wind power vehicles according to claim 1, characterized in that: The master control system includes a first central processing unit, a first data calculation module, a first data processing module, a first image processing module, a comparison module, a path planning module, a first simulation demonstration module, a first map navigation module, a scheduling module, a first wireless transmission module, a first wireless receiving module, a calibration module, a detection trolley control module, a wind power transport vehicle control module, a first data storage module, a first path guidance detection unit control module, a front detection unit control module, a rear detection unit control module, an intelligent sensor control module and a first display module. The first data calculation module, the first data processing module, the first image processing module, the comparison module, the path planning module, the first simulation demonstration module, the first map navigation module, the scheduling module, the first wireless transmission module, the first wireless receiving module, the calibration module, the detection trolley control module, the wind power transport vehicle control module, the first data storage module, the first path guidance detection unit control module, the front detection unit control module, the rear detection unit control module, the intelligent sensor control module and the first display module are respectively connected to the first central processing unit.

3. The multi-modal obstacle avoidance and path planning system for wind power vehicles according to claim 1, characterized in that: The detection system includes a second central processing unit and a multimodal perception system, a first laser measurement unit, a first image acquisition unit, a first ultrasonic detection unit, a second wireless transmission module, a second wireless receiving module, a second data storage module, an angle control module, a trolley path guidance module, a second data calculation module and a second data processing module. The multimodal perception system, the first laser measurement unit, the first image acquisition unit, the first ultrasonic detection unit, the second wireless transmission module, the second wireless receiving module, the second data storage module, the angle control module, the trolley path guidance module, the second data calculation module and the second data processing module are respectively connected to the second central processing unit.

4. The multi-modal obstacle avoidance and path planning system for wind power vehicles according to claim 1, characterized in that: The wind power transport vehicle control system includes a third central processing unit, a wind power transport vehicle control system, a third wireless receiving module, a third wireless transmitting module, a hydraulic system control module, a second laser measurement module, a second image acquisition module, a second ultrasonic detection unit, a second display module, a second map navigation module, a second simulation demonstration module, an alarm module, a second path guidance unit control module and an intelligent sensing module. The wind power transport vehicle control system, the third wireless receiving module, the third wireless transmitting module, the hydraulic system control module, the second laser measurement module, the second image acquisition module, the second ultrasonic detection unit, the second display module, the second map navigation module, the second simulation demonstration module, the alarm module, the second path guidance unit control module and the intelligent sensing module are respectively connected to the third central processing unit.

5. The multi-modal obstacle avoidance and path planning system for wind power vehicles according to claim 1, characterized in that: The detection system includes a path guidance detection unit, a front detection unit and a rear detection unit. According to the transportation path from near to far, the required number of wind power transport vehicles and map navigation selection, the path guidance detection unit is used to pre-detect the traffic conditions, road data and obstacle data of the selected path and transmit them to the main control system. The main control system performs modeling and simulation demonstration based on the data detected by the path guidance detection unit, and plans the transportable path and whether the front detection unit and the rear detection unit need to be matched. For paths with narrow roads and many obstacles, the front detection unit and the rear detection unit are configured, among which the path guidance detection unit, the front detection unit and the rear detection unit use small detection vehicles or drones.

6. The multi-modal obstacle avoidance and path planning system for wind power vehicles according to claim 1, characterized in that: If the master control system simulates that the wind turbine transport vehicle has difficulty passing through narrow transport paths and obstacles through its own obstacle avoidance system, the master control system needs to dispatch the front detection unit and the rear detection unit to accompany the wind turbine transport vehicle, and when the wind turbine transport vehicle passes through the obstacle, the front detection unit and the rear detection unit will perform real-time obstacle avoidance detection on the left and right sides respectively, and transmit the detection data to the master control system and the wind turbine transport vehicle control system. The master control system models the data to simulate the passing method and transmits it to the wind turbine transport vehicle system. The wind turbine transport vehicle system displays the simulation demonstration transmitted by the master control system through the display, and can also display the real-time images detected by the front detection system and the rear detection system, and use its own obstacle avoidance system to avoid obstacles.

7. The multi-modal obstacle avoidance and path planning system for wind power vehicles according to claim 1, characterized in that: The multimodal perception system integrates laser measurement, image acquisition and ultrasonic detection to obtain the dimensional data of the wind turbine transport vehicle and after loading the wind turbine blades, and uses laser measurement, image acquisition and ultrasonic detection through the front detection system to detect the width data, obstacle data and traffic condition data of the transportation path; through the front detection unit and the rear detection unit, laser measurement, image acquisition and ultrasonic detection are used to obtain real-time data and direct distance data of the wind turbine transport vehicle when passing through obstacles, and the data are fed back to the main control system and the wind turbine transport vehicle system in real time.

8. The multi-modal obstacle avoidance and path planning system for wind power vehicles according to claim 1, characterized in that: The wind turbine transporter's own obstacle avoidance system includes a laser measurement system, an image acquisition system, an ultrasonic detection system and a high-flow hydraulic system. The high-flow hydraulic system is connected to the adjustment frame. The adjustment frame is adjusted by the high-flow hydraulic system to adjust the inclination angle and posture of the wind turbine blades to avoid obstacles.

9. The multi-modal obstacle avoidance and path planning system for wind power vehicles according to claim 1, characterized in that: The master control system further includes a risk assessment module connected to the first central processor; the risk assessment module is configured to assess the risk level of the planned route based on the transport route status and obstacle status data acquired by the detection system, combined with historical transport data and a preset risk assessment model; When the assessed risk level exceeds a preset threshold, the risk assessment module generates risk warning information and transmits the information to the first central processor. The first central processor controls the first display module to display a warning. When the path is unique, the detection system is dispatched to perform a secondary detection of the path to obtain more accurate data and re-plan the path and conduct risk assessment.

10. The multi-modal obstacle avoidance and path planning system for wind power vehicles according to claim 1, characterized in that: The detection system further includes an environmental sensing unit, which includes a meteorological sensor and a light sensor; the meteorological sensor is used to monitor weather conditions along the transportation route in real time, including but not limited to wind speed, rainfall, and snowfall data; the light sensor is used to detect the light intensity of the transportation environment; the environmental sensing unit transmits the monitored meteorological and light data to the master control system; The master control system intelligently adjusts the detection parameters of the multimodal perception system based on environmental data. When the light intensity is low, the image acquisition unit's fill light function and image clarity processing algorithm are enhanced. When the wind speed is high, the laser measurement and ultrasonic detection data are corrected for the impact of wind resistance in combination with meteorological data. At the same time, the driving speed and path planning strategy of the wind power transport vehicle are adjusted according to weather conditions.

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