CN112880599B - Roadbed flatness detection system based on four-foot robot and working method - Google Patents
Roadbed flatness detection system based on four-foot robot and working method Download PDFInfo
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Abstract
The invention discloses a roadbed planeness detection system based on a four-foot robot and a working method. The road bed flatness detection system based on the four-footed robot takes the four-footed robot as a carrier, obtains a three-dimensional model of a road bed surface through panoramic modeling, and carries out path planning of flatness detection, the four-footed robot can carry on a panoramic camera to obtain high-definition images of sampling points according to specified tracks, accurately obtains elevation data of each sample point in a three-meter linear range on the basis of establishing a three-dimensional real scene model by utilizing the high-definition images, and obtains a flatness detection result by utilizing a maximum gap index calculation system. The flatness detection method improves the flatness detection accuracy and effectiveness, and realizes the intelligentization of the flatness detection.
Description
Technical Field
The invention relates to a road flatness detection technology, in particular to a roadbed flatness detection system based on a four-foot robot and a working method.
Background
The Road Surface flatness (Road Surface Roughness) refers to a deviation value of longitudinal concave-convex quantity of a Road Surface, is one of important technical indexes for evaluating the quality of the Road Surface, and is related to the safety and comfort of driving, the magnitude of impact force borne by the Road Surface and the service life of the Road Surface. Uneven road surfaces can increase the resistance of driving, so that the vehicle generates additional vibration, and the speed and the safety of driving are influenced, and the driving stability and the comfort of passengers are also influenced. Therefore, it is necessary to detect and maintain the evenness of the road surface.
The roadbed flatness refers to a deviation value of longitudinal concave-convex amount of a roadbed surface in a road construction process, is an important means for controlling the flatness of the roadbed, and is also an important measure for ensuring the construction stability and safety. The roadbed flatness is related to the accuracy of road base layer construction and the compaction performance of the road base layer, and has important influence on the overall acceptance quality of roads.
At present, the traditional road flatness detection method is still a three-meter ruler or a vehicle-mounted laser flatness meter. The detection method and the principle of the three-meter ruler are that the three-meter ruler is used for starting detection by randomly selecting a point at a position 0.8-1.0m away from a lane wheel on a road surface, every 200 meters is used for detecting two points, every point is used for continuously detecting 10 rulers, and the maximum gap between the reference surface of the three-meter ruler and the road surface represents the flatness of the road bed and the road surface, so that the three-meter ruler is widely applied to inspection and acceptance of construction quality of road surfaces such as urban roads, all levels of highways, airport runways and the like.
Because the traditional three-meter ruler detection is that sample points are manually selected and detected, errors exist in reading and detection, and the sample points are accidentally selected and have particularity, the whole-course flatness of the road bed and the road surface cannot be accurately reflected, and the flatness detection precision is reduced. Compared with a three-meter-ruler detection method, the detection method based on the quadruped robot liberates manual labor force, positioning, track planning and automatic obstacle avoidance of the quadruped robot can be performed by using RTK positioning and a laser radar, personnel investment is reduced, detection accuracy is improved, meanwhile, flatness detection can be performed on the roadbed environment with severe or dangerous environment, and the injury risk of personnel is reduced.
Disclosure of Invention
The invention aims to solve the technical problems of large workload and low detection precision caused by three-meter detection in the prior art, and provides a roadbed flatness detection system based on a quadruped robot and a working method thereof.
The technical scheme adopted by the invention for solving the technical problems is as follows:
the invention provides a roadbed planeness detection system based on a quadruped robot, wherein hardware of the detection system comprises: the system comprises a quadruped robot, an RTK positioning system, a laser radar, an external panoramic camera and a PC terminal; the software of the detection system comprises: integrating a mobile system, an automatic positioning system, a CAN/wireless protocol, a real scene modeling system and a maximum clearance index computing system; wherein:
the quadruped robot is used for loading an RTK positioning system and a laser radar, loading an external panoramic camera for photographing and serving as an autonomous positioning moving carrier, and realizing flatness information data acquisition on a roadbed surface instead of detection personnel;
the RTK positioning system is used for marking coordinates of sampling points, realizing the system positioning of the sampling points, realizing the four-footed robot to advance according to a set track and achieving the purposes of fixed-point advancing and fixed-point photographing; meanwhile, the RTK positioning system is also used for providing supplement and verification for the coordinate and elevation data of the sampling point in the live-action modeling, realizing the coordinate matching of the sampling point and ensuring the accuracy of modeling and flatness detection;
the laser radar is used for scanning obstacles in a real-time detection travelling track and providing an automatic obstacle avoidance function for the quadruped robot;
the external panoramic camera is used for photographing and collecting image information of a road base layer to obtain a high-precision panoramic image;
the PC end is used for outputting a maximum gap index calculation result and a flatness evaluation result, displaying a live-action modeling and a four-legged robot traveling track in a visual mode, and taking the result as an external display window and a data output window of the detection system;
the integrated mobile system is used for controlling the autonomous movement of the quadruped robot and realizing that the quadruped robot travels to a sampling point according to a set track;
the automatic positioning system is used for realizing the positioning of the four-footed robot in the process of moving and determining the position of the four-footed robot in the moving track so as to monitor the moving track of the four-footed robot in real time;
the real scene modeling system is used for processing the image information of the road subgrade and establishing a real scene model;
the maximum clearance index calculation system is used for acquiring high-precision elevation data of sampling points and sample points on the basis of the real-scene model, processing and completing calculation of maximum clearance indexes within a three-meter range, and detecting the flatness of a test road section; the specific method comprises the following steps:
selecting sample points from the established real-scene model to obtain corresponding elevation data, wherein the selection mode comprises manual selection and automatic sampling interval selection, determining the elevation numbers of all sample points within a certain distance linear range of the sampling points, and determining the maximum elevation value h according to the elevation data of each point within a certain distance range of the sampling pointsmax(x) Minimum value h of elevationmin(x) According to the formula Δ h ═ hmax(x)-hmin(x) And calculating the maximum gap delta h of the sampling point within a certain distance range, and judging the flatness according to the design requirement.
Furthermore, the quadruped robot can autonomously advance according to a specified track according to the specific condition of a road foundation layer, and the actions of squatting and lifting, linear advancing, stepping in situ, lateral moving, arc advancing and terrain following of the quadruped robot are realized through the mutual switching of the motion mode and the static mode; before flatness detection, the quadruped robot utilizes an own IMU positioning system to calibrate the robot, the advancing track of the quadruped robot is ensured to be a straight line, and the quadruped robot can be controlled to advance according to the appointed track by switching to a motion mode; through the integrated mobile system of the quadruped robot, the robot is switched to a static standing mode after reaching a first sampling point, image information collection of fixed-point photographing is achieved, the robot is switched to a motion mode again, the robot is guaranteed to move forward to a next sampling positioning point according to a reasonable reserved track, and image information collection of the detection roadbed section is achieved in a circulating mode in sequence.
Furthermore, the external panoramic camera is arranged on the quadruped robot through a detachable, anti-shaking and anti-seismic bottom plate; the external panoramic camera comprises 7 high-resolution lenses installed on a quadruped robot, wherein 1 lens is installed on the upper plane and the lower plane respectively, the images are taken from the overlooking and looking-up angles, 5 lenses are installed on the periphery of the external panoramic camera to ensure that the images are taken at intervals of 72 degrees in a two-dimensional plane, the panoramic camera loaded on the quadruped robot performs panoramic image taking at the height of about 50cm away from a roadbed, the fixed point position of each sampling point is modeled by seven high-definition pictures, and the elevation information of the sample point is acquired.
Furthermore, the automatic positioning system can sense the coordinate positioning of the robot in real time, compare the coordinate positioning with the RTK coordinate of the sampling point in real time, determine the position of the quadruped robot, adjust the quadruped robot to a static standing mode from a motion mode after reaching the sampling point, and then the panoramic camera can take a picture in multiple angles, or determine a picture taking time interval in advance according to the real-time advancing track and the advancing speed of the quadruped robot, so that the timed automatic picture taking is realized.
Furthermore, the automatic positioning system and the integrated moving system are software systems installed in the quadruped robot, the movement and the positioning of the quadruped robot are combined, the autonomous movement and the real-time positioning are realized, when the quadruped robot moves to the next sampling point, the automatic positioning system can determine the position and the accurate coordinate of the quadruped robot, the coordinate of the sampling point in the preset track is compared with the coordinate of the sampling point, when the coordinate displayed in the positioning system is the same as the coordinate of the sampling point in the preset track, the quadruped robot is shown to reach the specified sampling point, and the fixed-point photographing can be switched to a static mode.
Furthermore, the real-scene modeling system is used for processing the image information of the road subgrade and establishing a real-scene model to obtain the elevation data of the sampling point and the sample point within the three-meter linear range; and importing multi-angle high-definition image information acquired by photographing the panoramic camera into a live-action modeling system, automatically matching the feature points by using the coordinates of the sampling points, and automatically establishing a corresponding live-action model according to the resolution and the sampling rate of the image.
The invention provides a working method for detecting the road bed flatness based on a quadruped robot, which comprises the following steps:
step 1, scanning a road base surface by an unmanned aerial vehicle, establishing a large-range real scene model and automatically determining a sampling point position and a preset track of a quadruped robot;
step 2, determining the accurate coordinates of the sampling points through an RTK positioning system to be used as target positions in the traveling track of the quadruped robot;
step 3, realizing automatic advancing and moving by utilizing an integrated moving system of the quadruped robot;
step 4, realizing automatic obstacle avoidance in the advancing track through an automatic positioning system of the quadruped robot and a laser radar, and adjusting the advancing track in time;
step 5, the quadruped robot reaches the determined sampling point, the mode is switched to a static standing state, the external panoramic camera is connected to realize fixed-point photographing, and high-precision image data of the sampling point are obtained;
step 6, taking the photos shot by the panoramic camera as the input of the live-action modeling system, and establishing a high-precision live-action model;
step 7, selecting sample points within a three-meter straight line range of the sampling points according to the established real-scene model, and acquiring elevation data of the sample points;
step 8, taking the elevation data of the sample points as the input of a maximum clearance index calculation system, automatically calculating the maximum clearance index, and evaluating the flatness of the road bed surface;
step 9, realizing data exchange and storage in the detection system through a CAN/wireless protocol, and realizing data transmission;
and step 10, outputting the real-scene model, the traveling track and the maximum gap index calculation result through a data output window of the PC.
Further, the specific method of step 2 of the present invention includes:
firstly, marking a determined sampling point in a traveling track, inputting the specific coordinate and positioning of the sampling point into an RTK positioning system on a quadruped robot through a CAN/wireless protocol data transmission system, and accurately measuring the coordinate of the sampling point in the RTK positioning system; the coordinates of the sampling points are determined by using an RTK positioning system and are combined with scanning modeling of the unmanned aerial vehicle, the sampling points are determined on an actual roadbed surface, the coordinates and positioning are acquired, and the accuracy of the traveling track of the quadruped robot can be ensured; meanwhile, the coordinate information of the position of the quadruped robot is compared with the coordinate information of the position of the quadruped robot in the automatic positioning system, and the sampling point can be accurately reached.
Further, the specific method of step 6 of the present invention comprises:
firstly, automatically screening road subgrade pictures shot by a panoramic camera, removing pictures with visibility or definition lower than a threshold value, importing the screened pictures into a live-action modeling system, carrying out aerial triangular calculation by automatically or manually setting a sampling rate, cutting block division and a grid form, and automatically submitting a calculation result to reconstruct a model.
Further, the specific method of step 8 of the present invention includes:
firstly, manually or automatically setting a sampling interval delta x, obtaining elevation data h (x) of a sample taking point in a model through the set sampling interval within a three-meter straight line range of a sampling point, and calculating a maximum clearance index by a system according to the h (x)1)、h(x2)、h(x3)……h(xn) The maximum elevation value h is obtained by comparisonmax(x) Minimum value h of elevationmin(x) According to the formula Δ h ═ hmax(x)-hmin(x) And comparing to obtain the maximum gap delta h which is used as an evaluation index of the road subgrade flatness.
The invention has the following beneficial effects: the roadbed flatness detection system based on the quadruped robot and the working method thereof complete high-definition image acquisition and live-action modeling of sampling points through the quadruped robot and the external panoramic camera, set reasonable sampling intervals according to the detection principle of a three-meter ruler, synchronously obtain the elevations of the sample points, and obtain the maximum gap between the sample points through the maximum gap index calculation system.
The intelligent four-footed robot is taken as a carrier to carry an external panoramic camera to acquire high-precision image data, real-scene modeling is performed on the basis of the high-precision image data, and a flatness detection value is obtained by using a maximum gap index calculation system. The working method can reduce the personnel investment, greatly improve the flatness detection precision, and can also carry out the flatness detection in dangerous and severe environments such as tunnels, and the like, thereby providing a novel working method for detecting the roadbed flatness based on the quadruped robot.
Drawings
The invention will be further described with reference to the accompanying drawings and examples, in which:
FIG. 1 is a schematic diagram of a system architecture of an embodiment of the present invention;
FIG. 2 is a schematic diagram of a hardware system architecture of an embodiment of the present invention;
FIG. 3 is a schematic diagram of a software system architecture of an embodiment of the present invention;
fig. 4 is a flow chart of a method of an embodiment of the present invention.
Detailed Description
In order to make the objects, technical solutions and advantages of the embodiments of the present invention clearer, the technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are some, but not all, embodiments of the present invention. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
As shown in fig. 1, a road-based roadbed flatness detection system based on a quadruped robot according to an embodiment of the present invention includes: the system comprises a quadruped robot, an RTK positioning system, a laser radar, an external panoramic camera, a PC end data output window, an integrated mobile module, an automatic positioning system, a CAN/wireless protocol, a real scene modeling system and a maximum gap index calculation system.
The quadruped robot is used for loading an RTK positioning system and a laser radar, loading an external panoramic camera for photographing, and taking the quadruped robot as an autonomous positioning moving carrier to realize flatness information data acquisition on a roadbed surface instead of detection personnel.
Specifically, the quadruped robot can autonomously move according to a designated track according to the specific situation of a road foundation layer, and the actions of squatting and lifting, linear advancing, stepping in place, lateral moving, arc advancing, terrain following and the like of the quadruped robot are realized through mutual switching of modes such as motion and static. Before flatness detection, the quadruped robot utilizes an own IMU positioning system to calibrate the robot, the advancing track of the quadruped robot is guaranteed to be a straight line, and the quadruped robot can be controlled to advance according to the appointed track by switching to a motion mode. Through the integrated mobile system of the quadruped robot, the robot is switched to a static standing mode after reaching a first sampling point, image information collection of fixed-point photographing is achieved, the robot is switched to a motion mode again, the robot is guaranteed to move forward to a next sampling positioning point according to a reasonable reserved track, and image information collection of the detection roadbed section is achieved in a circulating mode in sequence.
It is worth to be noted that the quadruped robot in the roadbed flatness detection system based on the quadruped robot is used for loading an external hardware system and realizing autonomous movement and automatic data acquisition, and the main purpose is to realize flatness detection.
As can be seen from figure 2, the quadruped robot can realize the external panoramic camera of the load through the detachable, anti-shaking and anti-seismic bottom plate, and in addition, the synchronous installation of the RTK positioning system and the laser radar is also realized.
The RTK positioning system is used for being installed on the quadruped robot, marking the coordinates of the sampling points, realizing the system positioning of the sampling points, ensuring that the quadruped robot travels according to a set track, achieving the purposes of fixed-point travel and fixed-point photographing, simultaneously providing supplement and verification for the coordinates and elevation data of the sampling points in the real-scene modeling, realizing the coordinate matching of the sampling points, and ensuring the accuracy of modeling and flatness detection.
The laser radar is used for scanning obstacles in a real-time detection travelling track, provides an automatic obstacle avoidance function for the four-legged robot, and realizes the intellectualization and the flexibility of the flatness detection system.
The laser radar is installed on the quadruped robot, so that the quadruped robot can move according to a sampling point and a preset track, and the quadruped robot can meet construction machinery, construction personnel and the like in the actual moving process and even can meet unforeseen obstacles, so that the laser radar is required to scan in real time and implement obstacle avoidance in the moving process. The laser radar CAN scan and detect the obstacles, complete the real-time transmission of the obstacle information through a CAN/wireless protocol (data communication channel), adjust the traveling track of the quadruped robot in time and realize automatic obstacle avoidance.
The external panoramic camera is used for photographing and collecting image information of a road subgrade layer to obtain a high-precision panoramic image.
External panoramic camera is connected with the quadruped robot through detachable anti-shake antidetonation bottom plate equally, because a certain sampling point to the three-dimensional space needs the image through the three-dimensional space just can carry out complete description, consequently utilize panoramic camera's 7 high resolution camera lenses, 1 camera lens is installed respectively to upper and lower plane, shoot from overlook and the angle of looking up, install 5 camera lenses all around, guarantee to shoot at every 72 in the two-dimensional plane, panoramic camera who loads on the quadruped robot carries out the panorama shooting from the road bed face height of about 50cm, the fixed point position of every sampling point is through seven high definition photos completion live-action modeling, and acquire the elevation information of sample point. Because the image data fuzziness collected in the moving process of the quadruped robot is too strong, a high-precision real scene model cannot be accurately established, a panoramic camera is used for fixed-point and timing photographing, and the stability and the definition during photographing are ensured. The autonomous positioning system installed on the quadruped robot can sense the coordinate positioning of the robot in real time and compare the coordinate positioning with the RTK coordinate of a sampling point in real time to determine the position of the quadruped robot, and after the quadruped robot reaches the sampling point, the moving mode is adjusted to the static standing mode, and the panoramic camera can take pictures at multiple angles, or the shooting time interval is determined in advance according to the real-time advancing track and the advancing speed of the quadruped robot, so that the timed automatic shooting is realized.
And the PC end data output window is used for outputting the maximum gap index calculation result and the flatness evaluation result, and displaying the live-action modeling and the four-legged robot traveling track in a visual mode to serve as an external display window of the detection system. Specifically, the road bed flatness detection system based on the quadruped robot is a visual output window from the unmanned aerial vehicle scanning and building a road real scene model to the quadruped robot traveling track and from the panoramic camera photographing and modeling to the maximum gap index calculation result, is a systematized display window, and provides a referential learning window for non-basic operators.
The integrated mobile system is used for realizing the autonomous movement of the quadruped robot, and the quadruped robot can move to a sampling point according to a set track through autonomous switching of a motion mode and a static mode. The integrated mobile system changes the remote control operation into the autonomous control without manual remote control, and the quadruped robot not only realizes the combination of stillness, marching and switching of motion modes, but also realizes the combination of multiple modes through the integrated mobile system, and is used for flexibly completing the movement of the quadruped robot.
And the automatic positioning system is used for realizing the positioning of the four-footed robot in the process of traveling and determining the position of the four-footed robot in the traveling track so as to monitor the motion track of the four-footed robot in real time.
Specifically, the automatic positioning system and the integrated mobile system are software systems installed in the quadruped robot, the movement and the positioning of the quadruped robot are combined, the autonomous movement and the real-time positioning are realized, when the quadruped robot moves to the next sampling point, the automatic positioning system can determine the position and the accurate coordinate of the quadruped robot, the coordinate of the sampling point in the preset track is compared with the coordinate of the sampling point, when the coordinate displayed in the positioning system is the same as the coordinate of the sampling point in the preset track, the quadruped robot is shown to reach the specified sampling point, and the fixed-point photographing can be carried out by switching to a static mode.
The real-scene modeling system of the detection system is used for processing image information of a road subgrade and establishing a real-scene model to obtain elevation data of a sampling point and a sample point within a three-meter linear range of the sampling point. And importing multi-angle high-definition image information acquired by photographing the panoramic camera into a live-action modeling system, automatically matching the feature points by using the coordinates of the sampling points, and automatically establishing a corresponding live-action model according to the resolution and the sampling rate of the image.
The maximum clearance index calculation system is used for acquiring high-precision elevation data of sampling points and sample points on the basis of the real-scene model, processing and completing calculation of maximum clearance indexes within a three-meter range, and detecting the flatness of a test road section. The method specifically comprises the steps that firstly, sample points can be manually selected from an established real-scene model to obtain corresponding elevation data, sampling intervals can also be automatically set, the elevation data of all the sample points in a three-meter linear range of sampling points are determined, and the accuracy can reach millimeter level. Determining the maximum elevation value h according to the elevation data of each point in the three-meter linear range of the sampling pointmax(x) Minimum value h of elevationmin(x) According to the formula Δ h ═ hmax(x)-hmin(x) And (4) calculating the maximum gap delta h of the sampling point within a range of three meters, and judging the flatness according to the road technical specification.
The working method for detecting the road bed flatness based on the quadruped robot in the embodiment of the invention is characterized in that a road bed flatness detecting system based on the quadruped robot is installed on the quadruped robot, and the maximum gap delta h (x) of a sample point is obtained through real-scene modeling.
The roadbed flatness detection working method based on the four-legged robot is characterized in that firstly, the roadbed flatness detection working method is carried out according to a panoramic viewThe mapping radius r (t) of the camera determines a photographing range s (t), a sampling sample point x (t) of a road base surface is selected, positioning coordinates x (t) and y (t) of the sample point are recorded in an RTK positioning system, the movement mode of the quadruped robot is controlled and switched through an integrated mobile system to enable the quadruped robot to move to a positioning point, and fixed-point photographing is completed. After the sample points are determined, a panoramic camera is used for shooting at multiple angles, the images shot at fixed points are used as input information of a real-scene modeling system, the system carries out real-scene modeling according to high-definition roadbed image data collected by the panoramic camera to obtain a model of the roadbed sample points, the sampling interval delta x is determined to obtain elevation data h (x) of the sample points, and a maximum clearance index calculation system carries out calculation according to h (x)1)、h(x2)、h(x3)……h(xn) The maximum elevation value h is obtained by comparisonmax(x) Minimum value h of elevationmin(x) According to the formula Δ h ═ hmax(x)-hmin(x) And comparing to obtain the maximum gap delta h which is used as an evaluation index of the road subgrade flatness. The method specifically comprises the following steps:
automatically acquiring high-precision elevation data h of the sampling points according to the established real-scene model;
setting a sampling interval delta x according to the detection requirement of the flatness of the road bed surface, wherein the sampling interval delta x is generally set to be 1cm, 2cm, 5cm and the like;
obtaining high-precision elevation data of each sample point in a three-meter straight line range of the sampling point according to the sampling interval delta x, assuming that n sample points are counted, and the elevation data of the ith sample point is h (x)i)；
Taking elevation data h (x) of sample points in a three-meter straight line range of the sampling points as input, and comparing h (x)1)、h(x2)、h(x3)……h(xn) The maximum elevation value h is obtained by comparisonmax(x) And minimum value h of elevationmin(x)；
According to the maximum elevation value h of the road subgrade sample pointsmax(x) Minimum value h of elevationmin(x) According to the formula Δ h ═ hmax(x)-hmin(x) And calculating to obtain the maximum gap delta h index.
According to the flow chart of the embodiment shown in fig. 4, it can be seen that step 401 is:
the specific work flow of the four-foot robot-based roadbed flatness detection system is that firstly an unmanned aerial vehicle scans a road roadbed surface, a large-range real-scene model is built, and sampling point positions and a preset track of the four-foot robot are automatically determined. The method specifically comprises the steps that firstly, the unmanned aerial vehicle finishes regular shooting above the road through planning the navigation track of the unmanned aerial vehicle, the navigation height of the unmanned aerial vehicle is required to be set according to the modeling precision requirement while the overlapping rate and the resolution ratio of the pictures are ensured, and the modeling requirement is met. Generally speaking, because the unmanned aerial vehicle scanning carries out the live-action modeling and just is in order to satisfy the full field model of obtaining visual road way face, so that sampling point that can carry out the roughness detection selects and the orbit planning of marcing corresponding with it, and not in order to accurately obtain the concrete coordinate information of sampling point and road way face, consequently, requirement for unmanned aerial vehicle's scanning precision is not high, even its root objective is for fast scan, acquire the place model fast, so unmanned aerial vehicle's navigation height can be as high as possible under the prerequisite that satisfies the image definition, unmanned aerial vehicle's scanning range will be wider like this, also can fully consider road panorama's actual condition and factor when carrying out the roughness detection, rationalization selection sampling point, and plan the orbit route.
Step 402 is:
after the sampling point and the predicted travelling track are determined, the accurate coordinates of the sampling point can be determined by using an RTK positioning system carried by the quadruped robot to be used as a target position in the travelling track of the quadruped robot. The method specifically comprises the steps of firstly marking a determined sampling point in a traveling track, inputting specific coordinates and positioning of the sampling point into an RTK positioning system on the quadruped robot through data transmission systems such as a CAN/wireless protocol, and the like, and accurately measuring the coordinates of the sampling point in the RTK positioning system. It is worth explaining that the coordinates of the sampling points determined by the RTK positioning system and the scanning modeling of the unmanned aerial vehicle can be used for more accurately determining the sampling points on the actual road bed surface, acquiring the coordinates and positioning, and ensuring the accuracy of the travelling track of the quadruped robot. Meanwhile, the coordinate information of the position of the quadruped robot is compared with the coordinate information of the position of the quadruped robot in the automatic positioning system, and the sampling point can be accurately reached.
Step 403 is:
after the coordinates and the travel track of the sampling point are determined, the quadruped robot can automatically travel and move by utilizing the integrated moving system. The method specifically comprises the steps of comparing coordinates of a sampling point in an RTK system with self-positioning coordinates of the quadruped robot obtained through an automatic positioning system, obtaining a position relation with a next sampling point, automatically moving according to a travelling track generated by the system, and judging a real travelling track. Particularly, the integrated mobile system of the quadruped robot is a key part for automatically controlling the quadruped robot to move, is a premise and a foundation of the flatness detection system, and is also intelligent centralized embodiment, the integrated mobile system realizes the movement of the automatically controlled quadruped robot, namely, the mobile mode can be switched according to the RTK coordinates of the actual positioning and sampling point of the quadruped robot, and the intellectualization and the automation of the data acquisition process of the quadruped robot are accurately ensured.
Step 404 is:
after the advancing track and the sampling point coordinates are determined, the four-footed robot automatically moves through the integrated moving system, and in the advancing process, the situation that obstacles such as constructors or construction machinery and the like exist in a planned track cannot be avoided, so that the advancing track needs to be timely improved according to actual conditions, automatic obstacle avoidance in the advancing track is realized through an automatic positioning system of the four-footed robot and a laser radar, and the advancing track is timely adjusted, which is particularly important. The method is characterized in that when the quadruped robot moves according to a preset track, the laser radar CAN timely scan the surrounding environment and determine whether obstacles such as construction personnel or construction machinery which cannot pass or block passing exist in the moving track, once the obstacles which block passing are scanned, information of the obstacles existing is transmitted to the quadruped robot by using a data transmission system such as a CAN/wireless protocol, specific directions and positions of the obstacles are marked, at the moment, the quadruped robot carries out track planning again through the obtained obstacle information, the next sampling point is reached by another type of moving track which CAN pass, and the functions of automatic obstacle avoidance and real-time track planning are realized.
It should be noted that the automatic obstacle avoidance function of the laser radar is performed throughout the whole steps 2-4, and is a means for scanning and implementing the track change in real time, is a part of the system, and is not independent.
Step 405 is:
the determined sampling points are reached under the automatic moving and automatic obstacle avoiding functions of the quadruped robot, the mode is switched to be static to stand, the fixed-point photographing can be realized only by the external panoramic camera at the moment, and the high-precision image data of the sampling points are acquired. Specifically, the static mode signal adopted by the quadruped robot is sent to the panoramic camera through data transmission systems such as a CAN/wireless protocol, and the signal transmission is realized. And after receiving the corresponding information, the panoramic camera can take automatic photographing. Firstly, adjusting the mode to an anti-shaking mode to avoid external unnecessary interference, secondly, automatically adjusting the photographing angle according to the field environment, and acquiring multi-angle high-precision photos around the sampling point, wherein the acquired image data is the basis for high-precision real-scene modeling and maximum gap index and is the most fundamental requirement for flatness detection.
Step 406 is:
and taking the multi-angle and high-definition photos shot by the panoramic camera as the input of a real-scene modeling system, and establishing a high-precision real-scene model according to the input. The real-scene modeling system is specifically described in that firstly, road subgrade pictures shot by a panoramic camera are automatically screened, the pictures with low visibility or unclear pictures are removed, the screened pictures are led into the real-scene modeling system, aerial triangular calculation is carried out through automatic or manual setting of sampling rate, block division and grid form, and model reconstruction can be carried out after calculation results are automatically submitted.
Step 407 is:
and automatically selecting sample points within a three-meter straight line range of the sampling points in the real scene model according to the established real scene model, and acquiring the required elevation data. The steps of unmanned aerial vehicle scanning modeling, four groups of robot mobile scanning, panoramic camera photographing, live-action modeling and the like described above can achieve the acquisition of information such as coordinates and elevation, but are not limited thereto, and the acquisition of elevation data is only for calculating the maximum clearance index in flatness detection, and is information required for the purpose, but corresponding data and information can be selected according to additional requirements.
Step 408 is:
and according to the elevation data obtained in the step, taking the elevation data of the sample points as the input of a maximum clearance index calculation system, automatically calculating the maximum clearance index and evaluating the flatness of the road bed surface.
Firstly, manually or automatically setting a sampling interval delta x, and obtaining elevation data h (x) of a sample taking point in a model through the set sampling interval within a three-meter straight line range of a sampling point, which is a premise and a basis for calculating a maximum clearance index and is one of important steps for ensuring flatness detection accuracy. The obtained elevation data are arranged, the maximum value and the minimum value of the elevation of the calculated point are obtained through automatic system operation such as simple size sorting, and on the basis, the formula delta h is equal to hmax(x)-hmin(x) The maximum gap is obtained. Although the maximum clearance index is also utilized in the traditional flatness detection of the three-meter ruler, the indexes of continuous measurement for 10 times or 20 times and other limited times can be obtained through calculation, and the maximum clearance in the novel flatness detection system is obtained through calculation according to all point elevation data of a road base section to be detected, so that the range is wider, and the accuracy is higher.
Step 409 is:
in the system, data exchange and storage in the detection system are realized through a CAN/wireless protocol, and data transmission is realized, so that a transmission channel of the flatness detection system is also an important means for exchange and real-time transmission. The data transmission system penetrates through the whole flatness detection system, the data transmission system is used for scanning road data by the unmanned aerial vehicle, performing real-time modeling by using the data, planning to corresponding RTK coordinates from a sampling point and a predicted track, and performing real-time positioning and automatic obstacle avoidance from high-precision image data of the panoramic camera. Of course, not only CAN/wireless protocol but also other communication modes capable of realizing data real-time transmission and data storage such as image and the like in the system CAN be listed as the step.
Step 410 is:
in the whole flatness detection system, the real-scene model, the travelling track and the maximum gap index calculation result are output through the PC-end data output window, so that the PC-end data output window is used as an external display window of the system, and the system is a platform for an operator to visually acquire information.
It will be understood that modifications and variations can be made by persons skilled in the art in light of the above teachings and all such modifications and variations are intended to be included within the scope of the invention as defined in the appended claims.
Claims (10)
1. A road bed flatness detection system based on a quadruped robot is characterized in that hardware of the detection system comprises: the system comprises a quadruped robot, an RTK positioning system, a laser radar, an external panoramic camera and a PC terminal; the software of the detection system comprises: integrating a mobile system, an automatic positioning system, a CAN/wireless protocol, a real scene modeling system and a maximum clearance index computing system; wherein:
the quadruped robot is used for loading an RTK positioning system and a laser radar, loading an external panoramic camera for photographing and serving as an autonomous positioning moving carrier, and realizing flatness information data acquisition on a roadbed surface instead of detection personnel;
the RTK positioning system is used for marking coordinates of sampling points, realizing the system positioning of the sampling points, realizing the four-footed robot to advance according to a set track and achieving the purposes of fixed-point advancing and fixed-point photographing; meanwhile, the RTK positioning system is also used for providing supplement and verification for the coordinate and elevation data of the sampling point in the live-action modeling, realizing the coordinate matching of the sampling point and ensuring the accuracy of modeling and flatness detection;
the laser radar is used for scanning obstacles in a real-time detection travelling track and providing an automatic obstacle avoidance function for the quadruped robot;
the external panoramic camera is used for photographing and collecting image information of a road base layer to obtain a high-precision panoramic image;
the PC end is used for outputting a maximum gap index calculation result and a flatness evaluation result, displaying a live-action modeling and a four-legged robot traveling track in a visual mode, and taking the result as an external display window and a data output window of the detection system;
the integrated mobile system is used for controlling the autonomous movement of the quadruped robot and realizing that the quadruped robot travels to a sampling point according to a set track;
the automatic positioning system is used for realizing the positioning of the four-footed robot in the process of moving and determining the position of the four-footed robot in the moving track so as to monitor the moving track of the four-footed robot in real time;
the real scene modeling system is used for processing the image information of the road subgrade and establishing a real scene model;
the maximum clearance index calculation system is used for acquiring high-precision elevation data of sampling points and sample points on the basis of the real-scene model, processing and completing calculation of maximum clearance indexes within a three-meter range, and detecting the flatness of a test road section; the specific method comprises the following steps:
selecting sample points from the established real-scene model to obtain corresponding elevation data, wherein the selection mode comprises manual selection and automatic sampling interval selection, determining the elevation numbers of all sample points within a certain distance linear range of the sampling points, and determining the maximum elevation value h according to the elevation data of each point within a certain distance range of the sampling pointsmax(x) Minimum value h of elevationmin(x) According to the formula Δ h = hmax(x)-hmin(x) And calculating the maximum gap delta h of the sampling point within a certain distance range, and judging the flatness according to the design requirement.
2. The four-footed robot based roadbed flatness detection system of claim 1, wherein the four-footed robot can autonomously follow a specified track according to the concrete condition of the road roadbed layer, and the actions of squat lifting, straight advancing, stepping in place, lateral moving, arc advancing and terrain following of the four-footed robot are realized through the mutual switching of the motion mode and the static mode; before flatness detection, the quadruped robot utilizes an own IMU positioning system to calibrate the robot, the advancing track of the quadruped robot is ensured to be a straight line, and the quadruped robot can be controlled to advance according to the appointed track by switching to a motion mode; through the integrated mobile system of the quadruped robot, the robot is switched to a static standing mode after reaching a first sampling point, image information collection of fixed-point photographing is achieved, the robot is switched to a motion mode again, the robot is guaranteed to move forward to a next sampling positioning point according to a reasonable reserved track, and image information collection of the detection roadbed section is achieved in a circulating mode in sequence.
3. The roadbed flatness detection system based on the quadruped robot is characterized in that the external panoramic camera is installed on the quadruped robot through a detachable, anti-shake and anti-seismic bottom plate; the external panoramic camera comprises 7 high-resolution lenses installed on the quadruped robot, 1 lens is installed on the upper plane and the lower plane respectively, the images are taken from the overlooking and looking-up angles, 5 lenses are installed on the periphery of the external panoramic camera to ensure that the images are taken at intervals of 72 degrees in a two-dimensional plane, the panoramic camera loaded on the quadruped robot performs panoramic image taking at the height of 50cm away from a roadbed, the fixed point position of each sampling point is modeled by seven high-resolution images, and the elevation information of the sample point is acquired.
4. The roadbed flatness detection system based on the quadruped robot as claimed in claim 2, wherein the automatic positioning system can sense the coordinate positioning of the robot in real time, compare the coordinate positioning with the RTK coordinate of the sampling point in real time to determine the position of the quadruped robot, when the quadruped robot reaches the sampling point, the movement mode is adjusted to the static standing mode, and then the panoramic camera can take pictures in multiple angles, or the shooting time interval is determined in advance according to the real-time traveling track and the advancing speed of the quadruped robot, so as to realize the automatic shooting at regular time.
5. The roadbed flatness detection system based on the quadruped robot as claimed in claim 1, wherein the automatic positioning system and the integrated moving system are software systems installed in the quadruped robot, the movement and the positioning of the quadruped robot are combined to realize autonomous movement and real-time positioning, the automatic positioning system can determine the position and the accurate coordinates of the quadruped robot when the quadruped robot moves to the next sampling point, the coordinates are compared with the coordinates of the sampling point in the preset track, and when the coordinates displayed in the positioning system are the same as the coordinates of the sampling point in the preset track, the quadruped robot can be switched to a static mode to take a fixed-point photograph.
6. The system for detecting the flatness of the roadbed based on the quadruped robot as claimed in claim 1, wherein the real-scene modeling system is used for processing the image information of the roadbed of the road, and establishing a real-scene model to obtain the elevation data of a sampling point and a sample point within a three-meter straight line range; and importing multi-angle high-definition image information acquired by photographing the panoramic camera into a live-action modeling system, automatically matching the feature points by using the coordinates of the sampling points, and automatically establishing a corresponding live-action model according to the resolution and the sampling rate of the image.
7. A working method of four-legged robot-based road-bed flatness detection, using the four-legged robot-based road-bed flatness detection system according to any one of claims 1 to 6, comprising the steps of:
step 1, scanning a road base surface by an unmanned aerial vehicle, establishing a large-range real scene model and automatically determining a sampling point position and a preset track of a quadruped robot;
step 2, determining the accurate coordinates of the sampling points through an RTK positioning system to be used as target positions in the traveling track of the quadruped robot;
step 3, realizing automatic advancing and moving by utilizing an integrated moving system of the quadruped robot;
step 4, realizing automatic obstacle avoidance in the advancing track through an automatic positioning system of the quadruped robot and a laser radar, and adjusting the advancing track in time;
step 5, the quadruped robot reaches the determined sampling point, the mode is switched to a static standing state, the external panoramic camera is connected to realize fixed-point photographing, and high-precision image data of the sampling point are obtained;
step 6, taking the photos shot by the panoramic camera as the input of the live-action modeling system, and establishing a high-precision live-action model;
step 7, selecting sample points within a three-meter straight line range of the sampling points according to the established real-scene model, and acquiring elevation data of the sample points;
step 8, taking the elevation data of the sample points as the input of a maximum clearance index calculation system, automatically calculating the maximum clearance index, and evaluating the flatness of the road bed surface;
step 9, realizing data exchange and storage in the detection system through a CAN/wireless protocol, and realizing data transmission;
and step 10, outputting the real-scene model, the traveling track and the maximum gap index calculation result through a data output window of the PC.
8. The working method for detecting the flatness of the roadbed based on the quadruped robot as claimed in claim 7, wherein the concrete method of the step 2 comprises:
firstly, marking a determined sampling point in a traveling track, inputting the specific coordinate and positioning of the sampling point into an RTK positioning system on a quadruped robot through a CAN/wireless protocol data transmission system, and accurately measuring the coordinate of the sampling point in the RTK positioning system; the coordinates of the sampling points are determined by using an RTK positioning system and are combined with scanning modeling of the unmanned aerial vehicle, the sampling points are determined on an actual roadbed surface, the coordinates and positioning are acquired, and the accuracy of the traveling track of the quadruped robot can be ensured; meanwhile, the coordinate information of the position of the quadruped robot is compared with the coordinate information of the position of the quadruped robot in the automatic positioning system, and the sampling point can be accurately reached.
9. The working method for detecting the flatness of the roadbed based on the quadruped robot as claimed in claim 7, wherein the concrete method of the step 6 comprises:
firstly, automatically screening road subgrade pictures shot by a panoramic camera, removing pictures with visibility or definition lower than a threshold value, importing the screened pictures into a live-action modeling system, automatically or manually setting a sampling rate, dividing blocks, carrying out aerial triangular calculation in a grid mode, and automatically submitting a calculation result to reconstruct a model.
10. The working method for detecting the flatness of the roadbed based on the quadruped robot as claimed in claim 7, wherein the concrete method of the step 8 comprises:
firstly, manually or automatically setting a sampling interval delta x, obtaining elevation data h (x) of a sample taking point in a model through the set sampling interval within a three-meter straight line range of a sampling point, and calculating a maximum clearance index by a system according to the h (x)1)、h(x2)、 h(x3)……h(xn) The maximum elevation value h is obtained by comparisonmax(x) Minimum value h of elevationmin(x) According to the formula Δ h = hmax(x)-hmin(x) And comparing to obtain the maximum gap delta h which is used as an evaluation index of the road subgrade flatness.
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| CN114481770B (en) * | 2022-03-31 | 2022-07-05 | 中大检测(湖南)股份有限公司 | Method and system for detecting flatness of highway bridge |
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