CN113619605B - Automatic driving method and system for underground mining articulated vehicle - Google Patents

Automatic driving method and system for underground mining articulated vehicle Download PDF

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CN113619605B
CN113619605B CN202111024303.3A CN202111024303A CN113619605B CN 113619605 B CN113619605 B CN 113619605B CN 202111024303 A CN202111024303 A CN 202111024303A CN 113619605 B CN113619605 B CN 113619605B
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CN113619605A (en
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顾嘉俊
邱长伍
张彪
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Mengzhi Shanghai Technology Co ltd
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    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B60—VEHICLES IN GENERAL
    • B60W—CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION; CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES; ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TO THE CONTROL OF A PARTICULAR SUB-UNIT
    • B60W60/00—Drive control systems specially adapted for autonomous road vehicles
    • B60W60/001—Planning or execution of driving tasks
    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B62—LAND VEHICLES FOR TRAVELLING OTHERWISE THAN ON RAILS
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Abstract

The invention discloses an automatic driving method and system of an underground mining articulated vehicle, which comprises an automatic driving device and an automatic driving system of a vehicle, and is characterized in that: the automatic driving device comprises a front vehicle body, the rear end of the front vehicle body is fixedly connected with a hinge device, the rear end of the hinge device is fixedly connected with a corner sensor, the rear end of the front vehicle body is provided with a rear vehicle body, the hinge device is connected with the rear vehicle body through a hinge, the top of the front vehicle body is fixedly connected with a top laser radar, the front end of the front vehicle body is fixedly connected with a front laser radar, the rear end of the rear vehicle body is fixedly connected with a rear laser radar, the front end side of the front vehicle body is fixedly connected with a front ultrasonic radar, and two side faces of the front vehicle body are both fixedly connected with side ultrasonic radars.

Description

Automatic driving method and system for underground mining articulated vehicle
Technical Field
The invention relates to the technical field of mining and metallurgy, in particular to an automatic driving method and system of an underground mining articulated vehicle.
Background
The underground mine mining equipment in China, particularly large-scale mining equipment and unmanned mining equipment are still basically in the research stage, the mature large-scale mining equipment and unmanned mining equipment are basically imported and rarely applied in China, the application gap between the domestic underground mining equipment and the advanced mining industry of developed countries in the world is gradually increased along with the gradual increase of the application of the advanced technologies such as automation, intellectualization and networking in China, the integral development of the mining technology in China and the efficient development of mineral resources are seriously influenced, along with the research of green mines and intelligent mine technologies, the current unmanned mining technology becomes the consensus of future technical development in the industry, the safety of underground mine production can be greatly improved through high-degree informatization, automation, intellectualization and efficient and safe mining, and the mining efficiency is gradually improved;
the articulated vehicle adopts front wheel steering system to realize the advantage that turns to with the tradition to use in a flexible way, turns to the radius little, can accomplish under quiescent condition and turn to etc. more be fit for with narrower work scene such as underground mine, articulated vehicle compares with underground rail transport vechicle, has the route flexibility, need not infrastructure construction, climbing ability is strong, load advantage such as big, so articulated vehicle's application is increasing day by day at present.
The articulated vehicle generally adopts a manual driving mode to finish various carrying tasks in an underground mine, at present, a special wireless communication facility is provided, unmanned operation of the vehicle is realized by remote control driving in modes of images, sound return and the like, but the research of realizing mining operation only by means of autonomous detection of the environment and automatic driving of the vehicle is less, because the underground mine has the challenges of closed environment, poor lighting condition, severe environment, narrow space and the like, the method does not have implementation conditions in the actual environment of the underground mine, and therefore, the method and the system for automatically driving the articulated vehicle for underground mine, which have strong practicability and can independently finish the transportation operation only by a vehicle-mounted system, are necessary.
Disclosure of Invention
The invention aims to provide an automatic driving method and system of an underground mining articulated vehicle, which aim to solve the problems in the background technology.
In order to solve the technical problems, the invention provides the following technical scheme: the utility model provides an underground mining articulated vehicle autopilot method and system, includes autopilot device and vehicle autopilot system, autopilot device includes the front truck body, the rear end fixedly connected with hinge means of front truck body, hinge means's rear end fixedly connected with corner sensor, the rear end of front truck body is provided with the back truck body, hinge means and back truck body hinged joint, the top fixedly connected with top laser radar of front truck body, the front end fixedly connected with front laser radar of front truck body, the rear end fixedly connected with back laser radar of back truck body, the front end side fixedly connected with front ultrasonic radar of front truck body, the equal fixedly connected with side ultrasonic radar of both sides face of front truck body, the fast meter of fixedly connected with wheel on the wheel of back truck body, the upper end swing joint of back truck body has the car hopper, the inside of front truck body is provided with the equipment box.
According to the technical scheme, the automatic vehicle driving system comprises an intelligent decision-making module, an environment sensing module, an inertial navigation positioning module and a vehicle control module, wherein the intelligent decision-making module, the environment sensing module, the inertial navigation positioning module and the vehicle control module are respectively and electrically connected;
the intelligent decision module comprises a data recording module, a data calculating module, a logic judging module and a comparison module;
the environment sensing module comprises a laser detection module and an ultrasonic detection module;
the inertial navigation positioning module comprises a wheel speed detection module and a hinge angle acquisition module;
the vehicle control module comprises a steering control module, a speed control module and a start-stop module;
laser detection module and top laser radar (6), preceding laser radar (7), back laser radar (8) and side laser radar (10) electricity are connected, ultrasonic detection module is connected with preceding ultrasonic radar (9) electricity, and wheel speed detection module is connected with fast meter (12) electricity of wheel, hinge angle collection module is connected with corner sensor (11) electricity, turn to control module, speed control module and open and stop the inside that the module all set up at equipment box (5).
According to the technical scheme, the data recording module is used for recording various data detected in real time and simultaneously comprises system preset fixed data, the data calculating module is used for calculating data in the data recording module, the logic judging module is used for analyzing a calculation result and determining a driving strategy required to be taken, the comparison module is used for comparing acquired information with preset information, the laser detecting module is used for acquiring relevant information of a working environment and a roadway, the wheel speed detecting module is used for detecting the speed of a vehicle, the hinge angle acquiring module is used for acquiring angle information of a front vehicle body (1) and a rear vehicle body (2), the steering control module is used for controlling steering of the vehicle, the speed control module is used for controlling the speed of the vehicle, and the start-stop module is used for controlling starting and closing of the vehicle.
According to the above technical solution, the operation of the vehicle automatic driving system comprises the steps of:
s1, a vehicle receives a transportation operation instruction, exits a standby waiting state and enters an automatic driving state;
s2, acquiring three-dimensional data points of the surrounding environment of the vehicle through a laser detection module, and comparing the measured data with a preset high-precision working environment map through a comparison module so as to acquire the current position of the vehicle;
s3, calculating a feasible driving path by using a data calculation module according to the current position of the vehicle and the operation position specified by the transportation operation instruction, determining the shortest path through a logic judgment module, and controlling the vehicle to start automatic driving through a vehicle control module;
s4, in the automatic driving process, acquiring roadway wall data points by using a laser detection module, dividing the acquired data points into a plurality of intervals along the driving direction of the vehicle, judging whether the data points in each interval are positioned on the left side or the right side of the driving direction, and taking the points closest to the driving direction as the left boundary and the right boundary of the area, so as to obtain a group of roadway boundary values of the vehicle along the driving direction of the vehicle and further obtain the boundary value of the whole driving path;
s5, collecting three-dimensional data points in front of a driving path by using an environment sensing module, then forming a plurality of data point sets by using a distance-based K-means adaptive clustering method, calculating the maximum and minimum values of data point coordinates of each set, and taking the maximum and minimum values as the vertexes of the lower left corner and the upper right corner of the cube as the detection results of the obstacles;
s6, collecting three-dimensional data points around the vehicle by using an environment sensing module, and comparing the three-dimensional data points with a high-precision map near the position by using a comparison module in combination with a positioning result at the previous moment to obtain the vehicle positioning at the current moment;
obtaining the relative position and direction variation of the vehicle from the previous moment through an inertial navigation positioning module, and calculating the vehicle positioning at the current moment by combining the positioning result at the previous moment;
obtaining the vehicle positioning at the current moment by comparing the positioning difference of the two vehicles;
s7, correcting the advancing route of the vehicle by using an intelligent decision module according to the roadway boundary value obtained in the S4, meanwhile, judging whether the obstacle blocks the driving path of the vehicle or not by using a logic judgment module according to the obstacle information obtained in the S5, and avoiding collision accidents by means of deceleration and parking measures;
s8, acquiring the positioning of the vehicle in real time according to the inertial navigation positioning module, judging whether the vehicle reaches a specified operation position in real time by using a logic judgment module, and sending a confirmation signal after the vehicle reaches the specified operation position;
in the automatic driving process of the vehicle, the vehicle control module is used for combining the real-time positioning of the vehicle obtained by the inertial navigation positioning module according to the running track of the intelligent decision module, calculating the error between the vehicle and the planned track by using the data calculation module, determining corresponding steering, throttle and braking control instructions based on the magnitude and positive and negative values of the error, and driving corresponding vehicle execution components to complete automatic driving.
According to the technical scheme, the specific method for acquiring the current position of the vehicle in the step S2 is as follows:
s21, the inertial navigation positioning module acquires three-dimensional data points of the surrounding environment of the vehicle according to the laser detection module, and compares the measured data with a preset high-precision map of the working environment through the comparison module to obtain the positions P of the top laser radar (6), the front laser radar (7), the rear laser radar (8) and the side laser radar (10) L ；
S22, obtaining coordinate transformation relations between the laser radars and vehicle reference points through preset mounting positions of the top laser radar (6), the front laser radar (7), the rear laser radar (8) and the side laser radar (10) in the automatic vehicle driving system
Figure GDA0003812136450000051
S23, setting the position of a vehicle reference point as P V By transformation
Figure GDA0003812136450000052
The position of the vehicle reference point and thus the position of the vehicle can be obtained.
According to the technical scheme, when the vehicle is automatically driven in the step S3, the method for determining the shortest travel path is as follows:
the method comprises the steps of abstracting a working area into a directed graph in a comparison module, enabling lanes to be edges in the directed graph, enabling joints of the lanes to serve as nodes, simultaneously obtaining corresponding nodes in the directed graph according to an initial position of a vehicle and a target position given by an operation instruction, and obtaining a group of edges with the shortest distance or the shortest running time between the initial position and the target position by applying an open source Dijkstra graph search algorithm or other graph search algorithms, so that a group of lanes through which the vehicle is going to run is obtained and serves as the shortest running path of the vehicle.
According to the technical scheme, the method for determining the lane boundary value in the S4 comprises the following steps:
s41, dividing the collected data points of the roadway wall into a plurality of intervals according to the driving route, and using a mark S i Represents the ith interval;
s42, corresponding section S i At any point P in i Determining its projection point P on the travel path by its shortest distance to the travel path i ', thereby obtaining the interval S i At any point P in i Distance to travel Path | P i P i '|；
S43, respectively calculating the areas S i After the distance of each data point in the area S, respectively obtaining the minimum distance of the left and right sides of the driving path, and taking the minimum distance as the area S i The driving boundary of (1);
and S44, repeating the steps S1-S4 for each section, and obtaining the running boundary of the whole running path.
According to the technical scheme, the method for determining the obstacle in the S5 comprises the following steps:
s51, collecting three-dimensional data points in front of the driving path through a laser detection module, and forming a plurality of data points by applying a distance-based K-means adaptive clustering methodFor each set of data points, calculating the maximum and minimum values of the coordinates of the data points, using the maximum and minimum values as the vertexes of the lower left corner and the upper right corner of the cube as the detection result of the obstacle, and using the signs
Figure GDA0003812136450000061
The barrier list is used for showing the barrier list collected by the laser detection module at the moment T;
s52, collecting three-dimensional data points in front of the driving path through the ultrasonic detection module, generating an obstacle list collected by the ultrasonic detection module at the time T by using the method of S5, and using marks
Figure GDA0003812136450000062
Representing;
s53, combining the obstacle list O at the last moment T-1 And, and
Figure GDA0003812136450000063
and
Figure GDA0003812136450000064
removing the false-detected obstacles to generate an obstacle list O at time T T 。
According to the above technical solution, the method for obtaining the vehicle location in real time in S6 is as follows:
s61, obtaining the vehicle positioning of the vehicle T time by the method of S2, and using the mark
Figure GDA0003812136450000065
Represents;
s62, the vehicle positioning method for determining the current moment through the vehicle positioning at the previous moment comprises the following steps:
s621, setting a mark for positioning at a previous time on the vehicle
Figure GDA0003812136450000066
Is represented by the formula, wherein X T-1 And Y T-1 Representing the last moment vehicle reference point, the X and Y coordinates in a preset vehicle autopilot system coordinate system, theta T-1 Is shown onAn included angle between a vehicle reference point at a moment and the X direction in a preset coordinate system of the automatic driving system of the vehicle,
Figure GDA0003812136450000067
the direction angle difference between the front vehicle body (1) and the rear vehicle body (2) at the previous moment is represented;
s622, setting the turning radius of the vehicle T as R T The value is determined by the following formula:
Figure GDA0003812136450000068
wherein L is F Is the distance L from the hinge device (4) to the axle of the front vehicle body (1) R The distance between the hinge device (4) and the wheel axle of the rear vehicle body (2),
Figure GDA0003812136450000069
the direction angle difference between the front vehicle body (1) and the rear vehicle body (2) at the time T is shown;
s623, setting the rotation angular speed of the vehicle T at the moment to be omega T The value is determined by the following formula:
Figure GDA00038121364500000610
wherein v is T Represents the speed of a reference point of the vehicle at time T, the value of which is measured by a wheel speed meter (12);
s624, setting the direction variation of the vehicle reference point at the time T relative to the previous time as
Figure GDA0003812136450000071
The value is determined by:
Figure GDA0003812136450000072
wherein
Figure GDA0003812136450000073
Representing the time variation of the T moment and the last moment;
s625, setting the vehicle positioning of the T moment determined according to the previous moment as
Figure GDA0003812136450000074
The parameters are determined by the following formula:
Figure GDA0003812136450000075
wherein S T Represents the distance the vehicle reference point has moved from the previous time to time T;
s63, according to
Figure GDA0003812136450000076
And
Figure GDA0003812136450000077
obtaining the location P of the vehicle at the time T by using the weighted average T The value is defined by the following formula:
Figure GDA0003812136450000078
wherein
Figure GDA0003812136450000079
And
Figure GDA00038121364500000710
respectively represent
Figure GDA00038121364500000711
And
Figure GDA00038121364500000712
the weight of (c).
According to the above technical solution, the method for correcting the vehicle traveling route in S7 and the method for determining that the vehicle reaches the designated working position in S8 are as follows:
s101, in the driving process, dividing a driving path into a plurality of path points according to the driving path boundary value acquired in the S4 and the obstacle information, wherein for each path point, if the left boundary is lower than a preset threshold value, the vehicle shifts to the right side, if the right boundary is lower than the preset threshold value, the vehicle shifts to the left side, and if the distance between the left boundary and the right boundary is smaller than a width threshold value for the vehicle to pass, the vehicle is judged to be unable to pass, parking is planned, and the driving path is planned again;
and S102, judging whether the vehicle reaches the designated operation position or not according to the distance between the collected real-time position of the vehicle and the designated operation position, repeating S4-S7 to continue to travel to the designated operation position when the distance is greater than a threshold value, judging that the vehicle reaches the target position when the distance is less than or equal to the threshold value, and sending a confirmation signal.
Compared with the prior art, the invention has the following beneficial effects: the invention can realize unmanned and automatic operation of the underground mining articulated vehicle by arranging the automatic driving device and the automatic driving system of the vehicle, greatly improve the safety of underground mine production and improve the efficiency of transportation operation, thereby reducing the production cost and improving the international competitiveness of the mining industry in China.
Drawings
The accompanying drawings, which are included to provide a further understanding of the invention and are incorporated in and constitute a part of this specification, illustrate embodiments of the invention and together with the description serve to explain the principles of the invention and not to limit the invention. In the drawings:
FIG. 1 is a schematic view of the overall side structure of the present invention;
FIG. 2 is an overall front view of the present invention;
FIG. 3 is a schematic representation of a kinematic model of the vehicle of the present invention;
FIG. 4 is a schematic diagram of the interrelationship of the modules of the present invention;
in the figure: 1. a front vehicle body; 2. a rear vehicle body; 3. a car hopper; 4. a hinge device; 5. an equipment box; 6. a top laser radar; 7. a front laser radar; 8. a rear laser radar; 9. a front ultrasonic radar; 10. a side ultrasonic radar; 11. a rotation angle sensor; 12. a wheel speed meter.
Detailed Description
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 only a part of the embodiments of the present invention, and not all of the embodiments. 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.
Referring to fig. 1-4, the present invention provides the following technical solutions: an automatic driving method and system of underground mining articulated vehicle, including automatic driving device and automatic driving system of the vehicle, the automatic driving device includes the front car body 1, the rear end of the front car body 1 fixedly connects with the hinge means 4, the rear end of the hinge means 4 fixedly connects with the corner sensor 11, the rear end of the front car body 1 has back car body 2, the hinge means 4 is hinged with back car body 2, the top of the front car body 1 fixedly connects with the laser radar of top 6, the front end of the front car body 1 fixedly connects with the front laser radar 7, the rear end of the back car body 2 fixedly connects with the back laser radar 8, the front end side of the front car body 1 fixedly connects with the front ultrasonic radar 9, both sides of the front car body 1 fixedly connect with the side ultrasonic radar 10, the back car body 2 fixedly connects with the wheel speed meter 12 on the wheel, the upper end of the back car body 2 has car hopper 3 movably connected, the inside of the front car body 1 has apparatus boxes 5, through setting up automatic driving device and automatic driving system of the vehicle, can realize the unmanned, the automatic operation of underground mining articulated vehicle, greatly improve the safety of the underground mining production, thus reduce the production cost on the country of the competition;
the automatic vehicle driving system comprises an intelligent decision-making module, an environment sensing module, an inertial navigation positioning module and a vehicle control module, wherein the intelligent decision-making module, the environment sensing module, the inertial navigation positioning module and the vehicle control module are respectively and electrically connected;
the intelligent decision module comprises a data recording module, a data calculating module, a logic judging module and a comparison module;
the environment sensing module comprises a laser detection module and an ultrasonic detection module;
the inertial navigation positioning module comprises a wheel speed detection module and a hinge angle acquisition module;
the vehicle control module comprises a steering control module, a speed control module and a start-stop module;
the laser detection module is electrically connected with the top laser radar 6, the front laser radar 7, the rear laser radar 8 and the side laser radar 10, the ultrasonic detection module is electrically connected with the front ultrasonic radar 9, the wheel speed detection module is electrically connected with the wheel speed meter 12, the hinge angle acquisition module is electrically connected with the corner sensor 11, and the steering control module, the speed control module and the start-stop module are all arranged inside the equipment box 5;
the system comprises a data recording module, a logic judgment module, a comparison module, a laser detection module, a wheel speed detection module, a hinge angle acquisition module, a steering control module, a speed control module and a start-stop module, wherein the data recording module is used for recording various data detected in real time and simultaneously comprises fixed data preset by the system, the data calculation module is used for calculating the data in the data recording module, the logic judgment module is used for analyzing a calculation result and determining a driving strategy required to be taken, the comparison module is used for comparing acquired information with preset information, the laser detection module is used for acquiring relevant information of a working environment and a roadway, the wheel speed detection module is used for detecting the speed of a vehicle, the hinge angle acquisition module is used for acquiring angle information of a front vehicle body 1 and a rear vehicle body 2, the steering control module is used for controlling the steering of the vehicle, the speed control module is used for controlling the speed of the vehicle, and the start-stop module is used for controlling the start and stop of the vehicle;
the operation of the automatic driving system of the vehicle comprises the following steps:
s1, a vehicle receives a transportation operation instruction, exits from a standby waiting state and enters into an automatic driving state;
s2, collecting three-dimensional data points of the surrounding environment of the vehicle through a laser detection module, and comparing the measured data with a preset high-precision working environment map through a comparison module, so as to obtain the current position of the vehicle;
s3, calculating a feasible driving path by using a data calculation module according to the current position of the vehicle and the operation position specified by the transportation operation instruction, determining the shortest path through a logic judgment module, and controlling the vehicle to start automatic driving through a vehicle control module;
s4, in the automatic driving process, acquiring roadway wall data points by using a laser detection module, dividing the acquired data points into a plurality of intervals along the driving direction of the vehicle, judging whether the data points in each interval are positioned on the left side or the right side of the driving direction, and taking the points closest to the driving direction as the left boundary and the right boundary of the area, so as to obtain a group of roadway boundary values of the vehicle along the driving direction of the vehicle and further obtain the boundary value of the whole driving path;
s5, collecting three-dimensional data points in front of a driving path by using an environment sensing module, then forming a plurality of data point sets by applying a distance-based K-means adaptive clustering method, calculating the maximum and minimum values of data point coordinates of each set, and taking the maximum and minimum values as the top points of the lower left corner and the upper right corner of the cube as the detection results of the obstacles;
s6, collecting three-dimensional data points around the vehicle by using an environment sensing module, and comparing the three-dimensional data points with a high-precision map near the position by using a comparison module in combination with a positioning result at the previous moment to obtain the vehicle positioning at the current moment;
obtaining the relative position and direction variation of the vehicle from the previous moment through an inertial navigation positioning module, and calculating the vehicle positioning at the current moment by combining the positioning result at the previous moment;
obtaining the vehicle positioning at the current moment by comparing the positioning difference of the two vehicles;
s7, correcting the advancing route of the vehicle by using an intelligent decision module according to the roadway boundary value obtained in the S4, meanwhile, judging whether the obstacle blocks the driving path of the vehicle by using a logic judgment module according to the obstacle information obtained in the S5, and avoiding collision accidents by means of speed reduction and parking measures;
s8, acquiring the positioning of the vehicle in real time according to the inertial navigation positioning module, judging whether the vehicle reaches a specified operation position in real time by using a logic judgment module, and sending a confirmation signal after the vehicle reaches the specified operation position;
in the automatic driving process of the vehicle, the vehicle control module is used for calculating the error between the vehicle and a planned track by using the data calculation module according to the running track of the intelligent decision module and in combination with the real-time positioning of the vehicle obtained by the inertial navigation positioning module, determining corresponding steering, throttle and braking control instructions based on the magnitude and positive and negative values of the error, and driving corresponding vehicle execution components to complete automatic driving;
the specific method for acquiring the current position of the vehicle in the step S2 is as follows:
s21, the inertial navigation positioning module acquires three-dimensional data points of the surrounding environment of the vehicle according to the laser detection module, and the comparison module compares the measured data with a preset high-precision map of the working environment to obtain the positions P of the top laser radar 6, the front laser radar 7, the rear laser radar 8 and the side laser radar 10 L ；
S22, obtaining coordinate transformation relations between the laser radars and vehicle reference points through the preset installation positions of the top laser radar 6, the front laser radar 7, the rear laser radar 8 and the side laser radar 10 in the automatic vehicle driving system
Figure GDA0003812136450000111
S23, setting the position of a vehicle reference point as P V By transformation of
Figure GDA0003812136450000112
The position of the vehicle reference point can be obtained, and then the position of the vehicle can be obtained;
in S3, when the vehicle is automatically driven, the method for determining the shortest driving path comprises the following steps:
abstracting a working area into a directed graph in a comparison module, wherein the roadways are edges in the directed graph, the joints of the roadways are used as nodes, corresponding nodes are respectively obtained in the directed graph at the same time of the initial position of the vehicle and the target position given by the operation instruction, and an open source Dijkstra graph search algorithm or other graph search algorithms are applied to obtain a group of edges with the shortest distance or the shortest running time between the initial position and the target position, so that a group of roadways through which the vehicle is going to run is obtained and used as the shortest running path of the vehicle;
the method for determining the boundary value of the lane in the S4 comprises the following steps:
s41, dividing the collected data points of the roadway wall into a plurality of intervals according to the driving route, and using a mark S i Represents the ith interval;
s42, corresponding interval S i At any point P in i Determining the projection point P on the driving path according to the shortest distance between the projection point and the driving path i ', thereby obtaining a section S i At any point P in i Distance to travel Path | P i P i '|；
S43, respectively calculating the areas S i After the distance of each data point in the area S, respectively obtaining the minimum distance of the left and right sides of the driving path, and taking the minimum distance as the area S i The driving boundary of (1);
s44, repeating the steps S1-S4 for each interval, and then obtaining the running boundary of the whole running path;
the determination method of the obstacle in S5 is as follows:
s51, collecting three-dimensional data points in front of a driving path through a laser detection module, forming a plurality of data point sets by applying a distance-based K-means adaptive clustering method, calculating the maximum and minimum values of data point coordinates of each set, using the maximum and minimum values as vertexes of the lower left corner and the upper right corner of a cube as detection results of obstacles, and using marks
Figure GDA0003812136450000121
The barrier list is used for showing the barrier list collected by the laser detection module at the moment T;
s52, collecting three-dimensional data points in front of the driving path through the ultrasonic detection module, generating an obstacle list collected by the ultrasonic detection module at the time T by using the method of S5, and using marks
Figure GDA0003812136450000122
Represents;
s53, combining the obstacle list O at the previous moment T-1 And, and
Figure GDA0003812136450000123
and
Figure GDA0003812136450000124
removing the false-detected obstacles to generate an obstacle list O at time T T ；
The method for obtaining the vehicle positioning in real time in the S6 comprises the following steps:
s61, obtaining the vehicle positioning of the vehicle T time by the method of S2, and using the mark
Figure GDA0003812136450000131
Represents;
s62, the vehicle positioning method for determining the current moment through the vehicle positioning at the previous moment comprises the following steps:
s621, setting a mark for positioning at a time on the vehicle
Figure GDA0003812136450000132
Is represented by the formula, wherein X T-1 And Y T-1 Representing the last moment vehicle reference point, the X and Y coordinates in a preset vehicle autopilot system coordinate system, theta T-1 Representing the included angle between the vehicle reference point at the last moment and the X direction in the preset coordinate system of the automatic driving system of the vehicle,
Figure GDA0003812136450000133
indicating the difference of the direction angles of the front vehicle body 1 and the rear vehicle body 2 at the previous moment;
s622, setting the rotating radius of the vehicle T at the moment as R T The value is determined by the following formula:
Figure GDA0003812136450000134
wherein L is F Distance, L, from the hinge device 4 to the axle of the front body 1 R The distance from the hinge device 4 to the axle of the rear vehicle body 2,
Figure GDA0003812136450000135
the direction angle difference between the front vehicle body 1 and the rear vehicle body 2 at the time T is represented;
s623, setting the rotation angular speed of the vehicle T at the moment to be omega T The value is determined by the following formula:
Figure GDA0003812136450000136
wherein v is T Represents the speed of the reference point of the vehicle at time T, the value of which is measured by the wheel speed meter 12;
s624, setting the direction variation of the vehicle reference point at the moment T relative to the previous moment as
Figure GDA0003812136450000137
The value is determined by:
Figure GDA0003812136450000138
wherein
Figure GDA0003812136450000139
Representing the time variation of the T moment and the last moment;
s625, setting the vehicle positioning of the T moment determined according to the previous moment as
Figure GDA00038121364500001310
The parameters are determined by the following formula:
Figure GDA0003812136450000141
wherein S T Represents the distance the vehicle reference point has moved from the previous time to time T;
s63, according to
Figure GDA0003812136450000142
And
Figure GDA0003812136450000143
obtaining the location P of the vehicle at time T by using the weighted average T The value is defined by the following formula:
Figure GDA0003812136450000144
wherein
Figure GDA0003812136450000145
And
Figure GDA0003812136450000146
respectively represent
Figure GDA0003812136450000147
And
Figure GDA0003812136450000148
the weight of (c);
the method for correcting the vehicle traveling route in S7 and the method for determining that the vehicle has reached the designated work position in S8 are as follows:
s101, in the driving process, dividing a driving path into a plurality of path points according to the driving path boundary value acquired in S4 and combining obstacle information, wherein for each path point, if the left boundary is lower than a preset threshold value, the vehicle is deviated to the right side, if the right boundary is lower than the preset threshold value, the vehicle is deviated to the left side, and if the distance between the left boundary and the right boundary is smaller than a width threshold value at which the vehicle passes, the vehicle is judged to be unable to pass, parking is planned, and the driving path is planned again;
s102, judging whether the vehicle reaches the designated operation position or not according to the distance between the collected real-time position of the vehicle and the designated operation position, repeating S4-S7 to continue to travel to the designated operation position when the distance is greater than a threshold value, judging that the vehicle reaches the target position when the distance is less than or equal to the threshold value, and sending a confirmation signal.
It is noted that, herein, relational terms such as first and second, and the like may be used solely to distinguish one entity or action from another entity or action without necessarily requiring or implying any actual such relationship or order between such entities or actions. Also, the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus.
Finally, it should be noted that: although the present invention has been described in detail with reference to the foregoing embodiments, it will be apparent to those skilled in the art that changes may be made in the embodiments and/or equivalents thereof without departing from the spirit and scope of the invention. Any modification, equivalent replacement, or improvement made within the spirit and principle of the present invention should be included in the protection scope of the present invention.

Claims (7)

1. The automatic driving method of the underground mining articulated vehicle comprises an automatic driving device and an automatic vehicle driving system, wherein the automatic driving device comprises a front vehicle body (1), a hinge device (4) is fixedly connected to the rear end of the front vehicle body (1), a corner sensor (11) is fixedly connected to the rear end of the hinge device (4), a rear vehicle body (2) is arranged at the rear end of the front vehicle body (1), the hinge device (4) is hinged to the rear vehicle body (2), a top laser radar (6) is fixedly connected to the top of the front vehicle body (1), a front laser radar (7) is fixedly connected to the front end of the front vehicle body (1), a rear laser radar (8) is fixedly connected to the rear end of the rear vehicle body (2), a front ultrasonic radar (9) is fixedly connected to the front end side face of the front vehicle body (1), two side ultrasonic radars (10) are fixedly connected to two side faces of the front vehicle body (1), a wheel speed meter (12) is fixedly connected to wheels of the rear vehicle body (2), a movable hopper (3) is connected to the upper end of the rear vehicle body (2), and an internal device of the front vehicle body (1) is provided with an internal device (5);
the automatic vehicle driving system comprises an intelligent decision-making module, an environment sensing module, an inertial navigation positioning module and a vehicle control module, wherein the intelligent decision-making module, the environment sensing module, the inertial navigation positioning module and the vehicle control module are respectively and electrically connected;
the intelligent decision module comprises a data recording module, a data calculating module, a logic judging module and a comparison module;
the environment sensing module comprises a laser detection module and an ultrasonic detection module;
the inertial navigation positioning module comprises a wheel speed detection module and a hinge angle acquisition module;
the vehicle control module comprises a steering control module, a speed control module and a start-stop module;
the laser detection module is electrically connected with the top laser radar (6), the front laser radar (7) and the rear laser radar (8), the ultrasonic detection module is electrically connected with the front ultrasonic radar (9) and the side ultrasonic radar (10), the wheel speed detection module is electrically connected with the wheel speed meter (12), the hinge angle acquisition module is electrically connected with the corner sensor (11), and the steering control module, the speed control module and the start-stop module are all arranged inside the equipment box (5);
the method is characterized in that: the operation of the vehicle autopilot system comprises the steps of:
s1, a vehicle receives a transportation operation instruction, exits a standby waiting state and enters an automatic driving state;
s2, collecting three-dimensional data points of the surrounding environment of the vehicle through a laser detection module, and comparing the measured data with a preset high-precision working environment map through a comparison module, so as to obtain the current position of the vehicle;
s3, calculating a feasible driving path by using a data calculation module according to the current position of the vehicle and the operation position specified by the transportation operation instruction, determining the shortest path through a logic judgment module, and controlling the vehicle to start automatic driving through a vehicle control module;
s4, in the automatic driving process, a laser detection module is used for collecting lane wall data points, the collected data points are divided into a plurality of intervals along the driving direction of the vehicle, the data points in each interval are judged to be positioned on the left side or the right side of the driving path, the distance between the data points and the driving path is respectively obtained, the point with the minimum distance from the data points on the left side to the driving path is taken as the left boundary of the interval, the point with the minimum distance from the data points on the right side to the driving path is taken as the right boundary of the interval, so that a group of lane boundary values of the vehicle along the driving direction of the vehicle is obtained, and the boundary value of the whole driving path is further obtained;
s5, collecting three-dimensional data points in front of a driving path by using an environment sensing module, then forming a plurality of data point sets by using a distance-based K-means adaptive clustering method, calculating the maximum and minimum values of data point coordinates of each set, and taking the maximum and minimum values as the vertexes of the lower left corner and the upper right corner of the cube as the detection results of the obstacles;
s6, obtaining vehicle positioning in real time:
s61, obtaining the vehicle positioning of the current time of the vehicle by the method of S2, and using the mark
Figure FDA0003812136440000021
Represents;
s62, determining the vehicle positioning at the current moment through the vehicle positioning at the previous moment:
s621, setting a mark for positioning at a time on the vehicle
Figure FDA0003812136440000022
Is represented by the formula, wherein X T-1 And Y T-1 Representing the last moment vehicle reference point, the X and Y coordinates in a preset vehicle autopilot system coordinate system, theta T-1 Representing the included angle between the vehicle reference point at the last moment and the X direction in the preset coordinate system of the automatic driving system of the vehicle,
Figure FDA0003812136440000031
the direction angle difference between the front vehicle body (1) and the rear vehicle body (2) at the previous moment is represented;
s622, setting the rotating radius of the vehicle at the current moment to be R T The value is determined by the following formula:
Figure FDA0003812136440000032
wherein L is F Is the distance L from the hinge device (4) to the axle of the front vehicle body (1) R The distance between the hinge device (4) and the wheel axle of the rear vehicle body (2),
Figure FDA0003812136440000033
the direction angle difference between the front vehicle body (1) and the rear vehicle body (2) at the current moment is represented;
s623, setting the rotation angular speed of the vehicle at the current moment to be omega T The value is determined by the following formula:
Figure FDA0003812136440000034
wherein v is T Representing the speed of a reference point of the vehicle at the present moment, the value of which is measured by a wheel speed meter (12);
s624, setting the direction variation quantity of the vehicle reference point at the current moment relative to the last moment as theta T The value is determined by:
Figure FDA0003812136440000035
wherein
Figure FDA0003812136440000036
Representing the time variation of the current time and the last time;
s625, setting the vehicle positioning of the current time determined according to the previous time as
Figure FDA0003812136440000037
The parameters are determined by the following formula:
Figure FDA0003812136440000038
wherein S T Representing a distance moved by the vehicle reference point from a previous time to a current time;
s63, according to
Figure FDA0003812136440000041
And
Figure FDA0003812136440000042
obtaining the location P of the vehicle at the current moment by using the weighted average value T The value is defined by the following formula:
Figure FDA0003812136440000043
wherein
Figure FDA0003812136440000044
And
Figure FDA0003812136440000045
respectively represent
Figure FDA0003812136440000046
And
Figure FDA0003812136440000047
the weight of (c);
obtaining the vehicle positioning at the current moment by comparing the positioning difference of the two vehicles;
s7, correcting the advancing route of the vehicle by using an intelligent decision module according to the roadway boundary value obtained in the S4, meanwhile, judging whether the obstacle blocks the driving path of the vehicle or not by using a logic judgment module according to the obstacle information obtained in the S5, and avoiding collision accidents by means of deceleration and parking measures;
s8, according to the positioning of the vehicle acquired in real time, a logic judgment module is used for judging whether the vehicle reaches a specified operation position in real time, and a confirmation signal is sent after the vehicle reaches the specified operation position;
in the automatic driving process of the vehicle, the vehicle control module is used for calculating the error between the vehicle and the planned track by using the data calculation module according to the running track of the intelligent decision module and by combining the real-time positioning of the vehicle obtained by the inertial navigation positioning module and the environment sensing module, determining corresponding steering, throttle and braking control instructions based on the magnitude and the positive and negative values of the error, and driving corresponding vehicle execution components to finish automatic driving.
2. The automatic driving method of the underground mining articulated vehicle according to claim 1, characterized in that: the data recording module is specifically used for recording various data detected in real time and simultaneously comprises system preset fixed data, the data calculating module is specifically used for calculating data in the data recording module, the logic judging module is specifically used for analyzing a calculation result and determining a driving strategy required to be taken, the comparison module is specifically used for comparing acquired information with preset information, the laser detecting module is specifically used for acquiring working environment information, the working environment information specifically comprises related information of a roadway, the wheel speed detecting module is specifically used for detecting the speed of a vehicle, the hinge angle acquiring module is specifically used for acquiring angle information of a front vehicle body (1) and a rear vehicle body (2), the steering control module is specifically used for controlling steering of the vehicle, the speed control module is specifically used for controlling the speed of the vehicle, and the start and stop module is specifically used for controlling starting and closing of the vehicle.
3. The automatic driving method of the underground mining articulated vehicle according to claim 2, characterized in that: the specific method for acquiring the current position of the vehicle in S2 is as follows:
s21, collecting three-dimensional data points of the surrounding environment of the vehicle according to the laser detection module, comparing the measured data with a preset high-precision working environment map through the comparison module, and obtaining the positions P of the top laser radar (6), the front laser radar (7) and the rear laser radar (8) L ；
S22, through a preset top laser radar (6) in the automatic vehicle driving system) The installation positions of the front laser radar (7) and the rear laser radar (8) are used for obtaining the coordinate transformation relation between each laser radar and the vehicle reference point
Figure FDA0003812136440000051
S23, setting the position of a vehicle reference point as P V By transformation of
Figure FDA0003812136440000052
The position of the vehicle reference point can be obtained, and the position of the vehicle can be obtained.
4. The automatic driving method of the underground mining articulated vehicle according to claim 3, characterized in that: in S3, when the vehicle is automatically driven, the method for determining the shortest travel path is as follows:
the working area is abstracted into a directed graph in a comparison module, the lanes are edges in the directed graph, the joints of the lanes are used as nodes, meanwhile, the initial position of the vehicle and the target position given by the operation instruction are respectively obtained from the directed graph, and an open source Dijkstra graph search algorithm or other graph search algorithms are applied to obtain a group of edges with the shortest distance between the initial position and the target position or the shortest running time, so that a group of lanes through which the vehicle is going to run is obtained and used as the shortest running path of the vehicle.
5. The automatic driving method of the underground mining articulated vehicle according to claim 4, characterized in that: the method for determining the boundary value of the lane in the S4 comprises the following steps:
s41, dividing the collected lane wall data points into a plurality of intervals according to the driving lines and using a mark S i Represents the ith interval;
s42, for the section S i At any point P in i Determining its projection point P on the travel path by its shortest distance to the travel path i ', thereby obtaining a section S i At any point P in i Distance to travel path | P i P i '|；
S43, calculating interval S i After the distance from each data point to the driving path, taking the point with the minimum distance from the left data point to the driving path as an interval S i The point of the right data point whose distance to the travel path is the smallest is taken as the section S i Right driving boundary of (1);
and S44, repeating the steps S42-S43 for each section, and obtaining the running boundary of the whole running path.
6. The automatic driving method of the underground mining articulated vehicle according to claim 5, characterized in that: the determination method of the obstacle in S5 is as follows:
s51, collecting three-dimensional data points in front of a driving path through a laser detection module, forming a plurality of data point sets by applying a distance-based K-means adaptive clustering method, calculating the maximum and minimum values of data point coordinates of each set, using the maximum and minimum values as vertexes of the lower left corner and the upper right corner of a cube as detection results of obstacles, and using marks
Figure FDA0003812136440000061
The obstacle list represents the obstacle list collected by the laser detection module at the current moment;
s52, collecting three-dimensional data points in front of the driving path through the ultrasonic detection module, generating an obstacle list collected by the ultrasonic detection module at the current moment by using the method of S51, and using marks
Figure FDA0003812136440000062
Represents;
s53, combining the obstacle list O at the previous moment T-1 And, and
Figure FDA0003812136440000063
and
Figure FDA0003812136440000064
removing the false-detected obstacles thereinTo the obstacle list O of the current moment T 。
7. The automatic driving method of an articulated vehicle for underground mines according to claim 6, characterized in that: the method for correcting the vehicle traveling route in S7 and the method for determining that the vehicle reaches the designated work position in S8 are as follows:
s101, in the driving process, dividing a driving path into a plurality of path points according to the driving path boundary value acquired in S4 and the obstacle information detected in S5, wherein for each path point, if the distance from the vehicle to the left boundary is lower than a preset threshold value, the vehicle shifts to the right side, if the distance from the vehicle to the right boundary is lower than the preset threshold value, the vehicle shifts to the left side, and if the distance from the left boundary to the right boundary is smaller than a width threshold value for the vehicle to pass through, the vehicle is judged to be unable to pass through, parking is planned, and the driving path is planned again;
and S102, judging whether the vehicle reaches the designated operation position or not according to the distance between the collected real-time position of the vehicle and the designated operation position, repeating S4-S7 to continue to travel to the designated operation position when the distance is greater than a threshold value, judging that the vehicle reaches the target position when the distance is less than or equal to the threshold value, and sending a confirmation signal.
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