CN116803814A - An unmanned driving control method and system for mining trucks - Google Patents
An unmanned driving control method and system for mining trucks Download PDFInfo
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Abstract
The invention relates to an unmanned control method and system for an ore-carrying truck. The control method comprises the following steps: s1: and acquiring vehicle information and roadway information of the ore-carrying truck. S2: generating a driving route according to the roadway information; s3: judging whether the current roadway can pass or not, if so, setting the maximum running speed and the shortest braking distance; otherwise, suspending ore transportation operation; s4: establishing a prediction model, and inputting vehicle information and roadway information into the prediction model to obtain the next ideal state quantity of the ore-carrying truck; s5: and constructing a control model based on an Actor-Critic, and inputting the next ideal state quantity and roadway information into the control model to obtain the next ideal control quantity. According to the invention, the roadway profile is simulated through direct ranging, the detection method is simple, the control model is trained and updated according to the state quantity of the ore-carrying truck fed back in real time, and the unmanned control precision is improved.
Description
Technical Field
The invention relates to the technical field of unmanned operation, in particular to an unmanned control method and an unmanned control system for an ore transport truck.
Background
The articulated ore-carrying truck is a common vehicle for underground mine transportation, and has the advantages that the steering radius is smaller than that of the conventional truck, and the mobility is stronger, so that the articulated ore-carrying truck can be driven and operated more easily on narrow mine roads and turns, thereby improving the mine production efficiency and the transportation efficiency. In view of the applicability of the articulated ore-carrying truck in the construction of underground mines in the future, the automatic and intelligent transformation is necessary, wherein the unmanned transportation of the articulated ore-carrying truck in the underground tunnel is a key technology of the construction of intelligent mines. However, due to the complex steering and operating characteristics of the articulated hauler, the underground roadway environment is narrow and complex, and the development cost of the conventional SLAM and image recognition algorithm is too high to be suitable for automatic driving in narrow, multi-feature, dim environments in the pit.
Disclosure of Invention
Based on the problems of high detection cost and low control precision in the unmanned technology of the existing articulated ore-carrying truck caused by complex roadway road conditions in mining areas and excessive research and development costs of image recognition road conditions and image processing-based algorithms, the unmanned control method and system of the ore-carrying truck are provided.
The invention is realized by the following technical scheme: the unmanned control method of the ore-carrying truck comprises the following steps:
s1: acquiring vehicle information of an ore carrying truck and roadway information within the range of the ore carrying truck; the vehicle information comprises state quantity, characteristic quantity, control quantity and position information of the ore-carrying truck; the roadway information comprises roadway width, roadway outline, obstacle information, roadway temperature, ground humidity and ground amplitude;
s2: generating a driving route according to the characteristic quantity, the roadway width, the roadway outline and the obstacle information;
s3: judging whether the current roadway can pass or not according to the roadway temperature and the ground amplitude, if so, setting the maximum running speed and the shortest braking distance according to the ground humidity; otherwise, sending an alarm signal to the base station and suspending ore transportation operation;
s4: establishing a prediction model, and updating parameters of the prediction model according to the set maximum running speed and the set shortest braking distance; inputting the driving route, the state quantity and the control quantity into a prediction model to obtain the next ideal state quantity;
s5: and constructing a control model based on an Actor-Critic, and inputting the current control quantity, the current state quantity and the next ideal state quantity into a strategy network of the control model to obtain the next ideal control quantity.
The control method simulates the contour of the roadway through direct ranging, has the advantages of simplicity, quick response and easiness in implementation, does not need to record route characteristics, does not need to compare route action attributes, does not need to record and match control parameters one by one, and has a peak value with a lower calculation example. And aiming at the difference between the roadway of the mining area and the common road, the real-time measurement of the temperature, the humidity and the ground amplitude of the roadway is increased, the running speed of the mining truck is limited, the running safety of the mining truck is ensured, and the interference caused by the falling of goods to other vehicles in the cargo carrying process of the mining truck is avoided. In path planning and vehicle control, according to simulated roadway contours, corresponding driving routes are generated by taking roadway center lines as standards and combining obstacle information, so that the ore-carrying trucks are kept at sufficient intervals from two sides of the roadway to avoid collision, meanwhile, ideal control quantity of the ore-carrying trucks is output by adopting an Actor-Critic-based control model, the control model is trained and updated according to real-time feedback state quantity of the ore-carrying trucks, and control accuracy is improved.
Further, the state quantity comprises the pose and the vehicle speed of the ore-carrying truck; the control quantity comprises a corner variable and a speed variable of the ore-carrying truck; the state quantity, the control quantity and the roadway information are measured in real time by installing corresponding sensors.
Further, by installing a laser radar detector at the head of the ore carrying truck, detecting obstacle information and corresponding roadway contours in the front area of the ore carrying truck in real time; the roadway profile is represented by a plurality of detection points, the laser radar detector emits a plurality of detection waves with different angles, and the distance between the roadway side wall and the laser radar detector along different directions is measured according to echo signals; and fitting a plurality of detection points to form a roadway profile.
Further, the method for generating the driving route is as follows:
s21: and (3) taking the rotation center of the ore delivery truck hinge as an origin, taking the running direction of the ore delivery truck as a Y axis, and establishing a plane coordinate system based on roadway surfaces.
S22: and mapping the outlines of the two sides of the roadway into a coordinate system according to the installation position of the radar detector, the distance between the ore carrying truck and the two side walls of the roadway and the distance between the ore carrying truck and the two sides of the roadway in the front area, so as to form two-side roadway curves.
S23: and (5) averaging the abscissa of the roadway curves at the two sides to obtain a basic driving route. And fine tuning is carried out on the basic driving route, so that a smooth driving route is obtained.
S24: and updating the driving route in real time according to the obstacle information acquired in real time so as to avoid the obstacle.
Further, calculating a roadway abnormality index Q according to the roadway temperature T and the ground amplitude A d If Q d And if the operation is not less than 1, suspending the ore transportation operation. Wherein, roadway abnormality index expresses as:
Q d =ω 1 T/T 0 +ω 2 A/A 0
in which Q d Is roadway abnormality index omega 1 T is the weight of the temperature 0 For the temperature threshold, ω 2 Is the ground amplitude weight, and omega 1 +ω 2 =1，A 0 Is the ground amplitude threshold.
Further, the maximum running speed v max The method comprises the following steps:in the formula, v max0 Maximum running speed, RH, set for the maximum friction coefficient between the tires of the mining truck and the ground 1 For the ground humidity, RH when the tire of the ore-carrying truck and the ground reach the minimum friction coefficient 2 For the ground humidity when the maximum friction coefficient between the tires of the ore-carrying truck and the ground is reached, v max1 The maximum running speed is set when the tire of the ore-carrying truck reaches the maximum friction coefficient with the ground.
Shortest braking distance S min Can be set as follows:
S min =2S。S=v 2 /2gμ
wherein S is the emergency braking distance of the ore-carrying truck, v is the current speed of the ore-carrying truck, mu is the friction coefficient between the tire of the ore-carrying truck and the ground, and g is the gravitational acceleration.
Further, the next ideal state quantity is calculated by the following method:
to the current state quantity X i And the current control amount u i Inputting the predicted model to obtain a corresponding track function, wherein the track function is expressed as:in (1) the->For the next state quantity, +.>As a function of trajectory.
If the pose quantity of the next state quantity calculated according to the track function is equal to the next ideal pose in the driving route, the next ideal state quantity is directly expressed as the next state quantity, otherwise, the next ideal state quantity is calculated according to the state correction function. Wherein the state correction function is expressed as:in (1) the->For the next ideal stateThe amount is recorded asA is a state matrix, and B is a control matrix.
Further, the training method of the control model is as follows:
s51: an Actor-Critic based control model is initialized. The control model includes a policy network and a value network.
S52: and inputting the current control quantity, the current state quantity and the next ideal state quantity output by the prediction model into a strategy network, and adopting a Markov process to make a decision to generate the next ideal control quantity.
S53: and inputting the next ideal control quantity into a value network to obtain corresponding value, and updating the strategy network according to the value.
S54: and updating the value network according to the next control quantity and the next actual state quantity fed back in real time, wherein the value network and the strategy network form a circulation more.
The invention also provides an unmanned control system of the ore-carrying truck, which comprises a base station, a monitoring device and a controller.
The monitoring device is used for measuring state quantity and roadway information of the ore carrying truck in real time. The plurality of base stations are used for sending positioning signals to the monitoring device, and the real-time position of the ore-carrying truck is calculated according to the distances between the plurality of base stations and the monitoring device. The controller is used for receiving state quantity, real-time position and roadway information of the ore-carrying truck and generating a driving route according to the roadway information. And generating a control signal for the ore-carrying truck according to the state quantity and the driving route so as to enable the ore-carrying truck to drive according to the driving route.
Further, the monitoring device comprises a laser radar detector and a plurality of millimeter wave radar detectors. The laser radar detector is arranged at the head of the ore carrying truck and is used for detecting the contour of the side wall of the roadway and the information of the obstacle in front of the ore carrying truck. Millimeter wave radar detectors are respectively arranged at two sides of the ore carrying truck and used for detecting the distance between two sides of the ore carrying truck and two side walls of a roadway.
Compared with the prior art, the invention has the following beneficial effects:
the method simulates the roadway profile by adopting a radar ranging mode, has the advantages of simple detection method, quick response and easy realization, does not need to record route characteristics, does not need to compare route action attributes, does not need to record and match control parameters one by one, and has peak value with lower calculation example. And aiming at the difference between the roadway of the mining area and the common road, the real-time measurement of the roadway temperature, the humidity and the ground amplitude is increased, the running speed of the ore-carrying truck is limited, the running safety of the ore-carrying truck is ensured, the interference to other vehicles caused by the falling of goods in the process of carrying the ore-carrying truck is avoided, and the passing efficiency of ore-carrying operation is improved.
In path planning and vehicle control, according to the simulated roadway profile, the corresponding driving route is generated by taking the roadway center line as a standard and combining obstacle information, so that the distance between the ore-carrying truck and the two sides of the roadway is kept sufficient, and collision is avoided. Meanwhile, an ideal control quantity of the ore-transporting truck is output by adopting a control model based on an Actor-Critic, the control model is trained and updated according to the state quantity of the ore-transporting truck fed back in real time, the control precision is improved, the ore-transporting truck is driven according to a driving route, and the control precision and the robustness of the ore-transporting truck are improved.
Drawings
FIG. 1 is a step diagram of an unmanned control method of a mining truck in embodiment 1 of the present invention;
FIG. 2 is a schematic diagram of the roadway information monitoring method in FIG. 1;
FIG. 3 is a schematic diagram of a method of monitoring and controlling an ore delivery truck in a straight run;
FIG. 4 is a schematic diagram of a method of monitoring and controlling an ore delivery truck in a turn section;
FIG. 5 is a schematic diagram of a method of monitoring and controlling an ore delivery truck in the red section;
fig. 6 is a schematic structural diagram of an unmanned control system of a mining truck according to embodiment 2 of the present invention.
Detailed Description
The following description of the embodiments of the present invention will be made clearly and completely with reference to the accompanying drawings, in which it is apparent that the embodiments described are only some embodiments of the present invention, but not all embodiments. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.
It is noted that when an element is referred to as being "mounted to" another element, it can be directly on the other element or intervening elements may also be present. When an element is referred to as being "disposed on" another element, it can be directly on the other element or intervening elements may also be present. When an element is referred to as being "secured to" another element, it can be directly secured to the other element or intervening elements may also be present.
Unless defined otherwise, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention belongs. The terminology used herein in the description of the invention is for the purpose of describing particular embodiments only and is not intended to be limiting of the invention. The term "or/and" as used herein includes any and all combinations of one or more of the associated listed items.
Example 1
Referring to fig. 1-2, the embodiment provides an unmanned control method for an ore-carrying truck, which includes the following steps:
s1: and acquiring vehicle information of the ore-carrying truck and roadway information within the range of the ore-carrying truck. Wherein the vehicle information includes a feature quantity and a state quantity. The characteristic quantity comprises the self weight G of the ore-carrying truck t Weight G of the load l Length l, width d t Maximum steering angle delta max Maximum acceleration a max Shortest braking distance S min Etc., wherein the length l comprises a head length l h And a suspension length l s . The state quantity comprises the current speed v, the rotation angle delta, the position information, the pose and the like of the ore-carrying truck. The self weight, torque, length, width, maximum acceleration, shortest braking distance and the like of the ore-carrying truck can be directly obtained according to the specification information of the ore-carrying truck, or can be fedThe weight of the load can be obtained by subtracting the weight of the load from the weight of the whole vehicle after measuring the weight of the whole vehicle. The state quantity needs to be monitored in real time in the running process, and real-time measurement can be carried out by installing a corresponding speed sensor, an angle sensor, a ranging sensor, a UWB positioning card and the like on the ore-carrying truck.
The roadway information comprises the current roadway width, roadway outline, obstacle information, roadway temperature, ground humidity and ground amplitude. Specifically, the roadway information is obtained by the following method:
millimeter wave radar detectors are respectively arranged on two sides of the ore-carrying truck and are used for detecting the distance d between the ore-carrying truck and two side walls of a roadway 1 、d 2 . Width d of ore carrying truck t And distance d 1 、d 2 The sum of which is the actual roadway width.
And a laser radar detector is arranged at the head part of the ore carrying truck and is used for detecting the tunnel outline and the obstacle information in the front area of the ore carrying truck. The roadway profile is represented by a plurality of detection points, the laser radar detector emits a plurality of detection waves with different angles, and the distance between the roadway side wall along different directions and the laser radar detector is measured according to echo signals. And fitting a plurality of detection points to form a roadway profile. And calculating the contour of the roadway according to the plurality of intervals detected by the laser radar detector and the corresponding detection angles. For example, the laser radar detector detects the distance between the three directions in the front direction, and the distance is-45 degrees, 0 degrees and 45 degrees respectively with the running direction of the automobile, so that two (the distance between the front sides is larger than the detection distance) or three distance values are correspondingly obtained, and the roadway profile of the corresponding road section can be calculated according to the distance between the side surfaces and the distance between the front side walls which are correspondingly measured. Of course, the number of the actually measured intervals of the laser radar detector is more than 3, so that the corresponding roadway profile can be measured more accurately.
And a temperature sensor, a humidity sensor and a vibration sensor are arranged at the head of the ore-carrying truck, and the temperature, the humidity and the amplitude of the ground of the roadway are measured in real time. The vibration amplitude comprises ground vibration amplitude caused by mining area construction operation and vibration amplitude caused by vehicle speed and road surface during running of the mining truck.
S2: and generating a driving route according to the roadway width, the roadway profile and the obstacle information. And calculating the curvature of the driving route, and dividing the driving road section into a straight section, a steering section and a red section according to the curvature and the position.
Referring to fig. 3-5, in this embodiment, a plane coordinate system based on roadway surface is established with the rotation center of the hinge of the mining truck as the origin and the driving direction of the mining truck as the Y axis. Mapping the ore-carrying truck to a coordinate system to obtain a graph outline based on the appearance of the ore-carrying truck, wherein the graph outline comprises a fixed rectangle A which is bisected by a Y-axis and a rectangle B which is positioned in a third quadrant and a fourth quadrant, the distance from the center of the rectangle B to an origin is always unchanged, and when the ore-carrying truck is straight, the rectangle B is bisected by the Y-axis.
According to the installation position of the radar detector and the detected spacing d 1 、d 2 、d 3 、d 4 Mapping the outlines of two sides of the roadway into a coordinate system to form curves of the two sides of the roadway. And averaging the abscissa of the roadway curves at two sides to obtain a basic driving route, and then fine-tuning the basic driving route to ensure that the curvature of the basic driving route is continuous, so as to obtain the driving route.
In this embodiment, 3 millimeter wave radar detectors are respectively installed on two sides of the ore-carrying truck, corresponding to 6 measured distance values, and mapped to a coordinate system to obtain 6 coordinate points, including M located on the left side of the ore-carrying truck 1 、M 2 、M 3 N on right side of ore-carrying truck 1 、N 2 、N 3 。
The laser radar detector detects a plurality of interval values, and maps the interval values into a coordinate system to obtain a plurality of coordinate points P positioned in a second quadrant 1 、P 2 、……、P n And a plurality of coordinate points Q located in the first quadrant 1 、Q 2 、……、Q n . And linearly fitting the coordinate points to obtain two continuous and smooth curves. And averaging the abscissa of the two smooth curves to form a running route taking the origin as the starting point.
And when the obstacle information is detected, updating the driving route in real time according to the obstacle information acquired in real time. Specifically, the obstacle is mapped into a coordinate system according to the size and the relative position of the obstacle, and if the obstacle is in the area of the driving route (i.e. the area through which the mining truck drives according to the driving route), the route is re-planned to avoid the obstacle. The re-planned travel route should satisfy the following conditions: 1. when the ore transport truck runs along the running route, the ore transport truck does not pass through the barrier, and the distance between the two sides of the ore transport truck and the two sides of the roadway is not smaller than a preset distance threshold. 2. The difference between the curvature of the driving route and the original curvature is not higher than a preset error threshold value.
If the obstacle cannot be avoided, an alarm signal is sent out, and relevant personnel or machines are waited for to clear the obstacle.
In the driving route, the curvature of each point is defined as the change rate of the included angle between the tangent line of each point and the tangent line of the previous point, and is expressed as:wherein K is i For the curvature of the path of travel at point i, θ i Is the angle between the tangent line of the driving route at the point i and the tangent line at the point i-1.
In the travel route, the travel section is divided into a straight section and a turning section according to the curvature of the travel route. For example, a travel route having a curvature of less than 0.2 is defined as a straight travel segment, and a travel route having a curvature of 0.2 or more is defined as a steering segment. Of course, the definitions of the straight section and the steering section can be set according to the characteristic quantity or roadway information of the ore-carrying truck.
The red section is a driving route of the area where the ore unloading point is located, wherein the ore unloading point is provided with an inlet and an outlet, and an entrance guard, namely an induction type safety fence, is arranged at the inlet and the outlet.
S3: judging whether the current roadway can pass or not according to the roadway temperature and the ground amplitude, if so, setting the maximum running speed and the shortest braking distance according to the ground humidity, otherwise, sending an alarm signal to a base station, and suspending ore transportation operation.
Specifically, roadway abnormality indexes are calculated according to roadway temperature T and ground amplitude A, and are shown in the tableThe method comprises the following steps:in which Q d Is roadway abnormality index omega 1 T is the weight of the temperature 0 For the temperature threshold, ω 2 Is the ground amplitude weight, and omega 1 +ω 2 =1，A 0 Is the ground amplitude threshold.
Judgment of Q d If the number is more than or equal to 1, indicating that the ore transportation operation has a large risk, sending an alarm signal to the base station, and suspending the ore transportation operation.
At Q d When the speed is less than 1, setting the maximum running speed v of the ore-carrying truck according to the ground humidity RH max Shortest braking distance S min . Wherein the maximum travel speed v max Can be set as follows:in the formula, v max0 RH, which is the maximum running speed (in the case of straight running) set when the tire of the mining truck reaches the maximum friction coefficient with the ground 1 For the ground humidity, RH when the tire of the ore-carrying truck and the ground reach the minimum friction coefficient 2 For the ground humidity when the maximum friction coefficient between the tires of the ore-carrying truck and the ground is reached, v max1 The maximum running speed (in the example of straight running) is set for the tire of the mining truck to reach the maximum friction coefficient with the ground.
In the present embodiment, v max0 Set to 60km/h, v max1 Set to 30km/h, RH 1 Set to 80%, RH 2 Set to 40%.
Shortest braking distance S min Can be set as follows:
S min =2S
wherein S is the emergency braking distance of the ore-carrying truck.
In general, during the running of an automobile, the emergency braking distance S is related to the running speed of the automobile and the friction coefficient between the tire and the ground of the automobile, and can be expressed as:wherein v is the current speed of the ore-carrying truckMu is the friction coefficient between the tires of the ore-carrying truck and the ground, and g is the gravitational acceleration.
Wherein the coefficient of friction μ is related to the floor humidity, in this embodiment, the coefficient of friction μ is 0.2 when the floor humidity is not less than 80%, and 0.8 when the floor humidity is not more than 40%.
In order to guarantee safe operation of the ore carrying truck, in the embodiment, the shortest braking distance actually set is larger than the emergency braking distance, so that the ore carrying truck can brake stably in time, and accidents such as side turning and goods falling in the ore carrying process are avoided.
S4: and (3) establishing a prediction model, and inputting the updated driving route, the current state quantity and the current control quantity into the prediction model to obtain the next ideal state quantity.
Setting the current state quantity to X i （x i ，v i ) Wherein x is i Representing the current pose by the included angle alpha between the head and the tail of the truck and the rotation angle delta of the front wheel i Denoted as x i （α i ，δ i ）。v i Is the current speed of the ore-carrying truck.
Setting the current control amount to u i （Δδ i ，Δv i ) Wherein Δδ i Is the rotation angle control quantity, namely the control quantity of the front wheel rotation angle of the ore-carrying truck, deltav i The speed control quantity, namely the control quantity of the speed of the ore-carrying truck, is actually converted into the control quantity of the accelerator or the brake of the ore-carrying truck.
Inputting the current state quantity and the current control quantity into a preset prediction model to obtain a corresponding track function, wherein the track function is expressed as follows:in (1) the->For the next state quantity, +.>As a function of trajectory.
Therefore, the next state quantity of the ore-carrying truck can be calculated according to the current state quantity and the current control quantity of the ore-carrying truck, the next ideal position of the ore-carrying truck can be calculated according to the driving route, if the position and the position in the next state quantity are equal to the next ideal position and the next ideal position, the next ideal state quantity is directly expressed as the next state quantity, and otherwise, the next ideal state quantity is calculated according to the state correction function.
Wherein the state correction function can be expressed as:in (1) the->For the next ideal state quantity, it is marked as +.>A is a state matrix, and B is a control matrix.
S5: and constructing a control model based on an Actor-Critic, and inputting the current control quantity, the current state quantity and the next ideal state quantity into a strategy network of the control model to obtain the next ideal control quantity. And inputting the next ideal control quantity into a value network of the control model to obtain a corresponding value, and updating the strategy network. And then training and updating the value network according to the next state quantity fed back in real time, realizing the cyclic updating of the strategy network and the value network, and optimizing the output result. The specific updating method comprises the following steps:
s51: an Actor-Critic based control model is initialized.
Initializing content includes initializing a local network, an overall target network, dynamic barrier parameters, playing back experience pool data, super parameters, and the like.
S52: the current control quantity, the current state quantity and the next ideal state quantity output by the prediction model are input into a strategy network, a Markov process is adopted for decision making, the next ideal control quantity is generated, each decision making is updated once, and the next ideal state quantity and the next ideal control quantity are output. Wherein, the decision process of the policy network can be expressed as:wherein pi is a policy, representing the policy in different states s t Selecting different actions a t Conditional probability of a) t For output, i.e. the next desired control quantity of the ore-carrying truck s t For input, i.e. the next ideal state quantity, θ is a parameter of the policy network.
S53: and inputting the next ideal control quantity into a value network to obtain corresponding value, and updating the strategy network according to the value. The parameter update of the policy network can be expressed as:in the formula, A is a dominance function.
S54: and updating the value network according to the next control quantity and the next actual state quantity fed back in real time. The value network and the policy network form a cyclic update, and the following contents are updated simultaneously: updating and playing back experience pool data, and performing gradient update circulation: estimating the dominance function, updating the overall target network, and performing experience playback training. Wherein the updating of the value network is expressed as:where Q is the value and ω is a parameter of the value network.
The parameter update of the value network can be expressed as:where β is the update step size.
According to the control quantity output by the prediction model and the control model, unmanned driving of the ore-carrying truck is realized, and the following driving targets are achieved as far as possible in a roadway by the ore-carrying truck: 1. and on the straight running section, controlling the speed of the lifting ore-carrying truck until the preset maximum speed is reached, and the ore-carrying truck just passes through the updated running route.
2. And on the steering section, regulating the maximum running speed and the shortest braking distance according to the curvature of the running route, wherein the distance between the ore-carrying truck and the two sides of the roadway is always not smaller than the preset distance in the running process.
3. And on the red zone, when the distance between the ore-carrying truck and the red zone fence reaches a preset distance threshold value, controlling to open the red zone fence. And judging whether the red fence is abnormally opened according to the fence state data acquired in real time, if so, controlling the ore-transporting truck to stop, and sending out an alarm signal, otherwise, entering or leaving the red section by the ore-transporting truck according to a preset vehicle speed threshold value.
The unmanned control method of the ore-carrying truck simulates the roadway profile in a radar ranging mode, is simple in detection method, quick in response and easy to implement, does not need to record route characteristics, does not need to compare route action attributes, does not need to record and match control parameters one by one, and has a peak value with a lower calculation example. And aiming at the difference between the roadway of the mining area and the common road, the real-time measurement of the temperature, the humidity and the ground amplitude of the roadway is increased, the running speed of the mining truck is limited, the running safety of the mining truck is ensured, and the interference caused by the falling of goods to other vehicles in the cargo carrying process of the mining truck is avoided. In path planning and vehicle control, according to simulated roadway contours, corresponding driving routes are generated by taking roadway center lines as standards and combining obstacle information, so that the ore transport trucks are kept at sufficient intervals from two sides of the roadway to avoid collision, meanwhile, ideal control quantity of the ore transport trucks is output by adopting an Actor-Critic-based control model, the control model is trained and updated according to real-time feedback state quantity of the ore transport trucks, control precision is improved, the ore transport trucks are driven according to the driving routes, and control precision and robustness of the ore transport trucks are improved.
Example 2
Referring to fig. 6, the present embodiment provides an unmanned control system for an ore-carrying truck, which can adopt the unmanned control method for an ore-carrying truck of embodiment 1 to control, so as to implement unmanned ore-carrying operation in a mine roadway. The unmanned control system comprises a base station, a monitoring device, a controller and a safety fence.
The monitoring device comprises a UWB positioning card, a plurality of millimeter wave radar detectors, a laser radar detector, a temperature sensor, a humidity sensor and a vibration sensor. The ore-carrying truck measures the weight of the whole truck before running, and then calculates the load weight according to the weight of the ore-carrying truck.
The UWB positioning card performs data interaction with the base station, and then the position of the UWB positioning card is calculated according to the position of the base station and is used as the position information of the ore-carrying truck.
The millimeter wave radar detectors are respectively arranged at two sides of the ore carrying truck and used for detecting the distance between two sides of the ore carrying truck and two side walls of a roadway. The laser radar detector is used for detecting the distance between the front of the ore carrying truck and the two side walls of the roadway in the mining area according to the head of the ore carrying truck, and then simulating the outline of the roadway according to the distance data.
The temperature sensor, the humidity sensor and the vibration sensor are respectively used for detecting roadway temperature, ground humidity and ground amplitude.
The base station adopts a WIFI+UWB fusion positioning mode to realize full-channel coverage of mine roadways for positioning the position information of vehicles.
The safety fence is arranged at an inlet and an outlet of the ore unloading point and is used for identifying information of the ore delivery truck and limiting vehicles entering and exiting. In this embodiment, the safety barrier is used with monitoring device cooperation, carries out real-time supervision through monitoring device to the region that the safety barrier is located, when fortune ore deposit truck reaches the interval of predetermineeing, judges fortune ore deposit truck's pass right, opens the safety barrier after confirming fortune ore deposit truck possesses pass right.
The controller is used for receiving state information, roadway information and the like of the ore-carrying truck, generating a driving route according to the roadway information, and generating a control signal for the ore-carrying truck according to the state information and the driving route so as to enable the ore-carrying truck to carry out ore-carrying operation according to the driving route. Meanwhile, the controller calculates the distance between the ore-carrying truck and the safety fence according to the position information of the ore-carrying truck and the position information of the safety fence, acquires the switching state of the safety fence, judges whether the safety fence is abnormal, controls the ore-carrying truck to stop when the safety fence is abnormal, and sends an alarm signal to an uphole control room.
The technical features of the above-described embodiments may be arbitrarily combined, and all possible combinations of the technical features in the above-described embodiments are not described for brevity of description, however, as long as there is no contradiction between the combinations of the technical features, they should be considered as the scope of the description.
The above examples illustrate only a few embodiments of the invention, which are described in detail and are not to be construed as limiting the scope of the invention. It should be noted that it will be apparent to those skilled in the art that several variations and modifications can be made without departing from the spirit of the invention, which are all within the scope of the invention. Accordingly, the scope of protection of the present invention is to be determined by the appended claims.
Claims (10)
Priority Applications (1)
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