CN115309169B - Underground unmanned vehicle control method and device - Google Patents
Underground unmanned vehicle control method and device Download PDFInfo
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- G05D1/02—Control of position or course in two dimensions
- G05D1/021—Control of position or course in two dimensions specially adapted to land vehicles
- G05D1/0212—Control of position or course in two dimensions specially adapted to land vehicles with means for defining a desired trajectory
- G05D1/0214—Control of position or course in two dimensions specially adapted to land vehicles with means for defining a desired trajectory in accordance with safety or protection criteria, e.g. avoiding hazardous areas
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- G—PHYSICS
- G05—CONTROLLING; REGULATING
- G05D—SYSTEMS FOR CONTROLLING OR REGULATING NON-ELECTRIC VARIABLES
- G05D1/00—Control of position, course, altitude or attitude of land, water, air or space vehicles, e.g. using automatic pilots
- G05D1/02—Control of position or course in two dimensions
- G05D1/021—Control of position or course in two dimensions specially adapted to land vehicles
- G05D1/0212—Control of position or course in two dimensions specially adapted to land vehicles with means for defining a desired trajectory
- G05D1/0223—Control of position or course in two dimensions specially adapted to land vehicles with means for defining a desired trajectory involving speed control of the vehicle
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- G—PHYSICS
- G05—CONTROLLING; REGULATING
- G05D—SYSTEMS FOR CONTROLLING OR REGULATING NON-ELECTRIC VARIABLES
- G05D1/00—Control of position, course, altitude or attitude of land, water, air or space vehicles, e.g. using automatic pilots
- G05D1/02—Control of position or course in two dimensions
- G05D1/021—Control of position or course in two dimensions specially adapted to land vehicles
- G05D1/0231—Control of position or course in two dimensions specially adapted to land vehicles using optical position detecting means
- G05D1/0242—Control of position or course in two dimensions specially adapted to land vehicles using optical position detecting means using non-visible light signals, e.g. IR or UV signals
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- G05D—SYSTEMS FOR CONTROLLING OR REGULATING NON-ELECTRIC VARIABLES
- G05D1/00—Control of position, course, altitude or attitude of land, water, air or space vehicles, e.g. using automatic pilots
- G05D1/02—Control of position or course in two dimensions
- G05D1/021—Control of position or course in two dimensions specially adapted to land vehicles
- G05D1/0255—Control of position or course in two dimensions specially adapted to land vehicles using acoustic signals, e.g. ultra-sonic singals
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- G05D—SYSTEMS FOR CONTROLLING OR REGULATING NON-ELECTRIC VARIABLES
- G05D1/00—Control of position, course, altitude or attitude of land, water, air or space vehicles, e.g. using automatic pilots
- G05D1/02—Control of position or course in two dimensions
- G05D1/021—Control of position or course in two dimensions specially adapted to land vehicles
- G05D1/0257—Control of position or course in two dimensions specially adapted to land vehicles using a radar
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Abstract
The application provides a method and a device for controlling an underground unmanned vehicle, wherein the method comprises the following steps: measuring the running speed and the acceleration of the unmanned vehicle and the current position of the unmanned vehicle, and predicting the running track of the unmanned vehicle based on the running speed and the acceleration of the unmanned vehicle and the current position of the unmanned vehicle; detecting whether obstacles exist around the unmanned vehicle; when no obstacle exists, controlling the unmanned vehicle to run based on the running speed of the unmanned vehicle; when an obstacle is present, determining whether the obstacle is located on a trajectory of the unmanned vehicle, detecting a position, a size, and a speed of the obstacle in response to determining that the obstacle is located on the trajectory of the unmanned vehicle, and controlling the unmanned vehicle to maintain a current driving state or to decelerate to a stop or to determine an optimal detour path based on at least one of the position, the size, and the speed of the obstacle and a driving speed of the unmanned vehicle. The invention provides an automatic obstacle avoidance method for an underground unmanned vehicle, which improves the obstacle avoidance efficiency of the underground unmanned vehicle and requires fewer resources.
Description
Technical Field
The application relates to the technical field of wireless communication in a coal mine, in particular to a method and a device for controlling an underground unmanned vehicle.
Background
With the development of automatic control technology and artificial intelligence technology, unmanned vehicles are widely applied to coal mine tunnels to release manpower. When the unmanned vehicle runs underground, the running efficiency of the unmanned vehicle is generally affected due to the fact that the unmanned vehicle encounters an obstacle (such as falling rocks or other equipment). Therefore, how to control the automatic obstacle avoidance of the underground unmanned vehicle is a technical problem which needs to be solved urgently.
Disclosure of Invention
The application provides a method and a device for controlling an underground unmanned vehicle, which are used for automatically avoiding obstacles by the underground unmanned vehicle.
An embodiment of a first aspect of the application provides a method for controlling an underground unmanned vehicle, which includes:
measuring the running speed and the acceleration of the unmanned vehicle and the current position of the unmanned vehicle, and predicting the driving track of the unmanned vehicle based on the running speed and the acceleration of the unmanned vehicle and the current position of the unmanned vehicle;
detecting whether obstacles exist around the unmanned vehicle;
when it is detected that no obstacle exists around the unmanned vehicle, controlling the unmanned vehicle to travel based on the traveling speed of the unmanned vehicle;
when it is detected that an obstacle exists around the unmanned vehicle, determining whether the obstacle is located on a trajectory of the unmanned vehicle, detecting a position, a size, and a speed of the obstacle in response to determining that the obstacle is located on the trajectory of the unmanned vehicle, and controlling the unmanned vehicle to maintain a current driving state or to decelerate to a stop or to determine an optimal detour path based on at least one of the position, the size, and the speed of the obstacle and a driving speed of the unmanned vehicle.
An embodiment of a second aspect of the present application provides a downhole unmanned vehicle control device, including:
the first processing module is used for measuring the running speed and the acceleration of the unmanned vehicle and the current position of the unmanned vehicle and predicting the running track of the unmanned vehicle on the basis of the running speed and the acceleration of the unmanned vehicle and the current position of the unmanned vehicle;
the detection module is used for detecting whether obstacles exist around the unmanned vehicle or not;
the control module is used for controlling the unmanned vehicle to run based on the running speed of the unmanned vehicle when the fact that no obstacles exist around the unmanned vehicle is detected;
the second processing module is used for determining whether the obstacle is positioned on the driving track of the unmanned vehicle when the obstacle is detected to be positioned around the unmanned vehicle, detecting the position, the size and the speed of the obstacle in response to the fact that the obstacle is positioned on the driving track of the unmanned vehicle, and controlling the unmanned vehicle to keep the current driving state or decelerate and stop or determine the optimal detour path based on at least one of the position, the size and the speed of the obstacle and the driving speed of the unmanned vehicle.
In summary, in the method and the device for controlling the underground unmanned vehicle provided by the embodiment of the disclosure, the unmanned vehicle may measure the driving speed and the acceleration of the unmanned vehicle and the current position of the unmanned vehicle, and may predict the driving trajectory of the unmanned vehicle based on the driving speed and the acceleration of the unmanned vehicle and the current position of the unmanned vehicle; then, whether obstacles exist around the unmanned vehicle or not is detected; when it is detected that no obstacle exists around the unmanned vehicle, controlling the unmanned vehicle based on the running speed of the unmanned vehicle; when it is detected that an obstacle exists around the unmanned vehicle, it is determined whether the obstacle is located on a trajectory of the unmanned vehicle, wherein in response to determining that the obstacle is located on the trajectory of the unmanned vehicle, a position, a size, and a speed of the obstacle are detected, and the unmanned vehicle is controlled to maintain a current driving state or to decelerate to a stop or to determine an optimal detour path based on at least one of the position, the size, and the speed of the obstacle and a driving speed of the unmanned vehicle.
As can be seen from this, in the solution of the present disclosure, the unmanned vehicle predicts the driving track thereof, and, when the unmanned vehicle detects that there is an obstacle around the unmanned vehicle and the obstacle is located on the driving track of the unmanned vehicle, the unmanned vehicle is controlled to maintain the current driving state or decelerate and stop or determine the optimal detour path for automatic obstacle avoidance based on at least one of the position, size, and speed of the obstacle and the driving speed of the unmanned vehicle. The present disclosure provides an automatic obstacle avoidance method for an underground unmanned vehicle, thereby improving the driving efficiency of the underground unmanned vehicle. Moreover, in the method, when the unmanned vehicle automatically avoids the obstacle, the unmanned vehicle can determine the optimal detour path to avoid the obstacle, so that the obstacle avoiding efficiency can be improved, and the required resources are less.
Additional aspects and advantages of the present application will be set forth in part in the description which follows and, in part, will be obvious from the description, or may be learned by practice of the present application.
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The above and/or additional aspects and advantages of the present application will become apparent and readily appreciated from the following description of the embodiments, taken in conjunction with the accompanying drawings of which:
FIG. 1 is a schematic flow chart of a method for controlling a downhole unmanned vehicle according to one embodiment of the present application;
fig. 2 is a schematic structural diagram of a downhole unmanned vehicle control device according to an embodiment of the application.
Detailed Description
Reference will now be made in detail to embodiments of the present application, examples of which are illustrated in the accompanying drawings, wherein like or similar reference numerals refer to the same or similar elements or elements having the same or similar function throughout. The embodiments described below with reference to the drawings are exemplary and intended to be used for explaining the present application and should not be construed as limiting the present application.
The method and apparatus for controlling an unmanned downhole vehicle according to the embodiments of the present application will be described below with reference to the accompanying drawings.
Fig. 1 is a schematic flow chart of a method for controlling a downhole unmanned vehicle (hereinafter briefly described as an unmanned vehicle) according to an embodiment of the present application, and as shown in fig. 1, the method includes:
Among the embodiment of the disclosure, the unmanned vehicle is provided with a speed sensor, an acceleration sensor, a positioning module and a laser radar sensor. The speed sensor is used for measuring the running speed of the unmanned vehicle; the acceleration sensor is used for measuring the acceleration of the unmanned vehicle; the positioning module and the laser radar sensor are used for measuring the current position of the unmanned vehicle.
And, in an embodiment of the present disclosure, a method for an unmanned vehicle to predict a trajectory of the unmanned vehicle may include: and calculating the real-time speed of the unmanned vehicle in a future period of time based on the current running speed and the acceleration, and predicting the driving track of the unmanned vehicle based on the real-time speed in the future period of time. Wherein the future period of time may refer to 0-10 seconds into the future.
In addition, in the embodiment of the disclosure, the unmanned vehicle may further detect the surrounding environment information thereof, so that the unmanned vehicle may be controlled to avoid the obstacle with reference to the surrounding environment information in the following.
And 102, detecting whether obstacles exist around the unmanned vehicle.
Wherein, this unmanned car is last to be provided with ultrasonic ranging sensor and infrared sensor. And the unmanned vehicle may detect whether there is an obstacle around the unmanned vehicle using the ultrasonic ranging sensor and the infrared sensor.
And 103, controlling the unmanned vehicle to run based on the running speed of the unmanned vehicle when no obstacle is detected around the unmanned vehicle.
Specifically, the method for controlling the unmanned vehicle to run based on the running speed of the unmanned vehicle may include:
responding to the fact that the running speed of the unmanned vehicle is in a preset interval, and controlling the unmanned vehicle to keep a current running state;
in response to the traveling speed of the unmanned vehicle not being in the predetermined section, the unmanned vehicle is controlled to accelerate or decelerate so that the traveling speed of the unmanned vehicle is maintained in the predetermined section.
The predetermined interval may be preset, and the predetermined interval may be, for example: 20-25 km/h.
And 104, when the obstacle around the unmanned vehicle is detected, determining whether the obstacle is located on the driving track of the unmanned vehicle, detecting the position, the size and the speed of the obstacle in response to the determination that the obstacle is located on the driving track of the unmanned vehicle, and controlling the unmanned vehicle to keep the current driving state or decelerate and stop or determine the optimal detour path based on at least one of the position, the size and the speed of the obstacle and the driving speed of the unmanned vehicle.
Specifically, in the embodiment of the present disclosure, when the unmanned vehicle detects that an obstacle exists around the unmanned vehicle, the unmanned vehicle may further detect whether the obstacle is a living being, for example, whether the obstacle is a living being may be detected by detecting a temperature of the obstacle, wherein if the obstacle is a living being (such as a human being or an animal), a behavior of the unmanned vehicle cannot be accurately predicted due to specific self-consciousness of the living being, and therefore, in order to avoid collision between the unmanned vehicle and the living being, the unmanned vehicle should be controlled to immediately decelerate and stop, and an alarm is given to remind the living being to leave. And if the obstacle is an abiotic obstacle, detecting the position, the size and the speed of the obstacle, and controlling the unmanned vehicle to keep the current running state or decelerate and stop or determine the optimal detour path to automatically avoid the obstacle based on at least one of the position, the size and the speed of the obstacle and the running speed of the unmanned vehicle.
The position, size and speed of the obstacle and the running speed of the unmanned vehicle can be measured by the ultrasonic ranging sensor and the infrared sensor.
Further, the above-mentioned method of controlling the unmanned vehicle to maintain the current driving state or to decelerate to stop or to determine the optimal detour path based on at least one of the position, size and speed of the obstacle and the driving speed of the unmanned vehicle may include the steps of:
step 1, determining whether the size of the obstacle influences the normal running of the unmanned vehicle.
In practical situations, when the obstacle is small (for example, the obstacle is only a small stone), the obstacle does not affect the normal driving of the unmanned vehicle no matter where the obstacle is located and the speed is large, and at this time, the unmanned vehicle does not need to avoid the obstacle. Based on this, whether the size of the obstacle affects the normal running of the unmanned vehicle is determined, so that the automatic obstacle avoidance process is started only when the size of the obstacle affects the normal running of the unmanned vehicle, and the automatic obstacle avoidance process is not started when the size of the obstacle does not affect the normal running of the unmanned vehicle, and therefore unnecessary obstacle avoidance processes can be prevented from being triggered to save resources.
And 2, responding to the fact that the size of the obstacle does not influence the normal running of the unmanned vehicle, and controlling the unmanned vehicle to keep the current running state.
And 3, responding to the influence of the size of the obstacle on the normal running of the unmanned vehicle, determining whether the speed of the obstacle is zero, if so, executing the step 4, and if not, executing the step 5.
When the speed of the obstacle is zero or not zero, the specific obstacle avoidance procedure will be different, and details of this part will be described later.
Step 4, if the speed of the obstacle is zero, determining whether the unmanned vehicle can bypass the obstacle or not based on the position of the obstacle; when it is determined that the unmanned vehicle can bypass the obstacle, controlling the unmanned vehicle to determine a first optimal bypassing path of the unmanned vehicle based on at least one of the position and the size of the obstacle and the driving speed of the unmanned vehicle, wherein the first optimal bypassing path is as follows: the unmanned vehicle can successfully detour the obstacle and the path with the least required resources, and is controlled to travel according to the first optimal detour path; and when the unmanned vehicle is determined not to be capable of bypassing the obstacle, controlling the unmanned vehicle to decelerate and stop.
Specifically, the determining the first optimal detour path of the unmanned vehicle based on at least one of the position and the size of the obstacle and the traveling speed of the unmanned vehicle may include: and determining a path with the shortest detour required distance as a first optimal detour path based on at least one of the position and the size of the obstacle and the driving speed of the unmanned vehicle, or determining a path with the minimum driving speed change of the unmanned vehicle during detour as the first optimal detour path.
For example, if the unmanned vehicle detects that there is an obstacle around the unmanned vehicle, the speed of the obstacle is zero, and it is determined that the unmanned vehicle can bypass the obstacle, then if the unmanned vehicle detects that the obstacle is located at the front right side of the unmanned vehicle, the corresponding alternative bypassing schemes may be two: the first is that the unmanned vehicle detours to the right side to avoid the barrier; second, the drone walks to the left to avoid the obstacle. However, since the obstacle is located on the right side in front of the unmanned vehicle, the unmanned vehicle inevitably travels a large distance when detouring to the right, and only travels a short distance if detouring to the left, so that the required distance is shortest in the second alternative, the second alternative detouring scheme, that is, the unmanned vehicle detours to the left to avoid the obstacle, may be determined as the first optimal detouring path. Or, since the obstacle is located on the right side in front of the unmanned vehicle, when the unmanned vehicle detours to the right, the detour angle thereof is large, at this time, in order to ensure that the unmanned vehicle can stably travel, the traveling speed of the unmanned vehicle should be greatly reduced, and when the unmanned vehicle detours to the right, the traveling speed of the unmanned vehicle can be reduced by a small amount, so that the variation of the traveling speed of the unmanned vehicle is minimum in the second alternative, the second alternative detour scheme, that is, when the unmanned vehicle detours to the left to avoid the obstacle, can be determined as the first optimal detour path.
Step 5, if the speed of the obstacle is not zero, calculating the path track of the obstacle based on the position, the size and the speed of the obstacle, determining whether the path track of the obstacle and the driving track of the unmanned vehicle collide with each other, and controlling the unmanned vehicle to keep the current driving state when collision does not occur; when collision happens, the unmanned vehicle is controlled to determine a second optimal detour path of the unmanned vehicle based on at least one of the position and the size of the obstacle and the running speed of the unmanned vehicle, and the second optimal detour path is as follows: the collision between the unmanned vehicle and the barrier can be avoided, the required resource is the least, and the unmanned vehicle is controlled to travel according to the second optimal detour path.
Wherein the determining the second optimal detour path of the unmanned vehicle based on at least one of the position and the size of the obstacle and the traveling speed of the unmanned vehicle may include: and determining a path with the shortest detour required distance as a second optimal detour path based on at least one of the position and the size of the obstacle and the driving speed of the unmanned vehicle, or determining a path with the minimum driving speed change of the unmanned vehicle during detour as the second optimal detour path.
For example, if the unmanned vehicle detects that an obstacle exists around the unmanned vehicle, the speed of the obstacle is not zero, and it is determined that the path track of the obstacle and the driving track of the unmanned vehicle collide with each other on the front right side of the unmanned vehicle, several solutions may be provided for the corresponding alternative detour solutions: in the scheme I, the unmanned vehicle accelerates to the right side to bypass the obstacle; the unmanned vehicle decelerates to the right side to detour to avoid the obstacle; thirdly, the unmanned vehicle accelerates to the left side to bypass the obstacle; and fourthly, the unmanned vehicle decelerates to the left side to detour to avoid the obstacle. At this time, the unmanned vehicle may select a plan corresponding to the shortest detour route from among the first to fourth plans and determine the selected plan as the second optimal detour route, or select a plan corresponding to the unmanned vehicle having the smallest variation in travel speed and determine the selected plan as the second optimal detour plan. For example, assuming that the detour paths required by the first solution, the second solution, the third solution and the fourth solution are 2 meters, 1 meter, 3 meters and 4 meters, respectively, the second solution may be determined as the second optimal detour solution.
As can be seen from the above, the unmanned vehicle can efficiently perform automatic obstacle avoidance by performing the steps 1 to 5, and it is ensured that fewer resources are required in the automatic obstacle avoidance process of the unmanned vehicle.
Further, in one embodiment of the present disclosure, in response to controlling the unmanned vehicle to decelerate and stop, the unmanned vehicle further sends a first control signaling to the rear vehicle, where the first control signaling is used to notify the rear vehicle to decelerate and stop as well, so as to avoid a collision accident due to the fact that the rear vehicle is not stopped in time. And
when the first optimal detour path or the second optimal detour path is determined by responding to the control unmanned vehicle, the unmanned vehicle needs to send a second control signaling to the rear vehicle, the second control signaling comprises the first optimal detour path or the second optimal detour path determined by the unmanned vehicle, and the second control signaling is used for informing the rear vehicle to drive based on the first optimal detour path or the second optimal detour path, so that the rear vehicle can be ensured to successfully avoid obstacles.
In summary, in the method and the device for controlling the underground unmanned vehicle provided by the embodiment of the disclosure, the unmanned vehicle may measure the driving speed and the acceleration of the unmanned vehicle and the current position of the unmanned vehicle, and may predict the driving trajectory of the unmanned vehicle based on the driving speed and the acceleration of the unmanned vehicle and the current position of the unmanned vehicle; then, whether obstacles exist around the unmanned vehicle or not is detected; when it is detected that no obstacle exists around the unmanned vehicle, controlling the unmanned vehicle based on the running speed of the unmanned vehicle; when it is detected that an obstacle exists around the unmanned vehicle, it is determined whether the obstacle is located on a trajectory of the unmanned vehicle, wherein in response to determining that the obstacle is located on the trajectory of the unmanned vehicle, a position, a size, and a speed of the obstacle are detected, and the unmanned vehicle is controlled to maintain a current driving state or to decelerate to a stop or to determine an optimal detour path based on at least one of the position, the size, and the speed of the obstacle and a driving speed of the unmanned vehicle.
As can be seen from this, in the solution of the present disclosure, the unmanned vehicle predicts the driving track thereof, and, when the unmanned vehicle detects that there is an obstacle around the unmanned vehicle and the obstacle is located on the driving track of the unmanned vehicle, the unmanned vehicle is controlled to maintain the current driving state or decelerate and stop or determine the optimal detour path for automatic obstacle avoidance based on at least one of the position, size, and speed of the obstacle and the driving speed of the unmanned vehicle. The present disclosure provides an automatic obstacle avoidance method for an underground unmanned vehicle, thereby improving the driving efficiency of the underground unmanned vehicle. Moreover, in the method, when the unmanned vehicle automatically avoids the obstacle, the unmanned vehicle can determine the optimal detour path to avoid the obstacle, so that the obstacle avoiding efficiency can be improved, and the required resources are less.
Furthermore, it should be noted that the method of the present disclosure may be performed in real time while the unmanned vehicle is traveling downhole.
Fig. 2 is a schematic structural diagram of a downhole unmanned vehicle control device configured in a downhole unmanned vehicle according to an embodiment of the present application, and as shown in fig. 2, the downhole unmanned vehicle control device includes:
the first processing module is used for measuring the running speed and the acceleration of the unmanned vehicle and the current position of the unmanned vehicle and predicting the running track of the unmanned vehicle on the basis of the running speed and the acceleration of the unmanned vehicle and the current position of the unmanned vehicle;
the detection module is used for detecting whether obstacles exist around the unmanned vehicle or not;
the control module is used for controlling the unmanned vehicle to run based on the running speed of the unmanned vehicle when no obstacles around the unmanned vehicle are detected;
the second processing module is used for determining whether the obstacle is positioned on the driving track of the unmanned vehicle when the obstacle is detected to be positioned around the unmanned vehicle, detecting the position, the size and the speed of the obstacle in response to the fact that the obstacle is positioned on the driving track of the unmanned vehicle, and controlling the unmanned vehicle to keep the current driving state or decelerate and stop or determine the optimal detour path based on at least one of the position, the size and the speed of the obstacle and the driving speed of the unmanned vehicle.
Optionally, in an embodiment of the present disclosure, the unmanned vehicle is provided with a speed sensor, an acceleration sensor, a positioning module, a laser radar sensor, an ultrasonic ranging sensor, and an infrared sensor;
wherein the speed sensor is used for measuring the running speed of the unmanned vehicle;
the acceleration sensor is used for measuring the acceleration of the unmanned vehicle;
the positioning module and the laser radar sensor are used for measuring the current position of the unmanned vehicle;
the ultrasonic ranging sensor and the infrared sensor are used for measuring whether obstacles exist around the unmanned vehicle or not and the position, the size and the speed of the obstacles.
Optionally, in an embodiment of the present disclosure, the control module is further configured to:
controlling the unmanned vehicle to keep a current driving state in response to the fact that the driving speed of the unmanned vehicle is between a preset interval;
in response to the unmanned vehicle not being in the predetermined interval of travel speed, controlling the unmanned vehicle to accelerate or decelerate so that the unmanned vehicle's travel speed remains in the predetermined interval.
Optionally, in an embodiment of the present disclosure, the apparatus is further configured to:
in response to determining that an obstacle is present around the unmanned vehicle, detecting whether the obstacle is a living being;
if the barrier is a living thing, directly controlling the unmanned vehicle to decelerate and stop, and alarming and warning;
if the obstacle is an abiotic obstacle, detecting the position, the size and the speed of the obstacle, and controlling the unmanned vehicle to keep a current driving state or decelerate and stop or determine an optimal detour path based on at least one of the position, the size and the speed of the obstacle and the driving speed of the unmanned vehicle.
Optionally, in an embodiment of the disclosure, the second processing module is further configured to:
determining whether the size of the obstacle affects normal driving of the unmanned vehicle;
in response to that the size of the obstacle does not influence normal running of the unmanned vehicle, controlling the unmanned vehicle to keep a current running state; determining whether a speed of the obstacle is zero in response to the size of the obstacle affecting normal travel of the unmanned vehicle;
if the speed of the obstacle is zero, determining whether the unmanned vehicle can bypass the obstacle based on the position of the obstacle; when it is determined that the unmanned vehicle can bypass the obstacle, controlling the unmanned vehicle to determine a first optimal bypassing path of the unmanned vehicle based on at least one of the position and the size of the obstacle and the driving speed of the unmanned vehicle, wherein the first optimal bypassing path is as follows: the unmanned vehicle can successfully detour the obstacle and the path with the least required resources, and is controlled to run according to the first optimal detour path; when it is determined that the unmanned vehicle cannot circumvent the obstacle, controlling the unmanned vehicle to decelerate and stop;
if the speed of the obstacle is not zero, calculating the path track of the obstacle based on the position, the size and the speed of the obstacle, determining whether the path track of the obstacle and the driving track of the unmanned vehicle collide with each other, and controlling the unmanned vehicle to keep a current driving state when collision does not occur; when a collision occurs, controlling the unmanned vehicle to determine a second optimal detour path of the unmanned vehicle based on at least one of the position and the size of the obstacle and the driving speed of the unmanned vehicle, wherein the second optimal detour path is as follows: the collision between the unmanned vehicle and the barrier can be avoided, the required resource is the least, and the unmanned vehicle is controlled to run according to the second optimal detour path.
Optionally, in an embodiment of the disclosure, the second processing module is further configured to:
and determining a path with the shortest detour required path as a first optimal detour path or a second optimal detour path based on at least one of the position and the size of the obstacle and the driving speed of the unmanned vehicle, or determining a path with the minimum driving speed change of the unmanned vehicle during detour as the first optimal detour path or the second optimal driving path.
Optionally, in an embodiment of the present disclosure, the apparatus is further configured to:
responding to control of the unmanned vehicle to decelerate and stop, and sending a first control signaling to a rear vehicle of the unmanned vehicle, wherein the first control signaling is used for informing the rear vehicle of decelerating and stopping;
and responding to the control of the unmanned vehicle to determine a first optimal detour path or a second optimal detour path, and sending a second control signaling to the rear vehicle, wherein the second control signaling comprises the first optimal detour path or the second optimal detour path determined by the unmanned vehicle, and the second control signaling is used for informing the rear vehicle to run based on the first optimal detour path or the second optimal detour path.
In summary, in the downhole unmanned vehicle control device provided in the embodiment of the present disclosure, the unmanned vehicle may measure the driving speed and the acceleration of the unmanned vehicle and the current position of the unmanned vehicle, and may predict the driving trajectory of the unmanned vehicle based on the driving speed and the acceleration of the unmanned vehicle and the current position of the unmanned vehicle; then, whether obstacles exist around the unmanned vehicle or not is detected; when it is detected that no obstacle exists around the unmanned vehicle, controlling the unmanned vehicle based on the running speed of the unmanned vehicle; when it is detected that an obstacle exists around the unmanned vehicle, it is determined whether the obstacle is located on a trajectory of the unmanned vehicle, wherein in response to determining that the obstacle is located on the trajectory of the unmanned vehicle, a position, a size, and a speed of the obstacle are detected, and the unmanned vehicle is controlled to maintain a current driving state or to decelerate to a stop or to determine an optimal detour path based on at least one of the position, the size, and the speed of the obstacle and a driving speed of the unmanned vehicle.
As can be seen, in the solution of the present disclosure, the unmanned vehicle predicts the driving track thereof, and when the unmanned vehicle detects that an obstacle exists around the unmanned vehicle and the obstacle is located on the driving track of the unmanned vehicle, the unmanned vehicle is controlled to maintain the current driving state or decelerate and stop or determine an optimal detour path for automatic obstacle avoidance based on at least one of the position, size and speed of the obstacle and the driving speed of the unmanned vehicle. The present disclosure provides an automatic obstacle avoidance method for an underground unmanned vehicle, thereby improving the driving efficiency of the underground unmanned vehicle. Moreover, in the method, when the unmanned vehicle automatically avoids the obstacle, the unmanned vehicle can determine the optimal detour path to avoid the obstacle, so that the obstacle avoiding efficiency can be improved, and the required resources are less.
In the description of the present specification, reference to the description of "one embodiment," "some embodiments," "an example," "a specific example," or "some examples" or the like means that a particular feature, structure, material, or characteristic described in connection with the embodiment or example is included in at least one embodiment or example of the present application. In this specification, the schematic representations of the terms used above are not necessarily intended to refer to the same embodiment or example. Furthermore, the particular features, structures, materials, or characteristics described may be combined in any suitable manner in any one or more embodiments or examples. Furthermore, various embodiments or examples and features of different embodiments or examples described in this specification can be combined and combined by one skilled in the art without contradiction.
Any process or method descriptions in flow charts or otherwise described herein may be understood as representing modules, segments, or portions of code which include one or more executable instructions for implementing steps of a custom logic function or process, and alternate implementations are included within the scope of the preferred embodiment of the present application in which functions may be executed out of order from that shown or discussed, including substantially concurrently or in reverse order, depending on the functionality involved, as would be understood by those reasonably skilled in the art of the present application.
Although embodiments of the present application have been shown and described above, it is understood that the above embodiments are exemplary and should not be construed as limiting the present application, and that variations, modifications, substitutions and alterations may be made to the above embodiments by those of ordinary skill in the art within the scope of the present application.
Claims (2)
1. A method for controlling an unmanned vehicle in a well is characterized by being executed by the unmanned vehicle and comprising the following steps:
measuring the running speed and the acceleration of the unmanned vehicle and the current position of the unmanned vehicle, and predicting the driving track of the unmanned vehicle based on the running speed and the acceleration of the unmanned vehicle and the current position of the unmanned vehicle;
detecting whether obstacles exist around the unmanned vehicle;
controlling the unmanned vehicle to run based on the running speed of the unmanned vehicle when detecting that no obstacle exists around the unmanned vehicle;
when it is detected that an obstacle exists around the unmanned vehicle, determining whether the obstacle is located on a trajectory of the unmanned vehicle, detecting a position, a size, and a speed of the obstacle in response to determining that the obstacle is located on the trajectory of the unmanned vehicle, and controlling the unmanned vehicle to maintain a current driving state or decelerate to stop or determine an optimal detour path based on the position, the size, and the speed of the obstacle and a driving speed of the unmanned vehicle;
the unmanned vehicle is provided with a speed sensor, an acceleration sensor, a positioning module, a laser radar sensor, an ultrasonic ranging sensor and an infrared sensor;
wherein the speed sensor is used for measuring the running speed of the unmanned vehicle;
the acceleration sensor is used for measuring the acceleration of the unmanned vehicle;
the positioning module and the laser radar sensor are used for measuring the current position of the unmanned vehicle;
the ultrasonic ranging sensor and the infrared sensor are used for measuring whether obstacles exist around the unmanned vehicle or not and the position, the size and the speed of the obstacles;
the controlling the unmanned vehicle to travel based on the travel speed of the unmanned vehicle includes:
responding to the fact that the running speed of the unmanned vehicle is in a preset interval, and controlling the unmanned vehicle to keep a current running state;
in response to the traveling speed of the unmanned vehicle not being in the predetermined interval, controlling the unmanned vehicle to accelerate or decelerate so that the traveling speed of the unmanned vehicle is maintained in the predetermined interval;
in response to determining that an obstacle is present around the unmanned vehicle, detecting whether the obstacle is a living being;
if the barrier is a living thing, directly controlling the unmanned vehicle to decelerate and stop, and alarming and warning;
if the obstacle is an abiotic obstacle, detecting the position, the size and the speed of the obstacle, and controlling the unmanned vehicle to keep a current driving state or decelerate and stop or determine an optimal detour path based on the position, the size and the speed of the obstacle and the driving speed of the unmanned vehicle;
the controlling the unmanned vehicle to maintain a current driving state or to decelerate and stop or to determine an optimal detour path based on the position, size and speed of the obstacle and the driving speed of the unmanned vehicle includes:
determining whether the size of the obstacle affects normal driving of the unmanned vehicle;
controlling the unmanned vehicle to keep a current driving state in response to the fact that the size of the obstacle does not affect normal driving of the unmanned vehicle; determining whether a speed of the obstacle is zero in response to the size of the obstacle affecting normal travel of the unmanned vehicle;
if the speed of the obstacle is zero, determining whether the unmanned vehicle can bypass the obstacle based on the position of the obstacle; when it is determined that the unmanned vehicle can bypass the obstacle, controlling the unmanned vehicle to determine a first optimal bypassing path of the unmanned vehicle based on the position and the size of the obstacle and the driving speed of the unmanned vehicle, wherein the first optimal bypassing path is as follows: the unmanned vehicle can successfully detour the obstacle and the path with the least required resources and is controlled to run according to the first optimal detour path; when it is determined that the unmanned vehicle cannot bypass the obstacle, controlling the unmanned vehicle to decelerate and stop;
if the speed of the obstacle is not zero, calculating the path track of the obstacle based on the position, the size and the speed of the obstacle, determining whether the path track of the obstacle and the driving track of the unmanned vehicle collide with each other, and controlling the unmanned vehicle to keep a current driving state when collision does not occur; when collision happens, controlling the unmanned vehicle to determine a second optimal detour path of the unmanned vehicle based on the position and the size of the obstacle and the running speed of the unmanned vehicle, wherein the second optimal detour path is as follows: the unmanned vehicle can be prevented from colliding with the barrier and is controlled to run according to the second optimal detour path along the path with the least required resources;
determining a first optimal detour path or a second optimal driving path of the unmanned vehicle based on the position and the size of the obstacle and the driving speed of the unmanned vehicle, and the method comprises the following steps:
determining a path with the shortest detouring distance as a first optimal detouring path or a second optimal driving path or determining a path with the minimum driving speed change of the unmanned vehicle during detouring as the first optimal detouring path or the second optimal driving path based on the position and the size of the obstacle and the driving speed of the unmanned vehicle;
responding to control of the unmanned vehicle to decelerate and stop, and sending a first control signaling to a rear vehicle of the unmanned vehicle, wherein the first control signaling is used for informing the rear vehicle of decelerating and stopping;
and responding to the control of the unmanned vehicle to determine a first optimal detour path or a second optimal detour path, and sending a second control signaling to the rear vehicle, wherein the second control signaling comprises the first optimal detour path or the second optimal detour path determined by the unmanned vehicle, and the second control signaling is used for informing the rear vehicle to run based on the first optimal detour path or the second optimal detour path.
2. A downhole drone vehicle control apparatus, comprising:
the first processing module is used for measuring the running speed and the acceleration of the unmanned vehicle and the current position of the unmanned vehicle and predicting the driving track of the unmanned vehicle on the basis of the running speed and the acceleration of the unmanned vehicle and the current position of the unmanned vehicle;
the detection module is used for detecting whether obstacles exist around the unmanned vehicle or not;
the control module is used for controlling the unmanned vehicle to run based on the running speed of the unmanned vehicle when the fact that no obstacles exist around the unmanned vehicle is detected;
a second processing module, configured to, when it is detected that an obstacle exists around the unmanned vehicle, determine whether the obstacle is located on a trajectory of the unmanned vehicle, detect a position, a size, and a speed of the obstacle in response to determining that the obstacle is located on the trajectory of the unmanned vehicle, and control the unmanned vehicle to maintain a current driving state or to decelerate and stop or to determine an optimal detour path based on the position, the size, and the speed of the obstacle and a driving speed of the unmanned vehicle;
in response to determining that an obstacle is present around the unmanned vehicle, detecting whether the obstacle is a living being;
if the barrier is a living thing, directly controlling the unmanned vehicle to decelerate and stop, and alarming and warning;
if the obstacle is an abiotic obstacle, detecting the position, the size and the speed of the obstacle, and controlling the unmanned vehicle to keep a current driving state or decelerate and stop or determine an optimal detour path based on the position, the size and the speed of the obstacle and the driving speed of the unmanned vehicle;
the second processing module is further configured to:
determining whether the size of the obstacle affects normal driving of the unmanned vehicle;
controlling the unmanned vehicle to keep a current driving state in response to the fact that the size of the obstacle does not affect normal driving of the unmanned vehicle; determining whether a speed of the obstacle is zero in response to the size of the obstacle affecting normal travel of the unmanned vehicle;
if the speed of the obstacle is zero, determining whether the unmanned vehicle can bypass the obstacle based on the position of the obstacle; when it is determined that the unmanned vehicle can bypass the obstacle, controlling the unmanned vehicle to determine a first optimal bypassing path of the unmanned vehicle based on the position and the size of the obstacle and the running speed of the unmanned vehicle, wherein the first optimal bypassing path is as follows: the unmanned vehicle can successfully detour the obstacle and the path with the least required resources and is controlled to run according to the first optimal detour path; when it is determined that the unmanned vehicle cannot bypass the obstacle, controlling the unmanned vehicle to decelerate and stop;
if the speed of the obstacle is not zero, calculating the path track of the obstacle based on the position, the size and the speed of the obstacle, determining whether the path track of the obstacle and the driving track of the unmanned vehicle collide, and controlling the unmanned vehicle to keep the current driving state when collision does not occur; when collision happens, controlling the unmanned vehicle to determine a second optimal detour path of the unmanned vehicle based on the position and the size of the obstacle and the running speed of the unmanned vehicle, wherein the second optimal detour path is as follows: the unmanned vehicle can be prevented from colliding with the barrier and is controlled to run according to the second optimal detour path along the path with the least required resources;
the unmanned vehicle is provided with a speed sensor, an acceleration sensor, a positioning module, a laser radar sensor, an ultrasonic ranging sensor and an infrared sensor;
wherein the speed sensor is used for measuring the running speed of the unmanned vehicle;
the acceleration sensor is used for measuring the acceleration of the unmanned vehicle;
the positioning module and the laser radar sensor are used for measuring the current position of the unmanned vehicle;
the ultrasonic ranging sensor and the infrared sensor are used for measuring whether obstacles exist around the unmanned vehicle or not and the position, the size and the speed of the obstacles;
the controlling the unmanned vehicle to travel based on the traveling speed of the unmanned vehicle includes:
responding to the fact that the running speed of the unmanned vehicle is in a preset interval, and controlling the unmanned vehicle to keep a current running state;
in response to the traveling speed of the unmanned vehicle not being in the predetermined interval, controlling the unmanned vehicle to accelerate or decelerate so that the traveling speed of the unmanned vehicle is maintained in the predetermined interval;
in response to determining that an obstacle is present around the unmanned vehicle, detecting whether the obstacle is a living being;
if the barrier is a living thing, directly controlling the unmanned vehicle to decelerate and stop, and alarming and warning;
if the obstacle is an abiotic obstacle, detecting the position, the size and the speed of the obstacle, and controlling the unmanned vehicle to keep a current driving state or decelerate and stop or determine an optimal detour path based on the position, the size and the speed of the obstacle and the driving speed of the unmanned vehicle;
determining a first optimal detour path or a second optimal driving path of the unmanned vehicle based on the position and the size of the obstacle and the driving speed of the unmanned vehicle, wherein the method comprises the following steps:
determining a path with the shortest detouring distance as a first optimal detouring path or a second optimal driving path or determining a path with the minimum driving speed change of the unmanned vehicle during detouring as the first optimal detouring path or the second optimal driving path based on the position and the size of the obstacle and the driving speed of the unmanned vehicle;
responding to control of the unmanned vehicle to decelerate and stop, and sending a first control signaling to a rear vehicle of the unmanned vehicle, wherein the first control signaling is used for informing the rear vehicle of decelerating and stopping;
and responding to the control of the unmanned vehicle to determine a first optimal detour path or a second optimal detour path, and sending a second control signaling to the rear vehicle, wherein the second control signaling comprises the first optimal detour path or the second optimal detour path determined by the unmanned vehicle, and the second control signaling is used for informing the rear vehicle to run based on the first optimal detour path or the second optimal detour path.
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| CN202211242545.4A CN115309169B (en) | 2022-10-11 | 2022-10-11 | Underground unmanned vehicle control method and device |
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| US10324463B1 (en) * | 2016-01-22 | 2019-06-18 | State Farm Mutual Automobile Insurance Company | Autonomous vehicle operation adjustment based upon route |
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| JP6917406B2 (en) * | 2019-03-29 | 2021-08-11 | 本田技研工業株式会社 | Vehicle control system |
| CN111071249B (en) * | 2019-12-16 | 2021-02-05 | 南京航空航天大学 | Unmanned vehicle emergency steering obstacle avoidance method based on obstacle motion prediction |
| CN111775961B (en) * | 2020-06-29 | 2022-01-04 | 阿波罗智能技术(北京)有限公司 | Automatic driving vehicle planning method and device, electronic equipment and storage medium |
| CN111898835B (en) * | 2020-08-11 | 2022-02-22 | 腾讯科技（深圳）有限公司 | Intelligent traffic management method, device, computer and readable storage medium |
| CN113085850B (en) * | 2021-06-08 | 2021-09-21 | 新石器慧通（北京）科技有限公司 | Vehicle obstacle avoidance method and device, electronic equipment and storage medium |
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