CN117519214B - Snow shovel control and path planning method based on visual recognition - Google Patents
Snow shovel control and path planning method based on visual recognition Download PDFInfo
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Abstract
The invention provides a snow shovel blade control and path planning method based on visual identification, which relates to the technical field of snow shovel automatic control and specifically comprises the following steps: and acquiring the snow volume, the position and the road width of the snow in front of the snow shoveling knife of the unmanned snow remover. Based on the snow thickness and the road width, it is determined whether or not snow removal operation can be performed. And determining that the unmanned snow remover is in single-vehicle circulating operation or multi-vehicle formation operation based on the snow removing environment. And determining the starting position of the unmanned snow sweeper based on the acquired position information of the unmanned snow sweeper and the information of surrounding obstacles. And determining the angles of the snow shoveling knife in all directions based on the snow accumulation position. The technical scheme of the invention solves the problems that in the prior art, the snow shoveling knife cannot realize dynamic position adjustment according to different snow conditions, and simultaneously, the snow removing path cannot be reasonably planned, and the accurate multi-vehicle formation operation is performed, so that the snow removing efficiency is low.
Description
Technical Field
The invention relates to the technical field of automatic snow shoveling control, in particular to a snow shoveling control and path planning method based on visual identification.
Background
In the prior art, most snow removing operations rely on manual driving of trucks with fixed snow shovels or use of mechanical engineering equipment such as graders, loaders and the like, and the essence of the snow removing operations is to manually guide the running direction of unmanned snow throwers, realize snow removing and determine snow removing paths. Such conventional modes of operation have certain limitations. Because the limitation of mechanical equipment and manual operation can not realize dynamic position adjustment of the snow shovel according to different snow conditions, the snow removing path can not be reasonably planned at the same time, and accurate multi-vehicle formation operation can be performed, so that the snow removing efficiency is low.
Therefore, there is a need for a snow shoveling to control and path planning method based on visual recognition that can automatically control the attitude of a snow shoveling blade and can plan the path of a snow shovel.
Disclosure of Invention
The invention mainly aims to provide a snow shovel blade control and path planning method based on visual identification, which aims to solve the problems that in the prior art, dynamic position adjustment of the snow shovel blade according to different snow conditions cannot be realized, a snow removing path cannot be reasonably planned, and accurate multi-vehicle formation operation is performed, so that snow removing efficiency is low.
In order to achieve the above purpose, the invention provides a snow shovel control and path planning method based on visual identification, which comprises the following steps:
s1, acquiring the snow volume, the position and the road width of the snow in front of a snow shoveling knife of the unmanned snow remover.
S2, determining whether snow removing operation can be performed or not based on the thickness of the snow and the road width.
S3, determining that the unmanned snow sweeper is in single-vehicle circulating operation or multi-vehicle formation operation based on the snow removing environment.
And S4, determining the starting position of the unmanned snow sweeper based on the acquired position information of the unmanned snow sweeper and the information of surrounding obstacles.
S5, determining the angles of the snow shoveling knife in all directions based on the snow accumulation position.
S6, determining a snow removing path of the unmanned snow remover based on the direction of the snow removing target point, and operating the unmanned snow remover according to the path.
Further, the steps ofS1 specifically comprises the following steps: a plurality of cameras are arranged above the snow shoveling knife, snow information in front of the snow shoveling knife at the same moment is captured from three view angles of the front side, the left side and the right side, and a formula is utilizedObtaining the thickness of the snow cover，For the height of the snow shoveling knife,、the imaging heights of the snow shoveling knife and the snow accumulated in the camera are respectively; the snow volume in front of the snow shovel blade is calculated by using an integration method, and the obtained snow image is divided into countless high valuesEach small rectangle is the projection of the snow flake on the plane, and the rectangular length is the diameter of the flakeI.e. the volume of each lamellaThe method comprises the following steps:snow volume in front of snow shoveling knifeThe method comprises the following steps:
。
further, the step S2 specifically includes the following steps:
s2.1, judging whether the height of the snow shoveling knife is larger than the thickness of snow.
And S2.2, if the height of the snow shovel blade is larger than the thickness of the snow, continuously judging whether the width of the snow shovel blade is larger than the width of the lane.
And S2.3, if the width of the snow shovel blade is larger than the width of the lane, determining that the unmanned snow remover can work under the environment.
Further, the step S3 specifically includes the following steps:
s3.1, automatically judging whether other unmanned snow throwers exist around by the unmanned snow thrower through the second data communication module, and automatically selecting a cycle operation mode of the single vehicle by the unmanned snow thrower if the unmanned snow thrower does not exist and the road width is less than or equal to 7.5 m.
S3.2, when the road width is larger than 7.5m and a plurality of unmanned snow removing vehicles exist in the working environment, the unmanned snow removing vehicles automatically select a multi-vehicle circulation working mode.
Further, the step S4 specifically includes the following steps:
s4.1, acquiring whether obstacles exist around the unmanned snow sweeper through a millimeter wave radar installed on the unmanned snow sweeper, and calculating the distance from each obstacle to the center of a snow shovel blade of the unmanned snow sweeperFor a pair ofComparing, determining the shortest distance from the obstacle to the snow shovel blade of the unmanned snow sweeper asJudgingAnd (3) withIs a size relationship of (a).
S4.2, ifThe current parking position of the snow remover is A #) The center of the snow shoveling knife of the unmanned snow remover is used as the circle center, andthe unmanned snow sweeper path planning processor makes a virtual circle for radius, makes the virtual circle tangent with the boundary of the right road side of the road requiring snow sweeping, and makes the circle center farthest from the destination of the operation target, and at the moment, the relative coordinate of the parking place B of the current unmanned snow sweeper is as followsAnd is composed of:
；
；
obtaining the starting position B of the unmanned snow remover； The angle of the vehicle position coordinate relative to the positive direction of the x-axis under the global coordinate system of the unmanned snow remover is represented,the position of the newly defined parking place B relative to the vehicle, i.e. the angle of this position relative to the positive x-axis direction in the body coordinate system in which the vehicle is set as coordinates,the conversion of the angle in the vehicle body coordinate system into the angle in the global coordinate system with respect to the positive x-axis direction is shown.
S4.3, if no obstacle or the shortest distance between the obstacle and the center of the snow shovel bladeGreater thanThen the current parking position of the unmanned snow remover is usedAs a starting position for an unmanned snow plow.
Further, the step S5 specifically includes the following steps:
s5.1, acquiring snow position in front of the snow shoveling knife in real time according to image information in front of the snow shoveling knife acquired in real time by the unmanned snow remover.
S5.2, judging whether the snow position in front of the snow shovel blade exceeds the snow stacking road sideWherein, the method comprises the steps of, wherein,representing the length of the snow scraper, if exceedingJudging that the snow accumulation position is not close to the snow accumulation road side; if the side of the snow shovel is not close to the snow piling road side, the side inclination angle of the snow shovel is adjusted by controlling the fixed support of the snow shovelRoll angle ofIn order to make the side inclination angle of the snow shovel blade increase when the snow shovel blade rotates around the x axis, the larger the exceeding distance is, the more the side inclination angle increases.
S5.3, judging whether snow at one end far away from the snow piling road exceeds the boundary of the snow shoveling knife, if so, increasing the upper inclination angle of the snow shoveling knife by controlling the fixed support of the snow shoveling knifeOblique shovel angleWherein, the upper dip angleIn order to form an included angle with the yoz plane by the front surface of the snow shovel blade when rotating around the y axis, the angle of the inclined shovel bladeThe included angle between the front surface of the snow shovel blade and the yoz plane is called when the snow shovel blade rotates around the z axis.
Further, the upper inclination angleRoll angleAngle of inclined shovelIs all of the adjustable ranges ofThe method comprises the steps of carrying out a first treatment on the surface of the When the thickness of the snow coverWhen in use, the upper inclination angle of the snow shoveling knifeThe angle of adjustment is withinWhen the thickness of the snow coverWhen in use, the inclination angle of the snow shoveling knifeThe angle of adjustment is within。
Further, the step S6 specifically includes the following steps:
s6.1, enabling initial course angle of unmanned snow removerIs the included angle between the snow accumulation target point direction and the vehicle body x-axis direction, and is communicated withAnd acquiring surrounding environment information of the unmanned snow remover through the vehicle millimeter wave radar.
S6.2, judging whether an obstacle exists on the running path.
S6.3, if the obstacle exists, measuring and calculating the distance between the obstacle and the unmanned snow sweeper through the distance measurement function of the millimeter wave radar：
；
Wherein,represents the time difference between the emission of electromagnetic waves by the millimeter wave radar and the reception of reflected electromagnetic waves,representing the propagation velocity of the electromagnetic wave.
S6.4, comparisonDistance from safety distanceBy the formulaCalculating a safe distanceWherein, the method comprises the steps of, wherein,to operate the speed of travel of an unmanned snow plow when an obstacle is detected,is the maximum deceleration of the unmanned snow remover in the snow removing working environment, whenUnmanned snow removingThe vehicle immediately performs deceleration and parking.
S6.5, stopping the operation if stopping the vehicle, otherwise calculating the repulsive force of the obstacle and repulsive forceThe calculation formula is as follows:
；
wherein,representing the gain factor of the repulsive force,the repulsive potential field representing an obstacle affects the radius,indicating the relative distance between the obstacle and the unmanned snow plow.
Further, step S6 further includes the steps of:
s6.6, if no obstacle exists, calculating the gravitation of snow before the snow shoveling knife and the operation end point：
；
Wherein the method comprises the steps ofFor the gain factor of the gravitational force at the end of the operation,is the gravitational gain coefficient of accumulated snow in front of the snow shoveling knife,for the relative distance between the work end point and the unmanned snow plow,is the distance between the snow accumulation in front of the snow shoveling knife and the snow shoveling knife.
S6.7, calculating resultant forceWhereinRepresents the gravitation action of the unmanned snow remover,the repulsive force effect received by the unmanned snow remover is shown.
S6.8, the unmanned snow remover is in resultant forceIs advanced under the action of (a) and resultant forceThe included angle with the advancing direction of the X axis of the car body isThe method comprises the steps of carrying out a first treatment on the surface of the When the running speed is determined, calculating the running direction deviation and the running direction deviation angleFrom the formulaDetermining, whereinThe travel direction deviation angle at the time t is indicated,indicating the resultant force at time tAn included angle with the advancing direction of the x axis of the vehicle body,indicating running course angle of unmanned snow remover at time t, and combining unmanned snow remover controller with PID (proportion integration differentiation) unmanned snow removerThe control model gives the required rotation angle of the steering wheel of the unmanned snow sweeper for the next secondWherein, the method comprises the steps of, wherein,
；
in the middle of，Is the systematic error at the time t,is a coefficient of proportionality and is used for the control of the power supply,as a result of the differential coefficient,is an integral coefficient.
And S6.9, judging whether the unmanned snow remover reaches a working end point, stopping working if the unmanned snow remover reaches the working end point, and otherwise, repeating the step S5 and the step S6.
Further, the snow shovel blade control and path planning device is also included, the device includes: the device comprises a camera, a GNSS positioning system, a millimeter wave radar obstacle detection system, a display screen, a snow shovel blade control upper computer, a lower computer, a path planning upper computer and an action executing mechanism; the camera, the GNSS positioning system and the millimeter wave radar obstacle detection system are respectively connected with the snow shovel blade control upper computer; the camera, the GNSS positioning system and the millimeter wave radar obstacle detection system are respectively connected with the path planning upper computer; the display screen is respectively connected with the snow shovel blade control upper computer and the path planning upper computer; the lower computer is connected with the snow scraper control upper computer and the path planning upper computer and the action executing mechanism respectively; the snow shovel control upper computer comprises a first processor, a first memory and a first data communication module, wherein the first processor is connected with the first memory and exchanges information, and the first data communication module is connected with the first processor and exchanges information; the path planning upper computer comprises: the second processor is connected with the second memory and exchanges information, and the second data communication module is connected with the second processor and exchanges information; the action executing mechanism comprises: a snow shovel blade control executing mechanism and a direction control executing mechanism; the snow shovel control executing mechanism and the direction control executing mechanism are respectively connected with the lower computer.
The invention has the following beneficial effects:
according to the invention, the geographic position of the unmanned snow remover, people, vehicles and barriers around the vehicle body are obtained in real time, and the volume and position information of snow deposited in front of the snow shovel blade are obtained; the gesture of the snow shovel blade is adjusted in real time based on the volume and the position of snow in front of the snow shovel blade; the operation running path of the unmanned snow remover is adjusted in real time based on the posture of the snow shovel; based on real-time path control unmanned snow sweeper carries out snow removing operation automatically to realize unmanned snow sweeper's single car circulation operation or many car formation operation, promoted unmanned snow sweeper's snow removing efficiency.
Drawings
In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings that are needed in the description of the embodiments or the prior art will be briefly described, and it is obvious that the drawings in the description below are some embodiments of the present invention, and other drawings can be obtained according to the drawings without inventive effort for a person skilled in the art. In the drawings:
fig. 1 shows a flow chart of a snow shovel control and path planning method based on visual recognition according to the present invention.
Fig. 2 shows a schematic view of the starting position of the unmanned snow plow of the present invention.
Fig. 3 shows a schematic diagram of the snow shovel control and path planning apparatus of the present invention.
Fig. 4 shows a schematic diagram of a formation mode under the multi-vehicle operation of the present invention.
Fig. 5 shows a schematic view of the angle of adjustment of the snow scraper of the present invention.
Detailed Description
The following description of the embodiments of the present invention will be made apparent and fully in view of the accompanying drawings, in which some, but not all embodiments of the invention are shown. 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.
The snow shovel control and path planning method based on visual recognition as shown in fig. 1 specifically comprises the following steps:
s1, acquiring the snow volume, the position and the road width of the snow in front of a snow shoveling knife of the unmanned snow remover.
S2, determining whether snow removing operation can be performed or not based on the thickness of the snow and the road width.
S3, determining that the unmanned snow sweeper is in single-vehicle circulating operation or multi-vehicle formation operation based on the snow removing environment.
And S4, determining the starting position of the unmanned snow sweeper based on the acquired position information of the unmanned snow sweeper and the information of surrounding obstacles.
S5, determining the angles of the snow shoveling knife in all directions based on the snow accumulation position.
S6, determining a snow removing path of the unmanned snow remover based on the direction of the snow removing target point, and operating the unmanned snow remover according to the path.
Specifically, step S1 specifically includes: a plurality of cameras are arranged above the snow shoveling knife, snow information before the snow shoveling knife at the same moment is captured from three visual angles of the front side and the left side and the right side, stereo matching is carried out on the image information captured on the left side and the right side, depth information of snow is obtained, and an image captured by the front visual angle is analyzed and a formula is utilizedObtaining the thickness of the snow cover，Is a snow shovelThe height of the steel plate is equal to the height,、the imaging heights of the snow shoveling knife and the snow accumulated in the camera are respectively; the snow volume in front of the snow shovel blade is calculated by using an integration method, and the obtained snow image is divided into countless high valuesEach small rectangle is the projection of the snow flake on the plane, and the rectangular length is the diameter of the flakeI.e. the volume of each lamellaThe method comprises the following steps:snow volume in front of snow shoveling knifeThe method comprises the following steps:
。
specifically, the step S2 specifically includes the following steps:
s2.1, judging whether the height of the snow shoveling knife is larger than the thickness of snow.
And S2.2, if the height of the snow shovel blade is larger than the thickness of the snow, continuously judging whether the width of the snow shovel blade is larger than the width of the lane.
And S2.3, if the width of the snow shovel blade is larger than the width of the lane, determining that the unmanned snow remover can work under the environment.
Specifically, the step S3 specifically includes the following steps:
s3.1, automatically judging whether other unmanned snow throwers exist around by the unmanned snow thrower through the second data communication module, and automatically selecting a cycle operation mode of the single vehicle by the unmanned snow thrower if the unmanned snow thrower does not exist and the road width is less than or equal to 7.5 m.
S3.2, when the road width is larger than 7.5m and a plurality of unmanned snow removing vehicles exist in the working environment, the unmanned snow removing vehicles automatically select a multi-vehicle circulation working mode.
Specifically, as shown in fig. 4, when a multi-vehicle formation operation is performed, each vehicle in the formation acquires geographic position information of each vehicle by a GNSS, and each vehicle acquires snow before a snow shovel and road image information in real time; each vehicle identifies the position of snow accumulated in front of each snow shoveling knife, and uploads data to the cloud end and gathers the data; the upper computer of each vehicle snow shoveling knife acquires data from the cloud end and considers the comprehensive operation condition of formation; and each vehicle adjusts the posture of each snow shovel blade, performs path planning and each vehicle interval R, and transmits the data back to the cloud.
Specifically, step S4 specifically includes the following steps:
s4.1, as shown in FIG. 2, acquiring whether obstacles exist around the unmanned snow sweeper through a millimeter wave radar installed on the unmanned snow sweeper, and calculating the distance from each obstacle to the center of a snow shovel of the unmanned snow sweeperFor a pair ofComparing, determining the shortest distance from the obstacle to the snow shovel blade of the unmanned snow sweeper asJudgingAnd (3) withIs a size relationship of (a).
S4.2, ifThe current parking position of the snow remover is A #) The center of the snow shoveling knife of the unmanned snow remover is used as the circle center, andthe unmanned snow sweeper path planning processor makes a virtual circle for radius, makes the virtual circle tangent with the boundary of the right road side of the road requiring snow sweeping, and makes the circle center farthest from the destination of the operation target, and at the moment, the relative coordinate of the parking place B of the current unmanned snow sweeper is as followsAnd is composed of:
；
；
obtaining the starting position B of the unmanned snow remover； The angle of the vehicle position coordinate relative to the positive direction of the x-axis under the global coordinate system of the unmanned snow remover is represented,the position of the newly defined parking place B relative to the vehicle, i.e. the angle of this position relative to the positive x-axis direction in the body coordinate system in which the vehicle is set as coordinates,the conversion of the angle in the vehicle body coordinate system into the angle in the global coordinate system with respect to the positive x-axis direction is shown.
S4.3, if no obstacle or the shortest distance between the obstacle and the center of the snow shovel bladeGreater thanThen the current parking position of the unmanned snow remover is usedAs a starting position for an unmanned snow plow.
Specifically, step S5 specifically includes the steps of:
s5.1, acquiring snow position in front of the snow shoveling knife in real time according to image information in front of the snow shoveling knife acquired in real time by the unmanned snow remover.
S5.2, judging whether the snow position in front of the snow shovel blade exceeds the snow stacking road sideWherein, the method comprises the steps of, wherein,representing the length of the snow scraper, if exceedingJudging that the snow accumulation position is not close to the snow accumulation road side; if the side of the snow shovel is not close to the snow piling road side, the side inclination angle of the snow shovel is adjusted by controlling the fixed support of the snow shovelAs shown in fig. 5, the roll angleIn order to make the side inclination angle of the snow shovel blade increase when the snow shovel blade rotates around the x axis, the larger the exceeding distance is, the more the side inclination angle increases.
S5.3, judging whether snow at one end far away from the snow piling road exceeds the boundary of the snow shoveling knife, if so, increasing the upper inclination angle of the snow shoveling knife by controlling the fixed support of the snow shoveling knifeOblique shovel angleAs shown in FIG. 5, in which the upper inclination angleIn order to form an included angle with the yoz plane by the front surface of the snow shovel blade when rotating around the y axis, the angle of the inclined shovel bladeThe included angle between the front surface of the snow shovel blade and the yoz plane is called when the snow shovel blade rotates around the z axis.
Specifically, the upper inclination angleRoll angleAngle of inclined shovelIs all of the adjustable ranges ofThe method comprises the steps of carrying out a first treatment on the surface of the When the thickness of the snow coverWhen in use, the upper inclination angle of the snow shoveling knifeThe angle of adjustment is withinWhen the thickness of the snow coverWhen in use, the inclination angle of the snow shoveling knifeThe angle of adjustment is within。
Specifically, step S6 specifically includes the following steps:
s6.1, enabling initial course angle of unmanned snow removerFor snow target pointAnd the included angle between the direction and the x-axis direction of the vehicle body, and acquiring the surrounding environment information of the unmanned snow sweeper through the vehicle-mounted millimeter wave radar.
S6.2, judging whether an obstacle exists on the running path.
S6.3, if the obstacle exists, measuring and calculating the distance between the obstacle and the unmanned snow sweeper through the distance measurement function of the millimeter wave radar：
；
Wherein,represents the time difference between the emission of electromagnetic waves by the millimeter wave radar and the reception of reflected electromagnetic waves,representing the propagation velocity of the electromagnetic wave.
S6.4, comparisonDistance from safety distanceBy the formulaCalculating a safe distanceWherein, the method comprises the steps of, wherein,to operate the speed of travel of an unmanned snow plow when an obstacle is detected,is the maximum deceleration of the unmanned snow remover in the snow removing working environment, whenAnd the unmanned snow remover immediately performs deceleration and parking.
S6.5, stopping the operation if stopping the vehicle, otherwise calculating the repulsive force of the obstacle and repulsive forceThe calculation formula is as follows:
；
wherein,representing the gain factor of the repulsive force,the repulsive potential field representing an obstacle affects the radius,indicating the relative distance between the obstacle and the unmanned snow plow.
Specifically, step S6 further includes the steps of:
s6.6, if no obstacle exists, calculating the gravitation of snow before the snow shoveling knife and the operation end point：
；
Wherein the method comprises the steps ofFor the gain factor of the gravitational force at the end of the operation,is the gravitational gain coefficient of accumulated snow in front of the snow shoveling knife,for the relative distance between the work end point and the unmanned snow plow,is the distance between the snow accumulation in front of the snow shoveling knife and the snow shoveling knife.
S6.7, calculating resultant forceWhereinRepresents the gravitation action of the unmanned snow remover,the repulsive force effect received by the unmanned snow remover is shown.
S6.8, the unmanned snow remover is in resultant forceIs advanced under the action of (a) and resultant forceThe included angle with the advancing direction of the X axis of the car body isThe method comprises the steps of carrying out a first treatment on the surface of the When the running speed is determined, calculating the running direction deviation and the running direction deviation angleFrom the formulaDetermining, whereinThe travel direction deviation angle at the time t is indicated,indicating the resultant force at time tAn included angle with the advancing direction of the x axis of the vehicle body,unmanned snow remover for indicating t momentThe unmanned snow sweeper controller combines a PID unmanned snow sweeper control model to give the required rotation angle of the steering wheel of the unmanned snow sweeper of the next secondWherein, the method comprises the steps of, wherein,
；
in the middle of，Is the systematic error at the time t,is a coefficient of proportionality and is used for the control of the power supply,as a result of the differential coefficient,is an integral coefficient.
And S6.9, judging whether the unmanned snow remover reaches a working end point, stopping working if the unmanned snow remover reaches the working end point, and otherwise, repeating the step S5 and the step S6.
Specifically, as shown in fig. 3, the invention further includes a snow shovel control and path planning device, which includes: the device comprises a camera, a GNSS positioning system, a millimeter wave radar obstacle detection system, a display screen, a snow shovel blade control upper computer, a lower computer, a path planning upper computer and an action executing mechanism; the camera, the GNSS positioning system and the millimeter wave radar obstacle detection system are respectively connected with the snow shovel blade control upper computer; the camera, the GNSS positioning system and the millimeter wave radar obstacle detection system are respectively connected with the path planning upper computer; the display screen is respectively connected with the snow shovel blade control upper computer and the path planning upper computer; the lower computer is connected with the snow scraper control upper computer and the path planning upper computer and the action executing mechanism respectively; the snow shovel control upper computer comprises a first processor, a first memory and a first data communication module, wherein the first processor is connected with the first memory and exchanges information, and the first data communication module is connected with the first processor and exchanges information; the path planning upper computer comprises: the second processor is connected with the second memory and exchanges information, and the second data communication module is connected with the second processor and exchanges information; the action executing mechanism comprises: a snow shovel blade control executing mechanism and a direction control executing mechanism; the snow shovel control executing mechanism and the direction control executing mechanism are respectively connected with the lower computer.
It should be understood that the above description is not intended to limit the invention to the particular embodiments disclosed, but to limit the invention to the particular embodiments disclosed, and that the invention is not limited to the particular embodiments disclosed, but is intended to cover modifications, adaptations, additions and alternatives falling within the spirit and scope of the invention.
Claims (9)
1. A snow shovel blade control and path planning method based on visual recognition is characterized by comprising the following steps:
s1, acquiring the volume, the position and the road width of snow in front of a snow shoveling knife of an unmanned snow remover;
s2, determining whether snow removing operation can be performed or not based on the thickness and the road width of the snow;
s3, determining that the unmanned snow remover is in single-vehicle circulating operation or multi-vehicle formation operation based on the snow removing environment;
s4, determining the starting position of the unmanned snow sweeper based on the acquired position information of the unmanned snow sweeper and the information of surrounding obstacles;
s5, determining angles of the snow shoveling knife in all directions based on the snow accumulation position;
s6, determining a snow removing path of the unmanned snow remover based on the direction of the snow removing target point, and operating the unmanned snow remover according to the path;
the step S4 specifically comprises the following steps:
s4.1, acquiring whether obstacles exist around the unmanned snow sweeper through a millimeter wave radar installed on the unmanned snow sweeper, and calculating the distance from each obstacle to the center of a snow shovel blade of the unmanned snow sweeperFor->Comparing, determining the shortest distance from the obstacle to the snow shovel of the unmanned snow sweeper as +.>Judging->And->Is a size relationship of (2);
s4.2, ifThe current parking position of the snow sweeper is A (+)>) The center of the snow shoveling knife of the unmanned snow remover is used as the center of the circle, and +.>The unmanned snow sweeper path planning processor makes a virtual circle for radius, makes the virtual circle tangent with the boundary of the right road side of the road requiring snow sweeping, and makes the circle center farthest from the end point of the operation target, and at the moment, the relative coordinate of the parking place B of the current unmanned snow sweeper is ++>And is composed of:
；
；
obtaining the starting position B of the unmanned snow remover； />Representing the angle of the vehicle position coordinates relative to the positive x-axis direction of the unmanned snow sweeper in the global coordinate system,/>Representing the position of the newly determined parking place B relative to the vehicle, i.e. the angle of this position relative to the positive x-axis direction in the body coordinate system taking the vehicle as coordinate system, +.>Representing converting an angle in a vehicle body coordinate system into an angle in a global coordinate system with respect to a positive x-axis direction;
s4.3, if no obstacle or the shortest distance between the obstacle and the center of the snow shovel bladeIs greater than->Then the current parking position of the unmanned snow sweeper is used for +.>As a starting position for an unmanned snow plow.
2. The method for controlling a snow scraper and planning a path according to claim 1, wherein step S1 is specifically: a plurality of cameras are arranged above the snow shoveling knife, snow information in front of the snow shoveling knife at the same moment is captured from three view angles of the front side, the left side and the right side, and a formula is utilizedObtaining snow thickness->，/>Is the height of the snow shoveling knife>、The imaging heights of the snow shoveling knife and the snow accumulated in the camera are respectively; calculating snow volume before snow shoveling knife by using integration method, and dividing the obtained snow image into countless snow images with height of +.>Each small rectangle is the projection of the snow flake on the plane, and the rectangular length is the diameter of the flake +.>I.e. the volume of each lamella +.>The method comprises the following steps: />Snow volume in front of snow shoveling knife +.>The method comprises the following steps:
。
3. the method for controlling and planning a snow blower based on visual recognition according to claim 2, wherein the step S2 comprises the following steps:
s2.1, judging whether the height of the snow shoveling knife is larger than the thickness of snow;
s2.2, if the height of the snow shovel blade is larger than the thickness of the snow, continuously judging whether the width of the snow shovel blade is larger than the width of the lane;
and S2.3, if the width of the snow shovel blade is larger than the width of the lane, determining that the unmanned snow remover can work under the width of the lane.
4. A snow blower control and path planning method according to claim 3, wherein step S3 comprises the steps of:
s3.1, automatically judging whether other unmanned snow throwers exist around the unmanned snow throwers through the second data communication module, and automatically selecting a cycle operation mode of the single vehicle by the unmanned snow throwers if the unmanned snow throwers do not exist and the road width is less than or equal to 7.5 m;
and S3.2, when the road width is larger than 7.5m and a plurality of unmanned snow removing vehicles exist in the working environment, the unmanned snow removing vehicle automatically selects a multi-vehicle circulating working mode.
5. The method for controlling and planning a snow blower based on visual recognition according to claim 4, wherein the step S5 comprises the following steps:
s5.1, acquiring snow position in front of the snow shoveling knife in real time according to image information in front of the snow shoveling knife acquired in real time by the unmanned snow remover;
s5.2, judging whether the snow position in front of the snow shovel blade exceeds the snow stacking road sideWherein->Representing the length of the snow scraper, if exceeding +.>Judging that the snow accumulation position is not close to the snow accumulation road side; if the side of the snow shovel is not close to the snow piling road side, the side inclination angle of the snow shovel is adjusted by controlling the fixed support of the snow shovel>Roll angle->In order to increase the side inclination angle of the snow shovel blade when rotating around the x axis, the side inclination angle is increased more when the exceeding distance is larger;
s5.3, judging whether snow at one end far away from the snow piling road exceeds the boundary of the snow shoveling knife, if so, increasing the upper inclination angle of the snow shoveling knife by controlling the fixed support of the snow shoveling knifeAnd oblique shovel angle->Wherein, the upper dip angle->In order to form an included angle between the front surface of the snow shovel blade and the yoz plane when rotating around the y axis, the inclined shovel angle is +.>The included angle between the front surface of the snow shovel blade and the yoz plane is called when the snow shovel blade rotates around the z axis.
6. A snow scraper control and path planning method based on visual recognition according to claim 5, wherein the upper inclination angle isRoll angle->Angle of inclined shovel->Is +.>The method comprises the steps of carrying out a first treatment on the surface of the When snow thickness->When in use, the upper dip angle of the snow shoveling knife is +.>The adjusting angle range is +.>When snow thickness->When in use, the inclination angle of the snow shoveling knife is +.>The adjusting angle range is +.>。
7. The method for controlling and planning a snow blower based on visual recognition according to claim 6, wherein step S6 comprises the steps of:
s6.1, enabling initial course angle of unmanned snow removerAcquiring surrounding environment information of the unmanned snow remover by using a vehicle millimeter wave radar for an included angle between the snow accumulation target point direction and the x-axis direction of the vehicle body;
s6.2, judging whether an obstacle exists on the running path;
s6.3, if the obstacle exists, measuring and calculating the distance between the obstacle and the unmanned snow sweeper through the distance measurement function of the millimeter wave radar：
；
Wherein,representing the time difference between the emission of electromagnetic waves and the reception of reflected electromagnetic waves by a millimeter wave radar,/or->Representing the propagation speed of electromagnetic waves;
s6.4, comparisonDistance from safety->Is defined by the formula +.>Calculate the safe distance +.>Wherein->For the working travel speed of unmanned snow breaker when an obstacle is detected, +.>Is the maximum deceleration of the unmanned snow remover under the snow removing working environment, when +.>When no snow remover is used, the vehicle immediately decelerates and stops;
s6.5, stopping the operation if stopping the vehicle, otherwise calculating the repulsive force of the obstacle and repulsive forceThe calculation formula is as follows:
；
wherein,representing the repulsive force gain coefficient, < >>Representing the repulsive potential field influence radius of the obstacle, < ->Indicating the relative distance between the obstacle and the unmanned snow plow.
8. The method for controlling and planning a snow blower based on visual recognition according to claim 7, wherein step S6 further comprises the steps of:
s6.6, if no obstacle exists, calculating the gravitation of snow before the snow shoveling knife and the operation end point：
；
Wherein the method comprises the steps ofFor the operation end point gravity gain coefficient, < >>Is the gravity gain coefficient of accumulated snow in front of the snow shoveling knife, < + >>For the relative distance between the working end and the unmanned snow breaker +.>The distance between the snow accumulation before the snow shoveling knife and the snow shoveling knife;
s6.7, calculating resultant forceWherein->Indicates the gravitation applied by unmanned snow remover, < ->The repulsive force effect received by the unmanned snow remover is shown;
s6.8, the unmanned snow remover is in resultant forceIs advanced under the action of (2) resultant force->The included angle between the front axle and the advancing direction of the X axis of the car body is +.>The method comprises the steps of carrying out a first treatment on the surface of the When the driving speed is determined, the driving direction deviation is calculated, the driving direction deviation angle is +.>By the formula->Determining, wherein->Represents the deviation angle of the driving direction at the time t, +.>Indicating t moment resultant force->An angle between the X-axis of the car body and the advancing direction, < + >>The driving course angle of the unmanned snow remover at the time t is represented, and the unmanned snow remover controller is combined with the PID unmanned snow remover control model to give the required rotation angle of the steering wheel of the unmanned snow remover at the next second +.>Wherein, the method comprises the steps of, wherein,
，
in the middle of，/>For the systematic error at time t +.>Is a proportional coefficient->Is a differential coefficient +.>Is an integral coefficient;
and S6.9, judging whether the unmanned snow remover reaches a working end point, stopping working if the unmanned snow remover reaches the working end point, and otherwise, repeating the step S5 and the step S6.
9. A snow blower control and path planning apparatus based on visual recognition, using the method of any one of claims 1-8, further comprising a snow blower control and path planning apparatus, the apparatus comprising: the device comprises a camera, a GNSS positioning system, a millimeter wave radar obstacle detection system, a display screen, a snow shovel blade control upper computer, a lower computer, a path planning upper computer and an action executing mechanism;
the camera, the GNSS positioning system and the millimeter wave radar obstacle detection system are respectively connected with the snow shovel blade control upper computer;
the camera, the GNSS positioning system and the millimeter wave radar obstacle detection system are respectively connected with the path planning upper computer;
the display screen is respectively connected with the snow scraper control upper computer and the path planning upper computer;
the lower computer is respectively connected with the snow shovel blade control upper computer and the path planning upper computer and is connected with the action executing mechanism;
the snow shovel control upper computer comprises a first processor, a first memory and a first data communication module, wherein the first processor is connected with the first memory and exchanges information, and the first data communication module is connected with the first processor and exchanges information;
the path planning upper computer comprises: the system comprises a second processor, a second memory and a second data communication module, wherein the second processor is connected with the second memory and exchanges information, and the second data communication module is connected with the second processor and exchanges information;
the action executing mechanism comprises: a snow shovel blade control executing mechanism and a direction control executing mechanism; the snow shovel blade control executing mechanism and the direction control executing mechanism are respectively connected with the lower computer.
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Citations (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| JP2003013418A (en) * | 2001-06-29 | 2003-01-15 | Toshiba Corp | Method and system for moving snow-removing robot vehicle, and system for removing snow by using snow- removing robot vehicle |
| CN207143834U (en) * | 2017-05-24 | 2018-03-27 | 哈尔滨理工大学 | Collect the automation snow sweeper of clear snow and transport one |
| JP2018097528A (en) * | 2016-12-12 | 2018-06-21 | 株式会社Ｉｈｉエアロスペース | Unmanned mobile body and control method of unmanned mobile body |
| KR20190103519A (en) * | 2018-02-13 | 2019-09-05 | 한국기술교육대학교 산학협력단 | Automatic snow removing apparatus |
| JP2021014709A (en) * | 2019-07-11 | 2021-02-12 | 西日本旅客鉄道株式会社 | Snow removal system |
| CN114137981A (en) * | 2021-11-29 | 2022-03-04 | 西安空天能源动力智能制造研究院有限公司 | Intelligent snow removal planning method and system for large-scale road surface snow remover |
Family Cites Families (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| JP7191794B2 (en) * | 2019-09-04 | 2022-12-19 | 本田技研工業株式会社 | autonomous snow blower |
-
2024
- 2024-01-05 CN CN202410016503.1A patent/CN117519214B/en active Active
Patent Citations (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| JP2003013418A (en) * | 2001-06-29 | 2003-01-15 | Toshiba Corp | Method and system for moving snow-removing robot vehicle, and system for removing snow by using snow- removing robot vehicle |
| JP2018097528A (en) * | 2016-12-12 | 2018-06-21 | 株式会社Ｉｈｉエアロスペース | Unmanned mobile body and control method of unmanned mobile body |
| CN207143834U (en) * | 2017-05-24 | 2018-03-27 | 哈尔滨理工大学 | Collect the automation snow sweeper of clear snow and transport one |
| KR20190103519A (en) * | 2018-02-13 | 2019-09-05 | 한국기술교육대학교 산학협력단 | Automatic snow removing apparatus |
| JP2021014709A (en) * | 2019-07-11 | 2021-02-12 | 西日本旅客鉄道株式会社 | Snow removal system |
| CN114137981A (en) * | 2021-11-29 | 2022-03-04 | 西安空天能源动力智能制造研究院有限公司 | Intelligent snow removal planning method and system for large-scale road surface snow remover |
Non-Patent Citations (1)
| Title |
|---|
| 基于人工势场和虚拟领航者的智能车辆编队控制;王树凤;张钧鑫;张俊友;;上海交通大学学报;20200331(03);全文 * |
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