CN113377111A - Task scheduling system and method for unmanned sweeper - Google Patents
Task scheduling system and method for unmanned sweeper Download PDFInfo
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- CN113377111A CN113377111A CN202110734465.XA CN202110734465A CN113377111A CN 113377111 A CN113377111 A CN 113377111A CN 202110734465 A CN202110734465 A CN 202110734465A CN 113377111 A CN113377111 A CN 113377111A
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- 238000001514 detection method Methods 0.000 claims abstract description 61
- 238000004140 cleaning Methods 0.000 claims abstract description 59
- 238000005259 measurement Methods 0.000 claims abstract description 28
- 238000012544 monitoring process Methods 0.000 claims abstract description 6
- 238000012545 processing Methods 0.000 claims description 15
- 230000004888 barrier function Effects 0.000 claims description 9
- 238000013135 deep learning Methods 0.000 claims description 7
- 238000010408 sweeping Methods 0.000 claims description 7
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- G—PHYSICS
- G05—CONTROLLING; REGULATING
- G05D—SYSTEMS FOR CONTROLLING OR REGULATING NON-ELECTRIC VARIABLES
- G05D1/00—Control of position, course or altitude of land, water, air, or space vehicles, e.g. automatic pilot
- 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
- G05D1/0246—Control of position or course in two dimensions specially adapted to land vehicles using optical position detecting means using a video camera in combination with image processing means
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- G—PHYSICS
- G05—CONTROLLING; REGULATING
- G05D—SYSTEMS FOR CONTROLLING OR REGULATING NON-ELECTRIC VARIABLES
- G05D1/00—Control of position, course or altitude of land, water, air, or space vehicles, e.g. automatic pilot
- 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
- G05D1/0221—Control of position or course in two dimensions specially adapted to land vehicles with means for defining a desired trajectory involving a learning process
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- G—PHYSICS
- G05—CONTROLLING; REGULATING
- G05D—SYSTEMS FOR CONTROLLING OR REGULATING NON-ELECTRIC VARIABLES
- G05D1/00—Control of position, course or altitude of land, water, air, or space vehicles, e.g. automatic pilot
- 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
- G05D1/0276—Control of position or course in two dimensions specially adapted to land vehicles using signals provided by a source external to the vehicle
Abstract
The invention discloses a task scheduling system and method of an unmanned sweeper. The invention comprises a regional camera detection system and an unmanned sweeper; the regional camera detection system comprises a foreign matter detection and positioning system, a foreign matter cleaning path planning system and a command measurement and control system. The invention utilizes the combination of the thousand-searching position positioning and the graph theory planning path, invents a novel garbage cleaning method, can collect information in time through the real-time monitoring of the area camera, issues different cleaning tasks at high and low peaks, and improves the utilization rate of the trolley. Meanwhile, an obstacle avoidance function is added, and by using the move _ base packet in the ROS, the pedestrian and other obstacles can be prevented from being collided when a cleaning task is carried out, and new local path planning can be carried out in time according to the position of the obstacle. The scheme provided by the invention can more efficiently utilize the trolley, not only realizes low human resource consumption, but also has multiple extension functions, and provides a better leisure space while ensuring the cleanness of the ground in a public place.
Description
Technical Field
The invention relates to a method for cleaning garbage by utilizing camera area monitoring and graph theory path planning, in particular to a task scheduling system and method of an unmanned sweeper.
Background
In recent years, with the increasing living standard of people, the pursuit of people in the aspect of mental demand is enhanced. Therefore, people often go to squares to exercise and rest after meals, such as dancing squares or gathering and playing. Therefore, the garbage is not avoided to be generated in the public places such as squares which are relatively open, and the garbage disposal in the public places mostly depends on manual removal at present, which is time-consuming and labor-consuming, so that the problem of how to effectively remove the garbage in the public places in a labor-saving manner is difficult.
Although the existing sweeper appears, the existing sweeper needs manual driving, and consumes much manpower resources; and the current unmanned sweeper can not monitor a certain area in real time and needs manual detection and control.
Aiming at the problems, in order to reduce the consumption of human resources, the invention provides a foreign matter detection and calling method of an unmanned sweeper in an open public area such as a square by utilizing deep learning camera detection and graph theory to realize path planning.
Disclosure of Invention
The invention aims to provide a task scheduling system and method of an unmanned sweeper, aiming at the defects of the existing method.
In order to achieve the purpose, the invention provides the following technical scheme:
a task scheduling system of an unmanned sweeper comprises a regional camera detection system and the unmanned sweeper; the regional camera detection system comprises a foreign matter detection and positioning system, a foreign matter cleaning path planning system and a command measurement and control system;
the foreign matter detection and positioning system comprises a foreign matter detection module, a foreign matter positioning module and a detection data processing module; the foreign matter detection and positioning system identifies garbage and other obstacles through visual detection, and transmits the coordinates of the positioned and identified garbage to the cleaning path planning module to realize the detection and positioning of the garbage; the foreign matter detection module is used for detecting and positioning foreign matters on a square; the foreign matter positioning module is used for positioning the identified garbage coordinates; the detection data processing module is used for sending the foreign body coordinate information to the cleaning path planning system. The specific implementation of each module is as follows:
the foreign matter detection module collects enough information through deep learning to construct a calculation graph, and the recognition accuracy is continuously improved through training and testing to be used for recognizing and classifying garbage and other articles; the foreign body positioning module realizes millimeter-level accurate positioning by utilizing a thousand-searching position technology; the detection data processing module calculates the garbage coordinate data under the newly established square coordinate by establishing a coordinate system for the square and combining the physical positioning of the garbage by the foreign matter positioning module, and sends the garbage coordinate data to the cleaning path planning system.
The foreign matter cleaning path planning system comprises a path planning module and an obstacle avoidance module; after the foreign matter cleaning path planning system receives the garbage coordinate data, the system utilizes a path planning module to carry out global planning and sends the planned path information to a command measurement and control system; when other obstacles appear on the planned path in the advancing process, the obstacle avoidance module carries out local planning according to the coordinate data of the obstacles, and real-time obstacle avoidance is realized. The path planning module is realized through graph theory.
And the command measurement and control system is used for releasing a cleaning task to the unmanned sweeper and recovering the unmanned sweeper after cleaning is finished. The command measurement and control system sends the planned path and the working instruction to the unmanned sweeper and monitors the traveling path of the unmanned sweeper, and when the unmanned sweeper completes a sweeping task, the command measurement and control system sends an instruction to recover the unmanned sweeper to a specified storage position; and issuing different cleaning tasks when the garbage is at high peak and low peak, wherein the trolley has high activity frequency in the high peak period and low activity frequency in the low peak period, and issuing the tasks again for cleaning after the garbage on the square reaches a set threshold amount.
The method specifically comprises the following steps:
step 1, finding rubbish through the deep learning ability of a foreign matter detection module;
step 2, obtaining the coordinates of the monitored ground by using a foreign body positioning module through a camera fixed in the area; when the garbage is found, a physical center of the garbage is found by using the foreign body positioning module, then the physical center of the garbage is matched with the ground coordinates to obtain coordinates of the garbage, and the coordinate information of the garbage is transmitted to the detection data processing module;
the foreign body positioning module is realized by searching positions.
Step 3, transmitting the data to a foreign matter cleaning path planning system through analysis of the detection data processing module;
step 4, the foreign matter cleaning path planning system carries out path planning by using a graph theory and sends optimal planning path information to a command measurement and control system; and if new garbage occurs in the cleaning process, local path planning is carried out on the area where the new garbage occurs through the obstacle avoidance module, and local path information is sent to the command measurement and control system.
Step 5, commanding the measurement and control system to issue a command to control the trolley to clean the garbage according to the path; if the dynamic barrier exists, local planning is carried out through a barrier avoiding module in the path planning system, and real-time barrier avoidance is realized until garbage cleaning is finished;
the real-time obstacle avoidance is specifically realized as follows:
the graph theory path planning can carry out global planning according to all garbage coordinate points in the monitoring area to generate an integral cleaning route; after the global planning, in the process of implementing the task, an obstacle appears on the route, the obstacle existence informing information is generated through the foreign matter detection module, the route planning is carried out again on the local part through the obstacle avoiding module, the obstacle is bypassed, and the cleaning task of the original globally planned route is continued; if dynamic obstacles appear in a certain range around the trolley, obstacle existence informing information and parking informing information are generated through the foreign matter detection module, and a command is issued to continue cleaning the garbage after the dynamic obstacles move out of the moving range of the trolley.
And 6, commanding the measurement and control system to issue a command, recycling the trolley and waiting for the next task to be issued.
The invention has the following beneficial effects: :
1) the method combines the thousand-searching position positioning and the graph theory planning path, invents a novel garbage cleaning method, can collect information in time through the real-time monitoring of the area camera, issues different cleaning tasks at high and low peaks, and improves the utilization rate of the trolley;
2) the obstacle avoidance function is added, and the move _ base packet in the ROS is utilized, so that the pedestrian and other obstacles can be prevented from being collided during the cleaning task, and new local path planning can be performed in time according to the position of the obstacle;
3) the detection function can be further extended, and the method can be used for detecting the non-civilized behaviors such as garbage loss and the like, and improving the civilized literacy of the crowd.
The scheme provided by the invention can more efficiently utilize the trolley, not only realizes low human resource consumption, but also has multiple extension functions, and provides a better leisure space for people while ensuring the cleanness of the ground in a public place.
Drawings
FIG. 1 is a schematic structural view of the present invention;
FIG. 2 is a flow chart of the present invention;
FIG. 3 is a diagram illustrating a task implementation process of the present invention.
Detailed Description
The invention is further illustrated by the following figures and examples.
As shown in fig. 1, 2 and 3, a task scheduling system of an unmanned sweeping vehicle comprises an area camera detection system and the unmanned sweeping vehicle; the regional camera detection system comprises a foreign matter detection and positioning system, a foreign matter cleaning path planning system and a command measurement and control system;
as shown in fig. 1, the foreign object detection and positioning system includes a foreign object detection module, a foreign object positioning module and a detection data processing module; the foreign matter detection and positioning system identifies garbage and other obstacles through visual detection, and transmits the coordinates of the positioned and identified garbage to the cleaning path planning module to realize the detection and positioning of the garbage; the foreign matter detection module is used for detecting and positioning foreign matters on a square; the foreign matter positioning module is used for positioning the identified garbage coordinates; the detection data processing module is used for sending the foreign body coordinate information to the cleaning path planning system. The specific implementation of each module is as follows:
the foreign matter detection module collects enough information through deep learning to construct a calculation graph, and the recognition accuracy is continuously improved through training and testing to be used for recognizing and classifying garbage and other articles; the foreign body positioning module realizes millimeter-level accurate positioning by utilizing a thousand-searching position technology; the detection data processing module calculates the garbage coordinate data under the newly established square coordinate by establishing a coordinate system for the square and combining the physical positioning of the garbage by the foreign matter positioning module, and sends the garbage coordinate data to the cleaning path planning system.
The foreign matter cleaning path planning system comprises a path planning module and an obstacle avoidance module; after the foreign matter cleaning path planning system receives the garbage coordinate data, the system utilizes a path planning module to carry out global planning and sends the planned path information to a command measurement and control system; when other obstacles appear on the planned path in the advancing process, the obstacle avoidance module carries out local planning according to the coordinate data of the obstacles, and real-time obstacle avoidance is realized. The path planning module is realized through graph theory.
And the command measurement and control system is used for releasing a cleaning task to the unmanned sweeper and recovering the unmanned sweeper after cleaning is finished. The command measurement and control system sends the planned path and the working instruction to the unmanned sweeper and monitors the traveling path of the unmanned sweeper, and when the unmanned sweeper completes a sweeping task, the command measurement and control system sends an instruction to recover the unmanned sweeper to a specified storage position; and issuing different cleaning tasks when the garbage is at high peak and low peak, wherein the trolley has high activity frequency in the high peak period and low activity frequency in the low peak period, and issuing the tasks again for cleaning after the garbage on the square reaches a set threshold amount.
As shown in fig. 2 and 3, the present invention specifically includes the following steps:
step 1, finding rubbish through the deep learning ability of a foreign matter detection module;
step 2, obtaining the coordinates of the monitored ground by using a foreign body positioning module through a camera fixed in the area; when the garbage is found, a physical center of the garbage is found by using a foreign body positioning module, then the physical center of the garbage is matched with the ground coordinates to obtain coordinates of the garbage, and the coordinate information of the garbage is transmitted to a detection data processing module, such as five coordinates shown in figure 3;
the foreign body positioning module is realized by searching positions.
Step 3, transmitting the data to a foreign matter cleaning path planning system through analysis of the detection data processing module;
step 4, the foreign matter cleaning path planning system carries out path planning by using a graph theory, such as a curve from a coordinate 1 to a coordinate 5 in the graph 3, and sends optimal planning path information to the command measurement and control system; if new garbage appears during cleaning, the color of the purple color scale (x) in FIG. 33’,y3’) Then pair appearsThe new garbage area carries out local path planning through the obstacle avoidance module, and sends local path information to the command measurement and control system, as shown in fig. 3, the local path information is realized as an actual path, and a dotted line part is a planned path before new garbage appears.
Step 5, commanding the measurement and control system to issue a command to control the trolley to clean the garbage according to the path; if the dynamic barrier exists, local planning is carried out through a barrier avoiding module in the path planning system, and real-time barrier avoidance is realized until garbage cleaning is finished;
the real-time obstacle avoidance is specifically realized as follows:
the graph theory path planning can carry out global planning according to all garbage coordinate points in the monitoring area to generate an integral cleaning route; after the global planning, in the process of implementing the task, an obstacle appears on the route, the obstacle existence informing information is generated through the foreign matter detection module, the route planning is carried out again on the local part through the obstacle avoiding module, the obstacle is bypassed, and the cleaning task of the original globally planned route is continued; if dynamic obstacles appear in a certain range around the trolley, obstacle existence informing information and parking informing information are generated through the foreign matter detection module, and a command is issued to continue cleaning the garbage after the dynamic obstacles move out of the moving range of the trolley.
And 6, commanding the measurement and control system to issue a command, recycling the trolley and waiting for the next task to be issued.
The scheme provided by the invention can more efficiently utilize the trolley, not only realizes low human resource consumption, but also has multiple extension functions, and provides a better leisure space for people while ensuring the cleanness of the ground in a public place.
Claims (4)
1. A task scheduling system of an unmanned sweeper is characterized by comprising a regional camera detection system and the unmanned sweeper; the regional camera detection system comprises a foreign matter detection and positioning system, a foreign matter cleaning path planning system and a command measurement and control system;
the foreign matter detection and positioning system comprises a foreign matter detection module, a foreign matter positioning module and a detection data processing module; the foreign matter detection and positioning system identifies garbage and other obstacles through visual detection, and transmits the coordinates of the positioned and identified garbage to the cleaning path planning module to realize the detection and positioning of the garbage; the foreign matter detection module is used for detecting and positioning foreign matters on a square; the foreign matter positioning module is used for positioning the identified garbage coordinates; the detection data processing module is used for sending the foreign body coordinate information to the cleaning path planning system;
the foreign matter detection module collects enough information through deep learning to construct a calculation graph, and the recognition accuracy is continuously improved through training and testing to be used for recognizing and classifying garbage and other articles; the foreign body positioning module realizes millimeter-level accurate positioning by utilizing a thousand-searching position technology; the detection data processing module calculates the garbage coordinate data under the newly established square coordinate by establishing a coordinate system for the square and combining the physical positioning of the garbage by the foreign matter positioning module, and sends the garbage coordinate data to the cleaning path planning system;
the foreign matter cleaning path planning system comprises a path planning module and an obstacle avoidance module; after the foreign matter cleaning path planning system receives the garbage coordinate data, the system utilizes a path planning module to carry out global planning and sends the planned path information to a command measurement and control system; when other obstacles appear on the planned path in the advancing process, the obstacle avoidance module carries out local planning according to the coordinate data of the obstacles to realize real-time obstacle avoidance; the path planning module is realized through a graph theory;
the command measurement and control system is used for issuing a cleaning task to the unmanned sweeper and recovering the unmanned sweeper after cleaning is finished; the command measurement and control system sends the planned path and the working instruction to the unmanned sweeper and monitors the traveling path of the unmanned sweeper, and when the unmanned sweeper completes a sweeping task, the command measurement and control system sends an instruction to recover the unmanned sweeper to a specified storage position; and issuing different cleaning tasks when the garbage is at high peak and low peak, wherein the trolley has high activity frequency in the high peak period and low activity frequency in the low peak period, and issuing the tasks again for cleaning after the garbage on the square reaches a set threshold amount.
2. A task scheduling method of an unmanned sweeper is characterized by comprising the following steps:
step 1, finding rubbish through the deep learning ability of a foreign matter detection module;
step 2, obtaining the coordinates of the monitored ground by using a foreign body positioning module through a camera fixed in the area; when the garbage is found, a physical center of the garbage is found by using the foreign body positioning module, then the physical center of the garbage is matched with the ground coordinates to obtain coordinates of the garbage, and the coordinate information of the garbage is transmitted to the detection data processing module;
step 3, transmitting the data to a foreign matter cleaning path planning system through analysis of the detection data processing module;
step 4, the foreign matter cleaning path planning system carries out path planning by using a graph theory and sends optimal planning path information to a command measurement and control system; if new garbage occurs in the cleaning process, local path planning is carried out on the area where the new garbage occurs through an obstacle avoidance module, and local path information is sent to a command measurement and control system;
step 5, commanding the measurement and control system to issue a command to control the trolley to clean the garbage according to the path; if the dynamic barrier exists, local planning is carried out through a barrier avoiding module in the path planning system, and real-time barrier avoidance is realized until garbage cleaning is finished;
and 6, commanding the measurement and control system to issue a command, recycling the trolley and waiting for the next task to be issued.
3. The task scheduling method of an unmanned sweeping vehicle according to claim 2, wherein the foreign object locating module is implemented by searching for a position.
4. The task scheduling method of the unmanned sweeping vehicle as claimed in claim 2 or 3, wherein the real-time obstacle avoidance is implemented as follows:
the graph theory path planning can carry out global planning according to all garbage coordinate points in the monitoring area to generate an integral cleaning route; after the global planning, in the process of implementing the task, an obstacle appears on the route, the obstacle existence informing information is generated through the foreign matter detection module, the route planning is carried out again on the local part through the obstacle avoiding module, the obstacle is bypassed, and the cleaning task of the original globally planned route is continued; if dynamic obstacles appear in the moving range around the trolley, obstacle existence informing information and parking informing information are generated through the foreign matter detection module, and a command is issued to continue cleaning the garbage after the dynamic obstacles move out of the moving range of the trolley.
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Application publication date: 20210910 |